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Non-deterministic optimal power flow considering the uncertainties of wind power and load demand by multi-objective information gap decision theory and directed search domain method

机译:基于多目标信息缺口决策理论和定向搜索域方法的考虑风电和负荷需求不确定性的不确定性最优潮流

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摘要

Optimal power flow (OPF) as an important operation function of wind power-integrated power systems encounters the uncertainties of load demand and wind power. To cope with these uncertainty sources, various OPF models including deterministic OPF, probabilistic OPF, scenario-based OPF, stochastic OPF, robust OPF and recently information gap decision theory (IGDT)-based OPF have been presented in the literature. A multi-objective IGDT-based AC OPF model is presented which can simultaneously optimise various uncertainty horizons pertaining to load demands and wind powers considering the specified robustness level. Another main contribution of this study is presenting an effective directed search domain (DSD)-based multi-objective solution method to solve the proposed multi-objective IGDT-based AC OPF problem. The proposed OPF model and solution approach are tested on the IEEE 118-bus test system and the obtained results are compared with the results of other OPF models and solution methods. These comparisons illustrate the effectiveness of the proposed multi-objective IGDT-based AC OPF model as well as the proposed DSD-based multi-objective solution method.
机译:最优潮流(OPF)作为风电集成电力系统的重要运行功能,面临着负荷需求和风电的不确定性。为了应对这些不确定性来源,文献中提出了各种OPF模型,包括确定性OPF,概率OPF,基于情景的OPF,随机OPF,鲁棒的OPF和最近基于信息缺口决策理论(IGDT)的OPF。提出了一种基于多目标IGDT的AC OPF模型,该模型可以同时考虑指定的鲁棒性水平,优化与负载需求和风力相关的各种不确定性范围。这项研究的另一个主要贡献是提出了一种基于有效定向搜索域(DSD)的多目标解决方法,以解决所提出的基于多目标IGDT的AC OPF问题。在IEEE 118总线测试系统上测试了提出的OPF模型和解决方案方法,并将获得的结果与其他OPF模型和解决方案方法的结果进行了比较。这些比较说明了所提出的基于多目标IGDT的AC OPF模型以及所提出的基于DSD的多目标解决方法的有效性。

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