Open Access
REVIEW
Liming Sun, Tao Yu*
Energy Engineering, DOI:10.32604/ee.2026.080412
（This article belongs to the Special Issue: Artificial Intelligence in Energy Systems: Challenges, Opportunities, and Emerging Applications)
Abstract The large-scale deployment of electric vehicles (EVs) and charging infrastructure drives transportation electrification and energy structure transformation, but the spatiotemporal randomness and high power demand of EV charging loads challenges the safe and efficient operation of distribution networks. Grid hosting capacity (HC), the maximum additional charging load acceptable for the grid while ensuring reliable, high-quality power supply, is a critical constraint for the coordinated development of EVs, charging stations and the grid. This paper presents a systematic critical review of collaborative operation rules for the vehicle-charging station-grid (VCSG) system with grid HC as the core… More >
Open Access
ARTICLE
Longbo Luo1, Hongming Cai1, Zili Chen2, Meng Ye1, Min Liu2,*
Energy Engineering, DOI:10.32604/ee.2026.079667
Abstract Driven by the national “dual carbon” strategy, the large-scale integration of distributed renewable energy and direct current loads has introduced significant challenges to traditional alternating current distribution networks, including reduced operational efficiency, decreased voltage stability, and increased complexity in grid integration. To address these issues, research investigates the optimal dispatch of alternating current/direct current (AC/DC) hybrid distribution networks under high renewable energy penetration and proposes a coordinated active and reactive power scheduling method. A multi-objective optimization model is formulated to minimize total network losses and total voltage deviations across a 24-h scheduling horizon. The model… More >
Open Access
ARTICLE
Man Fan1, Shize Li1, Yingshan Liu1,2, Zhengping Shi1, Xiangfei Kong1,*, Wandong Zheng3,*, Han Li1, Jianjuan Yuan1
Energy Engineering, DOI:10.32604/ee.2026.078647
（This article belongs to the Special Issue: Smart Thermal Management: Emerging Energy Technologies for Built and Industrial Systems)
Abstract Highway service buildings, as critical transportation hubs, required efficient heating solutions to accommodate fluctuating occupant densities. Conventional thermal control systems struggled to accommodate dynamic occupant flux, often resulting in mismatches between thermal demand and supply. While existing research predominantly focused on static temperature regulation, this study bridged a critical gap by investigating the coupling effects of dynamic thermal comfort and energy efficiency. Firstly, field measurements and occupant surveys reveald substantial variations in thermal environment parameters across different functional zones within service buildings. Analysis of Thermal Sensation Vote (TSV) and Thermal Comfort Vote (TCV) distributions, augmented… More >
Graphic Abstract
Open Access
ARTICLE
Tao Tong1,*, Peng Wang1, Xiaolin Zhao2, Zhigang Zhao2, Ke Wang2, Chen Cao3, Xincai Ming4
Energy Engineering, DOI:10.32604/ee.2026.078218
（This article belongs to the Special Issue: Advanced Analytics on Energy Systems)
Abstract The power transformer serves as a critical hub equipment in the electric power industry, performing the core functions of voltage transformation and power transmission in power grids. Among various potential hazards, through-fault short-circuit impacts are particularly destructive, capable of inducing severe deformation of the transformer windings and even triggering internal faults, thereby posing a major threat to grid stability. Consequently, accurate diagnosis of transformer damage after short-circuit impacts and scientific formulation of targeted overhaul strategies are of vital practical significance for ensuring safe and reliable power supply. In this paper, a comprehensive diagnostic analysis method… More >
Open Access
ARTICLE
Jian Wang1, Xiaye Wang1,*, Jieyan Wang2, Gongqiang Yang1
Energy Engineering, DOI:10.32604/ee.2026.078180
Abstract With the large-scale integration of wind turbines into power systems, the voltage at the grid connection point exhibits continuous oscillation characteristics, which significantly increases the ride-through difficulty and off-grid risk of wind turbines during faults. To address the above problems, this paper proposes a low-high voltage ride-through (L-HVRT) control strategy based on rotor energy storage. This strategy reduces the load on the unloading resistor by decreasing the active power output from the machine-side converter (MSC). To prevent overspeed disconnection during this process, an active power reference value for the MSC output is preset to proactively More >
Open Access
ARTICLE
Shuo Tian1,2, Zetao Ma2,*, Jie Shu1,2, Kang Bie2, Changhong Wu1,2, Caijun Jiang3
Energy Engineering, DOI:10.32604/ee.2026.078142
（This article belongs to the Special Issue: Hydrogen Energy Systems: Storage, Power-to-Hydrogen, and AI-Enabled Design, Planning, and Operation)
Abstract Hydrogen production by water electrolysis, especially alkaline water electrolysis, has become a promising way to storage surplus energy for off-grid microgrids with high penetration of solar energy. To tackle the deterioration of system stability resulted from solar power fluctuation, this paper proposes a coordinated strategy for an off-grid DC microgrid coupling photovoltaic (PV) and alkaline water electrolyzer (AWE). First, a detailed model, considering power constraint related to the AWE temperature in particular, is developed for the PV/AWE/battery microgrid. Secondly, a distributed coordinated strategy, consisting of an adaptive droop control for an AWE and an analogous… More >
Open Access
ARTICLE
Meng Li, Mohan Yang*, Yang Gao, Xiaokai Su, Hanwen Liang, Song Zhang
Energy Engineering, DOI:10.32604/ee.2026.078284
（This article belongs to the Special Issue: Integrated Renewable Energy Systems for Heating, Cooling, Power Generation and Energy Management)
Abstract In order to maximise the potential flexibility of winter electric heating loads, this study proposes a master-slave game-theoretic optimisation scheduling strategy for virtual power plants incorporating a photovoltaic and thermal storage electric heating cluster. This strategy is formulated as a leader-follower game with dynamic clustering. First, a dynamic clustering approach based on the K-means algorithm is employed to analyse the load characteristics of differentiated users, taking into account dynamic factors such as the charging/discharging power of thermal storage devices and variations in indoor temperature. Next, a leader-follower game optimisation model is established in which the… More >
Open Access
REVIEW
Jalpa Thakkar1, Sidhharth Shankar Mishra2, V. Shanmugapriya3, Mohan Kolhe4,*
Energy Engineering, DOI:10.32604/ee.2026.078267
（This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)
Abstract The big challenge in developing wind energy over the past century, which has focused on environmentally friendly production methods to meet the requirements of modern power systems, is the need for holistic architectures that can cope with variability, connection issues, and sector coupling far beyond conventional electricity-only models. This review offers a critically synthesized, process-level overview of progressive wind–hydrogen hybrids, offering a collective view of advancements in electrical layouts, hydrogen-driven conversion routes, and AI-driven control schemes. In contrast to previous surveys that consider these areas in isolation, we provide an explicit examination of the technical… More >
Open Access
ARTICLE
Pujin Wang1,2,3, Guofa Ji1,2,3,*, Wenwei Zhao1,2,3, Liangping Yi4
Energy Engineering, DOI:10.32604/ee.2026.078171
（This article belongs to the Special Issue: Progress and Prospects of Hydraulic Fracture Network Morphology Characterization, Flow Simulation and Optimization Technology for Unconventional Oil and Gas Reservoirs)
Abstract In multi-cluster horizontal well fracturing, non-uniform propagation due to inter-cluster interference severely limits the effectiveness of reservoir stimulation. This study employs the discrete lattice method for numerical simulation, investigating the influence of cluster spacing, fracturing fluid injection rate, and horizontal stress difference on fracture propagation morphology by monitoring, in real time, the dynamic changes in flow pressure, flow rate, and fluid intake volume for each cluster. The results indicate that the stress shadow effect is the fundamental cause of non-uniform fracture propagation. Cluster spacing is a key parameter controlling the maximum flow pressure difference between… More >
Open Access
ARTICLE
Vilim Cvenk1, Filip Maletić1, Simon Erker2, Danijel Pavković3,*, Mihael Cipek3
Energy Engineering, DOI:10.32604/ee.2026.077842
（This article belongs to the Special Issue: Selected Papers from the SDEWES 2025 Conference on Sustainable Development of Energy, Water and Environment Systems)
Abstract All-solid-state lithium-based batteries represent a critical evolution in energy storage, offering enhanced safety, higher energy density, and superior fast-charging capabilities. However, the integration of solid-state electrolytes introduces complex mechanical interactions at the electrode-electrolyte interface that significantly impact performance and longevity. This study introduces a cyclic plastic hardening model for ceramic electrolytes, moving beyond traditional brittle or linear-elastic assumptions. It presents a Finite Element Method (FEM) analysis of a positive electrode representative volume element (RVE), consisting of spherical Nickel-Manganese-Cobalt (NMC811) active material particles embedded in an Li7La3Zr2O12 (LLZO) solid-state electrolyte matrix, with Gaussian-distribution of particle sizes aimed… More >
Graphic Abstract
Open Access
ARTICLE
Xin Guan*, Dechen Kong, Bo Liu, Hao Tang, Longlong Zong
Energy Engineering, DOI:10.32604/ee.2026.076901
（This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)
Abstract Unlike flat terrain, when air flows through mountainous terrain, it is affected by undulating terrain and ground obstacles, forming complex wind field basins. This leads to the actual power generated by wind turbines being lower than the predicted power. Due to the complexity and uncertainty of the terrain and environment of wind farms, there is a significant difference between the measured power of wind farms and the actual output power of wind turbines. Therefore, studying the influence of complex terrain on wind speed in wind farms is of great significance for the site selection and… More >
Open Access
ARTICLE
Xiangdong Meng1, Fengxiang Pei2,*, Dexin Li1, Haifeng Zhang1, Shuyu Zhou1, Yuhui Chen2
Energy Engineering, DOI:10.32604/ee.2026.078161
（This article belongs to the Special Issue: Next-Generation Distribution System Planning, Operation, and Control)
Abstract To address power imbalance in medium- and low-voltage distribution networks with high penetration of distributed generation (DG) following upstream-grid disconnection and transition to active islanded operation, this paper proposes a refined load shedding strategy based on comprehensive load weights. A comprehensive load evaluation framework is developed to quantify nodal load value by integrating user-side subjective preferences with system-side objective operating information. Subjective and objective weights are derived using the analytic hierarchy process (AHP) and the CRITIC method, respectively, and are then fused to obtain comprehensive load weights and priority rankings. Based on these rankings, a… More >
Open Access
ARTICLE
Zhi Xu1, Min Ren1, Zhiwei Yuan2, He Jiang1, Risheng Qin1, Xinze Xi1, Yinfeng Ma3,*
Energy Engineering, DOI:10.32604/ee.2026.079755
（This article belongs to the Special Issue: Next-Generation Distribution System Planning, Operation, and Control)
Abstract The integration of high-penetration renewable energy and multi-energy loads introduces significant volatility and complexity into the operation of Rural Integrated Energy Systems (RIES). To address the challenges of ensuring economic efficiency and operational resilience, this paper proposes a novel multi-time-scale optimization framework grounded in a whole-process dynamic simulation. Initially, a dynamic simulation model is developed to accurately capture system behavior under typical rural disturbance scenarios. This model underpins a two-stage scheduling strategy: a day-ahead steady-state plan aimed at global economic optimization, followed by an intra-day rolling optimization that leverages real-time data to correct forecast deviations.… More >
Open Access
ARTICLE
Zhukui Tan1, Xiaoyong Cao2,*, Qihui Feng1, Dong Liu2, Xiayu Chen3, Fei Chen2
Energy Engineering, DOI:10.32604/ee.2026.078440
Abstract The rapid integration of photovoltaic (PV) generation and energy storage systems has significantly increased the operational complexity of low-voltage direct current (LVDC) distribution networks in zero-carbon parks. Under highly variable operating conditions, conventional DC protection schemes relying on fixed overcurrent thresholds often suffer from maloperation or failure to trip, particularly during fluctuations in PV power, load switching, and changes in network topology. To address these challenges, this paper proposes an adaptive DC protection strategy based on an artificial neural network (ANN)-driven dynamic threshold optimization mechanism. The proposed method replaces static protection settings with an adaptive… More >
Open Access
ARTICLE
Yechun Xin1, Xinxin Cheng1, Yanxu Wang1,*, Weiru Wang1, Jiexiang Han2, Zhen Niu3
Energy Engineering, DOI:10.32604/ee.2026.079043
（This article belongs to the Special Issue: Integration of Renewable Energies with the Grid: An Integrated Study of Solar, Wind, Storage, Electric Vehicles, PV and Wind Materials and AI-Driven Technologies)
Abstract Addressing voltage violations and renewable energy absorption bottlenecks arising from high-penetration photovoltaic (PV) integration, this paper proposes a hierarchical optimisation architecture for a Hybrid Energy Storage System (HESS) based on microgrid-distribution network coordination to enhance collaborative regulation of energy storage across multiple microgrids. The methodology comprises a PV hosting capacity assessment model and an HESS operation model that accounts for power supply reliability, forming a two-layer planning framework that integrates distributed decision-making with centralized coordination. At the microgrid level, HESS capacity is determined to minimise the local comprehensive cost, while the allocation ratio between lithium-based More >
Open Access
ARTICLE
Zhanbin Zhao1, Li Wan2, Yixuan Zheng1, Tao Zhang1,3,*, Zhengrong Shi1,3,*
Energy Engineering, DOI:10.32604/ee.2026.078598
（This article belongs to the Special Issue: Advanced Solar Cogeneration Systems for Buildings)
Abstract Cooling channels in proton exchange membrane fuel cell (PEMFC) bipolar plates are commonly arranged in parallel and connected by inlet and outlet manifolds. Under high heat flux, uneven flow distribution among parallel channels can lead to non-uniform temperatures and local hot spots, weakening thermal management reliability. To address this problem, this study develops a vapor–liquid two-phase computational fluid dynamics model to investigate flow-boiling cooling in a silicon-based bipolar plate. The Mixture multiphase model is combined with a user-defined phase-change source term to simulate water boiling in parallel channels. The thermal performance is evaluated using the… More >
Open Access
ARTICLE
Hechong Chen1, Fan Yang1, Shuxian Fan2,*, Lei Xia3
Energy Engineering, DOI:10.32604/ee.2026.079083
（This article belongs to the Special Issue: Operation and Control of Grid-connected New Energy and Emerging Loads)
Abstract To address the issue that traditional pilot current differential protection, due to fixed restraint coefficients, struggles to balance sensitivity to high-resistance internal faults and selectivity for external faults after inverter-interfaced distributed generators are connected in a T-configuration to active distribution networks, an adaptive protection method based on the fusion of dual features is proposed. This method first constructs normalized differential current amplitude and the contribution degree of T-connected power sources to short-circuit current as a combined criterion. Subsequently, based on the contribution degree partition, a Gaussian kernel function is adopted to achieve smooth adaptive adjustment More >
