Jian Wang¹, Hui Qi¹, Feilong Jiang^2,*, Biao Jiang³, Tiankui Sun⁴, Lingyi Ji¹, Yajun Zhao², Feifei Bu²

Energy Engineering, Vol.122, No.12, pp. 4873-4897, 2025, DOI:10.32604/ee.2025.069071 - 27 November 2025

Abstract To enhance power supply reliability and reduce customer outage time, Mobile Emergency Power Supply Vehicles (MEPSVs), including Mobile Diesel Generator Vehicles (MDGVs) and Mobile Energy Storage Vehicles (MESVs), have become indispensable sources for grid maintenance and disaster response. However, in practice, relying solely on MESVs is constrained by battery capacity, making it difficult to meet long-duration power demands. Conversely, using only MDGVs often results in low efficiency and high fuel consumption under fluctuating load conditions, posing challenges to achieving economical and efficient power supply. To address these issues, this paper investigates the parallel power supply… More >

Abdullrahman A. Al-Shamma’a¹, Hassan M. Hussein Farh^1,*, Ridwan Taiwo², Al-Wesabi Ibrahim³, Abdulrhman Alshaabani¹, Saad Mekhilef ⁴, Mohamed A. Mohamed^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1303-1347, 2025, DOI:10.32604/cmes.2025.071302 - 26 November 2025

Abstract Optimal sizing and allocation of distributed generators (DGs) have become essential computational challenges in improving the performance, efficiency, and reliability of electrical distribution networks. Despite extensive research, existing approaches often face algorithmic limitations such as slow convergence, premature stagnation in local minima, or suboptimal accuracy in determining optimal DG placement and capacity. This study presents a comprehensive scientometric and systematic review of global research focused on computer-based modelling and algorithmic optimization for renewable DG sizing and placement. It integrates both quantitative and qualitative analyses of the scholarly landscape, mapping influential research domains, co-authorship structures, the 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 >

Xiangyang Cao^1,2, Yaojie Zheng^1,2, Hanbin Xiao^1,2,*, Min Xiao^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 289-334, 2025, DOI:10.32604/cmes.2025.063954 - 11 April 2025

Abstract This study investigates the Maximum Power Point Tracking (MPPT) control method of offshore wind-photovoltaic hybrid power generation system with offshore crane-assisted. A new algorithm of Global Fast Integral Sliding Mode Control (GFISMC) is proposed based on the tip speed ratio method and sliding mode control. The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter. An offshore wind power generation system model is presented to verify the algorithm effect. An offshore More >

Caifeng Wen¹, Feifei Xue^1,*, Hongliang Hao², Edwin E. Nyakilla², Ning Yang^1,*, Yongsheng Wang³, Yuwen Zhang²

Energy Engineering, Vol.122, No.4, pp. 1511-1529, 2025, DOI:10.32604/ee.2025.060810 - 31 March 2025

Abstract This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output. It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity. To enable more accurate predictions of the optimal wind-solar ratio, a comprehensive complementarity rate is proposed, which allows for the optimization of wind-solar capacity based on this measure. Initially, the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power, enabling the calculation of the comprehensive complementarity rate. Following this, a joint planning… More >

Jian Gao¹, Hongliang Hao², Caifeng Wen^1,*, Yongsheng Wang³, Zhanhua Han⁴, Edwin E. Nykilla², Yuwen Zhang²

Energy Engineering, Vol.122, No.3, pp. 1175-1198, 2025, DOI:10.32604/ee.2025.061083 - 07 March 2025

Abstract Power quality is a crucial area of research in contemporary power systems, particularly given the rapid proliferation of intermittent renewable energy sources such as wind power. This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra, PSD, and random signal power spectra. The relationship was derived, validated through experiments and simulations, and subsequently applied to multi-objective optimization. Various optimization algorithms were compared to achieve optimal system power quality. The findings revealed that the relationships between power quality indices and PSD were influenced by variations in More >

Yun Zhang^1,*, Zifen Han², Biao Tian¹, Ning Chen², Yi Fan³

Energy Engineering, Vol.122, No.1, pp. 167-184, 2025, DOI:10.32604/ee.2024.056190 - 27 December 2024

Abstract The new energy power generation is becoming increasingly important in the power system. Such as photovoltaic power generation has become a research hotspot, however, due to the characteristics of light radiation changes, photovoltaic power generation is unstable and random, resulting in a low utilization rate and directly affecting the stability of the power grid. To solve this problem, this paper proposes a coordinated control strategy for a new energy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit. Firstly, the variational mode decomposition algorithm is… More >

Daixuan Zhou¹, Yujin Liu¹, Xu Wang², Fuxing Wang¹, Yan Jia^2,*

Energy Engineering, Vol.121, No.12, pp. 3573-3616, 2024, DOI:10.32604/ee.2024.055853 - 22 November 2024

Abstract With the increasing proportion of renewable energy in China’s energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. More > Graphic Abstract

Yuxuan Zhao^1,2,*, Bo Wang¹, Shu Wang¹, Wenjun Xu², Gang Ma²

Energy Engineering, Vol.121, No.12, pp. 3711-3733, 2024, DOI:10.32604/ee.2024.054032 - 22 November 2024

Abstract The output of photovoltaic power stations is significantly affected by environmental factors, leading to intermittent and fluctuating power generation. With the increasing frequency of extreme weather events due to global warming, photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions. The integration of these stations on a large scale into the power grid could potentially pose challenges to system stability. To address this issue, in this study, we propose a network architecture based on VMD-KELM for predicting the power output of photovoltaic power plants during severe weather… More >

Jingbin Wu^1,*, Hongming Yang², Sheng Xiang²

Energy Engineering, Vol.121, No.11, pp. 3263-3287, 2024, DOI:10.32604/ee.2024.054019 - 21 October 2024

Abstract Currently, the operational performance assessment system in the power market primarily focuses on power generation and electricity retail companies, lacking a system tailored to the operational characteristics of power generation/selling integrated companies. Therefore, this article proposes an assessment index system for assessing the operational performance of a power generation/selling integrated company, encompassing three dimensions: basic capacity, development potential, and external environment. A dynamic proportional adjustment coefficient is designed, along with a subjective and objective weighting model for assessment indexes based on a combined weighting method. Subsequently, the operational performance of an integrated company is assessed More > Graphic Abstract