Yi Qi¹, Yuhao Xie^2,*, 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 >

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 >

Xincheng Han¹, Hongyan Ma^1,2,3,*, Shuo Meng¹, Chengzhi Ren¹

Energy Engineering, DOI:10.32604/ee.2025.072906

Abstract Lithium-ion (Li-ion) batteries stand as the dominant energy storage solution, despite their widespread adoption, precisely determining the state of charge (SOC) continues to pose significant difficulties, with direct implications for battery safety, operational reliability, and overall performance. Current SOC estimation techniques often demonstrate limited accuracy, particularly when confronted with complex operational scenarios and wide temperature variations, where their generalization capacity and dynamic adaptation prove insufficient. To address these shortcomings, this work presents a PSO-TCN-Transformer network model for SOC estimation. This research uses the Particle Swarm Optimization (PSO) method to automatically configure the architectural parameters of… More >

Dexiecia Anak Francis¹, Jalal Tavalaei¹, Hadi Nabipour Afrouzi^2,*

Energy Engineering, DOI:10.32604/ee.2025.070501

Abstract Wave energy is a promising form of marine renewable energy that offers a sustainable pathway for electricity generation in coastal regions. Despite Malaysia’s extensive coastline, the exploration of wave energy in Sarawak remains limited due to economic, technical, and environmental challenges that hinder its implementation. Compared to other renewable energy sources, wave energy is underutilized largely because of cost uncertainties and the lack of local performance data. This research aims to identify the most suitable coastal zone in Sarawak that achieves an optimal balance between energy potential, cost-effectiveness, and environmental impact, particularly in relation to… More >

Mehran Karimi¹, Hesamodin Heidarigoujani¹, Mehdi Jahangiri^1,*, Milad Torabi Anaraki², Daryosh Mohamadi Janaki³

Energy Engineering, DOI:10.32604/ee.2025.070190

Abstract The technical, economic, and environmental performance of solar hot-water (SWH) systems for Swedish residential apartments—where approximately 80% of household energy is devoted to space heating and sanitary hot-water production—was assessed. Two collector types, flat plate (FP) and evacuated tube (ET), were simulated in TSOL Pro 5.5 for five major cities (Stockholm, Göteborg, Malmö, Uppsala, Linköping). Climatic data and cold-water temperatures were sourced from Meteonorm 7.1, and economic parameters were derived from recent national statistics and literature. All calculations explicitly accounted for heat losses from collectors, storage tanks, and internal and external piping systems, and established… More >

Zujun Ding, Shuaichao Wu, Chenliang Ji, Xinyu Feng, Yuanyuan Shi, Baolian Liu, Wan Chen, Qiuchan Bai, Hengrui Zhou, Hui Huang, Jie Ji^*

Energy Engineering, DOI:10.32604/ee.2025.068106

Abstract In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector, the recovery of waste heat from diesel engines has become a critical area of focus. This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle (ORC) systems for waste heat recovery from diesel engines. The study assessed the performance of five candidate working fluids—R11, R123, R113, R245fa, and R141b—under a range of operating conditions, specifically varying overheat temperatures and evaporation pressures. The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency, net output power,… More >

Qiang Xu^1,*, 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 >

Yansen Sun^1,2, Yi Ding³, Hualei Cui⁴, Yuanchao Hui⁵, Yupeng He^1,2,*

Energy Engineering, DOI:10.32604/ee.2025.072860

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 >

Luyao Liu^*, Xiao Liao, Yiqian Li, Shaofeng Zhang

Energy Engineering, DOI:10.32604/ee.2025.072631

Abstract Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions. In the context of carbon neutrality, the integration of data centers with renewable energy has become a prevailing trend. To advance the renewable energy integration in data centers, it is imperative to thoroughly explore the data centers’ operational flexibility. Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulation within data center micro-grids. This paper identifies and categorizes delay-tolerant computing workloads into three types (long-running non-interruptible, long-running interruptible, and short-running) and develops… More >

Xian Shi^1,2,*, Botao Zhang^1,2, Weidong Zhang^1,2, 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 >