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REVIEW

Hao Tan^1,2, Zeai Huang^1,2,*, Runxian Gong², Junming Mei², Kejie Wu², Tianyu Yan², Daoquan Zhu², Zhibin Zhang², Ruiyang Zhang^1,2
Energy Engineering, Vol.122, No.11, pp. 4331-4347, 2025, DOI:10.32604/ee.2025.070226 - 27 October 2025
Abstract Under the driving goal of carbon neutrality, biogas reforming technology has garnered significant attention due to its ability to convert greenhouse gases (CH₄/CO₂) into syngas (H₂/CO). Conventional nickel-based catalysts suffer from issues such as carbon deposition, sintering and sulfur poisoning. Non-nickel-based perovskite materials, with their tunable crystal structure, dynamic oxygen vacancy characteristics, and excellent anti-coking/anti-sulfur performance, have emerged as a promising alternative. This review systematically summarizes the design for non-nickel-based perovskite materials, including optimizing lattice oxygen migration ability and active site stability by A/B site doping, defect engineering and heterojunction construction. The enhancing the conversion rate… More >

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Eakbodin Gedkhaw, Nantinee Soodtoetong^*
Energy Engineering, Vol.122, No.11, pp. 4349-4363, 2025, DOI:10.32604/ee.2025.068577 - 27 October 2025
（This article belongs to the Special Issue: AI in Green Energy Technologies and Their Applications)
Abstract This research aimed to study the efficiency of solar power system in controlling hydro-organic smart farming system in closed greenhouse by developing an off-grid system consisting of 450 W solar panel, MPPT charge controller, 500 W Pure Sine Wave inverter and 2150 Ah Deep Cycle batteries in series as 24 V system to supply power to automatic control devices, including temperature, humidity, pH sensor and water pump in NFT (Nutrient Film Technique) hydroponic system using organic nutrient solution. The test result between 08:00–17:00 or 30 days found that the system can produce a maximum of… More >

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Yang Liu¹, Lifu Ding^2,*, Zhenfan Yu¹, Tannan Xiao², Qiuyu Lu¹, Ying Chen², Weihua Wang¹
Energy Engineering, Vol.122, No.11, pp. 4365-4384, 2025, DOI:10.32604/ee.2025.068712 - 27 October 2025
（This article belongs to the Special Issue: Integrated Technology Development and Application of Wind Power Systems)
Abstract Wake effects in large-scale wind farms significantly reduce energy capture efficiency. Active Wake Control (AWC), particularly through intentional yaw misalignment of upstream turbines, has emerged as a promising strategy to mitigate these losses by redirecting wakes away from downstream turbines. However, the effectiveness of yaw-based AWC is highly dependent on the accuracy of the underlying wake prediction models, which often require site-specific adjustments to reflect local atmospheric conditions and turbine characteristics. This paper presents an integrated, data-driven framework to maximize wind farm power output. The methodology consists of three key stages. First, a practical simulation-assisted… More >

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357

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REVIEW

Mir Majid Etghani¹, Homayoun Boodaghi^2,*
Energy Engineering, Vol.122, No.11, pp. 4385-4474, 2025, DOI:10.32604/ee.2025.070668 - 27 October 2025
（This article belongs to the Special Issue: AI and Advanced Computational Techniques for Sustainable Renewable Energy Systems)
Abstract Energy system optimization has become crucial for enhancing efficiency and environmental sustainability. This comprehensive review examines the synergistic application of Artificial Neural Networks (ANN) and Taguchi methods in optimizing diverse energy systems. While previous reviews have focused on these methods separately, this paper presents the first integrated analysis of both approaches across multiple energy applications. We systematically analyze their implementation in: Internal combustion engines, Thermal energy storage systems, Solar energy systems, Wind and tidal turbines, Heat exchangers, and hybrid energy systems. Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90% when compared More >

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Jing Li¹, Yinghua Xie¹, Guoxing Wu¹, Ming Xiao¹, Guoteng Wang², Keheng Lou², Ying Huang^2,*
Energy Engineering, Vol.122, No.11, pp. 4475-4495, 2025, DOI:10.32604/ee.2025.068711 - 27 October 2025
Abstract With the accelerating urbanization process, the load demand of urban power grids is constantly increasing, giving rise to a batch of ultra-large urban power grids featuring large electricity demand, dense load distribution, and tight construction land constraints. This paper establishes a network planning method for urban power grids based on series reactors and MMC-MTEDC, focusing on four aspects: short-circuit current suppression, accommodation of external power supply, flexible inter-regional power support, and voltage stability enhancement in load centers. It proposes key indicators including node short-circuit current margin, line thermal stability margin, maximum fault-induced regional power loss,… More >

