Title :
Optimal planning of substation locating and sizing based on adaptive niche differential evolution algorithm
Author :
Zifa, Liu ; Xing, Liu
Author_Institution :
Key Lab. of Power Syst. Protection & Dynamic Security Monitoring & Control of Minist. of Educ., North China Electr. Power Univ., Beijing, China
Abstract :
To deal with reactive power optimization problem, an adaptive Niche Particle Swarm Optimization algorithm (ANPSO) is presented. Differential Evolution algorithm (DE) is easy to use and has the advantages of strong robustness, but its efficiency is limited and probably to fall into local optimum because the population loss of diversity after several generations. ANDE introduces niche-sharing mechanisms to change the individual values and accelerates to eliminate individuals which have low value. Niching radius can also be adjusted adaptively on the basis of the relative distance between individuals which reflect the aggregation of population. Using the above method, algorithm´s global searching ability is improved. The proposed algorithm is tested on a realistic planning project and the results show its better performance on celerity, accuracy and efficiency.
Keywords :
evolutionary computation; particle swarm optimisation; power system planning; reactive power; substations; ANPSO; adaptive niche differential evolution algorithm; adaptive niche particle swarm optimization algorithm; optimal substation location planning; optimal substation sizing planning; power system planning; reactive power optimization problem; Algorithm design and analysis; Convergence; Genetic algorithms; Optimization; Planning; Search problems; Substations; differential evolution algorithm; niche; power distribution; power system planning;
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
Conference_Location :
Weihai, Shandong
Print_ISBN :
978-1-4577-0364-5
DOI :
10.1109/DRPT.2011.5994088