Open Access
ARTICLE
Qi Wang1,2,3, Tao Zhu1,*, Yibo Huang1
Energy Engineering, DOI:10.32604/ee.2026.078633
（This article belongs to the Special Issue: New Energy and Energy Storage System)
Abstract Accurate SOP estimation is essential for energy management and safety control of lithium-ion batteries in new energy vehicles under complex operating conditions. However, strong nonlinearity and time-varying characteristics still limit the accuracy and robustness of conventional approaches. To address this issue, this paper proposes a model-based and data-driven fusion strategy for SOP estimation. A physics-based battery model is employed to describe the dynamic behavior of the battery, and an SOP estimation framework is constructed by jointly considering multiple practical constraints, including terminal voltage, SOC, and the intrinsic current limit, so as to enable online evaluation… More >
Open Access
ARTICLE
Bing Wang1,2,*, Qingshuai Yang1, Lu Zhang1, Yuzhi Gao1
Energy Engineering, DOI:10.32604/ee.2026.078263
Abstract Under the constraints of carbon peaking and carbon neutrality goals, the low-carbon transition of the power sector is imperative for China. Underground Coal Gasification Combined Cycle (UCGCC) coupled with Carbon Capture and Storage (CCS) offers a potential pathway for clean coal utilization, yet a systematic evaluation of its environmental benefits compared to mature technologies remains lacking. This study establishes a comprehensive Life Cycle Assessment (LCA) model to benchmark the energy consumption and greenhouse gas (GHG) emissions of the UCGCC-CCS system against the Integrated Gasification Combined Cycle (IGCC)-CCS system. The system boundaries encompass the entire process… More >
Open Access
ARTICLE
Haiqing Cai1,2, Liang Tu1,2, Wei Chen3,4, Wencong Wu3,4, Qingyan Zhang5, Jian Wang5,*
Energy Engineering, DOI:10.32604/ee.2026.080048
（This article belongs to the Special Issue: Operation and Control of Grid-connected New Energy and Emerging Loads)
Abstract To address the difficulty of adapting reactive power optimization strategies in distribution networks to diverse scenarios due to source-load uncertainty, which increases the risk of over-voltage and overloads, a reactive power optimization strategy for distribution networks is proposed based on probabilistic power flow sensitivity. Firstly, considering the impact of source-load uncertainty on the dispatching strategy of distribution networks, a reactive power optimization model based on chance constraints is constructed, and the probabilistic models of random variables for voltage and branch power fluctuations in the chance constraints are respectively characterized by probabilistic power flow sensitivity. Then,… More >
Open Access
ARTICLE
Ivan Pliško, Mihael Cipek*, Danijel Pavković
Energy Engineering, DOI:10.32604/ee.2026.078275
（This article belongs to the Special Issue: Selected Papers from the SDEWES 2025 Conference on Sustainable Development of Energy, Water and Environment Systems)
Abstract Nowadays, battery electric vehicles are increasingly used, from passenger cars to heavy-duty commercial vehicles, trains, and ships, all in an effort to reduce greenhouse gas emissions. In electric vehicles, battery capacity significantly affects their range and performance, but a larger battery also increases the vehicle’s mass and cost. This paper proposes parametric optimization of battery capacity and peak electric motor power for electric vehicles under different load types and vehicle capacities. A computational model of an electric vehicle is developed, with parameters such as battery capacity, payload, and peak motor power being variable. Using parametric More >
Open Access
ARTICLE
Wenkui Xi1,2, Bin Zhao1,*, Wei Tian2,3, Min Wang2,4, Shuqin Xiao2,3, Shichun Liu2,3
Energy Engineering, DOI:10.32604/ee.2026.077980
（This article belongs to the Special Issue: Green and Low-Carbon Pipeline Transportation Theory and Technology for Petroleum, Natural Gas, and Unconventional Media)
Abstract To mitigate the issues of pipeline narrowing and obstruction in metal tubing caused by natural gas hydrate formation during the extraction of onshore natural gas wells, particularly in cold regions, Changqing Oilfield has proposed an integrated gathering and transportation mode termed “Wellbore Insulation-Wellhead Throttling”. This mode uses metal-reinforced composite insulation pipe as the production tubing for natural gas wells. This study simulates the operational conditions of the Changqing Sulige gas field and employs the Computational Fluid Dynamics (CFD) method to examine the multiphase flow characteristics of hydrates within the insulation pipe of this structure. This… More >
Open Access
ARTICLE
Tongfei Cui*, Shiyang Rong, Tengkai Yu, Qi Zhang, Shaopeng Zhang, Yang Li
Energy Engineering, DOI:10.32604/ee.2026.076756
（This article belongs to the Special Issue: Global Intelligent Optimization and Advanced Control of Photovoltaic Systems Under Complex Operating Conditions)
Abstract The high penetration of distributed photovoltaic (DPV) systems poses significant challenges to voltage stability in distribution networks due to their intermittency and volatility. The diversification of inverter control strategies, particularly the coexistence of grid-forming (GFM) and grid-following (GFL) inverters, creates complex hybrid integration scenarios. Coordinating these inverter types with traditional devices like on-load tap changers (OLTCs) and shunt capacitor banks (SCBs) for effective voltage regulation is thus a crucial issue. This study develops a novel bi-level active-reactive coordinated voltage regulation strategy. A comprehensive voltage regulation model for hybrid inverter systems is established, followed by the… More >
Open Access
ARTICLE
Jian Zhang1,*, Jun Lu1, Yu Liu1, Yanhua He2, Changhui Yu3, Lingyao Lei3, Xiao Qi3
Energy Engineering, DOI:10.32604/ee.2026.078236
（This article belongs to the Special Issue: Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation)
Abstract High renewable energy penetration compels thermal power units to operate across wide load ranges, causing significant parameter variations that degrade the performance of traditional fixed-parameter automatic generation control (AGC). To address the resulting nonlinear dynamics, this paper proposes a frequency control strategy based on deep learning nonlinear model predictive control (DL-NMPC). Specifically, an attention-based bidirectional long short-term memory (Attention-BiLSTM) network is constructed to accurately model the variable-parameter frequency regulation dynamics of thermal units. Serving as the predictive core of the nonlinear model predictive control (NMPC) framework, this model forecasts grid frequency responses, while the whale… More >
Open Access
ARTICLE
Zheng Zhang1,2,*, Zhenning Qiao1,2, Jianbo Du3, Yanfeng Gao4, Yu Zhao5, Yi Yang1,2, Zhibo Xu1,2
Energy Engineering, DOI:10.32604/ee.2026.077029
Abstract To inhibit hydrate reconfiguration during deepwater dual-wall drill string dual-gradient reverse circulation drilling, accurate wellbore thermal profile characterization is critical. In this study, a novel two-dimensional transient heat field model is established. Unlike previous steady-state or one-dimensional approaches, this model explicitly captures the radial-axial thermal coupling and the transient ‘shallow-section heating’ effect unique to the dual-wall, counter-current flow architecture, providing a more accurate tool for hydrate stability assessment. A comprehensive numerical sensitivity study shows the system exhibits strong thermal decoupling. Circulating medium injection temperature governs the outlet temperature, where a
Open Access
ARTICLE
Thatsamaphon Boonchuntuk1, Thanyapisit Buaprakhong1, Varintorn Sithisint1, Awirut Phusaensaart1, Sinthon Wilke1, Thittaporn Ganokratanaa1,*, Mahasak Ketcham2
Energy Engineering, DOI:10.32604/ee.2026.069005
（This article belongs to the Special Issue: AI in Green Energy Technologies and Their Applications)
Abstract Urban traffic congestion directly contributes to excessive energy consumption and urban air pollution, requiring adaptive traffic signal control strategies that incorporate sustainability objectives alongside mobility performance. This study proposes a Large Language Model (LLM) driven traffic signal optimization framework that transforms detailed intersection-level traffic states into structured natural-language prompts, enabling the LLM to reason over congestion patterns, queue asymmetry, phase history, and estimated energy emission impacts. Unlike reinforcement learning (RL) based controllers, the LLM requires no task-specific training and operates in a zero-shot manner through carefully designed structured prompts that encode traffic states, phase history,… More >
Open Access
ARTICLE
Lanyue Liu1, Chunzhi Zhang1,*, Zhongyi Yu2
Energy Engineering, DOI:10.32604/ee.2025.071463
Abstract This study develops an optimized integrated system for full-capacity hot water supply in hotels by combining solar thermal energy and air-source heat pumps. Using a hotel in Wuhan as a case study, a four-season × four-occupancy multidimensional working-condition matrix was established. Dynamic simulation and multi-objective optimization were performed on TRNSYS-TRNOPT, with the cost-benefit ratio (CBR) as the core evaluation metric. Key parameters—including collector area, tilt and azimuth angles, heat pump capacity, and storage tank volume—were jointly optimized. Model calibration against measured data yielded a deviation of less than 8%. The results demonstrate that the optimized More >
Open Access
ARTICLE
Yang Liu1, Yinguo Yang1, Pingping Xie1, Qiuyu Lu1, Yue Chen1, Zhanpeng Xu2,*, Zejie Huang2
Energy Engineering, DOI:10.32604/ee.2025.068436
（This article belongs to the Special Issue: Advances in Renewable Energy and Storage: Harnessing Hydrocarbon Prediction and Polymetric Materials for Enhanced Efficiency and Sustainability)
Abstract With the large-scale integration of wind and solar energy into the power grid, the power system is facing uncertainty challenges in multiple links, such as source, grid, and load. How to efficiently dispatch flexible resources, such as energy storage, has become an urgent problem to be solved. To this end, this paper considers the correlation between new energy stations due to natural conditions, uses Vine-Copula theory to describe the correlation characteristics of the output of multiple new energy stations, and proposes a wind solar new energy output scenario generation method based on Vine-Copula theory; Then,… More >
Open Access
ARTICLE
Xinyu Yue1, Zhenhua Li1,2,*, Zhenxing Li1, Tao Zhang1, Yanchun Xu1, Xiaozhen Zhao3
Energy Engineering, DOI:10.32604/ee.2026.077395
Abstract Winding deformation is a predominant cause of transformer failures and critically compromises the safe, reliable, and economic operation of power systems. To overcome the inadequacy of the conventional three-dimensional (3D) Lissajous curve method in discriminating among various types of winding faults, this paper proposes an online monitoring method for transformer winding deformation based on 3D Lissajous curves. In the proposed method, the primary current
Open Access
ARTICLE
Gangui Yan, Lu Chen, Aolan Xing*, Jianshu Li, Leiyujie Xiao
Energy Engineering, DOI:10.32604/ee.2026.076781
（This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)
Abstract Wind power prediction is affected by seasonal meteorological conditions, exhibiting significant multi-scale spatio-temporal coupling characteristics and random volatility. Existing models still fail to consider the volatility and uncertainty of power aggregation under seasonal characteristics. Therefore, based on the data of 36 wind farms in three regions (Siping, Baicheng, and Songyuan) in Jilin Province, this paper proposes a wind power prediction method based on multi-level spatio-temporal feature fusion. In the time dimension, this method uses the temporal convolutional network and the seasonal embedding module to jointly model the multi-scale trends and fluctuation characteristics of the power… More >
Open Access
ARTICLE
Jianjun He1,*, Hai Zhang1, Junzhe Tian1, Hongxiang Luo2, Yuexin Du1, Zhiqing Deng1
Energy Engineering, DOI:10.32604/ee.2026.078867
（This article belongs to the Special Issue: AI and Advanced Computational Techniques for Sustainable Renewable Energy Systems)
Abstract To address the limitations of traditional deep learning models in diagnosing multiple coupled faults in photovoltaic arrays—such as manual hyperparameter tuning, susceptibility to local optima, and limited diagnostic accuracy—this study proposes an intelligent diagnostic method. The method integrates an improved sparrow search algorithm (ISSA) with a CNN-Transformer model. First, the original SSA is enhanced by incorporating a Circle chaotic map, a dynamic adaptive weight, and a sine-cosine search strategy to improve its global optimization capability and convergence stability. Second, a CNN-Transformer base model is constructed. This model employs a 1D-CNN to extract local fault features… More >
Open Access
ARTICLE
Zhengji Meng1, Lei Wang1, Xuekai Hu1, Zijian Wang2,*, Linjun Shi2
Energy Engineering, DOI:10.32604/ee.2026.077923
Abstract With the rapid popularization of distributed photovoltaic (PV) systems, traditional load forecasting is facing more and more challenges due to various problems caused by distributed PV grid connection. Distributed PV significantly affects the net load distribution and weakens the effectiveness of traditional forecasting methods. Therefore, improving the accuracy of load forecasting under high PV penetration has become a key issue for the safe and efficient operation of modern power systems. To solve this problem, a load forecasting method based on Particle Swarm Optimization and Bi-directional Long Short-Term Memory (PSO-BiLSTM) network with distributed PV identification and… More >
Open Access
ARTICLE
Man Fan1, Yifang Li1, Yang Qiao1, Yin Zhang2,*, Bowen Xu1,*, Xiangfei Kong1, Han Li1, Ramy Rabie3, Tamer M. Mansour4
Energy Engineering, DOI:10.32604/ee.2026.077085
Abstract Bifacial photovoltaic (bPV) harnesses solar energy from both sides, significantly enhancing power generation. However, accurate and rapid power estimation for bPV remains challenging as most research has focused on monofacial photovoltaic (mPV). Unlike mPV, the power output of bPV is significantly influenced by complex thermal behavior due to bilateral energy absorption, necessitating models coupling thermal and electrical performance. This study firstly tested the thermal and electrical properties of mPV and bPV under various meteorological conditions. Five power estimation models were then developed and compared, including two linear models, two simplified single-diode models (SDM), and one… More >
Open Access
ARTICLE
Safaa M. Ali1, Ranj S. Abdullah2, Hussain H. Al-Kayiem3, Ali M. Tukkee4,5,*
Energy Engineering, DOI:10.32604/ee.2026.076252
（This article belongs to the Special Issue: Advancements in Energy Resources and Their Processes, Systems, Materials and Policies for Affordable Energy Sustainability)
Abstract Energy supply and ventilation for isolated offices in rural areas are strongly recommended to be powered by renewable or standalone energy systems under the concept of net-zero-energy building (netZEB). A rooftop solar chimney is one of the adopted methods for space ventilation to improve thermal comfort. This approach has not been investigated under forced convection to support the netZEB. The objective of the current work is to experimentally assess the effectiveness of natural and forced ventilation methods for a prototype net-zero-energy office with a rooftop solar chimney. The prototype is a low-cost office constructed in… More >
Graphic Abstract
Open Access
ARTICLE
Longqiao Hu1, Yunjin Wang1,*, Jia Liu1, Jiacheng Yin1, Siyu Zhang2, Mengyu Li1, Qi Wu1, Jiawei Li1, Fujian Zhou3
Energy Engineering, DOI:10.32604/ee.2026.079317
