Mengxuan Shi¹, Lintao Li², Dejun Shao¹, Xiaojie Pan¹, Xingyu Shi^2,*, Yuxun Wang²

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069915 - 27 December 2025

Abstract In wind power transmission via modular multilevel converter based high voltage direct current (MMC-HVDC) systems, under traditional control strategies, MMC-HVDC cannot provide inertia support to the receiving-end grid (REG) during disturbances. Moreover, due to the frequency decoupling between the two ends of the MMC-HVDC, the sending-end wind farm (SEWF) cannot obtain the frequency variation information of the REG to provide inertia response. Therefore, this paper proposes a novel coordinated source-network-storage inertia control strategy based on wind power transmission via MMC-HVDC system. First, the grid-side MMC station (GS-MMC) maps the frequency variations of the REG to… More >

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

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 >

Fan Chen^*, Tianhui Zhang, Man Wang, Zhiheng Zhuang, Qiang Zhang, Zihan Ma

Energy Engineering, Vol.122, No.10, pp. 4099-4120, 2025, DOI:10.32604/ee.2025.069346 - 30 September 2025

Abstract The configuration of a hybrid energy storage system (HESS) plays a pivotal role in mitigating wind power fluctuations and enabling primary frequency regulation, thereby enhancing the active power support capability of wind power integration systems. However, most existing studies on HESS capacity configuration overlook the self-recovery control of the state of charge (SOC), creating challenges in sustaining capacity during long-term operation. This omission can impair frequency regulation performance, increase capacity requirements, and shorten battery lifespan. To address these challenges, this study proposes a bi-level planning–operation capacity configuration model that explicitly incorporates SOC self-recovery control. In… More >

Ziming Hu¹, Jingfa Li^1,*, Chaoyang Fan¹, Jiale Xiao¹, Huijie Huang², Bo Yu¹, Baocheng Shi¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.010823

Abstract Hydrogen production from offshore wind power is an effective means to address the challenges of wind power grid integration and has emerged as a focal point in the development and research of offshore wind energy in recent years. However, the current state of hydrogen storage and transportation technologies for offshore applications lacks comprehensive economic analysis. This study aims to provide a thorough economic evaluation of these technologies by considering both fixed investment costs and operational and maintenance costs. A levelized cost model is employed to analyze four offshore hydrogen storage and transportation schemes: gas hydrogen… More >

Hao Wang^*, Wenyue Zhou, Yiping Luo

Energy Engineering, Vol.122, No.9, pp. 3737-3752, 2025, DOI:10.32604/ee.2025.067938 - 26 August 2025

Abstract Currently, renewable energy has been broadly implemented across diverse sectors, particularly evidenced by its substantially higher integration levels in power systems. The large-scale integration of renewable energy resources introduces distinct fault characteristics into power grids, potentially rendering traditional line protection schemes inadequate for transmission lines interfacing with these sources. Therefore, it is imperative to study line protection methods unaffected by the integration of renewable energy resources. After analyzing the propagation process of the fault traveling wave along the transmission line, a non-unit protection based on traveling wave distance measurement is proposed. The core principle of… More >

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 >

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

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 >

Namal Rathnayake¹, Jeevani Jayasinghe^2,3, Rashmi Semasinghe², Upaka Rathnayake^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2287-2305, 2025, DOI:10.32604/cmes.2025.064464 - 30 May 2025

Abstract In this study, a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions. Using data on wind speed, air temperature, nacelle position, and actual power, lagged features were generated to capture temporal dependencies. Among 24 evaluated models, the ensemble bagging approach achieved the best performance, with R² values of 0.89 at 0 min and 0.75 at 60 min. Shapley Additive exPlanations (SHAP) analysis revealed that while wind speed is the primary driver for short-term predictions, air temperature and nacelle position become more More >

Xingxu Zhu¹, Guiqing Zhao¹, Gangui Yan¹, Junhui Li^1,*, Hongda Dong², Chenggang Li²

Energy Engineering, Vol.122, No.5, pp. 1645-1668, 2025, DOI:10.32604/ee.2025.063192 - 25 April 2025

Abstract The participation of wind farms in the former energy market faces challenges such as power fluctuations and energy storage construction costs. To this end, this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasing model, which assists wind farms in bidding for participation in the former energy market through leasing services, thereby enhancing energy storage efficiency and maximizing economic benefits. In this paper, based on the Weibull probability distribution to portray the uncertainty of wind power, and considering the lifetime capacity loss caused by charging and discharging of… More > Graphic Abstract