Title :
Multi-objective locating and sizing optimization of distributed generation
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
This paper proposes a method to realize better locating and sizing optimization of distributed generation. It combines the advantages of improved particle swarm optimization algorithm and principal component analysis technology. Based on artificial bee colony algorithm, it proposes the improvement about traditional particle swarm optimization algorithm to improve the convergence. Meanwhile, by means of using principal component analysis, it builds comprehensive model including several economy index, voltage stability index and constrained condition for comprehensive evaluation of multi-objective optimization to enhance credibility of the method proposed.
Keywords :
distributed power generation; particle swarm optimisation; power distribution economics; power system simulation; principal component analysis; voltage regulators; artificial bee colony algorithm; distributed generation; economy index; multiobjective location optimization; particle swarm optimization algorithm; principal component analysis technology; sizing optimization; voltage stability index; Convergence; Distributed power generation; Optimization; Power system stability; Principal component analysis; Reactive power; distributed generation; optimization; particle swarm optimization; principal component analysis;
Conference_Titel :
Environment and Electrical Engineering (EEEIC), 2013 12th International Conference on
Conference_Location :
Wroclaw
Print_ISBN :
978-1-4673-3060-2
DOI :
10.1109/EEEIC.2013.6549601