（This article belongs to the Special Issue: Enhanced Oil and Gas Recovery in Unconventional ReservoirsⅡ)
Abstract The flow mechanisms of shale oil are inherently complex, characterized by diverse occurrence states. Establishing a robust production forecasting model is essential for thoroughly evaluating well deliverability and the efficacy of reservoir stimulation. While conventional analytical techniques, numerical reservoir simulation, and production decline analysis constitute standard practice, they often struggle to balance computational efficiency with predictive fidelity. Intelligent algorithms offer superior precision in short-term forecasting following extensive data training; however, they frequently exhibit poor generalization and underfitting during long-term performance projections. Consequently, integrating domain-specific production decline theory as physical constraints represents a strategic pathway to… More >
Open Access
ARTICLE
Marcelo Dario Rodas Britez1,*, Francesco Ghionda2, Vasileios Tatsis3, Dimosthenis Ioannidis3
Energy Engineering, DOI:10.32604/ee.2026.078082
（This article belongs to the Special Issue: Selected Papers from the SDEWES 2025 Conference on Sustainable Development of Energy, Water and Environment Systems)
Abstract Current energy systems are increasingly complex, considering multi-energy systems, the integration of non-programmable renewable energy sources, and the simultaneous evaluation of multiple evaluation objectives (i.e., costs vs carbon dioxide emissions). This complexity opens the opportunity to explore optimization algorithms as assistance for systematic and automatic management of energy systems. The implementation of a multi-energy system poses multiple challenges, including managing multiple energy vectors with different technologies applied across energy production, energy storage, and renewable energy sources. Also, multi-objective evaluation should be considered to manage reductions in costs and carbon dioxide emissions. Therefore, this paper proposes… More >
Open Access
ARTICLE
Jing Shi1, Zesen Li1, Delv Zhu1, Bingjie Li1, Lang Gao2,*
Energy Engineering, DOI:10.32604/ee.2026.077553
（This article belongs to the Special Issue: Advances in Renewable Energy and Storage: Harnessing Hydrocarbon Prediction and Polymetric Materials for Enhanced Efficiency and Sustainability)
Abstract In view of the multi-energy subject coupling and operation optimization problems faced by the integrated energy system in the low-carbon transformation, taking a certain city in Jiangsu Province as the experimental object, the research first constructs a city-level low-carbon integrated energy system with hydrogen energy storage as the core hub. Then, the mathematical models of key equipment such as gas turbines, gas boilers, and thermal storage tanks are established. Finally, the multi-energy subject system achieves autonomous optimization and collaborative control through multi-agent DDPG. This method showed good energy utilization efficiency and scheduling flexibility in different… More >
Open Access
ARTICLE
Song Gao1, Jiarui Wang2, Yu Zhang1, Ling Jiang3,*
Energy Engineering, DOI:10.32604/ee.2026.076467
Abstract This paper proposes a cooperative fault recovery method for distribution networks and microgrids considering dynamic network reconfiguration. First, an optimization model is constructed with the objectives of minimizing electricity purchase costs, voltage deviations, network losses, load shedding, and microgrid operation costs. The model thoroughly considers operational conditions, including power flow constraints, security operation constraints, and network reconfiguration constraints, within the distribution network. Second, to address the privacy protection requirements of distributed energy resources (DERs) in microgrids, a k-order approximation method is employed to establish an operation feasible region (OFR) model for microgrid operational flexibility resources. This… More >
Open Access
ARTICLE
Yujie Shi, Guoxing Wu*, Qingwei Wang, Xieli Fu, Wenfeng Yang
Energy Engineering, DOI:10.32604/ee.2026.074213
（This article belongs to the Special Issue: Advances in Renewable Energy and Storage: Harnessing Hydrocarbon Prediction and Polymetric Materials for Enhanced Efficiency and Sustainability)
Abstract This study proposes an optimized ensemble learning framework for energy-efficiency assessment in low-voltage distribution networks by integrating multiple data sources. The framework integrates heterogeneous data from smart meters, SCADA systems, meteorological stations, and network topology databases, employing advanced feature engineering to extract 89 essential predictors from 147 initial features. Three gradient boosting algorithms—Random Forest, XGBoost, and LightGBM—are combined through an elastic net stacking strategy with Bayesian hyperparameter optimization. The stacking ensemble achieved superior performance with an MAE of 118.4 kWh, an RMSE of 164.2 kWh, an MAPE of 3.98%, and an R2 of 0.952, representing 16.8%… More >
Open Access
ARTICLE
V. V. Poplygin1,*, A. Dieng2, Min Wang3, Xian Shi3
Energy Engineering, DOI:10.32604/ee.2025.074170
（This article belongs to the Special Issue: Geomechanical Issures in the Development of Reservoirs and New Energy)
Abstract Hydraulic fracturing in carbonate reservoirs presents unique challenges due to their complex pore structures and heterogeneous mechanical properties. This paper explores the application of statistical methods to improve fracture prediction and optimization in carbonate formations. Hydraulic fracturing is actively carried out on these formations. In order to properly plan hydraulic fracturing, it is necessary to identify the main factors affecting oil production after hydraulic fracturing. This study introduces an integrated framework combining information amount theory (IAT) and Gray relational analysis (GRA) to identify and rank the dominant parameters controlling hydraulic fracturing performance in heterogeneous carbonate… More >
Open Access
ARTICLE
Siying Li1, Xinyu Feng2, Xin Ma2, Hui Huang2, Zhipeng Wang2, Baolian Liu2, Zujun Ding2, Weihong Ding2, Xiaolong Huang2, Jie Ji2,*
Energy Engineering, DOI:10.32604/ee.2026.078062
Abstract This study introduces a novel Dual-Stage GT-RO-PCC (Game Theory-Robust Optimization-Price Coupling Control) paradigm to address operational challenges in community-integrated energy microgrids (CIEMs) characterized by multi-energy complementarity and distributed generation. By synergizing strategic interaction mechanisms with uncertainty-aware energy management, the proposed framework establishes a tripartite governance structure integrating microgrid operators, user-side aggregators, and shared energy storage operators. The first stage formulates a Stackelberg game-theoretic model to optimize day-ahead electricity/heat pricing strategies through bilevel optimization, incorporating flexible load management modeling with flexible load disaggregation and carbon emission trading mechanisms. The second stage constructs a two-stage stochastic robust… More >
Open Access
ARTICLE
Dexin Li1, Yuhang He2, Song Gao1, Jianyi Che2,*, Shuyu Zhou1, Rundong Tian2, Yuman Song2
Energy Engineering, DOI:10.32604/ee.2026.078052
（This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)
Abstract The integration of new-energy power electronic devices into the grid is prone to induce subsynchronous/supersynchronous oscillations, posing a threat to grid stability. Conventional oscillation identification methods are often affected by mode mixing and noise interference during parameter extraction, which compromises analysis accuracy. To address these issues, this paper proposes a variational mode decomposition (VMD) method based on a trigonometric topology aggregation optimization (TTAO) algorithm. The TTAO algorithm adaptively optimizes the key VMD parameters—the number of modes K and the penalty factor α—thereby improving the accuracy and robustness of signal decomposition. Furthermore, the total least squares-estimating signal… More >
Open Access
ARTICLE
Ze’ang Ma1, Jie Chen2,*, Shuai Lyu3
Energy Engineering, DOI:10.32604/ee.2026.076832
Abstract To address the operational volatility and complexity caused by the high penetration of renewable energy in distribution networks, the traditional static and isolated operation mode of distribution transformers struggles to simultaneously ensure power supply quality and economic efficiency. This paper proposes a coordinated dispatch strategy for interconnected distribution transformers based on regional dynamic partitioning and shared energy storage systems. Firstly, an improved K-means partitioning model for distribution transformers is constructed. By integrating a comprehensive distance metric that combines load characteristics and geospatial information, the limitations of traditional single-dimensional partitioning are overcome. Furthermore, a bi-level optimization… More >
Open Access
ARTICLE
Ningling Wang1, Chaoyun Yang1, Pengjun Li2,3, Zhicheng Qi4, Shanshan Xu4, Tianwei Gu4, Jiale Wen1, Xiaoxiao Dou1, Liqiang Duan1, Chengzhou Li2,3,*
Energy Engineering, DOI:10.32604/ee.2026.076636
Abstract In the context of the integration of energy and transportation, the integrated energy system (IES) is a promising alternative energy supply mode for express scenarios. To guarantee the feasibility and reliability of the IES, a scientific evaluation of system performance is required to assist the system design and operation optimization. Therefore, this paper proposes an innovative comprehensive evaluation method for the expressway integrated energy system (E-IES) considering its distinctive energy-use character. Firstly, a multi-attribute index system is constructed covering energy efficiency, economy, environmental protection, reliability, and industry impact, which considers the influence of renewable energy… More >
Open Access
ARTICLE
Houhe Chen1, Yuxi Song1, Zheng Yang1,*, Yunjing Liu1,2, Lizhong Lu2, Zaifeng Li2, Tiebin Guo2
Energy Engineering, DOI:10.32604/ee.2026.077103
（This article belongs to the Special Issue: Data-Driven Energy Systems: Industrial Efficiency, Renewable Integration, and Intelligent Optimization)
Abstract Addressing the challenges of harmonic source tracing caused by low micro-PMU (μPMU) coverage and multi-source coupling in distribution networks, this paper proposes a distributed harmonic source localization method based on subsystem partitioning and virtual current injection. Initially, to achieve high-precision extraction of target harmonic phasors from limited measurement data, an improved windowed interpolation Fast Fourier Transform (FFT) combined with a subspace projection denoising algorithm is utilized. Subsequently, a topology-based subsystem partitioning strategy is proposed to construct a “virtual harmonic current injection” model; by tentatively injecting virtual currents at nodes within the subsystem and calculating the… More >
Open Access
ARTICLE
Zujun Ding, Zhi Liu, Peng Huang, Yuhan Qian, Chengyi Li, Zizhuo Yu, Hui Huang, Baolian Liu, Wan Chen, Jie Ji*
Energy Engineering, DOI:10.32604/ee.2025.074440
Abstract Under extreme weather conditions (such as hurricanes and heatwaves causing sudden drops in renewable energy output and surges in load), microgrid operations face severe challenges due to the uncertainty of renewable energy and load fluctuations. Although existing research has focused on microgrid optimal scheduling or electric vehicle integration, there has not yet been a systematic approach to multi-timescale scheduling that combines electric vehicle fleets under extreme weather scenarios, and particularly, explicit modeling of weather events and their impact on component failure rates and transmission lines is lacking. This paper proposes, for the first time, a… More >
Open Access
ARTICLE
Serhiy Serbin1,*, Bohdan Lychko2, Kateryna Burunsuz1
Energy Engineering, DOI:10.32604/ee.2026.076966
（This article belongs to the Special Issue: Selected Papers from the SDEWES 2025 Conference on Sustainable Development of Energy, Water and Environment Systems)
Abstract This study investigates the use of ammonia as a carbon-free fuel for gas turbines in decarbonized hybrid energy systems. The objective is to predict the emission characteristics of a gas turbine combustion chamber operating on gaseous ammonia by employing detailed combustion kinetics. The chamber is modeled as a network of chemical reactors to simulate the primary reaction zone and the secondary air-mixing zone. The model is based on solving mass and energy conservation equations for chemically reacting flows. Four high-temperature ammonia oxidation mechanisms, comprising 71 to 286 chemical reactions, were used as kinetic schemes. New More >
Open Access
ARTICLE
Yurong Zhao, Daozhi Chen*, Yu Yin*
Energy Engineering, DOI:10.32604/ee.2026.075847
Abstract In order to investigate the impacts of government policy and market environment on the development of renewable energy, this paper constructs a computable general equilibrium (CGE) model to simulate the impacts of policy scenarios, market scenarios and policy-market scenarios on renewable energy output and investment, energy structure, economy and environment based on China’s input-output extension table in 2020. The results show that: the subsidy can optimize the energy structure and power structure, and non-hydropower renewable energy represented by wind power and solar power will become a new force of energy supply in China; the market… More >
Open Access
ARTICLE
Fukang Zhang, Yang Wang*, Runtian Tang, Zhixin Yun
Energy Engineering, DOI:10.32604/ee.2026.077390
Abstract The large-scale integration of electric vehicle (EV) and exchange stations (EC) into distribution networks introduces strong spatiotemporal load fluctuations and charging capacity constraints, leading to frequent voltage violations and reduced control flexibility. Traditional centralized control approaches face critical limitations, including high communication latency and computational complexity. To address these challenges, this paper proposes a Hybrid Intelligence (HI)-driven framework for distribution networks, which explicitly considers EV/EC charging power limits, cluster-level resource balance, and voltage security constraints. By incorporating spatiotemporal characteristics with intelligent optimization techniques, a Variant Monte Carlo Sampling (VMCS) algorithm is developed to generate the… More >
Open Access
ARTICLE
Wenbiao Li1,2, Shengxuan Sun3,*, Cheng Liu1, Yuchi Zhang1, Yu Qi4, Yuhang Li1
Energy Engineering, DOI:10.32604/ee.2026.075762
Abstract To address voltage fluctuations caused by high-penetration wind power integration, this paper proposes a hybrid reactive power compensation strategy based on Sample Entropy-improved Symplectic Geometric Mode Decomposition (SE-improved SGMD) for smoothing wind power output. The innovation lies in enhancing SGMD by introducing SE to quantitatively evaluate the complexity of decomposed Symplectic Geometry Components (SGCs). This improvement enables adaptive reconstruction of high-, medium-, and low-frequency components from system unbalanced reactive power, effectively overcoming modal aliasing and subjective parameter dependency inherent in conventional methods like Empirical Mode Decomposition (EMD) and Variational Mode Decomposition (VMD). The reconstructed components… More >
Open Access
ARTICLE
Hao Yang1,*, Shuo Feng1, Bo Jin1, Fang Shi2, Zhenglong Sun1, Xiaohan Shi2
Energy Engineering, DOI:10.32604/ee.2026.077417
Abstract To ensure secure post-fault frequency ride-through in modern power systems, the grid codes specify strict frequency recovery criterion (FRC) for different regional power systems. In response to the FRC, this paper proposes a decentralized adaptive load shedding strategy to enhance frequency recovery. First, a Markov decision process (MDP) is constructed to characterize the load shedding control procedure for frequency control. The frequency evolution status used to decide load shedding actions is extracted based on the FRC, which includes the magnitude deviation and the recovery time deviation of bus frequency. The load shedding amount and time… More >
Open Access
ARTICLE
Qiang Li1, Yue Sun2, Jingbo Wang1, Xingxu Zhu2, Cuiping Li2, Junhui Li2,*
