Electric distribution network multiobjective design using a problem-specific genetic algorithm

被引:121
作者
Carrano, EG [1 ]
Soares, LAE
Takahashi, RHC
Saldanha, RR
Neto, OM
机构
[1] Univ Fed Minas Gerais, Dept Engn Eletr, BR-30123970 Belo Horizonte, MG, Brazil
[2] Strike Engn & Consultoria, BR-30123970 Belo Horizonte, MG, Brazil
[3] Univ Fed Minas Gerais, Dept Matemat, BR-30123970 Belo Horizonte, MG, Brazil
关键词
decision-making; energy distribution networks; genetic algorithms (GAs); multiobjective optimization; network topology optimization;
D O I
10.1109/TPWRD.2005.858779
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
This paper presents a multiobjective approach for the design of electrical distribution networks. The objectives are defined as a monetary cost index (including installation cost and energy losses cost) and a system failure index. The true Pareto-optimal solutions are found with a multiobjective genetic algorithm that employs an efficient variable encoding scheme and some problem-specific mutation and crossover operators. Results based on 21- and 100-bus systems are presented. The information gained from the Pareto-optimal solution set is shown to be useful for the decision-making stage of distribution network evolution planning.
引用
收藏
页码:995 / 1005
页数:11
相关论文
共 28 条
[1]   Evolving non-dominated solutions in multiobjective service restoration for automated distribution networks [J].
Augugliaro, A ;
Dusonchet, L ;
Sanseverino, ER .
ELECTRIC POWER SYSTEMS RESEARCH, 2001, 59 (03) :185-195
[2]  
Bazaraa MS., 2008, LINEAR PROGRAMMING N
[3]  
BERNALAGUSTIN JL, 1998, THESIS ZARAGOZA U ZA
[4]  
Carrano E.G., 2005, MULTIOBJECTIVE GENET
[5]   Optimal distribution network expansion planning under uncertainty by evolutionary decision convergence [J].
Carvalho, PMS ;
Ferreira, LAFM .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 1998, 20 (02) :125-129
[6]  
Chankong V., 1983, Multiobjective Decision Making: Theory and Methodology
[7]   An updated survey of GA-based multiobjective optimization techniques [J].
Coello, CAC .
ACM COMPUTING SURVEYS, 2000, 32 (02) :109-143
[8]  
Cossi AM, 2005, IEEE T POWER DELIVER, V20, P205, DOI [10.1109/TPWRD.2004.839229, 10.1109/tpwrd.2004.839229]
[9]   Solving to optimality the uncapacitated fixed-charge network flow problem [J].
Cruz, FRB ;
Smith, JM ;
Mateus, GR .
COMPUTERS & OPERATIONS RESEARCH, 1998, 25 (01) :67-81
[10]   Reactive power compensation for radial distribution networks using genetic algorithm [J].
Das, D .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2002, 24 (07) :573-581