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Franjo Pranjić^1,*, Doris Beljan², Primož Praper³, Matej Fike¹, Peter Virtič¹, Antun Pfeifer², Neven Duić^2,4
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.080284 - 12 July 2026
（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 paper evaluates the role of aggregated demand-side flexibility from public buildings in supporting renewable energy integration and decarbonization of the Slovenian energy system. Using high-resolution monitoring data from over 100 public buildings and the H2RES energy system optimization model, two long-term scenarios are analyzed for the period 2020–2050: a reference scenario without public building flexibility and a flexibility scenario in which public building heat demand is electrified via heat pumps. The year 2020 is used as an internally consistent optimization reference for demand levels and technology availability, rather than as a statistical reconstruction of… More >

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Yueyang Ji¹, Yaohui Peng¹, Haoran Ji^1,*, Xinran Na¹, Yuxuan Chen¹, Wei Li², Shengbin Chen²
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.074599 - 12 July 2026
（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 >

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414

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Gábor Hasulyó^*
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.081099 - 12 July 2026
（This article belongs to the Special Issue: Hydrogen Energy Systems: Storage, Power-to-Hydrogen, and AI-Enabled Design, Planning, and Operation)
Abstract The current global energy situation is very fragile. Much more stable and predictable energy security is needed. Due to global climate conditions, it is advisable to prioritize fuels that are high in energy content and relatively easy to produce, such as hydrogen. However, the widespread deployment of hydrogen refueling stations is hampered by significant safety challenges, including hydrogen’s high flammability, its tendency to leak, and high-pressure storage requirements. This study examines how digital twin technology can be implemented to improve the safety and operational efficiency of hydrogen facilities. A dynamic digital twin model was developed… More >

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112

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REVIEW

Xing Wen¹, Huan Chen¹, Ning Wang^1,*, Yu Song¹, Zhuqiao Qiao², Bin Zhang¹
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.073567 - 12 July 2026
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 >

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1507

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Yan Shi^1,2,*, Rong Zhuang², Yunshan Bai², Wenguo Xiang¹, Cai Liang¹
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.082971 - 12 July 2026
Abstract The performance evaluation of gas turbine inlet air filtration systems is commonly based on standardized laboratory testing; however, discrepancies frequently arise between laboratory results and actual operating performance. In this study, an on-site testing apparatus was developed to investigate filtration behavior under realistic operating conditions. Field measurements were conducted to analyze pressure loss evolution, particle-size-dependent filtration efficiency, and the influence of environmental parameters, including temperature, humidity, and ambient particulate concentration. Results show that filter pressure loss increased progressively with operational loading, while short-term fluctuations were associated with variations in environmental conditions. Filtration efficiency exhibited an… More >

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45

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Kiran A. S.¹, Dayakar G. Devaru^1,*, Mohan N.², Bhaskaran Gopalakrishnan³
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.080851 - 12 July 2026
Abstract The dairy processing industries are energy-intensive because of the high level of thermal and refrigeration processes. In this study, a large-scale dairy processing unit in South India has been analyzed thermodynamically and optimized by applying integrated energy and exergy analysis along with heat exchanger network (HEN) optimization. The operational data of one year of a plant manufacturing milk, curd, butter and ghee was analysed. Estimation of theoretical electrical and thermal energy requirements was carried out and compared with the actual plant energy consumption. The exergy analysis was used to identify the thermodynamic irreversibilities and the… More >

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Xiaotong Li^1,2, Mingquan Qiu², Wenjun Zhang², Pengfei Li², Chong Liu², Chong Yang², Han Xiao², Feng Hu², Binghui Liu^1,*, He Wang¹
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.071598 - 12 July 2026
Abstract To address the operational uncertainties and power quality challenges brought by high-penetration distributed energy integration into distribution networks, this paper proposes a precision renovation optimization method for active distribution networks (ADNs) that considers probabilistic power flow. First, based on probabilistic power flow analysis, a comprehensive power quality evaluation index system is constructed to accurately quantify the impact of uncertainties caused by photovoltaic fluctuations on distribution network power quality under high-penetration distributed photovoltaic (PV) scenarios. On this basis, a precision renovation optimization model is established with the goals of minimizing renovation cost, maximizing renewable energy hosting… More >