Energy Engineering, DOI:10.32604/ee.2026.077140
（This article belongs to the Special Issue: New Energy and Energy Storage System)
Abstract During the process of energy storage clusters participating in power system Automatic Generation Control (AGC), the rational allocation of command power directly impacts the execution effectiveness of frequency regulation commands. Most existing strategies allocate power based on the proportional rated power, without considering the differences in capacity and power among diverse types of energy storage units. This can easily cause the State of Charge (SOC) of some energy storage stations to rapidly exceed limits, leading to output limitation, significant command tracking errors, and ultimately compromising system stability. To address the aforementioned issues, this paper proposes… More >
Open Access
ARTICLE
Xiaolan Li1,2, Yanting Wang1,2,*
Energy Engineering, DOI:10.32604/ee.2026.076417
（This article belongs to the Special Issue: Advances in Renewable Energy Systems: Integrating Machine Learning for Enhanced Efficiency and Optimization)
Abstract To address the operational challenges of power systems with high renewable penetration, this research targets the non-stationarity and stochasticity of wind power. A novel hybrid framework for probabilistic forecasting and risk assessment is proposed. Initially, Empirical Mode Decomposition (EMD) adaptively decomposes the raw power signal into multi-scale Intrinsic Mode Functions (IMFs) and a residual trend, effectively segregating temporal features and reducing complexity. These components are then fused with historical data to form a comprehensive input. The core predictor is a Bidirectional Gated Recurrent Unit (BiGRU) network enhanced with a Temporal Attention (TA) mechanism. The BiGRU… More >
Open Access
ARTICLE
Dongfeng Yang1, Zibin Yang1, Xiaojun Liu1,*, Chao Jiang1, Hexiang Niu1, Gang Huang2
Energy Engineering, DOI:10.32604/ee.2026.076060
Abstract With the continuous integration of high-proportion renewable energy into islanded microgrids, these systems face the dual challenges of fluctuations in wind and solar power output and seasonal imbalances in energy demand. In isolated grid environments, scalable energy storage technology has become a critical solution to address renewable energy curtailment and insufficient system regulation capacity. However, a single storage technology struggles to economically accommodate the full spectrum of temporal fluctuations, ranging from intra-day variations to seasonal imbalances. To overcome this limitation, this study proposes a temporally driven collaborative planning method for electricity-ammonia-thermal energy storage capacity. By… More >
Open Access
ARTICLE
Wei Yin1,*, Jun Wang1, Ming Tong1, Zhijun Chen1, Ke Zhang1, Meiqing Huang2, Ran Gu2, Keman Lin2
Energy Engineering, DOI:10.32604/ee.2026.075066
（This article belongs to the Special Issue: Operation and Control of Grid-connected New Energy and Emerging Loads)
Abstract With the high penetration of renewable energy and the rapid development of AC/DC (Alternating Current/Direct Current) hybrid power grid, the power grid is confronted with challenges such as frequent voltage fluctuations and insufficient dynamic reactive power reserves. Full utilization of unified power flow controller (UPFC) in dynamic voltage regulation is of great significance for mitigating voltage excursions of the power grid. This paper proposes a double-time-scale dynamic reactive power optimization method for the AC/DC hybrid power grid with UPFC. A control framework for reactive power optimization of slow-time-scale and fast-time-scale is constructed incorporating the LCC-HVDC… More >
Open Access
ARTICLE
Yunlong Li1,*, Yuer Zhao1, Li Pan2, Huimin Zhang1, Jun Wang1
Energy Engineering, DOI:10.32604/ee.2026.078123
（This article belongs to the Special Issue: Neutronic and Thermal-Hydraulic Analysis of Advanced Nuclear Reactors)
Abstract Micro Gas-Cooled Reactor (MGCR) has garnered attention in relevant domains, owing to its advantages of miniaturization and transportability, which is capable of providing stable electrical power to off-grid and special regions. As a typical multi-physics coupled system, a dynamic model for the MGCR integrating nuclear, thermal-hydraulic, mechanical, and electrical subsystems was developed in this study using the multi-physics modeling language Modelica. Steady-state validation results indicate that the maximum deviation between the simulated values and the design parameters is merely 1.05%. Meanwhile, transient validation demonstrates a high degree of consistency with the outcomes generated by the… More >
Open Access
ARTICLE
Dong Liu1, Xinyu Li1, Yuanqiang Zhao1, Jinhuan Liu1, Xiangfei Kong2,*
Energy Engineering, DOI:10.32604/ee.2026.077639
（This article belongs to the Special Issue: Integrated Renewable Energy Systems for Heating, Cooling, Power Generation and Energy Management)
Abstract Despite the significant carbon dioxide emissions associated with the combustion of gas-fired boilers, they remain widely used in modern heating systems. The integration of gas-fired boilers with solar thermal utilization systems enables the synergistic use of traditional and sustainable energy sources, offering an effective pathway for energy conservation and carbon reduction in the heating sector. This study innovatively proposes an advanced predictive control strategy that combines mass flow regulation with artificial neural network modeling. This approach allows for real-time hourly control of the system’s thermal output, effectively addressing the limitations of traditional control strategies that… More >
Open Access
ARTICLE
Aimable Ngendahayo1,*, Adrià Junyent-Ferré2, Joan Marc Rodriguez Bernuz3
Energy Engineering, DOI:10.32604/ee.2026.077594
（This article belongs to the Special Issue: Renewable Energy Community (REC) Engineering towards Sustainable Development and Energy Poverty Reduction)
Abstract Bugesera, a historically drought-prone region in Rwanda, is undergoing transformation through investment in modern irrigation and sustainable agricultural practices. However, extending the national electrical grid to numerous dispersed smallholder farms poses a major challenge. The persistent water scarcity and rising conventional energy costs necessitate the development of innovative and sustainable solutions. This study investigates the use of photovoltaic (PV) pumping systems as a green energy alternative for off-grid rural areas, supporting both agricultural irrigation and domestic water supply. A model system serving five one-hectare market-gardening plots and 25 inhabitants was analyzed, with a total daily… More >
Open Access
ARTICLE
Limeng Wang, Haonan Shen*, Xingchao Chai, Saihang Li
Energy Engineering, DOI:10.32604/ee.2026.078006
（This article belongs to the Special Issue: Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation)
Abstract Under the “dual-carbon” strategic goal, in order to improve the economy, a low-carbon and multi-energy coupling of integrated energy system (IES), this paper proposes an optimal scheduling method of the integrated energy system considering low-carbon demand response and multiple utilization of hydrogen energy. Initially, power-to-gas (P2G) is coupled with carbon capture to achieve carbon recovery and reuse. Building upon the conventional P2G framework, this study develops an expanded hydrogen-energy utilization scheme that integrates hydrogen fuel cells, a hydrogen tank, and a gas-fired combined heat and power (CHP) unit operating with hydrogen blending, thereby fully harnessing… More >
Open Access
ARTICLE
Xiang Ding1,2,3, Huai Chen1,3, Wenfeng Gao1,2,3,*, Baihong Liu1,3, Qiong Li1,3
Energy Engineering, DOI:10.32604/ee.2026.076058
Abstract Building sectors in China contributes more than 40% of the total national energy consumption, and thus efficient control of energy is important in meeting the 2-carbon target. This paper proposes QEMES–ASHP (Quantum-Enhanced Multi-Physics Energy Simulation with Air Source Heat Pump integration) as a real-time platform, combining thermal, electrical, and fluid dynamics modelling with adaptive control using AI. The main innovations of the framework include: (i) real-time multi-physics coupling, in which modelling heat–power–airflow interactions under dynamic climate conditions, (ii) machine learned system switching in solar–ASHP–PCM systems, and (iii) fractal-based time modelling, which uses a Brownian motion… More >
Open Access
ARTICLE
Asma Nousheen1, Silvia Peruccacci2, Cosimo Magazzino3,4,5,*
Energy Engineering, DOI:10.32604/ee.2026.076916
（This article belongs to the Special Issue: Advancing Carbon Mitigation Strategies for a Sustainable Future)
Abstract Green growth has revolutionized society by reducing carbon dioxide (CO2) emissions, intensifying energy efficiency, and promoting environmentally friendly technologies and energy utilization, eventually leading to sustainable economic development. However, research on the intricate relationship between green growth and CO2 emissions is limited. This study aims to evaluate the impact of green growth, Information and Communication Technology (ICT), renewable energy, and population on environmental sustainability for a panel of 20 OECD countries from 2000 to 2023. Cointegration regression methods (Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Pooled Mean Group-AutoRegressive Distributed Lags) and pairwise panel More >
Open Access
ARTICLE
Pingzhen Xu, Xin Shen*
Energy Engineering, DOI:10.32604/ee.2026.076327
（This article belongs to the Special Issue: Bridging Renewable Energy Technologies and Marine Resources Toward Integrated Strategies for a Resilient Blue Economy)
Abstract In the context of global climate change, increasing energy security challenges, and marine ecological degradation, advancing the intelligent transformation of industrial systems and accelerating the development of marine renewable energy have become crucial pathways to achieving low-carbon growth and building a sustainable blue economy. Industrial intelligence plays a key role in supporting marine energy development through intelligent manufacturing and smart operation and maintenance technologies. Drawing on data from 30 provinces in China between 2011 and 2022, this study employs a structural equation model to systematically examine the impact mechanism of industrial intelligence on carbon emissions. More >
Open Access
ARTICLE
Lei Shen1,2, Qiang Gao1, Shanyun Gu1, Wei Li1, Jun Li1, Jianquan Li1, Ruyi Xia1, Jie Ji2,*
Energy Engineering, DOI:10.32604/ee.2026.075509
Abstract Aiming at the contradiction between green energy consumption and diesel dependence in temporary construction camps under the condition of “weak data-weak communication”, this paper puts forward a collaborative framework of off-grid light storage and firewood storage with tight coupling of “prediction-scheduling”. The prediction layer constructs a lightweight IOOA-CNN-BiLSTM-Markov model: CNN extracts the spatial characteristics of tower crane shadow and cloud cluster, BiLSTM captures the bidirectional time series dependence, Markov residual compensates the non-stationary disturbance, and uses the improved Osprey algorithm to complete the small sample superparameter self-tuning at the edge of ARM, thus realizing the… More >
Open Access
ARTICLE
Wei Wang1,2, Xiaogang Li1,2, Binbin Shi1,2, Kai Shen3,*, Wentao Zhu1,2, Xing Hong1,2, Hao Bai1,2
Energy Engineering, DOI:10.32604/ee.2026.075896
Abstract Coalbed methane (CBM) reservoirs are typically characterized by ultra-low permeability, pronounced heterogeneity, and strong stress sensitivity. A primary challenge in horizontal-well hydraulic fracturing is to accurately characterize complex fracture morphology and efficiently simulate fracture–matrix flow, which is essential for coordinated optimization of production performance and economics. This study proposes the Fracture Connection Element Method (FCEM), which departs from conventional grid-based discretization by representing both matrix and fractures as nodes. Matrix nodes are generated via Poisson-disk sampling to achieve spatially uniform coverage. The hydraulic-fracture network is converted into a node–edge topology using Dijkstra’s shortest-path algorithm, preserving… More >
Open Access
ARTICLE
Yonghua Yang1, Xiaolan Teng1, Yulong Zhang1, Li Lu1, Wenjun Xu2,3,*, Yuanai Liao2,3
Energy Engineering, DOI:10.32604/ee.2026.076993
（This article belongs to the Special Issue: Enhanced Oil and Gas Recovery in Unconventional Reservoirs)
Abstract Tight sandstone gas reservoirs have significant development potential; however, due to strong reservoir tightness and pronounced heterogeneity, conventional hydraulic fracturing is often constrained by water-blocking effects and insufficient formation energy, resulting in limited stimulation performance. To address these challenges, this study focuses on a tight sandstone gas reservoir in western Sichuan and develops a triple-medium gas–water two-phase productivity prediction model coupling the main fracture, stimulated reservoir volume (SRV), and matrix, in which key physical mechanisms such as fracture geometry, gas slippage effects, stress sensitivity, and capillary forces are systematically considered. Based on this model, an… More >
Open Access
ARTICLE
Saddam Husain Dhobi1,2,*, Kishori Yadav2, Suresh Prasad Gupta2,*, Jeevan Jyoti Nakarmi1, Ajay Kumar Jha3
Energy Engineering, DOI:10.32604/ee.2026.076691
（This article belongs to the Special Issue: Green Energy Engineering: Optimizing Systems for Net Zero Emissions)
Abstract Increasing requirements on clean, efficient, and sustainable energy technologies have raised interest in hydrogen fuel cells, particularly proton exchange membrane fuel cells (PEMFCs), which are operationally characterized by high efficiency with zero emissions. The objective of this work is to study the scattering behaviors of particles participating in scattering under various conditions (energy, efficiency, temperature, cell voltage) at/around the electrode of PEMFC theoretically. For this, we developed a model using a scattering matrix, the Kroll-Watson approximation, the thermal wave function of an electron in a laser field, interaction potential, and Bessel functions to study the… More >
Open Access
ARTICLE
Xiaobiao Fu1, Jing Zhang2,*, Baoju Li1, Guanqun Zhuang1, Yiming Li1, Chao Pan2
Energy Engineering, DOI:10.32604/ee.2026.076430
（This article belongs to the Special Issue: Integrated Renewable Energy Systems for Heating, Cooling, Power Generation and Energy Management)
Abstract To enhance the wind-solar accommodation rate and the low-carbon operation of integrated energy system (IES), the utilization potential of waste heat is explored for participation in heterogeneous energy flow interaction. Firstly, a waste heat cascade utilization system is proposed. The relationship between waste heat temperature and carbon emissions of the system is investigated. Building on this, the time-varying characteristics of waste heat temperature are analyzed in accordance with carbon emission variation. And an intraday waste heat cascade utilization strategy is formulated. Then, a comprehensive benefit evaluation model is constructed with economic costs, wind-solar accommodation rate, More >
Open Access
ARTICLE
Hongwei Ji, Zhenyu Lin, Xingya Chen*
Energy Engineering, DOI:10.32604/ee.2026.076052
Abstract With advancing science and technology, traditional fossil-fuel vehicles are being replaced by new energy vehicles. Hydrogen fuel cell vehicles are hailed as their ultimate form for zero-pollution operation and water-only emission. The air compressor, a core component of their air supply system, directly impacts overall system efficiency. This paper calculates the initial parameters to obtain detailed impeller dimensions and performs simulations. For the nozzle part, MATLAB is used for programming to calculate detailed curve coordinates based on parameters. After verifying the simulation, the number of nozzle blades, nozzle blade outlet angle, nozzle inlet radius, and… More >
Open Access
ARTICLE
Yixuan Wang1, Yanchao Li1, Qiang Feng1, Haicheng Sun2, Guchang Zhang3, Zhiming Zhao1, Jianfeng Xiao1, Jingyun Huang1, Tiankui Guo3,*
Energy Engineering, DOI:10.32604/ee.2026.076849
