Simultaneous optimisation of photovoltaic hosting capacity and energy loss of radial distribution networks with open unified power quality conditioner allocation

被引:37
|
作者
Lakshmi, Shubh [1 ]
Ganguly, Sanjib [1 ]
机构
[1] Indian Inst Technol, Dept Elect & Elect Engn, Gauhati 781039, India
关键词
photovoltaic power systems; power supply quality; power distribution planning; invertors; power generation planning; particle swarm optimisation; Pareto optimisation; set theory; approximation theory; simultaneous objective function optimisation; photovoltaic hosting capacity; energy loss level; radial distribution networks; open unified power quality conditioner allocation; multiobjective planning approach; UPQC-O; PVHC; series inverter; shunt inverter; Pareto-dominance-based approach; bus voltage magnitude; line current flow; maximum PV generation capacity; optimal PV generation capacity; voltage sag mitigated load; operational constraints; multiobjective particle swarm optimisation; solution strategy; Pareto-approximation set; PV deployment; energy loss reduction; PV capacity integration; STOCHASTIC MATHEMATICAL-MODEL; DISTRIBUTION-SYSTEMS; RECONFIGURATION; IMPROVE; MULTISTAGE; IMPACT;
D O I
10.1049/iet-rpg.2018.5389
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study presents a multi-objective planning approach to optimally place open unified power quality conditioner (UPQC-O) by simultaneously optimising the photovoltaic (PV) hosting capacity (PVHC) and energy loss of distribution networks. The modelling of UPQC-O consisting of a series and a shunt inverter is carried out so as to place in distribution networks. The Pareto-dominance-based approach is used to simultaneously optimise the objective functions to determine the optimal PV generation capacity in each bus and the locations of the inverters of UPQC-O. The limits on bus voltage magnitude, line current flow, maximum PV generation capacity in each bus, and the percentage of voltage sag mitigated load are considered to be the operational constraints in this planning problem. The solution strategy used is the multi-objective particle swarm optimisation. The approach provides the Pareto-approximation set consisting of a number of trade-off solutions in view of PVHC and energy loss. A utility can choose a solution for implementation depending on its desired PVHC and/or energy loss level. The results show that the PV deployment in distribution networks reduces the energy loss. However, the amount of energy loss reduction diminishes with higher and higher values of PV capacity integration.
引用
收藏
页码:1382 / 1389
页数:8
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