Title :
Improved genetic algorithm for loss and simultaneously reliability optimization in radial distribution systems
Author :
Shakerian, Reza ; Tavakkolaii, Hamid ; Kamali, Seyed Hossein ; Hedayati, Maysam
Author_Institution :
Young Researchers Club, Islamic Azad Univ., Amol, Iran
Abstract :
This study presents a new method to improve simultaneously reliability and minimize active power losses in radial distribution systems (RDS), through a process of network reconfiguration. The methodology adopted to enhance reliability uses the Monte Carlo (MC) simulation and historical data of the network, such as the severity of the potential contingencies in each branch. Due to a large number of possible configurations and the need of an efficient search, the optimization is made through an improved genetic algorithm (IGA) with adaptive crossover and mutation probabilities, and with other new features. The method analyses the RDS considering in a first step, the absence of investment, and in a second step, the possibility of placing a limited number of new tie-switches, defined by a decision agent, in certain branches. The effectiveness of the proposed method is demonstrated through the analysis of a 69 bus RDS.
Keywords :
Monte Carlo methods; genetic algorithms; power distribution reliability; power engineering computing; 69 bus RDS; Monte Carlo simulation; adaptive crossover probability; improved genetic algorithm; mutation probability; network reconfiguration; radial distribution system; reliability optimization; Reliability engineering; Improved Genetic Algorithm; Loss Minimization; Monte Carlo; Reliability;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579500