Abstract Achieving uniform proppant distribution among multiple perforation clusters is essential for the effectiveness of horizontal well fracturing, yet remains challenging due to complex solid-liquid transport mechanisms. This study presents a comprehensive numerical investigation using Computational Fluid Dynamics to analyze proppant transport heterogeneity in a full-scale 90-m horizontal wellbore with five perforation clusters. An Eulerian-Eulerian multiphase model is employed to simulate proppant transport and settling in the wellbore and perforations. The effects of key operational and geometric parameters—including injection rate, proppant concentration and size, fluid viscosity and phase angle—are systematically evaluated. Results demonstrate that flow rate… More >
Open Access
ARTICLE
Fabiano Thulu, Zeyun Wu*
Energy Engineering, DOI:10.32604/ee.2026.076328
（This article belongs to the Special Issue: Neutronic and Thermal-Hydraulic Analysis of Advanced Nuclear Reactors)
Abstract Real-time prediction of temperature distribution in the pressurizer walls of Pressurized Water Reactors (PWRs) during severe accidents, such as Station Blackout (SBO) and Loss-of-Coolant Accident (LOCA) is vital for structural integrity assessment. However, conventional thermal-hydraulic simulations used for such predictions are computationally intensive, limiting their applicability for real-time analysis. This study develops and compares three surrogate models: Polynomial Regression, Deep Neural Network (DNN), and a Physics-Informed Neural Network (PINN). Thermal-hydraulic simulation data generated by RELAP5-3D are integrated with physics-constrained learning techniques to model transient heat conduction in the pressurizer wall. The internal wall temperature evolution… More >
Open Access
ARTICLE
Zhongjin Shi#, Zhe Zang#, Chong Wang#, Yue Yang*
Energy Engineering, DOI:10.32604/ee.2026.074923
Abstract To address the critical challenges of power fluctuations and the imperative for efficient reactive power optimization in distribution networks with high photovoltaic (PV) penetration, this study proposes an innovative solution: a robust reactive power optimization approach that integrates VMD-LSTM-based PV power forecasting with the advanced Lion Swarm Optimization (LSO) algorithm. The methodology commences by employing Variational Mode Decomposition (VMD) to decompose the PV power sequence into distinct modal components in a seamless manner. Each modal component is subsequently modeled using a dedicated forecasting framework built on Long Short-Term Memory (LSTM) networks, with the LSO algorithm… More >
Open Access
ARTICLE
Hongbo Liu, Jingzhou Zhu, Li Sun*, Fanjun Zeng
Energy Engineering, DOI:10.32604/ee.2026.075768
Abstract This paper tackles the challenge of balancing computational efficiency with analytical rigor in Probabilistic Power Flow (PPF) analysis for power systems with integrated wind power. We propose an enhanced steady-state security region (SSR) assessment method based on PPF theory. The methodology first employs a hybrid Monte Carlo technique that integrates Latin Hypercube Sampling (LHS) with Importance Sampling (IS) to compute and analyze the probabilistic power flow distribution. This hybrid strategy ensures comprehensive global coverage while intensively sampling critical risk regions, thereby improving both computational efficiency and accuracy. Subsequently, a fast-search model for the SSR is… More >
Open Access
ARTICLE
Xiaoming Yu1, Peng Wang1, Jun Wang1, Zhijun Chen1, Ke Zhang1, Duicheng Zhao2, Jiapeng Shen2, Chuyang Wang2,*, Li Zhang2
Energy Engineering, DOI:10.32604/ee.2026.073475
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract Electrolytic capacitors in Modular Multilevel Converter-based Unified Power Flow Controllers (MMC-UPFC) are prone to parameter degradation, significantly affecting system reliability. Accurate identification of their degradation parameters—capacitance (C) and equivalent series resistance (ESR)—is essential for equipment health management. This study proposes a non-intrusive degradation parameter identification method for electrolytic capacitors in MMC-UPFC full-bridge submodules based on digital twin technology and an improved intelligent optimization algorithm. First, the degradation mechanism of electrolytic capacitors under long-term operational conditions is systematically analyzed. Second, a high-fidelity digital twin model integrating the main circuit, sampling circuit, and modulation circuit of the… More >
Open Access
ARTICLE
Yihua Zhu1, Chao Luo1, Yuxia Tang1, Renxin Yang2,*
Energy Engineering, DOI:10.32604/ee.2026.075636
Abstract With the rapid development of renewable energy, the proportion of wind power generation in modern power systems has been steadily increasing. Benefiting from the high controllability of power electronic converters, wind energy can be efficiently transmitted to the grid through power conversion stages. However, the reliability of wind turbine systems is closely related to the thermal stress and degradation of power semiconductor devices. The diversity of actual operating conditions and the rapid fluctuations of grid load bring significant challenges to their safe and stable operation. To address these issues, this paper establishes an online electro-thermal… More >
Open Access
ARTICLE
Xuefeng Yang1,2, Chunyu Ren1,2, Deliang Zhang1,2, Huaicai Fan1,2, Yue Chen1,2, Yue Yang1,2, Yan Zhang1,2, Shuai Wu1,2, Baoyun Zhang3,*, Xin Zhao3
Energy Engineering, DOI:10.32604/ee.2025.074956
（This article belongs to the Special Issue: Progress and Prospects of Hydraulic Fracture Network Morphology Characterization, Flow Simulation and Optimization Technology for Unconventional Oil and Gas Reservoirs)
Abstract In southern Sichuan’s deep shale gas development, multi-stage fractured horizontal wells are commonly used. Evaluating fracturing results is challenging due to complex fracture networks. This study classifies fracture systems into four types: single-wing, bi-wing, branched, and serial fractures. A discrete fracture model (DFM) combined with matrix-fracture flow is used to establish a single-stage well testing interpretation model. To address multi-solution issues in well testing, an equivalent fracture network model based on a trilinear flow model is proposed, adjusting crossflow coefficients and the fracture network volume ratio. The study finds significant differences in the pressure derivative More >
Open Access
ARTICLE
Kewen Li, Xiaoyong Yu, Shifeng Ou*, Jueming Pan
Energy Engineering, DOI:10.32604/ee.2025.073825
（This article belongs to the Special Issue: Advanced Analytics on Energy Systems)
Abstract The increasing integration of renewable energy sources (e.g., wind and solar power) into distribution grids and the development of new, source–grid–load–storage coordinated power systems have led to a substantial expansion in the volume of situational awareness data in the distribution networks. Moreover, the transmission of low-voltage distribution measurement data via a power line carrier (PLC) is often susceptible to packet loss and, consequently, data gaps. To address these issues, this paper proposes a data completion method using a conditional generative adversarial network (CGAN) integrated with a three-dimensional convolutional neural network (3D-CNN). This approach leverages the… More >
Open Access
ARTICLE
Xiang Xiao, Peng Zhang*, Yuan Yuan, Zhiyuan Feng, Kui Hu, Yuan Xu, Yunhuang Zhang, Guoming Liu
Energy Engineering, DOI:10.32604/ee.2026.073741
（This article belongs to the Special Issue: Neutronic and Thermal-Hydraulic Analysis of Advanced Nuclear Reactors)
Abstract As a promising solution to the challenges of future clean and reliable energy supply, the Gas-Cooled Micro-Reactor (GCMR) has attracted increasing attention due to its potential for decentralized power generation, carbon-free operation, and flexible deployment in remote or extreme environments. As a novel reactor concept, the GCMR offers advantages such as compact size, inherent safety, and high thermal efficiency. However, conventional core calculation methods face significant challenges due to the complex geometric configurations, heterogeneous material distribution, and pronounced neutron leakage characteristics of the GCMR. This study proposes a diffusion-based homogenization method for GCMR analysis. First,… More >
Open Access
ARTICLE
Yinfeng Ma1, Kuan Zhang1,*, Youxin Chen1, Nian Liu1, Zhi Xu2, Min Ren2
Energy Engineering, DOI:10.32604/ee.2026.077169
（This article belongs to the Special Issue: Next-Generation Distribution System Planning, Operation, and Control)
Abstract With the advancement of the Rural Revitalization Strategy and the “Dual Carbon” goals, rural energy systems are exhibiting pronounced multi-energy coupling, a high penetration of renewable energy, and strong load randomness, placing higher demands on the construction of source-load scenarios across multiple time scales. Addressing the limitations of traditional statistical models in generating high-quality short-term source-load scenarios and the tendency of deep learning methods to overlook medium- to long-term seasonal evolution patterns, this paper proposes a hybrid data- and model-driven method for constructing multi-energy source-load scenarios in rural systems. This method establishes a multi-time-scale generation… More >
Open Access
ARTICLE
Rongyi Niu1,2, Chong Li1,2,*, Gang Gu1,2, Qunhui Hu1,2
Energy Engineering, DOI:10.32604/ee.2026.076567
Abstract To address the operational complexity caused by the high proportion of new energy integration into distribution networks, a multilevel resource-coordinated operation strategy based on an improved whale optimization algorithm (improved WOA) is proposed for active distribution networks (ADNs). A bilevel optimization model is established to ensure the economic and safe operation of ADNs. The upper level is used to minimize the total system operation cost, while the lower level is used to optimize the power balance. Subsequently, the improved WOA, integrated with an adaptive weight and chaotic disturbance mechanisms, is used to solve the bilevel… More >
Open Access
ARTICLE
Xintong Mao1, Yechi Xu1, Yaowen Sun2, Zhihan Liu1, Yumeng Wang1, Chuyang Wang2,*
Energy Engineering, DOI:10.32604/ee.2026.076436
（This article belongs to the Special Issue: Operation and Control of Grid-connected New Energy and Emerging Loads)
Abstract The self-adaption STATCOM and line commutation converter (SLCC) system based on the static var generator and filter (SVF) utilizes the compensation capability of the SVF to reduce the commutation process’s dependence on the AC grid, thereby enhancing the SLCC’s ability to resist commutation failure. However, existing SLCC control strategies have not fully considered the boundary conditions for the safe and stable operation of the SVF (i.e., the SVF withstand capability), which limits or even deteriorates the ability of the SVF to provide commutation support for the SLCC under AC grid voltage fault conditions. To address… More >
Open Access
ARTICLE
Yuanxiang Luo, Xinmeng Pan*, Xuyang Gao
Energy Engineering, DOI:10.32604/ee.2026.076019
（This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)
Abstract The integration of a high proportion of renewable energy sources via power electronic devices poses significant challenges to power systems. Their grid-connection characteristics differ considerably from those of synchronous generators, leading to a reduction in system inertia. Furthermore, the complex interactions between renewable energy units and the power grid substantially impact the transient stability of the system. Based on the virtual synchronous control characteristics of grid-forming wind turbines (GWT), this paper proposes an adaptive control method to enhance system transient stability. Firstly, a transient stability model for integrating GWT into conventional power systems is established,… More >
Open Access
ARTICLE
Zhan Lv*, Lan Lan, Zijian Hu, Honghua Xu, Hong Zhu, Jiehua Hou
Energy Engineering, DOI:10.32604/ee.2026.075769
（This article belongs to the Special Issue: Digital and Intelligent Planning and Operation Technologies for Flexible Distribution Network)
Abstract To fully utilize the diverse source-grid-load-storage flexible resources integrated in new distribution networks, this paper proposes an optimal load transfer strategy that coordinates distributed generator island operation with network reconfiguration. Following a fault event, the strategy prioritizes the black-start capability of distributed generators and establishes island operation model to maximize and locally restore critical loads while respecting island operational constraints. To solve this model, the actual topology of the new distribution network is abstracted as a tree structure, and an improved Kruskal algorithm is employed to derive the minimum spanning tree, achieving optimal island partition… More >
Open Access
ARTICLE
Wenqiang Xie*, Xiaolong Xiao, Fangfang Zhu, Ziran Guo, Xiaoxing Lu
Energy Engineering, DOI:10.32604/ee.2025.075298
（This article belongs to the Special Issue: Artificial Intelligence-Driven Collaborative Optimization of Electric Vehicle, Charging Station and Grid: Challenges and Opportunities)
Abstract In the framework of the comprehensive energy transition, the proton exchange membrane fuel cell (PEMFC) powered by renewable energy emerges as a promising alternative, particularly with relevance to applications like electric vehicles (EVs), where clean and efficient power sources are crucial. However, the accurate prediction of PEMFC performance degradation poses significant challenges due to the combined effects of complex and variable aging mechanisms and operational conditions, which are especially critical in the context of EV applications where reliability and durability directly impact vehicle performance and user safety. These challenges pose notable constraints on the feasibility… More >
Open Access
ARTICLE
Yunlong Du1, Shuyi Zhuang2,*, Zhigang Ye2, Qiangsheng Bu2, Yun Chai1, Yuanbing Wang3
Energy Engineering, DOI:10.32604/ee.2025.074702
（This article belongs to the Special Issue: Advanced Analytics on Energy Systems)
Abstract Under the dual challenges of global warming and energy transition, improving the short-term forecasting accuracy of surface solar radiation is of great practical importance for photovoltaic (PV) power integration. In this study, a short-term solar radiation forecasting model based on the XGBoost machine learning algorithm was developed for Jiangsu Province by integrating multispectral data from the Fengyun-4A (FY-4A) geostationary satellite with ground-based meteorological observations. The model incorporated 18 input features—including satellite reflectance, solar zenith angle, normalized difference vegetation index (NDVI), elevation, and land-cover data—to dynamically predict ground horizontal irradiance (GHI) with 0–4 h lead times.… More >
Open Access
ARTICLE
Meng Zhang1, Lijuan Zhang2, Jie Zhang1, Shiliang Miao2, Jiangong Yang2, Yajun Zhao1,*, Feifei Bu1
Energy Engineering, DOI:10.32604/ee.2025.074465
Abstract Conventional electric servo drive systems suffer from high common-mode voltage (CMV) due to the use of zero vectors in Space Vector Pulse Width Modulation (SVPWM). To mitigate this issue, this paper proposes an inverted SVPWM (I-SVPWM) strategy. By simply inverting the switching actions of a specific phase, this strategy avoids the use of zero vectors and achieves an effect similar to Active Zero-State PWM (AZSPWM), thereby effectively suppressing common-mode voltage. Compared with AZSPWM, the proposed method eliminates the need to recalculate vector action times or design new switching sequences. It can be seamlessly implemented by… More >
Open Access
ARTICLE
Xinhao Lin1, Lei Yu1, Shuyin Duan1, Yinliang Liu1, Lvzerui Yuan1, Xiao Chen1,*, Yiqing Lian2
Energy Engineering, DOI:10.32604/ee.2026.072845
（This article belongs to the Special Issue: Next-Generation Distribution System Planning, Operation, and Control)
