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 >

Tareq Hamadneh¹, Belal Batiha², Frank Werner^3,*, Mehrdad Ahmadi Kamarposhti^4,*, Ilhami Colak⁵, El Manaa Barhoumi⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1519-1548, 2025, DOI:10.32604/cmes.2025.063571 - 30 May 2025

Abstract Reconfiguration, as well as optimal utilization of distributed generation sources and capacitor banks, are highly effective methods for reducing losses and improving the voltage profile, or in other words, the power quality in the power distribution system. Researchers have considered the use of distributed generation resources in recent years. There are numerous advantages to utilizing these resources, the most significant of which are the reduction of network losses and enhancement of voltage stability. Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Intersect Mutation Differential Evolution (IMDE) algorithms are used in this… More >

Xueqian Wang^*, Hongsheng Su

Energy Engineering, Vol.122, No.2, pp. 667-680, 2025, DOI:10.32604/ee.2024.058102 - 31 January 2025

Abstract As the proportion of new energy increases, the traditional cumulant method (CM) produces significant errors when performing probabilistic load flow (PLF) calculations with large-scale wind power integrated. Considering the wind speed correlation, a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed. Firstly, based on constructing discrete scenes of wind farms, the Nataf transform is used to handle the correlation between wind speeds. Then, the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation. Finally, the PLF calculation results of More >

Wenhui Zhao¹, Yibo Yin^1,*, Lu Mao², Konglu Zhong³, Guanghui Yuan⁴, Hai Huang⁵, Yige Yang⁶

Energy Engineering, Vol.118, No.4, pp. 1009-1026, 2021, DOI:10.32604/EE.2021.014650 - 31 May 2021

Abstract Changes in the energy price system will determine the direction of evolution of the energy industry structure. As a country where coal is the dominant energy source, what is the effect of coal price fluctuations on China’s industry development costs and energy consumption structure? To investigate this problem, this paper utilized an economy–energy–environment computable general equilibrium model. In this study, four aspects were analyzed: Energy supply side, proportion of renewable energy consumption, macroeconomy, and changes in CO₂ emissions. The results of this study show that an increase of 10%–20% in coal prices contributes to a shift More >