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Jalpa Thakkar¹, Siddharth Shankar Mishra², V. Shanmugapriya³, Mohan Kolhe^4,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078267 - 18 June 2026
（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 >

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Yingjie Su¹, Yubin Qiu², Zhuojun Dong¹, Jiying Liu^2,*, Bo Gao^1,3,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074454 - 18 June 2026
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 >

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V. V. Poplygin^1,*, A. Dieng², Min Wang³, Xian Shi³
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074170 - 18 June 2026
（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 >

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133

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Siying Li¹, Xinyu Feng², Xin Ma², Hui Huang², Zhipeng Wang², Baolian Liu², Zujun Ding², Weihong Ding², Xiaolong Huang², Jie Ji^2,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078062 - 18 June 2026
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 >

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195

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Wei Yin^1,*, Jun Wang¹, Ming Tong¹, Zhijun Chen¹, Ke Zhang¹, Meiqing Huang², Ran Gu², Keman Lin²
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.075066 - 18 June 2026
（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 >

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177

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Jesús Águila-León¹, Carlos Vargas-Salgado^2,*, Dácil Díaz-Bello², Fabián Lara-Vargas³
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078087 - 18 June 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 Integrating renewable energy sources presents technical challenges due to their variable nature, particularly in predicting and managing microgrid operational modes. Accurate identification of grid states—interconnected or islanded—is essential for maintaining stability and optimizing performance under fluctuating environmental conditions to meet energy demand. This work proposes a bio-inspired, optimized binary classification model based on Multi-Layer Perceptron Artificial Neural Networks (MLP-ANN), with the architecture and hyperparameters tuned using the novel Mosquito Mating Swarm Optimization (MMSO) algorithm, inspired by mosquito mating behavior and swarm dynamics. The model employs an MLP-ANN with a variable number of hidden layers and… More >

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Xiaolan Li^1,2, Yanting Wang^1,2,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.076417 - 18 June 2026
（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 >

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121

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Xin Li, Shuang Shi^*, Qiyi Liu, Yan Zhang
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.079956 - 18 June 2026
（This article belongs to the Special Issue: Operation and Control of Grid-connected New Energy and Emerging Loads)
Abstract Electric heavy-duty truck battery swapping stations (EHDT-BSS) are emerging as flexible resources for power systems due to their high controllability and significant power capacity. However, the participation of EHDT-BSSs in grid frequency regulation is severely constrained by the limited battery quantity and the high stochasticity of swapping demand, where forecasting errors can affect system reliability. To address these challenges, this paper proposes a two-stage optimization strategy for EHDT-BSSs participating in frequency regulation considering demand uncertainty. First, the basic operation mode of BSS is designed, and a deep learning-based method is utilized to forecast swapping demand. More >

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56

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Yuanxiang Luo, Xinmeng Pan^*, Xuyang Gao
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.076019 - 18 June 2026
（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 >

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Ivan Pliško, Mihael Cipek^*, Danijel Pavković
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078275 - 18 June 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 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 >

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424

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Guofeng Zhuang¹, Xiuzhen Zhao², Xuemei Luo^3,*, Shibin Chen³, Xujun Zhang³
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.072999 - 18 June 2026
（This article belongs to the Special Issue: Advances in Grid Integration and Electrical Engineering of Wind Energy Systems: Innovations, Challenges, and Applications)
Abstract This paper investigates voltage fluctuations in direct-drive wind farms induced by wide-band oscillations during grid integration. A sequence impedance model of the wind farm is established, incorporating key components such as direct-drive wind turbines, static var generators (SVGs), transformers, and transmission lines. Based on this model, positive- and negative-sequence impedance expressions are derived. The quantitative relationship among voltage fluctuation, system strength (short-circuit ratio, SCR), and power imbalance is formulated, leading to a comprehensive expression that highlights the influence of impedance mismatch between positive and negative sequences on wide-band oscillations. Simulation results confirm an approximately linear… More >

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Yifan Liu¹, Dengpan Zhang^1,*, Jiayi Du¹, Deqing Mei¹, Yinnan Yuan²
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.083105 - 18 June 2026
（This article belongs to the Special Issue: Climate Change, Clean Energy, and the Revolution in Energy Generation)
Abstract The hygroscopic growth of engine-emitted particulate matter in exhaust plumes is strongly influenced by surface wettability. In this study, molecular dynamics simulations were performed on biodiesel- and diesel-derived combustion-particle models constructed on a unified defective carbon framework to investigate wetting behavior under representative exhaust-plume temperature and humidity conditions. Under the reference condition of 333 K and a saturation ratio of 1.2, the equilibrium contact angles on smooth biodiesel, rough biodiesel, and rough diesel surfaces were 45.4°, 63.5°, and 95.5°, respectively. The trends in work of adhesion and interfacial hydrogen-bond statistics were consistent with the contact-angle… More >

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Yun Yu¹, Li Lin^2,*, Ximing Zhang¹, Yang Yu³, Wei Zhang², Kai Cheng³
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.073445 - 18 June 2026
（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 >

