Multiobjective Optimal Power Flow Using Multiobjective Search Group Algorithm

被引:19
作者
Truong Hoang Bao Huy [1 ]
Kim, Daehee [1 ]
Dieu Ngoc Vo [2 ,3 ]
机构
[1] Soonchunhyang Univ, Dept Future Convergence Technol, Asan 31538, South Korea
[2] Ho Chi Minh City Univ Technol HCMUT, Dept Power Syst, Ho Chi Minh City 72506, Vietnam
[3] Vietnam Natl Univ Ho Chi Minh City VNU HCM, Ho Chi Minh City 71308, Vietnam
来源
IEEE ACCESS | 2022年 / 10卷
关键词
Costs; Fuels; Optimization; Generators; Sorting; Search problems; Linear programming; Multi-objective search group algorithm; multi-objective optimal power flow; fuel cost; emissions; OPTIMIZATION ALGORITHMS; GENETIC ALGORITHM; COST; NONSMOOTH; EMISSION;
D O I
10.1109/ACCESS.2022.3193371
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a new multi-objective method that efficiently solves the multi-objective optimal power flow (MOOPF) problem in power systems. The objective of solving the MOOPF problem is to concurrently optimize the fuel cost, emissions, and active power loss. The proposed multi-objective search group algorithm (MOSGA) is an effective method that combines the merits of the original search group algorithm with fast nondominated sorting, crowding distance, and archive selection strategies to acquire a nondominated set in a single run. The MOSGA is employed on IEEE 30-bus and 57-bus systems to validate its robustness and efficiency. It was found that implementing MOSGA to solve the MOOPF significantly enhanced the performance of power systems in terms of economic, environmental, and technical benefits. As for Case 6, the fuel cost, emissions, and active power loss were reduced by 16.5707%, 52.0605%, and 60.9443%, respectively. The simulation results were analyzed and compared with those of previously reported studies based on the best individual solutions, compromise solutions, and performance indicators. The comparative results confirmed the potential and advantage of MOSGA when solving the MOOPF problem efficiently and MOSGA had high-quality optimal solutions.
引用
收藏
页码:77837 / 77856
页数:20
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