Research on Multi-Objective reactive power optimization based on modified Particle Swarm Optimization algorithm

This paper proposes modified Multi-Objective Particle Swarm Optimization (MPSO) algorithm based on Pareto solution to overcome the conventional MPSO algorithm can easily fall into its local maximum value and improve the diversity of solution set. This algorithm is composition of a modified Tabu Sear...

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Vydáno v:2010 Chinese Control and Decision Conference s. 477 - 480
Hlavní autoři: Jianhua Wu, Nan Li, Lihong He, Bin Yin, Jianhua Guo, Yaqiong Liu
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2010
Témata:
active network loss
Mathematical model
MPSO
Multi-Objective Reactive Power Optimization
Pareto optimization
Particle swarm optimization
Power generation economics
Power system economics
Power system security
Power system simulation
Power system stability
PSO
Reactive power
TABU
Voltage
voltage stability
ISBN:1424451817, 9781424451814
ISSN:1948-9439
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Shrnutí:This paper proposes modified Multi-Objective Particle Swarm Optimization (MPSO) algorithm based on Pareto solution to overcome the conventional MPSO algorithm can easily fall into its local maximum value and improve the diversity of solution set. This algorithm is composition of a modified Tabu Search with Multi-Objective Particle Swarm Optimization (TSMPSO). With this algorithm Establishing the memory devices- taboo list of global optimal solution, Store the history of the particle that is selected to be the optimal global. And through this approach to strengthen performance of particle swarm optimization in global and local searching. TSMPSO is simple and easy to implement. Simulation results of IEEE 30-bus system show that this algorithm can enhance power system voltage stability, meanwhile economic operation of power system is also implemented, thus the effectiveness and superiority of TSMPSO algorithm are verified.
ISBN:1424451817
9781424451814
ISSN:1948-9439
DOI:10.1109/CCDC.2010.5499012