Title :
A Differential Evolution Based Method for Power System Planning
Author :
Dong, Zhao Yang ; Lu, Miao ; Lu, Zhe ; Wong, Kit Po
Author_Institution :
Univ. of Queensland, Brisbane
Abstract :
Power system planning is a complex multi-objective optimization problem. It aims at locating the minimum cost of additional transmission lines that must be installed to satisfy the forecasted load in a power system. A number of different methods for power system planning have been investigated over the past decades. In this paper, a differential evolution (DE) based approach is proposed as an optimization tool to solve the power system planning problem. A comparison between genetic algorithms, evolutionary strategy (ES), and five different DE schemes are carried out on two benchmark power systems. The results shown that, as a relatively new heuristic optimization method, DE is able to provide robust and efficient solution to power system planning problems.
Keywords :
evolutionary computation; optimisation; power system planning; differential evolution; evolutionary strategy; genetic algorithm; multiobjective optimization problem; power system planning; transmission lines; Chromium; Costs; Genetic algorithms; Large-scale systems; Optimization methods; Power generation; Power system modeling; Power system planning; Power system security; Power transmission lines;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688646