Abstract To address the operational challenges posed by renewable energy generation uncertainty and load fluctuations in DC microgrids, this paper proposes a hierarchical coordinated optimization control strategy for electricity-hydrogen hybrid DC microgrids (EH-DC-MG). The strategy aims to leverage the synergistic advantages of hybrid electricity-hydrogen energy storage to simultaneously achieve multiple objectives, including economic system operation, efficient utilization of renewable energy, and reliable power supply. The upper optimization scheduling layer formulates a mixed-integer linear programming model with the objective of minimizing the total system cost, which incorporates equipment operation and maintenance expenses, battery depreciation, penalties for renewable… More >
Open Access
ARTICLE
Hongsheng Su, Dan Li*, Yuwei Du
Energy Engineering, DOI:10.32604/ee.2025.072397
Abstract When the three-phase grid-connected inverter system is in operation, there are problems of significant switching losses and power losses. At the same time, if the switching frequency is not fixed, it will lead to problems such as a high content of low-order harmonics in the current on the grid side. This paper takes the three-phase grid-connected inverter as the research object and proposes a solution. Establish a mathematical model for the inverter system and analyze the transformation relationships of relevant electrical quantities across different coordinate systems. First, the paper proposes an improved three-vector model predictive… More >
Open Access
REVIEW
Zhen Pan1, Lijuan Huang1, Kaiwen Huang1, Feipeng Huang1, Bo Yang2,*
Energy Engineering, DOI:10.32604/ee.2026.077000
Abstract With the global pursuit of carbon neutrality and the rapid development of marine renewable energy, offshore power transmission has become a key link in the integration of offshore power into onshore power grids. This paper summarizes the current advanced offshore transmission technologies, including high voltage alternating current transmission, high voltage direct current transmission, multi-terminal high voltage direct current transmission, hybrid high voltage direct current transmission, frequency division transmission, offshore overhead line transmission and energy storage transmission system. The application scenarios of various technologies are analyzed in detail: High voltage alternating current transmission is suitable for More >
Open Access
ARTICLE
He Wang, Yuyan Wang, Jing Bian*, Huanan Yu
Energy Engineering, DOI:10.32604/ee.2026.076766
Abstract Addressing the challenges of peak shaving and curtailment caused by integrating a large amount of renewable energy into the grid, this paper proposes an optimized operation method for microgrid electricity-hydrogen hybrid energy storage (EH-HES), which considers electrolyzer arrays and an energy management strategy (EMS). Firstly, the time span of the energy-rich season and the energy-poor season is determined through time series decomposition, and a hydrogen energy storage (HES) operation mode based on seasonal typical scenarios is proposed. Secondly, the key equipment for EH-HES is modeled, including the hybrid electrolyzer arrays model that considers rotation strategy… More >
Open Access
ARTICLE
Xiaolan Li1,2,*, Jinyu Shen1,2, Jinhuang Liang1,2, Yanting Wang1,2
Energy Engineering, DOI:10.32604/ee.2026.076521
Abstract The intrinsic volatility and stochasticity of large-scale wind power generation pose significant challenges to grid stability. To address the limitations of conventional models in capturing strong non-stationarity, this study proposes a novel Multi-Stage Adaptive Forecasting Network (MSAF-Net). The framework features a hierarchical signal refinement strategy coupled with an intelligently optimized hybrid predictor. Initially, input redundancy is minimized via Pearson Correlation Coefficient (PCC) analysis to isolate significant meteorological variables. A two-phase decomposition-reconstruction mechanism is then implemented: the wind power series is first decomposed using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). To optimize the… More >
Open Access
ARTICLE
Wanxing Sheng1, Xiaoyu Yang1, Dongli Jia1, Keyan Liu1, Zewei Chen2,*
Energy Engineering, DOI:10.32604/ee.2026.075810
Abstract Accurate forecasting of electricity consumption patterns is a fundamental task of power demand-side management (DSM), particularly for industrial and commercial users who significantly influence market supply-demand balance and price fluctuations. Traditional forecasting methods, including statistical models and deep learning approaches, often struggle to capture the complex multi-factor, non-linear, and spatio-temporal dependencies inherent in power load data. To address these limitations, this paper introduces GBCTT (GAT-TBA-CNN-TCN), a novel multi-factor load forecasting model. The model integrates a Graph Attention Network (GAT) to dynamically learn spatial dependencies among heterogeneous influencing factors (e.g., temperature, humidity, electricity prices), a Time… More >
Open Access
ARTICLE
Weijia Tang, Qiang Li*, Ningyu Zhang
Energy Engineering, DOI:10.32604/ee.2026.074698
（This article belongs to the Special Issue: Research and Application of Marine Renewable Energy Technologies)
Abstract Large-scale offshore wind farm clusters (OWFCs) have been increasingly connected to the power grid, and requires advanced forecasting models to enhance the prediction accuracy of OWFC’s power output. This paper proposes a multi-source fusion with patch-guided multi-task learning for power prediction of offshore wind farm clusters. Unlike traditional graph-based approaches that rely on predefined topological relationships, which are limited in capturing the highly similar but rapidly changing meteorological conditions among closely spaced offshore farms, the proposed model employs a parameter-sharing multi-task learning network to achieves both independence and correlation among offshore wind farm clusters, followed More >
Open Access
ARTICLE
Shu Zhou, Wenfeng Yang, Guoxing Wu*, Xinming Jiang, Qingmiao Guo
Energy Engineering, DOI:10.32604/ee.2025.072997
（This article belongs to the Special Issue: Advances in Renewable Energy and Storage: Harnessing Hydrocarbon Prediction and Polymetric Materials for Enhanced Efficiency and Sustainability)
Abstract The integration of high-penetration distributed photovoltaic (PV) systems in low-voltage (LV) distribution networks introduces significant challenges, including voltage violations, power quality degradation, and coordination difficulties among multiple distributed energy resources. Grid-forming converters with droop control offer autonomous voltage and frequency regulation capabilities, yet conventional fixed-parameter droop strategies perform poorly in resistance-dominant LV networks under variable PV generation conditions. This paper proposes an adaptive droop control method that dynamically adjusts control parameters to address these challenges. The proposed strategy incorporates three key innovations: (1) power-flow-aware adaptive voltage droop coefficients specifically designed for resistance-dominant networks, (2) a… More >
Open Access
REVIEW
Rajanand Patnaik Narasipuram1,*, Md M. Pasha2, Suresh Badugu3, Saleha Tabassum4, Attuluri R.Vijay Babu5, Bharath Kumar N5, Amit Singh Tandon6
Energy Engineering, DOI:10.32604/ee.2026.076542
（This article belongs to the Special Issue: Advances in Renewable Energy and Storage: Harnessing Hydrocarbon Prediction and Polymetric Materials for Enhanced Efficiency and Sustainability)
Abstract Supercapacitors are increasingly deployed as high power buffers in modern energy systems, yet their broader impact is constrained by limited energy density, fragmented testing practices, and incomplete understanding of lifecycle implications. This article presents a critical, method driven review based on a structured literature survey and explicit inclusion criteria, aggregating quantitative performance data for major electrode families (carbon materials, transition metal oxides, conducting polymers, biomass derived carbons, MXenes, and hybrid composites), electrolytes (aqueous, organic, ionic liquid, and gel/solid state), and device architectures (flexible, micro, solid state, lithium ion capacitors, and structural supercapacitors) under harmonized metrics… More >
Graphic Abstract
Open Access
ARTICLE
Mingqi Liu, Ying Wang*, Wujiang Li, Juyong Cao, Fuyong Yang
Energy Engineering, DOI:10.32604/ee.2026.074783
Abstract Accurately predicting battery life is essential for performance management and system safety. Due to the complexity and diversity of internal mechanisms in lithium-ion batteries, their nonlinear characteristics directly give rise to uncertainty in the battery degradation process. However, most existing prediction methods do not fully account for the uncertainty caused by various factors and only provide a point estimate finally. To address this issue, this paper proposes a new framework that combines Random Forest and Conformal Prediction to predict battery life and quantify the uncertainty of the results. This approach leverages the efficiency of Random… More >
Open Access
ARTICLE
Mingxuan Ji1, Jing Gao1,*, Dantian Zhong1, Yingqi Xu1, Shuxiang Yang1, Zhongxiao Du1, Yingming Liu2
Energy Engineering, DOI:10.32604/ee.2026.074643
Abstract The intermittency of wind power poses severe challenges to the safe and stable operation of power grids, while conventional forecasting models are deficient in prediction accuracy and adaptability to variable weather conditions. To address these issues, this study proposes an adaptive short-term wind power forecasting model integrating affinity propagation (AP) clustering and a black-winged kite algorithm (BKA)-optimized temporal convolutional network-bidirectional long short-term memory (TCN-BiLSTM) hybrid architecture. First, mutual information was employed to screen key meteorological features, and AP clustering categorized historical data into six distinct weather scenarios. A scenario-specific TCN-BiLSTM model was then constructed for… More >
Open Access
ARTICLE
Nan Li1,2,*, Yinan Wang2, Liang Huang3, Yabin Zhu4, Guangyao Zhang5
Energy Engineering, DOI:10.32604/ee.2025.073712
Abstract The large-scale integration of new energy into power systems significantly elevates the risk of instability. To achieve an accurate assessment of power system transient stability, a multi-classification assessment model based on an improved TCN-ResNeXt is proposed. The core of this model lies in a dual-branch structure, which enables the extraction and interactive fusion of dynamic temporal features and spatial features at multiple scales. By integrating the Triplet Attention mechanism, the model enhances focus on key features across the three dimensions of channel, space, and time—effectively boosting the assessment performance of the transient stability multi-classification model.… More >
Open Access
ARTICLE
Qianfeng Wu1, Dabo Xie1, Wenhua Ni2, Junjie Zhou1, Xuantong Lu1, Chengying Ma1, Rongqiang Li2,*, Yang Li2,*
Energy Engineering, DOI:10.32604/ee.2026.073197
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract With the deepening of the power system reform, an increasing number of microgrids are being integrated into the distribution network. In traditional centralized optimization algorithms, the optimal power flow model of the distribution network and the optimal scheduling model of microgrid clusters are directly coupled and solved simultaneously. This process involves extensive information exchange between the upper distribution network system and the lower microgrid clusters, which not only increases the communication burden but also prolongs computation time and raises computational complexity. Moreover, it requires excessive information sharing, making it difficult to achieve limited information exchange… More >
Open Access
ARTICLE
Guanghua He1, Jinlong Qi1,*, Yao Feng1, Jiayi Han1, Heng Chen2, Baoming Huang3, Jiangtao Li3
Energy Engineering, DOI:10.32604/ee.2026.076354
（This article belongs to the Special Issue: Advanced Analytics on Energy Systems)
Abstract The identification of the traveling wave head is an important factor affecting the accuracy of fault traveling wave positioning. In practice, in addition to the attenuation of traveling wave amplitude and rising speed caused by distribution line factors, various traveling wave sensors can also cause transmission distortion of high-frequency traveling wave signals, which in turn affects the calibration of traveling wave arrival time and the accuracy of fault distance measurement. The inversion technology of sensor transmission characteristics using analytical methods has limited ability to reflect factors such as stray capacitance and sensor differences. In comparison,… More >
Open Access
ARTICLE
Yi Pan, Mingshen Wang, Ye Xue, Huiyu Miao, Kemin Dai, Xiaodong Yuan*, Fei Zeng
Energy Engineering, DOI:10.32604/ee.2025.074882
（This article belongs to the Special Issue: Sustainable Transport Technologies and Strategies: Impacts on Energy and Environment)
Abstract Electric vehicles (EVs), characterized by their large-scale deployment and flexible charging–discharging scheduling, represent a growing form of transportation. However, their widespread adoption poses considerable challenges to the security and stability of the power grid during peak charging periods, highlighting the need for effective management of the coupled traffic–grid system. To address this issue, this paper proposes a blockchain-driven optimization model for charging scheduling in dynamic traffic networks. Blockchain technology is introduced to ensure data transparency and security in decentralized decision-making. First, a queuing model integrating the Bureau of Public Roads (BPR) function with the M/M/c/K… More >
Open Access
ARTICLE
Qiang Liu1, Yongqiang Zhou1, Chaoyang Lu2, Zhen Yan1, Yanwen Li1, Gangui Yan2, Yupeng Wang2,*
Energy Engineering, DOI:10.32604/ee.2025.074766
（This article belongs to the Special Issue: New Energy and Energy Storage System)
Abstract Hybrid photovoltaic and energy storage systems play a critical role in enhancing grid stability; however, the sub-synchronous oscillation issues induced by their power electronic interfaces cannot be overlooked. This study proposes a graphical block-based modeling method for a hybrid power generation system composed of grid-following (GFL) photovoltaic and grid-forming (GFM) energy storage units. The method abstracts each system component into graphical modules with clearly defined interfaces, enables intuitive construction in the Matlab/Simulink environment, and utilizes built-in functions to automatically generate global system equations. While ensuring model accuracy, it significantly improves modeling intuitiveness, efficiency, and scalability,… More >
Open Access
ARTICLE
Nantian Huang*, Jingyuan Zhang, Shicheng Ren, Hao Zhang, Bingling Li, Yaoyao Wang
Energy Engineering, DOI:10.32604/ee.2025.072993
Abstract User electricity consumption behavior analysis and multi-load forecasting in integrated energy systems are crucial for system operation and scheduling. Traditional user electricity consumption behavior analysis fails to adequately incorporate meteorological factors, limiting the accuracy of characterizing user electricity consumption patterns. Traditional multi-load forecasting models do not consider the differentiated coupling relationships with meteorological factors across different seasons, which restricts the improvement of forecasting accuracy. To address the above issues, a method integrating data cleaning and meteorological correlation for electricity consumption behavior and multi-dimensional forecasting analysis is proposed. First, the Akima interpolation method is used to… More >
Open Access
ARTICLE
Lizhong Lu1, Guangze Li2, Zheng Yang2,*, Yunjing Liu1,2, Xiaozhuo Guan1, Tiebin Guo1
Energy Engineering, DOI:10.32604/ee.2025.075585
Abstract With the substantial advancement of the manufacturing industry, a large number of new types of loads are being connected to the distribution network via power electronic devices, exacerbating the deterioration of power quality at the Point of Common Coupling and making harmonic problems increasingly severe. Currently, most researchers focus on improving harmonic suppression performance from the perspective of the controller, but they overlook the fact that excessive performance enhancement may lead to issues such as resonance in the distribution network. To address this, this paper proposes an adaptive harmonic compensation strategy for scenarios with limited… More >
