An improved generalized differential evolution algorithm for multi-objective reactive power dispatch

被引:25
|
作者
Ramesh, S. [1 ]
Kannan, S. [2 ]
Baskar, S. [3 ]
机构
[1] Arulmigu Kalasalingam Coll Engn, Instrumentat & Control Engn Dept, Krishnankoil, Tamil Nadu, India
[2] Kalasalingam Univ, Elect & Elect Engn Dept, Krishnankoil, Tamil Nadu, India
[3] Thiagarajar Coll Engn, Elect & Elect Engn Dept, Ctr Adv Res Evolutionary Computat CAREC, Madurai, Tamil Nadu, India
关键词
dynamic crowding distance; differential evolution; optimization; reactive power dispatch; recombination; selection; GENETIC ALGORITHM; OPTIMIZATION; MODE; REAL; FLOW;
D O I
10.1080/0305215X.2011.576761
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An improved multi-objective generalized differential evolution (I-GDE3) approach to solve optimal reactive power dispatch (ORPD) with multiple and competing objectives is proposed in this article. The objective functions are minimization of real power loss and bus voltage profile improvement. For maintaining good diversity, the concepts of simulated binary crossover (SBX) based recombination and dynamic crowding distance (DCD), are implemented in the GDE3 algorithm. I-GDE3 obtains the Pareto-solution set for ORPD that is impervious to load drifts and perturbations. The performance of the proposed approach is tested in standard IEEE 118-bus and IEEE 300-bus test systems and the result demonstrates the capability of the I-GDE3 algorithm in generating diverse and well distributed Pareto-optimal solutions that are less sensitive to various loading conditions along with load perturbations. The performance of I-GDE3 is compared with respect to multi-objective performance measures namely span, hyper-volume and C-measure. The results show the effectiveness of I-GDE3 and confirm its potential to solve the multi-objective RPD problem.
引用
收藏
页码:391 / 405
页数:15
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