Two-stage multi-objective optimal dispatch of hybrid power generation system for ramp stress mitigation

被引:0
|
作者
Zhang, Kunpeng [1 ]
Liu, Tianhao [1 ]
Liu, Yutian [1 ]
Ma, Huan [2 ]
Ma, Linlin [3 ]
机构
[1] Shandong Univ, Key Lab Power Syst Intelligent Dispatch & Control, Minist Educ, Jinan 250061, Peoples R China
[2] State Grid Shandong Elect Power Res Inst, Power Grid Technol Ctr, Jinan 250003, Peoples R China
[3] State Grid Shandong Elect Power Co, Shandong Elect Power Dispatching & Control Ctr, Jinan 250001, Peoples R China
关键词
Hybrid energy storage system; Multi-objective optimization; NSGA-III; Power generation dispatch; Power ramping mitigation; OPTIMIZATION; ALGORITHM; ENERGY; STRATEGY; IMPACT;
D O I
10.1016/j.ijepes.2024.110328
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As the penetration of renewable energy continues to rise, the occurrence of ramp events in renewable generation poses significant challenges to power system security and efficient renewable energy utilization. To optimize the power allocation of hybrid energy storage systems (HESS) and enhance adjustable reserves to mitigate ramp events, a day-ahead and intraday two-stage multi-objective optimal dispatch strategy is proposed for hybrid power generation systems containing wind, photovoltaic, battery and hydrogen energy storage system (ESS). First, a novel optimization objective is presented to regulate the response priorities of different ESS by minimizing the energy loss, and balance the conservatism by a penalty factor. Then, a two-stage optimal dispatch model is proposed including two sub-models. The day-ahead multi-objective dispatch model considers generation plan, available storage capacity and energy loss, which identifies time slots when adjustable reserves is insufficient; the intraday dispatch model dynamically adjusts penalty factor for each time slot based on the day- ahead results to enhance adjustable reserves in advance. This combination of day-ahead and intraday dispatch models improves the farsightedness and computational efficiency. Finally, a non-isometric scaling method is presented to improve the distribution of Pareto optimal solutions for the non-dominated sorting genetic algorithm III (NSGA-III). Simulation results based on the actual data from Belgium and China demonstrate that the proposed method effectively mitigates the ramp stress and improves renewable energy utilization, with high computational efficiency and robustness to parameters.
引用
收藏
页数:14
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