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Multiobjective reactive power planning considering the uncertainties of wind farms and loads using Information Gap Decision Theory

机译:多目标无功功率规划考虑了风电场的不确定性和使用信息差距决策理论的负载

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摘要

This study deals with multiobjective reactive power planning, considering the uncertainties of load demand and wind power generation. The main feature of the current study is to examine the impact of multiple uncertainties on Reactive Power Planning (RPP), while several objectives exist. To fulfill this goal, the Information Gap Decision Theory (IGDT) is used to handle the uncertainties of load demand and wind power production. In order to cope with the probabilistic optimal RPP problem and to create Pareto optimal solutions, the epsilon-Constraint method is utilized. Fuzzy Decision Maker (FDM) and min-max approach are jointly applied to find the Best Compromise Solution (BCS). To evaluate the efficiency and the proficiency of the proposed multiobjective RPP model, it is implemented on the IEEE-30 bus test system via the GAMS software environment. To prove the superiority of the proposed model, the obtained results are compared with the scenario-based approach. The results imply that for specific amounts of uncertainty, the IGDT method performs reasonably towards the scenario-based approach. (C) 2020 Published by Elsevier Ltd.
机译:本研究涉及多目标无功率规划,考虑到负载需求和风力发电的不确定性。目前研究的主要特点是检查多种不确定性对无功率规划(RPP)的影响,而存在几个目标。为了满足这一目标,信息差距决策理论(IGDT)用于处理负荷需求和风力发电的不确定性。为了应对概率最佳RPP问题并创建帕累托最优解,利用epsilon-约束方法。模糊决策者(FDM)和最小最大方法是共同应用的,以找到最佳的妥协解决方案(BCS)。为了评估所提出的多目标RPP模型的效率和熟练程度,它通过GAMS软件环境在IEEE-30总线测试系统上实现。为了证明所提出的模型的优越性,将获得的结果与基于场景的方法进行比较。结果意味着对于特定的不确定性,IGDT方法可合理地朝着基于场景的方法进行。 (c)2020由elestvier有限公司发布

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