随着孤岛微电网中可再生能源渗透率的提升以及电力需求的增长,加剧了源荷双侧的不确定性,给孤岛微电网的安全、稳定和经济运行带来严峻挑战。然而传统的鲁棒优化方法,过于注重系统的极端情况,以至拖
累了系统运行的经济性。该文使用模糊理论生成了系统的随机优化场景,基于场景的发生概率与场景最小混合
储能系统容量配置情况对场景进行了的剔除,提出了一种基于随机优化的孤岛微电网调度方法。通过构建可再
生能源与负荷的不确定性模型生成随机优化场景,建立数学模型,并在每一场景下进行需求响应调度,最后剔
除极端场景。最后,将所提方法应用于某岛屿微电网算例中进行实验验证。相较于传统鲁棒优化方法,采用所
提出的方法使系统运行成本下降了 20.17%,验证了所提方法的有效性与优越性。
The increasing penetration of renewable energy and growing electricity demand in islanded microgrids have intensified the uncertainties on both the generation and load sides,posing severe challenges to their secure,stable,and economic operation. Traditional robust optimization methods,which over-emphasize extreme system conditions,often compromise operational economy. This paper employs fuzzy theory to generate stochastic optimization scenarios for the system. Based on the probability of scenario occurrence and the minimum hybrid energy storage system capacity required for each scenario,a scenario reduction process is conducted. A stochastic optimization-based dispatch method for islanded microgrids is proposed. The method involves establishing uncertainty models for renewable energy and load to generate stochastic scenarios,formulating a mathematical model,performing demand response dispatch under each scenario,and finally filtering out extreme scenarios. Finally,based on the proposed method,experimental verification is carried out in an island microgrid case. The proposed method reduces the system operating cost by 20.17% compared to the traditional robust optimization approach. The results verify the effectiveness and superiority of the proposed method.