Ruigang Zhang^1,*, Qihui Yan², Jialiang Wang¹, Hao Wang¹, Jie Sun², Junjiao Shi²

Energy Engineering, Vol.122, No.9, pp. 3609-3624, 2025, DOI:10.32604/ee.2025.066880 - 26 August 2025

Abstract As the core facility of offshore wind power systems, the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms. With the global energy transition toward green and low-carbon goals, offshore wind power has emerged as a key renewable energy source, yet its booster stations face harsh marine environments, including persistent wave impacts, salt spray corrosion, and equipment-induced vibrations. Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations: low efficiency, poor real-time performance, and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.… More >

Jikai Chen, Jiawei Wang, Jiayang Zhang, Shuangshuang Yao, Qianxin Li, Haoru Li^*

Energy Engineering, Vol.122, No.9, pp. 3703-3718, 2025, DOI:10.32604/ee.2025.066620 - 26 August 2025

Abstract As a new dynamic reactive power compensator, the grid-forming Static Var Generator (GF-SVG) can not only provide reactive power-voltage support, but also has inertial support capability. It has been experimentally deployed in many wind farms. However, studies have shown that when the three-phase short-circuit fault occurs in the wind farm, the transient overcurrent during the fault occurrence and fault clearance is suppressed, making it difficult for GF-SVG to use traditional fixed virtual impedance. Aiming at the problem, firstly, the influence of virtual reactance on control stability is analyzed using the GF-SVG’s current open-loop transfer function.… More >

James Hancock^*, Matthew Craven, Craig McNeile, Davide Vadacchino

Journal of Quantum Computing, Vol.7, pp. 55-79, 2025, DOI:10.32604/jqc.2025.068127 - 11 August 2025

Abstract This paper investigates Windfarm Layout Optimization (WFLO), where we formulate turbine placement considering wake effects as a Quadratic Unconstrained Binary Optimization (QUBO) problem. Wind energy plays a critical role in the transition toward sustainable power systems, but the optimal placement of turbines remains a challenging combinatorial problem due to complex wake interactions. With recent advances in quantum computing, there is growing interest in exploring whether hybrid quantum-classical methods can provide advantages for such computationally intensive tasks. We investigate solving the resulting QUBO problem using the Variational Quantum Eigensolver (VQE) implemented on Qiskit’s quantum computer simulator, More >

Mehmet Balci^1,*, Emrah Dokur², Ugur Yuzgec³

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 945-968, 2025, DOI:10.32604/cmes.2025.067851 - 31 July 2025

Abstract Accurate prediction of wind energy plays a vital role in maintaining grid stability and supporting the broader shift toward renewable energy systems. Nevertheless, the inherently variable nature of wind and the intricacy of high-dimensional datasets pose major obstacles to reliable forecasting. To address these difficulties, this study presents an innovative hybrid method for short-term wind power prediction by combining a Long Short-Term Memory (LSTM) network with a Single Candidate Optimizer (SCO) algorithm. In contrast to conventional techniques that rely on random parameter initialization, the proposed LSTM-SCO framework leverages the distinctive capability of SCO to work More > Graphic Abstract

Yi-Hao Tu, Yi-Wei Ma^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4563-4582, 2025, DOI:10.32604/cmc.2025.066899 - 30 July 2025

Abstract This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network (SETL-DDQN) and an extended Gumbel distribution method, designed to optimize the Contention Window (CW) in IEEE 802.11 networks. Unlike conventional Deep Reinforcement Learning (DRL)-based approaches for CW size adjustment, which often suffer from overestimation bias and limited exploration diversity, leading to suboptimal throughput and collision performance. Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions. First, SETL adopts a DDQN architecture (SETL-DDQN) to improve Q-value estimation accuracy and enhance training stability. Second, we incorporate a… More >

Yuqian Huang¹, Luyi Chen², Zilun Peng¹, Lin Cui^1,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 6015-6034, 2025, DOI:10.32604/cmc.2025.066717 - 30 July 2025

Abstract Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods, which are critical for identifying long-term behaviors and subtle security threats. Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments, yet they are fundamentally limited in computational and memory resources. Accurate and memory-efficient persistent flow detection on programmable switches is therefore essential. However, existing approaches often rely on fixed-window sketches or multiple sketches instances, which either suffer from insufficient temporal precision or incur substantial memory overhead, making them ineffective… More >

Yunfei Xu¹, Jianfeng Liu^1,*, Tianxing Sun¹, Heran Kang¹, Xiaoqing Hao²

Energy Engineering, Vol.122, No.8, pp. 3155-3176, 2025, DOI:10.32604/ee.2025.065753 - 24 July 2025

Abstract In order to promote the utilization level of new energy resources for local and efficient consumption, this paper introduces the biogas (BG) fermentation technology into the integrated energy system (IES). This initiative is to study the collaborative and optimal scheduling of IES with wind power (WP), photovoltaic (PV), and BG, while integrating carbon capture system (CCS) and power-to-gas (P2G) system. Firstly, the framework of collaborative operation of IES for BG-CCS-P2G is constructed. Secondly, the flexible scheduling resources of the source and load sides are fully exploited, and the collaborative operation mode of CCS-P2G is proposed… More >

Qing Zhu¹, Denghui Guo¹, Rui Ruan¹, Zhidong Chai¹, Chaoqun Wang², Zhiwen Guan^2,*

Energy Engineering, Vol.122, No.8, pp. 3133-3154, 2025, DOI:10.32604/ee.2025.063165 - 24 July 2025

Abstract This study presents an emergency control method for sub-synchronous oscillations in wind power grid-connected systems based on transfer learning, addressing the issue of insufficient generalization ability of traditional methods in complex real-world scenarios. By combining deep reinforcement learning with a transfer learning framework, cross-scenario knowledge transfer is achieved, significantly enhancing the adaptability of the control strategy. First, a sub-synchronous oscillation emergency control model for the wind power grid integration system is constructed under fixed scenarios based on deep reinforcement learning. A reward evaluation system based on the active power oscillation pattern of the system is… More >

Yinguo Yang¹, Lifu Ding^2,*, Yang Liu¹, Bingchen Wang², Weihua Wang¹, Ying Chen²

Energy Engineering, Vol.122, No.7, pp. 2571-2587, 2025, DOI:10.32604/ee.2025.065716 - 27 June 2025

Abstract This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn (FLOW Redirection and Induction Dynamics) dynamic wake model. First, the impact of wakes on turbine effective wind speed is analyzed, leading to a quantitative method for assessing wake interactions. Based on these interactions, a partitioning method divides the wind farm into smaller, computationally manageable zones. Subsequently, a heuristic control algorithm is developed for yaw optimization within each partition, reducing the overall computational burden associated with multi-turbine optimization. The algorithm’s effectiveness is evaluated through case More >

Dongfeng Yang, Ruirui Zhang, Chuang Liu^*, Guoliang Bian

Energy Engineering, Vol.122, No.7, pp. 2673-2694, 2025, DOI:10.32604/ee.2025.062154 - 27 June 2025

Abstract Under the current long-term electricity market mechanism, new energy and thermal power face issues such as deviation assessment and compression of generation space. The profitability of market players is limited. Simultaneously, the cooperation model among various energy sources will have a direct impact on the alliance’s revenue and the equity of income distribution within the alliance. Therefore, integrating new energy with thermal power units into an integrated multi-energy complementary system to participate in the long-term electricity market holds significant potential. To simulate and evaluate the benefits and internal distribution methods of a multi-energy complementary system… More >