Simultaneous optimal allocation and sizing of DGs and capacitors in radial distribution systems using SPEA2 considering load uncertainty

被引:10
|
作者
Biswal, Saubhagya Ranjan [1 ]
Shankar, Gauri [1 ]
机构
[1] Indian Inst Technol, Indian Sch Mines, Dept Elect Engn, Dhanbad, Jharkhand, India
关键词
distribution networks; genetic algorithms; evolutionary computation; Pareto optimisation; power distribution planning; optimisation; distributed power generation; load flow; fuzzy set theory; capacitors; radial distribution systems; multiobjective optimisation technique based approach; multiobjective strength Pareto evolutionary algorithm 2; distributed generator; capacitor placement problem; nondominated Pareto optimal solution; Pareto optimal solutions; 69-bus radial distribution test systems; simultaneous optimal allocation; SPEA2 considering load uncertainty; load demand results; higher line; distribution system augmentation; fluctuating loads; simultaneous optimal placement; distributed generations; POWER LOSS REDUCTION; OPTIMAL PLACEMENT; DISTRIBUTION NETWORKS; SHUNT CAPACITORS; GENERATION; LOCATION; ALGORITHM; BANKS; IMPACT; UNITS;
D O I
10.1049/iet-gtd.2018.5896
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The rapid growth in load demand results in higher line loses in distribution systems and also demands distribution system augmentation. Apart from this, due to fluctuating loads, it becomes a challenge for the utility sectors to maintain voltage stability of the system under healthy condition. For addressing such problems, simultaneous optimal placement of distributed generations (DGs) and capacitors in radial distribution systems employing multi-objective optimisation technique based approach is explored in this work. In line with this, the present work uses a simple and powerful multi-objective strength Pareto evolutionary algorithm 2 (SPEA2) for solving distributed generator and capacitor placement problem considering load uncertainty. The uncertainty characteristics of load are designed by probabilistic approach and the same is utilised during the optimisation process. Thereafter, a set of non-dominated Pareto optimal solution is obtained according to the objective function value. A compromised solution is selected from the set of Pareto optimal solutions by using fuzzy set theory. Along with the above, the impact of reverse power flow is studied by taking different test cases. The studied algorithm has been tested on different standard IEEE 33-bus and 69-bus radial distribution test systems.
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页码:494 / 505
页数:12
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