Title :
Combining Differential Evolution Algorithm with biogeography-based optimization algorithm for reconfiguration of distribution network
Author :
Jingwen Li ; Jinquan Zhao
Author_Institution :
Sch. of Energy & Electr. Eng., Hohai Univ., Nanjing, China
fDate :
Oct. 30 2012-Nov. 2 2012
Abstract :
A method combining differential evolution algorithm with biogeography-based optimization algorithm was proposed for distribution network reconfiguration with the objective of network loss minimum. In the solving processes, through simplifying the structure of distribution network topology and using the encoded mode, which based on the loop coding, the number of solutions, which can´t keep the network radiating, was greatly reduced. The proposed optimization method combines the advantages of differential evolution algorithm and biogeography-based optimization algorithm. It effectively overcomes the defect of early-maturing, improves the search speed and increases the probability of the optimal solution. A typical example of 69 nodes case was simulated by using the proposed algorithm. The results show that the proposed method is efficient, rapidly convergent and having good stability.
Keywords :
distribution networks; evolutionary computation; optimisation; power system stability; biogeography-based optimization algorithm; differential evolution algorithm; distribution network reconfiguration; distribution network topology; loop coding; optimal solution; probability; stability; Encoding; Indexes; Niobium; Optimization; Switches; Biogeography-Based Optimization; Differential Evolution; Distribution Network Reconfiguration; Loop Coding; Network Simplification;
Conference_Titel :
Power System Technology (POWERCON), 2012 IEEE International Conference on
Conference_Location :
Auckland
Print_ISBN :
978-1-4673-2868-5
DOI :
10.1109/PowerCon.2012.6401351