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807

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Dheyaa Abdulraheem Khalaf^1,*, Ammar Sami Mohammad²
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.080456 - 18 June 2026
（This article belongs to the Special Issue: Advanced Analytics on Energy Systems)
Abstract Transient thermodynamic analysis of a multilayer phase-change material (PCM)–assisted evacuated tube solar collector (PCM–ETSC) is presented. A compact enthalpy-based numerical model is formulated to capture coupled heat transfer among the absorber tube, a mixed-mean heat-transfer fluid (HTF) control volume, and multiple PCM layers with staggered melting temperatures under time-dependent irradiance. Performance is evaluated using solar-referenced thermal and exergy efficiencies and reported over a sunlit window defined by G (t) > 0.1 G_max. For the baseline run, the simulated temperature ranges are Tf∈[298.000,306.489] and Tt∈[298.000,310.432] K with PCM, compared with Tf∈[298.000,306.774] and Tt∈[298.000,310.848] K without… More >

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Tao Wang¹, Ze Feng^1,*, Jinghao Ma², Shenhui Chen², Jihui Zhang², Tong Wang²
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074054 - 18 June 2026
（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 >

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486

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Weijia Tang, Qiang Li^*, Ningyu Zhang
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.074698 - 18 June 2026
（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 >

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381

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Jakkrawut Techo¹, Panupon Trairat¹, Karthikeyan Velmurugan^2,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.080474 - 18 June 2026
（This article belongs to the Special Issue: Alternative Energy Sources for a Carbon-Free Society: Limitations and Futuristic Trends)
Abstract In this study, selective and non-selective absorber-coated trays were employed to dry carrots and pears. Two trays with a selective absorber coating (1 mm thickness) were used, each loaded with 600 g of sliced carrots and pears. Similarly, two additional trays with a non-selective absorber coating were utilised. Furthermore, the performance of both selective and non-selective absorber-coated trays was compared with conventional open sun drying. The selective absorber-coated tray demonstrated higher thermal energy absorption and enabled the drying of carrots within 2 days, resulting in a weight loss of 529 g. In contrast, owing to… More >

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76

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Junjian Wu, Jingliao Sun^*, Yejun Xiang, Zhenyu Zhou, Zhengchai Shi
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.073042 - 18 June 2026
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 >

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526

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Jiguang Wu¹, Qing Zhi^2,*, Jin Guan², Ruopeng Zhang², Lixia Wu², Shuhui Zhang², Caifeng Wen^3,4
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.073914 - 18 June 2026
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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592

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Biswanath Hajoary^1,*, Ranjay Das¹, Ganesh Roy², Daijiry Narzary³
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.075305 - 18 June 2026
Abstract The increasing integration of photovoltaic systems into smart grids requires accurate evaluation of power conversion efficiency and output performance. In this context, Z Source Multilevel Inverters function as voltage boosting converters and offer a certain degree of fault tolerance. However, conventional control strategies such as proportional integral controllers and hybrid optimization-based methods including POA-RFA (Pelican Optimization Algorithm-Random Forest Algorithm) are limited in their ability to maintain dynamic stability, efficiency, and operational safety under varying solar irradiance and load conditions. This study proposes a safe and explainable Deep Q Network based intelligent switching control framework for… More >

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Xiaolan Li^1,2,*, Jinyu Shen^1,2, Jinhuang Liang^1,2, Yanting Wang^1,2
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.076521 - 18 June 2026
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 >

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702

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Meng Zhang¹, Lijuan Zhang², Jie Zhang¹, Shiliang Miao², Jiangong Yang², Yajun Zhao^1,*, Feifei Bu¹
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074465 - 18 June 2026
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 >

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Zahid Javid^1,2, Kush Lohana², Danial Murtaza², William Holderbaum^3,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.080073 - 18 June 2026
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract This paper introduces a novel hybrid method for Power System State Estimation (PS-SE) that effectively integrates the strengths of Weighted Least Squares (WLS) and the Extended Kalman Filter (EKF) through an adaptive weighting mechanism. The proposed method addresses key challenges in modern PS-SE, including measurement uncertainties, bad data detection and handling, and convergence reliability. By incorporating an adaptive weighting mechanism, the hybrid approach dynamically adjusts estimation parameters based on the quality of the measurements, enabling it to maintain high accuracy for clean data while demonstrating exceptional resilience against outliers and noisy measurements. The performance of… More >

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Yansen Sun^1,2, Yi Ding³, Hualei Cui⁴, Yuanchao Hui⁵, Yupeng He^1,2,*
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.072860 - 18 June 2026
（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 >

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1010

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Media Nadhim Mahmood¹, Oday I. Abdullah^1,2,3,*, Amani I. Altmimi⁴
Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078421 - 18 June 2026
（This article belongs to the Special Issue: Recent Advance and Development in Solar Energy)
Abstract The highly important requirement for achieving urban sustainability for any city is the availability of renewable energy, as reducing carbon emissions is considered one of the most important factors in improving the quality of life and health of people in green cities. The main objective of this research is to provide an in-depth study and analysis of the role of renewable energies, especially solar energies, in promoting sustainable development in cities around the world, in general, and in Iraq in particular. Strategies for using clean energy sources in a hybrid manner, such as solar energy,… More >

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