Open Access
ARTICLE
Jiyuan Liao1, Jiangyan Zhao2,*, Xin Li3, Changmao Liu1, Banghong Tang1, Zihan Ling3
Energy Engineering, DOI:10.32604/ee.2025.074667
（This article belongs to the Special Issue: Advanced Energy Management and Process Optimization in Industrial Manufacturing: Towards Smart, Sustainable, and Efficient Production Systems)
Abstract To address the uncertainty and volatility of renewable energy while meeting the requirements of low-carbon economic operation, this paper proposes a two-stage robust optimal dispatch model for an integrated wind-solar-hydro-thermal-storage energy system with coupled power-to-gas (P2G) and carbon capture system (CCS). First, a mathematical model of the integrated wind-solar-hydro-thermal-storage energy system with P2G-CCS coupling is developed to promote internal carbon cycling and enhance the capability to accommodate renewable energy. Second, the scheduling problem is formulated as a two-stage robust optimization model. A cardinality-based uncertainty set is adopted to model deviations in renewable energy output, and… More >
Open Access
ARTICLE
Peng Wang1,2, Zhiying Gao1,2,*, Yongyan Chen1, Rina Su1,2, Yefei Bai2, Jianlong Ma1,2, Tianhao Zhang1
Energy Engineering, DOI:10.32604/ee.2025.073862
Abstract We propose a novel procedure, Time-Domain De-Dopplerized Orthogonal Matching Pursuit deconvolution approach for the mapping of acoustic sources (TD-OMP-DAMAS), for separating aerodynamic noise sources distributed across wind turbine blades (WTB), a task that is typically hindered by mutual interference and spatial mixing. The proposed procedure is a two-stage, hybrid de-Doppler/sparse-reconstruction algorithm based on time-domain de-Doppler (TD, Stage 1) and an orthogonal matching pursuit (OMP)-based deconvolution scheme (Stage 2), enabling sparse-reconstruction techniques to be effectively applied in rotating-source scenarios. The method is validated using both simulated rotating-source data and wind-tunnel measurements, and its performance is systematically… More >
Open Access
ARTICLE
Zhenjie Yuan, HaiLong Yu*, Hongjun Cao
Energy Engineering, DOI:10.32604/ee.2025.076483
Abstract Low-NOx combustion of natural gas is essential for cleaner industrial heat supply under increasingly strict emission regulations. However, many existing low-NOx swirl burners still rely on single-mechanism control and suffer trade-offs between temperature suppression, combustion stability, and mixing uniformity. This work develops and numerically optimizes a structurally integrated cyclonic-impingement natural-gas burner that combines four rows of impinging secondary-air jets with four axially deflected main fuel nozzles, realizing a coupled swirl-impingement-staging mechanism that differs fundamentally from conventional swirl burners employing only geometric swirl or simple air staging. Validated three-dimensional RANS CFD simulations (realizable k-ε turbulence model,… More >
Open Access
ARTICLE
Lin Chen1, Anqi Zhao2, Yunpei Zhang1, Sai-Mi-La XiaFuKaiTi1, Yao Qin1, Chuan Wang1, Gang Chen2, Jiqiang Li2, Shilai Hu2,*
Energy Engineering, DOI:10.32604/ee.2025.075878
（This article belongs to the Special Issue: Progress and Prospects of Hydraulic Fracture Network Morphology Characterization, Flow Simulation and Optimization Technology for Unconventional Oil and Gas Reservoirs)
Abstract The shale oil resources in the Permian Fengcheng Formation of the Mahu Sag exhibit significant potential but are characterized by strong heterogeneity and complex production dynamics, posing challenges for development. This study conducts a comprehensive analysis of the reservoir characteristics and production performance of the shale oil reservoir in the second member of the Fengcheng Formation within the MX Block. Utilizing data from three appraisal wells (M1X, M2X, M3H), we systematically evaluated the geological structural features, sedimentary characteristics, complex mineralogy, and petrophysical properties of the reservoir. The production dynamics of all wells display a multi-stage… More >
Open Access
ARTICLE
Junwei Zhang1, Pei Liu1, Huihang Li1, Guokang Huang1, Bozheng Yuan1, Wenjing Wei1, Xiaoshun Zhang2,*
Energy Engineering, DOI:10.32604/ee.2025.072462
（This article belongs to the Special Issue: Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation)
Abstract Addressing global climate challenges necessitates urgent low carbon transitions in high energy consuming enterprises (HECEs). This study proposes a comprehensive framework to assess their carbon reduction potential (CRP) by integrating electricity usage behavior analysis and dynamic carbon emission factor (DCEF) prediction. HECEs are classified into “electricity reduction” and “electricity transfer” categories based on load characteristics, enabling tailored optimization strategies. The framework employs machine learning to predict DCEFs, capturing real time variations in grid carbon intensity. A low carbon optimization model is then formulated to minimize emissions while adhering to production requirements and grid constraints, solved… More >
Open Access
ARTICLE
Yueyang Ji1, Yaohui Peng1, Haoran Ji1,*, Xinran Na1, Yuxuan Chen1, Wei Li2, Shengbin Chen2
Energy Engineering, DOI:10.32604/ee.2025.074599
（This article belongs to the Special Issue: Digital and Intelligent Planning and Operation Technologies for Flexible Distribution Network)
Abstract With the increasing penetration of distributed generations and continuous growth of loads, traditional rural distribution networks face severe challenges in both hosting capacity and reliability. Addressing these issues requires planning approaches that strike a balance between economic efficiency in infrastructure development and resilience in operation. Considering the dynamic growth of distributed generations and rural loads over the planning horizon, this paper presents a multi-stage expansion planning approach that coordinates flexible interconnection devices (FIDs) with substation and line construction to improve both economic performance and system reliability. The proposed method account for the time-varying growth of… More >
Open Access
ARTICLE
Xiutai Cao1, Yuxin Sun1, Bowen Shi1, Hao Zhang1, Hongli Tang1, Yongbin Bi1,2, Huiying Zhong1,3,*
Energy Engineering, DOI:10.32604/ee.2025.074439
（This article belongs to the Special Issue: Enhanced Oil and Gas Recovery in Unconventional Reservoirs)
Abstract With the steady advancement of China’s “Dual-Carbon” goals, CO2 huff-and-puff technology has become one of the mainstream methods for enhancing oil recovery (EOR) in oilfields. However, differences in sweep radius of CO2, CO2-oil interaction mechanisms, injection parameters, and huff-and-puff modes between conventional heavy-oil and light-oil reservoirs still require further investigation. The NP oilfield consists of an upper heavy-oil zone and a lower light-oil zone, with the reservoir inclined at a certain angle. Taking this oilfield as the study area, a positively rhythmic reservoir geological model was established. A compositional numerical simulation approach was employed to analyze the… More >
Open Access
ARTICLE
Yangjun Zhou1, Chenying Yi1, Wei Zhang1, Juntao Pan2,*, Ke Zhou1, Weixiang Huang1, Like Gao1, Shan Li1, Yuanchao Zhou3, Ling Li2, Liwen Qin1, Hongwen Wu4, Lijuan Yan2
Energy Engineering, DOI:10.32604/ee.2025.073787
（This article belongs to the Special Issue: Next-Generation Distribution System Planning, Operation, and Control)
Abstract The increasing integration of distributed generation (DG) and energy storage systems (ESS) has significantly enhanced the flexibility and efficiency of distribution networks. However, the growing frequency of extreme weather events has exposed the vulnerability of distribution lines, posing serious challenges to the reliability and resilience of such systems. Existing DG and ESS planning models often neglect this vulnerability dimension, leading to suboptimal siting decisions and reduced system robustness. To address this issue, this paper proposes a comprehensive multi-objective optimization framework that coordinates the allocation of DG and ESS and explicitly incorporates line vulnerability under extreme… More >
Open Access
REVIEW
Xing Wen1, Huan Chen1, Ning Wang1,*, Yu Song1, Zhuqiao Qiao2, Bin Zhang1
Energy Engineering, DOI:10.32604/ee.2025.073567
Abstract High voltage direct current (HVDC) systems play a pivotal role in long-distance, high-capacity, and cross-regional power transmission. However, their complex structure, wide-ranging impact of faults, and stringent safety requirements pose significant challenges to operational stability. Conventional model-based and data-driven methods for tasks such as text classification, fault diagnosis, and operation and maintenance support suffer from limited scalability and interpretability. Recent advances in large language model (LLM) provide new opportunities to address these issues. This paper provides a systematic review of LLM applications in HVDC systems. Firstly, it introduces the core architecture and training mechanisms of… More >
Open Access
ARTICLE
Yingjie Su1, Yubin Qiu2, Zhuojun Dong1, Jiying Liu2,*, Bo Gao1,3,*
Energy Engineering, DOI:10.32604/ee.2025.074454
Abstract In response to the high energy consumption, large load fluctuations, and insufficient adaptability associated with conventional control strategies in industrial park heating and hot water systems, this paper studies a 15,000 m2 factory office building in Jinan as its object of study. A photovoltaic-thermal integrated air-source heat pump system (PVT-ASHP) is developed. This system leverages its hardware parameter co-optimization and intelligent operational strategy control to perform cost reduction and efficiency increase, while focusing on the novel innovative high effectiveness of its operational strategies. The study first employs the Hooke-Jeeves algorithm to optimize key hardware parameters so… More >
Open Access
ARTICLE
Junjian Wu, Jingliao Sun*, Yejun Xiang, Zhenyu Zhou, Zhengchai Shi
Energy Engineering, DOI:10.32604/ee.2025.073042
Abstract The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids. In response, this paper proposes a novel robust optimization strategy grounded in uncertain boundary decision-making and enhanced through innovations in the multi-objective cross-entropy method. An uncertainty budget-aware environmental economic dispatch model is first established, integrating photovoltaic and wind power generation. By employing mathematical sophistication—particularly Lagrangian transformation—the proposed method effectively resolves embedded uncertainties, transforming the original model into a deterministic multi-objective optimization framework robust against renewable energy volatility. Furthermore, by incorporating the dynamic operational demands of microgrids, More >
Open Access
ARTICLE
Junmin Tang1,*, Yi Ding2, Juzheng Zhu3, Hongbo Zhong3, Yanliang Long4, Shuo Dong5
Energy Engineering, DOI:10.32604/ee.2025.074489
Abstract With the rapid growth of the electric vehicle (EV) population and the development of active distribution networks (DN), the optimal scheduling of power systems that incorporate EVs has become increasingly important. electric vehicle battery swap stations (EVBSS), leveraging their substantial battery resources and suitability for centralized scheduling, offer a new approach for enhancing DN flexibility. Accordingly, this paper proposes a two-stage optimal scheduling method for DN that considers low-carbon demand response and the battery life of EVBSS. The method employs dynamic carbon emission factors as penalty components in time-of-use electricity pricing, thereby transmitting carbon signals… More >
Open Access
ARTICLE
Lihua Zhong1, Feng Pan1, Yuyao Yang1, Lei Feng1, Jinghe Jiang2, Guo Lin2, Xiaoshun Zhang3,*
Energy Engineering, DOI:10.32604/ee.2025.073240
（This article belongs to the Special Issue: Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation)
Abstract This paper addresses the challenge of efficiently calculating dynamic carbon emission factors (CEFs) in large-scale power systems. Traditional methods that rely on direct matrix inversion are computationally intensive and become impractical for networks with thousands of nodes. To overcome this limitation, a fast and scalable computational framework is proposed based on the incomplete LU (ILU) preconditioned biconjugate gradient stabilized (BiCGSTAB) iterative solver. The proposed approach formulates the nodal CEF model as a sparse linear system and employs Krylov subspace acceleration with ILU preconditioning to enhance convergence and numerical stability. The method is applied to synthetic… More >
Open Access
ARTICLE
Ximing Zhang1,*, Zhuohuan Li2, Xuexia Quan1, Kai Cheng2, Yang Yu2
Energy Engineering, DOI:10.32604/ee.2025.073912
（This article belongs to the Special Issue: Digital and Intelligent Planning and Operation Technologies for Flexible Distribution Network)
Abstract The “N-1” criterion represents a fundamental principle for assessing the reliability of power systems in static security analysis. Existing studies mainly rely on centralized single-agent reinforcement learning frameworks, where centralized control is difficult to cope with regional autonomy and communication delays. In high-dimensional state–action spaces, these approaches often suffer from low efficiency and unstable policies, limiting their applicability to large-scale grids. To address these issues, this paper proposes a Multi-Agent Deep Reinforcement Learning (MADRL) method enhanced with Curriculum Learning (CL) and Prioritized Experience Replay (PER). The proposed framework adopts a Centralized Training with Decentralized Execution… More >
Open Access
ARTICLE
Jiguang Wu1, Qing Zhi2,*, Jin Guan2, Ruopeng Zhang2, Lixia Wu2, Shuhui Zhang2, Caifeng Wen3,4
Energy Engineering, DOI:10.32604/ee.2025.073914
Abstract This paper proposes a hybrid energy storage control method that coordinates the minimum output of the wind–storage system and the SOC self-recovery capability, applied to stand-alone energy storage stations. Under the premise of meeting the wind power smoothing requirements, model predictive control (MPC) is employed to rapidly regulate the SOC and output of the energy storage system during the smoothing process, thereby enhancing its sustained and stable operation capability, and decomposing the original wind power into a direct grid-connected component and a hybrid energy storage smoothing component. Subsequently, the Northern Goshawk Algorithm-Improved Complete Ensemble Empirical… More >
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ARTICLE
Hong Zhang1, Bin Xu1, Jinzhong Li1, Xiaoxiao Meng2,*, Cheng Qian2, Wei Ma1, Yuguang Xie1
Energy Engineering, DOI:10.32604/ee.2025.073542
（This article belongs to the Special Issue: Operation and Control of Grid-connected New Energy and Emerging Loads)
Abstract The increasing integration of distributed renewable energy sources in the distribution network leads to unbalanced load rates in the distribution network. The traditional load balancing methods are mainly based on network reconfiguration, which have problems such as a long time scale and poor adaptability. In response to these issues, this paper proposes a distributed iterative learning control (ILC) strategy for load balancing in flexible AC/DC hybrid distribution systems. This method combines the consensus algorithm with the ILC mechanism to construct a multi-terminal AC/DC flexible interconnection system model. It is only necessary to measure the load… More >
Open Access
ARTICLE
Guoqing Li, Jian Lou, Shouqi Jiang*, Yechun Xin, Yanxu Wang, Tuo Wang
Energy Engineering, DOI:10.32604/ee.2025.074947
Abstract To mitigate the frequency stability challenges arising from insufficient system inertia and inadequate damping capacity, a phased active frequency support control strategy for the sending-end grid with collaborative participation of wind power and modular multilevel converter-based high-voltage direct current (MMC-HVDC) is proposed, which realizes flexible mutual support and efficient utilization of multiple frequency regulation units. For wind power, a macro-variable considering frequency and power deviations is constructed based on cooperative control theory, then an adaptive frequency cooperative control method is designed based on rotor speed and pitch angle adjustment, which realizes differentiated utilization of rotor… More >