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222

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He Wang, Shiqiang Li^*, Yiqi Liu, Jing Bian
Energy Engineering, Vol.122, No.11, pp. 4497-4521, 2025, DOI:10.32604/ee.2025.065244 - 27 October 2025
Abstract With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures, the number of measurement points supporting synchronous communication remains relatively limited. This poses challenges for conventional fault distance estimation methods, which are often tailored to simple topologies and are thus difficult to apply to large-scale, multi-node DC networks. To address this, a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper. First, a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range… More >

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163

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Yifan Li^*, Congzhe Zhu, Rong Gao^*, Bin Yang
Energy Engineering, Vol.122, No.11, pp. 4523-4539, 2025, DOI:10.32604/ee.2025.068480 - 27 October 2025
（This article belongs to the Special Issue: Advancements in Energy Efficiency and Thermal Management for Data Center)
Abstract The local overheating issue is a serious threat to the safe operation of data centers (DCs). The chip-level liquid cooling with pool boiling is expected to solve this problem. The effect of nano configuration and surface wettability on the boiling characteristics of copper surfaces is studied using molecular dynamics (MD) simulation. The argon is chosen as the coolant, and the wall temperature is 300 K. The main findings and innovations are as follows. (1) Compared to the smooth surface and fin surface, the cylindrical nano cavity obtains the superior boiling performance with earlier onset of… More >

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Prasongsuk Songsree^*, Chaiyapon Thongchaisuratkrul^*
Energy Engineering, Vol.122, No.11, pp. 4541-4559, 2025, DOI:10.32604/ee.2025.068448 - 27 October 2025
（This article belongs to the Special Issue: AI in Green Energy Technologies and Their Applications)
Abstract The purpose of this research is to design and develop a demonstration Set of a water cooling system using a Peltier with solar energy and technology, and IoT (Internet of Things), and test and measure the performance of the Peltier Plate Water Cooling System Demonstration Set under different environmental conditions. To be used as a model for clean energy systems and experimental learning materials. The prototype system consists of a 100-W solar panel, a 12 V 20 Ah battery, a Peltier plate, a DS18B20 sensor, and a NodeMCU microcontroller. The system performance is determined by… More >

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228

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Jiayun Ding, Bin Chen^*, Yutong Lei, Wei Zhang
Energy Engineering, Vol.122, No.11, pp. 4561-4577, 2025, DOI:10.32604/ee.2025.067574 - 27 October 2025
Abstract In the field of low-carbon building systems, the combination of renewable energy and hydrogen energy systems is gradually gaining prominence. However, the uncertainty of supply and demand and the multi-energy flow coupling characteristics of this system pose challenges for its optimized scheduling. In light of this, this study focuses on electro-thermal-hydrogen trigeneration systems, first modelling the system’s scheduling optimization problem as a Markov decision process, thereby transforming it into a sequential decision problem. Based on this, this paper proposes a reinforcement learning algorithm based on deep deterministic policy gradient improvement, aiming to minimize system operating… More >

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143

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Cheng Peng^1,*, Hao Qi²
Energy Engineering, Vol.122, No.11, pp. 4579-4602, 2025, DOI:10.32604/ee.2025.067704 - 27 October 2025
Abstract Integrated energy systems (IES) are widely regarded as a key enabler of carbon neutrality, enabling the coordinated use of electricity, heat, and gas to support large-scale renewable integration. Yet their practical deployment still faces major challenges, including rigid thermoelectric coupling, insufficient operational flexibility, and fragmented carbon and certificate market mechanisms. To address these issues, this study proposes a low-carbon economic dispatch model for integrated energy systems (IES) that reduces emissions and costs while improving renewable energy utilization. A coordinated framework integrating carbon capture, utilization, and storage, two-stage power-to-gas, combined heat and power, and ground-source heat… More >

