考虑负荷需求和太阳能-风力发电系统季节性不确定性的配电系统RDG优化配置

M. Zellagui, N. Belbachir, C. El‐Bayeh
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引用次数: 5

摘要

近年来,将可再生分布式发电系统(RDG)安装到配电系统(EDS)中,成为保证电力消耗和生产平衡的最佳解决方案之一,也显示出各种优势。除了提供清洁能源外,它们还有助于最大限度地减少功率损耗,并增强电压分布。本文利用灰狼优化器(GWO)的元启发式优化算法,考虑RDG输出电能的不确定性以及各季节负荷需求的变化,将基于RDG的多个PV和WT机组优化分配到EDS中。本文提出的多目标函数(MOF)是为了同时最小化过流继电器(OCR)的有功功率损耗指数(APLI)、无功功率损耗指数(RPLI)、电压偏差指数(VDI)、运行时间指数(OTI)的总和,并提高安装在IEEE 33总线EDS测试系统中的过流继电器的协调时间间隔指数(CTII)。
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Optimal Allocation of RDG in Distribution System Considering the Seasonal Uncertainties of Load Demand and Solar-Wind Generation Systems
Recently, the installation of Renewable Distributed Generation (RDG) into the Electrical Distribution System (EDS) became one of the best solutions that guarantee the balance between electric energy consumption and production, also show various advantages. In addition to delivering clean energy, they contribute to minimizing power losses, as well as enhancing the voltage profiles. In this paper, the metaheuristic optimization algorithm of the Grey Wolf Optimizer (GWO) is utilized to optimally allocate the RDG based multiple PV and WT units into EDS considering the uncertainty of electrical output energy from the RDGs as well as load demand variation during all seasons. The Multi-Objective Functions (MOF) developed in this paper is considered to minimize simultaneous the indices of the total of Active Power Loss Index (APLI), the Reactive Power Loss Index (RPLI), the Voltage Deviation Index (VDI), the Operation Time Index (OTI) of the overcurrent relay (OCR), and enhance the Coordination Time Interval Index (CTII) of the overcurrent relays installed in the test system which is the IEEE 33-bus EDS.
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