Open Access
ARTICLE
Wei Chen, Zhi Wei*, Tingting Pei, Jianghao Zhu, Yang Wu
Energy Engineering, DOI:10.32604/ee.2025.073843
Abstract Wind turbine gearboxes are critical components in large-scale power generation systems, and their unexpected failures often result in significant economic losses, long downtime, and decreased energy efficiency. Accurate prediction of their Remaining Useful Life (RUL) is therefore vital for enhancing operational reliability, implementing condition-based maintenance, and optimizing lifecycle management. However, existing approaches often neglect the memory effect in degradation processes and fail to establish an effective interaction between stochastic degradation modeling and RUL prediction. To address these challenges, this study proposes a novel fusion method that integrates a stochastic degradation model with an intelligent prediction framework.… More >
Open Access
ARTICLE
Sheng Lei1,2,3, Guanglong Sheng1,2,3,*, Hui Zhao1,2,3
Energy Engineering, DOI:10.32604/ee.2025.073788
（This article belongs to the Special Issue: Progress and Prospects of Hydraulic Fracture Network Morphology Characterization, Flow Simulation and Optimization Technology for Unconventional Oil and Gas Reservoirs)
Abstract Multi-stage fractured horizontal wells are among the most prevalent technologies in contemporary shale oil development. This article provides a comprehensive overview of several prevalent issues by examining pertinent simulation methods applicable to existing fractured horizontal wells. First, traditional methods primarily concentrate on individual stages of fracturing, shut-in, and production. These stages are relatively isolated and lack continuity. Second, the effects of reservoir stimulation vary under different operational conditions. The conventional dual (or multiple) porosity model is overly idealized, while analytical (or semi-analytical) models often struggle to accurately represent actual fracture geometries and internal fracture-grid characteristics,… More >
Open Access
ARTICLE
Yun Yu1, Li Lin2,*, Ximing Zhang1, Yang Yu3, Wei Zhang2, Kai Cheng3
Energy Engineering, DOI:10.32604/ee.2025.073445
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract Traditional transient stability preventive control calculation methods suffer from low computational efficiency, struggling to meet the real-time decision demands of increasingly large-scale power systems. Meanwhile, reinforcement learning-based preventive control approaches, which adopt an “offline training, online application” framework, show greater promise in preventive control. However, they still face challenges such as low computational efficiency in electromechanical transient simulation and insufficient decision robustness. Therefore, this paper proposes a power system predictive control strategy based on Generative Adversarial Proximal Policy Optimization (GA-PPO). Firstly, considering multiple constraints in transient stability operation, a power system preventive control model is… More >
Open Access
ARTICLE
Xingzuo Pan1, Yi Ding2, Zhilong Wei3, Tonglin Liu4, Jianxin Ni5, Yupeng He1,*
Energy Engineering, DOI:10.32604/ee.2025.072849
（This article belongs to the Special Issue: Innovative Energy Engineering for Resilient and Green Systems)
Abstract Wind and photovoltaic generation integration into power systems has steadily increased in recent years. To mitigate increasing renewable curtailment and deteriorating operational economics associated with high penetrations of wind and PV, this paper develops a robust optimal scheduling framework for integrated energy systems that integrates waste-heat recovery from power-to-ammonia (P2A) processes and ammonia cofiring as a substitution strategy. First, the energy transfer pathways of electricity–heat, ammonia, and the heat release characteristics of the entire P2A process are analyzed, enabling waste heat recovery throughout the conversion process. Second, considering the low-carbon characteristics of ammonia cofiring in… More >
Open Access
ARTICLE
Cheng Yang1, Xiuyu Yang1,*, Gangui Yan1, Hongda Dong2, Chenggang Li2
Energy Engineering, DOI:10.32604/ee.2025.072773
Abstract The integration of renewable energy introduces significant uncertainty into daily power system operation scenarios. Traditional deterministic unit commitment methods struggle to adapt to these conditions, often resulting in poor economic performance and high curtailment rates in planning outcomes. To address these challenges, this paper proposes a coordinated thermal power-energy storage planning methodology for managing renewable energy uncertainty. First, the operational effectiveness of daily unit commitment under uncertain renewable energy scenarios is analyzed, with quantitative assessment of how different commitment strategies impact supply-demand balance and economic performance. Subsequently, by conducting flexibility evaluation under multiple renewable energy… More >
Open Access
ARTICLE
Chenying Yi1, Yangjun Zhou1,2, Wei Zhang1, Like Gao1, Hongwen Wu3, Yuanchao Zhou4,*, Ke Zhou1, Weixiang Huang1, Juntao Pan5, Shan Li1, Bin Feng5
Energy Engineering, DOI:10.32604/ee.2025.073805
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract Ensuring reliability in distribution networks is essential under increasing operational and economic constraints. Traditional planning models rely on power flow calculations, leading to high computational costs and poor scalability. This study proposes a quantitative decomposition framework that establishes a direct linkage among reliability improvement measures, reliability parameters, and reliability indices, enabling fast and analytical reliability evaluation without power flow analysis. A bi-objective optimization model is developed to minimize both reliability indices (SAIDI) and investment costs, solved using Pareto-based multi-objective PSO combined with the TOPSIS method. Case studies on a 519-node distribution network demonstrate that the More >
Open Access
ARTICLE
Yifeng Wang1,*, Wei Cui1, Zhihui Wang2, Yanning Xue2, Bing Wang2
Energy Engineering, DOI:10.32604/ee.2025.074707
（This article belongs to the Special Issue: Innovative Renewable Energy Systems for Carbon Neutrality: From Buildings to Large-Scale Integration)
Abstract This paper proposes a photovoltaic (PV) output prediction and trading strategy based on fractal theory. Firstly, rescaled range analysis (R/S analysis) is employed to quantify the fractal characteristics of PV output sequences under different weather conditions. By calculating the Hurst exponent and fractal dimension, the self-similarity patterns and complexity differences are revealed. Secondly, a fractal interpolation prediction method based on the iterated function system is constructed to achieve high-precision fitting of typical daily output curves. Finally, by integrating the fractal prediction results, a trading decision-making model aimed at minimizing daily electricity procurement costs is established, More >
Open Access
ARTICLE
Tao Wang1, Ze Feng1,*, Jinghao Ma2, Shenhui Chen2, Jihui Zhang2, Tong Wang2
Energy Engineering, DOI:10.32604/ee.2025.074054
（This article belongs to the Special Issue: Advances and Emerging Trends in Photovoltaic Technologies, Energy Storage, and Green Hydrogen)
Abstract This paper develops an MPPT control strategy utilizing the particle swarm optimization (PSO) algorithm to enhance the tracking accuracy of photovoltaic arrays under complex operating conditions and to mitigate the transient effects on energy storage batteries during grid-connected and off-grid transitions. Initially, the operational principle of the three-phase voltage source PWM converter and the bidirectional DC/DC converter within solar power generation and energy storage systems is carefully examined, leading to the establishment of the appropriate mathematical model. Secondly, a voltage and current double closed-loop control structure utilizing feedforward decoupling is devised to meet the cooperative… More >
Open Access
ARTICLE
Yi Qi1, Yuhao Xie2,*, Zhibing Hu1, Fan Ding1, Junxian Ma3, Liang Zhao3, Shouqi Jiang2
Energy Engineering, DOI:10.32604/ee.2025.073663
Abstract To address the challenges of low inertia support capability and poor frequency stability encountered in the process of power system electronification, this paper designs a coordinated inertia support control strategy for offshore wind power connected to the grid via Modular Multilevel Converter Based High Voltage Direct Current (MMC-HVDC), which enhances the system inertia level and accounts for secondary frequency drop. In terms of inertia support, building on the existing coupling relationship between grid frequency and DC voltage, the influence of wind turbine (WT) rotor speed is further integrated, leading to the proposal of a virtual… More >
Open Access
ARTICLE
Li Sun, Fanjun Zeng, Hongbo Liu, Chenglian Ma*, Qiting Zhang, Jingzhou Zhu
Energy Engineering, DOI:10.32604/ee.2025.073405
Abstract The widespread integration of large-scale wind power has resulted in decreased equivalent inertia in power systems, thereby compromising their frequency regulation (FR) capabilities. Conventional synthetic inertia control faces challenges under stochastic wind conditions, including inadequate utilization of rotor kinetic energy in high wind condition regions and the risk of triggering rotor speed stability limits in low wind condition regions. To overcome these limitations, in this paper, a parameter adaptive synthetic virtual inertial control (SVIC) framework based on wind speed partition is proposed. The control mechanisms are designed differently across partitioned wind condition intervals: in high-wind-speed More >
Open Access
ARTICLE
Qiang Xu1,*, Leyao Cong1, Jianing Wang1, Xingyu Zhu1, Shaojun Cui1, Guoqiang Sun2, Xueheng Shi2
Energy Engineering, DOI:10.32604/ee.2025.073947
Abstract Power system faults can trigger a massive influx of complex alarm signals to the operation and maintenance center, posing significant challenges for dispatchers in accurately identifying the underlying faults. To address the issues of sample imbalance and low accuracy in traditional power grid monitoring alarm event identification methods, a power grid monitoring alarm event identification method based on BERT large language model is proposed. Firstly, information entropy is employed to filter effective monitoring alarm signals, and the k-means clustering algorithm is used to group all alarm signals into different event types, forming the initial power… More >
Open Access
ARTICLE
Yansen Sun1,2, Yi Ding3, Hualei Cui4, Yuanchao Hui5, Yupeng He1,2,*
Energy Engineering, DOI:10.32604/ee.2025.072860
（This article belongs to the Special Issue: Revolution in Energy Systems: Hydrogen and Beyond)
Abstract Integrated energy systems (IES) are pivotal for achieving low-carbon transitions, yet their optimization under carbon constraints remains challenging. This paper proposes an optimal scheduling model for IES that synergistically combines power-to-gas coupled with carbon capture systems (P2G-CCS) and hydrogen-blended natural gas under a tiered carbon trading mechanism. The model innovatively refines the P2G process into two stages (electrolysis and methanation), utilizing methanation reaction heat to enhance efficiency. It further incorporates hydrogen blending into gas turbines and boilers and implements a tiered carbon trading mechanism to constrain emissions. The objective is to minimize total costs, including… More >
Open Access
ARTICLE
Xian Shi1,2,*, Botao Zhang1,2, Weidong Zhang1,2, Zenghua Ma3, Bo Zhang3, Ahmad Ramezanzadeh4, Bin Li5, Jian Mao5
Energy Engineering, DOI:10.32604/ee.2025.073586
Abstract To investigate the mechanism governing the continuous decline in fracture conductivity of unconsolidated sandstone reservoirs post-hydraulic fracturing, this study centers on the synergistic effects of two key mechanisms—particle migration and proppant embedment. Through the integration of laboratory experiments and computational fluid dynamics-discrete element method (CFD-DEM) coupled numerical simulations, this study systematically examines the influence patterns of varying closure pressures, particle concentrations, fluid properties, and proppant parameters on fracture conductivity. The experimental results demonstrate that particle migration induces pore blockage within the proppant packing layer. When the fines mass concentration reaches 10%, fracture conductivity is almost… More >
Open Access
ARTICLE
Taotao Zhu, Pai Pang, Yang Wang*
Energy Engineering, DOI:10.32604/ee.2025.073516
Abstract Frequent extreme weather events and the increasing popularity of renewable energy have exacerbated the frequency spatiotemporal imbalance in the new power system. To address these issues, this paper proposes a collaborative optimization strategy for virtual inertia spatiotemporal distribution replenishment, aiming to enhance nodal frequency stability through targeted virtual inertia allocation. This strategy integrates the nodal inertia characteristics with frequency response dynamics to establish a spatiotemporal quantitative model for evaluating the equivalent inertia distribution across nodes, thereby overcoming the limitations of conventional global inertia assessments. Furthermore, by implementing differentiated virtual inertia supplementation from renewable energy power More >
Open Access
ARTICLE
Jian Wang1, Gongqiang Yang1,*, Yufeng Sun2, Gangui Yan1, Jie Long3
Energy Engineering, DOI:10.32604/ee.2025.072828
Abstract Given that the power grid partitioning method relying mainly on line reactive power flow information sees frequent changes in partitioning results with reactive power flow fluctuations under high-proportion fixed-power-factor PV-connected distribution networks, and traditional distributed PV collaborative optimization fails to adapt due to such changes, a stable partitioning and distributed PV collaborative optimization method for this scenario is proposed. Firstly, the Gaussian mixture model (GMM) is used to characterize the characteristics of PV reactive power output, obtaining the typical curve of PV reactive power output. Secondly, the Monte Carlo Simulation (MCS) probabilistic power flow calculation… More >
Open Access
ARTICLE
Qiang Liu1, Yongqiang Zhou1, Chaoyang Lu2, Zhen Yan1, Gangui Yan2, Cheng Yang2,*, Yupeng Wang2
Energy Engineering, DOI:10.32604/ee.2025.073028
（This article belongs to the Special Issue: New Energy and Energy Storage System)
Abstract The increasing proportion of power generated by new energy has meant that grid-forming energy storage has become a key method for improving power grid flexibility. However, the small disturbance stability problem has become an important challenge. The issue is that grid-forming energy storage is prone to low-frequency oscillation under strong grid conditions. Therefore, this study proposes a multi damping torque model to analyze the small signal stability of grid-forming energy storage converters. The impact of grid strength, operating conditions, and control parameters on the damping characteristics of the low-frequency oscillation by the system was quantitatively More >
Open Access
ARTICLE
Qian Yang1, Shenglei Du1,2, Boyang Chen1, Yalu Sun1, Ding Li1, Zhiheng Zhang3,*
Energy Engineering, DOI:10.32604/ee.2025.073720
Abstract In recent years, as the core infrastructure of the digital economy, data centers have witnessed increasingly prominent issues of energy consumption and carbon emissions. To achieve the goals of “carbon peak” and “carbon neutrality”, data centers have gradually introduced new energy power such as wind and photovoltaic power. However, the randomness and volatility of their output pose challenges to efficient absorption. Based on the spatiotemporal complementary characteristics of new energy output in multiple data centers and the spatiotemporal migration capability of computing tasks, this paper proposes a new energy-aware adaptive collaborative scheduling strategy for computation… More >
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