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Xinjian Li¹, Yu Zhang^1,2,*, Zewen Wang¹, Zhenyun Song¹
Energy Engineering, Vol.122, No.11, pp. 4603-4619, 2025, DOI:10.32604/ee.2025.065799 - 27 October 2025
（This article belongs to the Special Issue: AI in Green Energy Technologies and Their Applications)
Abstract Power prediction has been critical in large-scale wind power grid connections. However, traditional wind power prediction methods have long suffered from problems, for instance low prediction accuracy and poor reliability. For this purpose, a hybrid prediction model (VMD-LSTM-Attention) has been proposed, which integrates the variational modal decomposition (VMD), the long short-term memory (LSTM), and the attention mechanism (Attention), and has been optimized by improved dung beetle optimization algorithm (IDBO). Firstly, the algorithm’s performance has been significantly enhanced through the implementation of three key strategies, namely the elite group strategy of the Logistic-Tent map, the nonlinear… More >

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Leonid Plotnikov^1,*, Danil Davydov^1,2, Dmitry Krasilnikov^1,2, Alexander Ryzhkov²
Energy Engineering, Vol.122, No.11, pp. 4621-4633, 2025, DOI:10.32604/ee.2025.070713 - 27 October 2025
（This article belongs to the Special Issue: Thermal Engineering Technology Innovation and Sustainable Development)
Abstract Improving the specific, technical, economic, and environmental characteristics of piston engines (ICE) operating on alternative gaseous fuels is a pressing task for the energy and mechanical engineering industries. The aim of the study was to optimize the parameters of the ICE working cycle after replacing the base fuel (propane-butane blend) with syngas from wood sawdust to improve its technical and economic performance based on mathematical modeling. The modeling results were verified through experimental studies (differences for key parameters did not exceed 4.0%). The object of the study was an electric generator based on a single-cylinder… More >

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144

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Jian Wang, Hui Qi, Lingyi Ji^*, Zhengya Tang, Hui Qian
Energy Engineering, Vol.122, No.11, pp. 4635-4651, 2025, DOI:10.32604/ee.2025.068667 - 27 October 2025
（This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)
Abstract This paper proposes a cost-optimal energy management strategy for reconfigurable distribution networks with high penetration of renewable generation. The proposed strategy accounts for renewable generation costs, maintenance and operating expenses of energy storage systems, diesel generator operational costs, typical daily load profiles, and power balance constraints. A penalty term for power backflow is incorporated into the objective function to discourage undesirable reverse flows. The Bald Eagle Search (BES) meta-heuristic is adopted to solve the resulting constrained optimization problem. Numerical simulations under multiple load scenarios demonstrate that the proposed method effectively reduces operating cost while preventing More >

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128

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Yukun Yang^*, Jun He, Wenfeng Chen, Zhi Li, Kun Chen
Energy Engineering, Vol.122, No.11, pp. 4653-4678, 2025, DOI:10.32604/ee.2025.068199 - 27 October 2025
Abstract To address the issues of unclear carbon responsibility attribution, insufficient renewable energy absorption, and simplistic carbon trading mechanisms in integrated energy systems, this paper proposes an electric-heat-hydrogen integrated energy system (EHH-IES) optimal scheduling model considering carbon emission stream (CES) and wind-solar accommodation. First, the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate, branch carbon intensity, and node carbon potential, realizing accurate tracking of carbon flow in the process of multi-energy coupling. Second, a stepped carbon pricing mechanism is established to… More >

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648

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198

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Xin Liu¹, Zheng Zhang^2,*, Yu Zhao³, Yi Yang², Zhenning Qiao², Zhibo Xu², Xianzhi Yu²
Energy Engineering, Vol.122, No.11, pp. 4679-4702, 2025, DOI:10.32604/ee.2025.068371 - 27 October 2025
Abstract With the growing demand for offshore energy, deepwater drilling has become a vital technology in petroleum engineering. However, conventional drilling systems often face limitations such as delayed bottomhole pressure response and low control precision, particularly under narrow pressure window and complex formation conditions. To address these challenges, Dual-layer Pipe dual-gradient drilling (DGD) technology has been introduced, utilizing a dual-pipe structure and downhole lift pumps to extend the pressure control range. Despite these advantages, current DGD systems lack fast and precise bottomhole pressure control due to their reliance on indirect flow-based methods. This study proposes a… More >

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134

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Ahmad S. Azzahrani^*
Energy Engineering, Vol.122, No.11, pp. 4703-4713, 2025, DOI:10.32604/ee.2025.067398 - 27 October 2025
（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 The Light Detection and Ranging (LiDAR) data analysis method has emerged as a powerful and versatile tool for characterizing atmospheric conditions and modeling light propagation through various media. In the context of renewable energy, particularly wind energy, LiDAR is increasingly utilized to analyze wind flow, turbine wake effects, and turbulence in complex terrains. This study focuses on advancing LiDAR data interpretation through the development and application of the LiDAR Statistical Barnes Objective Analysis (LiSBOA) method. LiSBOA enhances the capacity of scanning LiDAR systems by enabling more precise optimization of scan configurations and improving the retrieval… More >