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27

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ARTICLE

Ruosong Hou^1,2,*, Jiakun An¹, Zihao Zhao¹, Wei Guo¹, Hua Shao²
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.069068 - 12 July 2026
Abstract This article evaluates the connectivity with energy sharing in low-voltage distribution areas. Indicators like wind-solar complementing effectiveness, source-load energy sharing possibility, or transformer capacity interconnection measurements are part of the assessment index framework for interconnection capacity that is established after an analysis of the features of linked scenarios. Radial and inflexible, conventional distribution systems can’t handle bidirectional power flow, fluctuating demand, or grid disruptions. Using real-world examples, we can see that the suggested strategy improves power supply efficiency across zones and increases the usage of distributed energy resources, proving the method’s validity. With the help… More >

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50

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Mohamed R. Aboelmagd^1,*, Ali Selim^1,2,*, Mamdouh Abdel-Akher¹
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.079171 - 12 July 2026
（This article belongs to the Special Issue: AI and Advanced Computational Techniques for Sustainable Renewable Energy Systems)
Abstract To enable the integration of photovoltaic (PV) power into electrical grids, accurate predictions are vital. This study applies the Multistage Attention Neural Ordinary Differential Equation (MANODE) model, which combines Long Short-Term Memory (LSTM) networks, Temporal Convolutional Networks (TCN), and a two-stage attention mechanism to capture complex spatiotemporal patterns for PV power forecasting. The improved MANODE model is evaluated on three real-world datasets from PV stations in Egypt. Each dataset contains 12 feature parameters and spans an entire year. Comprehensive comparisons are conducted between the improved MANODE model and other neural network models, including one-layer and More >

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71

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Xiutai Cao¹, Yuxin Sun¹, Bowen Shi¹, Hao Zhang¹, Hongli Tang¹, Yongbin Bi^1,2, Huiying Zhong^1,3,*
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.074439 - 12 July 2026
（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 >

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Chuan Lin^*, Weixian Chen, Guangtao Hao^*
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.080605 - 12 July 2026
Abstract Accurate building electricity load forecasting (BELF) can provide a regulatory basis for building energy management systems and promote the transition of buildings toward low-carbon and intelligent operation modes. However, building electricity load is influenced by historical loads, as well as outside environmental conditions such as humidity and temperature, which reduces the prediction accuracy of models. To tackle these challenges, this study presents a BELF model, which consists of a modal component grouping approach, grouped feature attention mechanism, and multi-scale residual depthwise convolution memory module. First, the modal component grouping method analyzes building electricity load in… More >

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84

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REVIEW

Zewen Ge^1,*, Jihui Liu², Shuai Yuan¹, Mufan Zhuang^3,*
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.082217 - 12 July 2026
（This article belongs to the Special Issue: Toward Net-Zero Emission: Multidimensional Perspectives on Energy Transition)
Abstract Limiting warming to the Paris temperature goals requires a rapid scale-up of low-carbon energy, yet recent experience suggests that deployment is increasingly shaped by delivery constraints rather than by technology cost trends alone. This review synthesizes peer-reviewed evidence on five constraints that repeatedly slow net-zero buildouts: lengthy approval and grid-connection processes; capital-intensive investment profiles that heighten sensitivity to the cost of capital and revenue risk; bottlenecks in critical minerals, processing, and manufacturing; social contestation and local governance that translate into siting exclusions, delays, and cancellations; and modeling traditions that can underrepresent these non-marginal frictions. Accordingly,… More >

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Chenying Yi¹, Yangjun Zhou^1,2, Wei Zhang¹, Like Gao¹, Hongwen Wu³, Yuanchao Zhou^4,*, Ke Zhou¹, Weixiang Huang¹, Juntao Pan⁵, Shan Li¹, Bin Feng⁵
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.073805 - 12 July 2026
（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 >

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328

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Mingxuan Ji¹, Jing Gao^1,*, Dantian Zhong¹, Yingqi Xu¹, Shuxiang Yang¹, Zhongxiao Du¹, Yingming Liu²
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.074643 - 12 July 2026
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 >

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438

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Mingqi Liu, Ying Wang^*, Wujiang Li, Juyong Cao, Fuyong Yang
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.074783 - 12 July 2026
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 >

