Title :
Enhanced PSO based multi-objective distributed generation placement and sizing for power loss reduction and voltage stability index improvement
Author :
Musa, H. ; Adamu, S.S.
Author_Institution :
Dept. of Electr. Eng., Bayero Univ., Kano, Nigeria
Abstract :
This paper presents an enhanced particle swarm optimization (PSO) algorithm for Distributed Generation (DG) placement and sizing using multi-objective optimization concept. It is based on the combination of Evolutionary Programming (EP) and PSO. The merits of EP and PSO are combined together so as to achieve faster convergence and accuracy of the DG sizes. The quality of the solution is improved by exploring the less crowded area in the existing solution space to obtain more non-dominated solutions. The proposed approach was tested on standard IEEE 33 -Bus test system. Result obtained shows the ability of the proposed algorithm towards production of well-distributed Pareto optimal non-dominated solution of the multi-objective DG sizing problem.
Keywords :
IEEE standards; Pareto optimisation; distributed power generation; evolutionary computation; particle swarm optimisation; DG sizes; Pareto optimal nondominated solution; enhanced PSO based multiobjective distributed generation placement; enhanced PSO based multiobjective distributed generation sizing; enhanced particle swarm optimization algorithm; evolutionary programming; multiobjective DG sizing problem; multiobjective optimization concept; nondominated solutions; power loss reduction; standard IEEE 33-bus test system; voltage stability index improvement; Convergence; Equations; Indexes; Load flow; Optimization; Power system stability; Stability criteria; Distributed Generation; Particle Swarm optimization; Power losses; Voltage stability Index; placement and sizing;
Conference_Titel :
Energytech, 2013 IEEE
Conference_Location :
Cleveland, OH
DOI :
10.1109/EnergyTech.2013.6645315