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331

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153

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Qingliang Wang¹, Chengkai Liu¹, Zhaohui Zhou¹, Ye Han¹, Luebin Fang², Moxuan Zhao³, Xiao Cao^3,*
Energy Engineering, Vol.122, No.11, pp. 4715-4732, 2025, DOI:10.32604/ee.2025.068105 - 27 October 2025
（This article belongs to the Special Issue: AI-Driven Innovations in Sustainable Energy Systems: Advances in Optimization, Storage, and Conversion)
Abstract Grid-supplied load is the traditional load minus new energy generation, so grid-supplied load forecasting is challenged by uncertainties associated with the total energy demand and the energy generated off-grid. In addition, with the expansion of the power system and the increase in the frequency of extreme weather events, the difficulty of grid-supplied load forecasting is further exacerbated. Traditional statistical methods struggle to capture the dynamic characteristics of grid-supplied load, especially under extreme weather conditions. This paper proposes a novel grid-supplied load prediction model based on Convolutional Neural Network-Bidirectional LSTM-Attention mechanism (CNN-BiLSTM-Attention). The model utilizes transfer… More >

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309

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Wenbiao Li^1,2, Zhichong Cao^1,*, Zhengyu Li³, Wenbiao Tao³, Cheng Liu¹, Yuxin Shi³, Rundong Tian¹
Energy Engineering, Vol.122, No.11, pp. 4733-4754, 2025, DOI:10.32604/ee.2025.068683 - 27 October 2025
（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 With the increasing penetration of renewable energy in power systems, grid structures and operational paradigms are undergoing profound transformations. When subjected to disturbances, the interaction between power electronic devices and dynamic loads introduces strongly nonlinear dynamic characteristics in grid voltage responses, posing significant threats to system security and stability. To achieve reliable short-term voltage stability assessment under large-scale renewable integration, this paper innovatively proposes a response-driven online assessment method based on energy function theory. First, energy modeling of system components is performed based on energy function theory, followed by analysis of energy interaction mechanisms during… More >

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284

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Jack Kiing Teck Wei¹, Mohanad Taher Mohamed Sayed Roshdy¹, Bryan Ho Liang Hui¹, Jalal Tavalaei¹, Hadi Nabipour Afrouzi^2,*
Energy Engineering, Vol.122, No.11, pp. 4755-4775, 2025, DOI:10.32604/ee.2025.069980 - 27 October 2025
（This article belongs to the Special Issue: Artificial Intelligence-Driven Collaborative Optimization of Electric Vehicle, Charging Station and Grid: Challenges and Opportunities)
Abstract In this article, a hybrid energy storage system powered by renewable energy sources is suggested, which is connected to a grid-tied electric vehicle charging bay (EVCB) in Sarawak and is examined for its techno-economic effects. With a focus on three renewable energy sources, namely hydrokinetic power, solar power, and hydrogen fuel cells, the study seeks to minimize reliance on the electrical grid while meeting the growing demand from the growing electric vehicle (EV) infrastructure. A hybrid renewable energy storage system that combines solar power, hydrogen fuel cells, hydrokinetic power, and the grid was simulated and… More >

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Hongsheng Su¹, Wenyao Su¹, Yulong Che^1,*, Xiping Ma², Tian Zhao¹, Limiao Ren¹
Energy Engineering, Vol.122, No.11, pp. 4777-4797, 2025, DOI:10.32604/ee.2025.068134 - 27 October 2025
（This article belongs to the Special Issue: Revolution in Energy Systems: Hydrogen and Beyond)
Abstract Aiming at the issues of insufficient carrying capacity, limited flexibility, and weak source-network-load-storage coordination capability in distribution networks under the background of high-proportion new energy integration. This study proposes a bi-level optimization model for ADN integrating hybrid wind-solar-hydrogen-storage systems. First, an electro-hydrogen coupling system framework is constructed, including models for electrolytic hydrogen production, hydrogen storage, and fuel cells. Meanwhile, typical scenarios of wind-solar joint output are developed using Copula functions to characterize the variability of renewable energy generation. Second, a bi-level optimization model for ADN with electrolytic hydrogen production and storage systems is established: the… More >

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