Title :
Stochastic Optimal Power Flow Based Improved Differential Evolution
Author :
Yan, Hongwen ; Li, Xinran
Author_Institution :
Dept. of Electr. Eng., Hunan Universit, Changsha, China
Abstract :
This paper presents a improved differential evolution approach to solve the stochastic optimal power flow (OPF) problem. The stochastic OPF problem minimizes the total the expected cost of a base-case operating state considering the stochastic load and generator. The improved Optimal settings of stochastic OPF control variables produced by Monte Carlo method are designed by this improved differential evolution (DE) algorithm. The proposed methods are illustrated on the the standard IEEE 30-bus system and the result shows that its effectiveness and robustness.
Keywords :
Monte Carlo methods; differential equations; load flow control; minimisation; stochastic processes; IEEE 30-bus system; Monte Carlo method; improved differential evolution; stochastic optimal power flow; Generators; Load flow; Monte Carlo methods; Optimization; Power system dynamics; Reactive power; Stochastic processes; Differential Evolution; Monte Carlo Introduction; Stochastic OPF;
Conference_Titel :
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9247-3
DOI :
10.1109/GCIS.2010.110