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2056

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Omar Ghoulam¹, Hind Talbi^1,2, Kamal Amghar¹, Hamza Faraji^3,*, Saloua Senhaji⁴, Ismael Driouch¹
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.076813 - 12 July 2026
Abstract This study numerically investigates turbulent flow and thermal performance in evaporator tubes equipped with rectangular partitions positioned at different locations. Two configurations are analyzed: (A) partitions on the top wall, center of channel, and bottom wall, and (B) partitions on the bottom wall, center of channel, and top wall. In addition, we examine the effect of varying the positions of the obstacles (S=D2,S=D,S=5D4, andS=3D/2) and the inclination angle (θ=60∘, θ=75∘, θ=90∘, θ=105∘ and θ=120∘) of the detached obstacle relative to the walls, an innovative aspect that had not been addressed in previous studies. More >

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89

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Qian Yang¹, Shenglei Du^1,2, Boyang Chen¹, Yalu Sun¹, Ding Li¹, Zhiheng Zhang^3,*
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.073720 - 12 July 2026
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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1319

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Huajie Zhang^1,2, Xiaopeng Li^1,2, Hanlin Xiao^3,*, Lifeng Xing³, Wenyue Zhou^1,2
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.086505 - 12 July 2026
Abstract This article has no abstract. More >

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71

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Qiang Xu^1,*, Leyao Cong¹, Jianing Wang¹, Xingyu Zhu¹, Shaojun Cui¹, Guoqiang Sun², Xueheng Shi²
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.073947 - 12 July 2026
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 >

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619

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Miftakhul Maulidina^*, Erna Daniati
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.080751 - 12 July 2026
（This article belongs to the Special Issue: Intelligent Integration of Renewable, Storage, and Mobility Systems for a Sustainable Energy Future)
Abstract The global energy transition toward net-zero emissions requires the massive development of renewable energy infrastructure. However, the efficiency and safety of installations such as wind turbines, solar panels, and energy storage systems are highly dependent on subsurface physical characteristics. Neglecting geological structures such as active faults or corrosive zones, risks structural failure and electrical system malfunctions. This research proposes the use of the Very Low Frequency Electromagnetic (VLF-EM) method as a fast and non-destructive geophysical screening tool. This method utilizes low-frequency signals to map variations in subsurface electrical conductivity. Furthermore, the data were processed using… More >

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79

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Yurong Zhao, Daozhi Chen^*, Yu Yin^*
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.075847 - 12 July 2026
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 >

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980

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380

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Nantian Huang^*, Jingyuan Zhang, Shicheng Ren, Hao Zhang, Bingling Li, Yaoyao Wang
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.072993 - 12 July 2026
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 >

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325

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Md. Liton Hossain^1,*, Md. Zahid Ansary², Jiefeng Hu¹, Syed Islam¹, Maaspaliza Azri³, Norezmi Md. Jamal⁴
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.079961 - 12 July 2026
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract Inverters play an essential and indispensable role in energy conversion within modern electrical power systems. Conventional two-level inverters (2LIs) have been widely adopted across industrial applications due to their simple structure and mature control strategies. However, 2LIs exhibit several limitations when interfacing with utility-scale grid systems, including higher harmonic distortion, increased switching stress, and reduced efficiency in high-voltage and high-power operations. Multilevel Inverters (MLIs) have emerged as a transformative solution, enabling high-voltage and high-power applications with improved efficiency and significantly lower harmonic distortion compared to traditional two-level configurations. This review investigates the broad range of… More >

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117

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Xuefeng Yang^1,2, Chunyu Ren^1,2, Deliang Zhang^1,2, Huaicai Fan^1,2, Yue Chen^1,2, Yue Yang^1,2, Yan Zhang^1,2, Shuai Wu^1,2, Baoyun Zhang^3,*, Xin Zhao³
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.074956 - 12 July 2026
（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 >

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184

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Johannes D. Pelda^*, Sebastian Aichele, Dmitry Romanov, Stefan Holler
Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.079450 - 12 July 2026
（This article belongs to the Special Issue: Selected Papers from the SDEWES 2025 Conference on Sustainable Development of Energy, Water and Environment Systems)
Abstract The transformation of district heating systems in Germany is a central topic in energy and climate policy, given the 2045 climate neutrality targets. This study focuses on the main district heating system in the city of Göttingen in Germany, whose heat generation currently relies primarily on three Combined Heat and Power (CHP) plants subsidized under the German CHP Act, one wood chip boiler and two gas boilers. In 2025, the network’s heating demand amounted to 89 GWh, which was mainly covered by wood chips or biogas (41%) and natural gas (21%). This paper examines an… More >

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