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

IF 5 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Kunpeng Zhang , Tianhao Liu , Yutian Liu , Huan Ma , Linlin Ma
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引用次数: 0

Abstract

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.
缓解斜坡压力的两阶段多目标混合发电系统优化调度
随着可再生能源渗透率的不断提高,可再生能源发电中出现的斜坡事件对电力系统安全和可再生能源的高效利用提出了重大挑战。为了优化混合储能系统(HESS)的功率分配,增强可调储备以缓解斜坡事件,针对包含风能、光伏、电池和氢储能系统(ESS)的混合发电系统,提出了一种日前和日内两阶段多目标优化调度策略。首先,提出了一个新的优化目标,通过最小化能量损失来调节不同 ESS 的响应优先级,并通过惩罚因子来平衡保守性。然后,提出了一个两阶段优化调度模型,包括两个子模型。日前多目标调度模型考虑发电计划、可用储能容量和能量损失,确定可调储备不足的时段;日内调度模型根据日前结果动态调整每个时段的惩罚因子,提前增强可调储备。这种将日前调度模型和日内调度模型相结合的方法提高了远见度和计算效率。最后,介绍了一种非等距缩放方法,以改善非支配排序遗传算法 III(NSGA-III)的帕累托最优解分布。基于比利时和中国实际数据的仿真结果表明,所提出的方法能有效缓解斜坡压力,提高可再生能源利用率,同时具有较高的计算效率和对参数的鲁棒性。
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来源期刊
International Journal of Electrical Power & Energy Systems
International Journal of Electrical Power & Energy Systems 工程技术-工程:电子与电气
CiteScore
12.10
自引率
17.30%
发文量
1022
审稿时长
51 days
期刊介绍: The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces. As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.
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