Multi-Objective Optimal Power Flow Using Differential Evolution

被引：48
|
作者：
Abido, M. A. [1 ]
Al-Ali, N. A. [2 ]
机构：
[1] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia
[2] Saudi Elect Co, Transmiss Asset Planning Dept, Dammam, Saudi Arabia
来源：
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING | 2012年 / 37卷 / 04期
关键词：
Optimal power flow; Multi-objective optimization; Evolutionary algorithms; Differential evolution; ALGORITHMS;
D O I：
10.1007/s13369-012-0224-3
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper presents a multi-objective differential-evolution-based approach to solve the optimal power flow (OPF) problem. The OPF problem has been treated as a true multi-objective constrained optimization problem. Different objective functions and operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. In addition, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE 30-bus and IEEE 118-bus standard test systems show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well-distributed Pareto-optimal solutions.
引用
收藏
页码：991 / 1005
页数：15
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