Utilizing PSO Technique for Locational-dependent Feeder PV Hosting Capacity Evaluation

被引:1
作者
Panchalogaranjan, Vinushika [1 ]
Moses, Paul [1 ]
机构
[1] Univ Oklahoma, Sch Elect & Comp Engn, Norman, OK 73019 USA
来源
2023 IEEE 50TH PHOTOVOLTAIC SPECIALISTS CONFERENCE, PVSC | 2023年
关键词
Distribution system; Particle swarm optimization; PV hosting capacity; Renewable energy resources; IMPACTS;
D O I
10.1109/PVSC48320.2023.10360041
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Integration of renewable energy resources (RER) like solar photovoltaic (PV) power in the distribution system (DS) is one of the key aspects in the evolution of modern power systems. Maximizing the utilization of the RER while adhering to stringent grid standards has become a crucial technical challenge in distributed power systems. The analysis of overall network performance and PV capacity limitations is essential before the installation of a PV source in a distribution feeder. This paper analyses the locational-dependent PV hosting capacity (PVHC) for a central PV plant integrated into the DS using the particle swarm optimization (PSO) method. The proposed methodology is applied in simulations of a real distribution feeder and examines the effectiveness of the framework. The results show that PSO is an effective method to determine the locational-dependent PVHC.
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页数:5
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