TY - GEN

T1 - SVC Planning in Large–scale Power Systems via a Hybrid Optimization Method

A1 - Yang,Guang ya

A1 - Majumder,Rajat

A1 - Xu,Zhao

AU - Yang,Guang ya

AU - Majumder,Rajat

AU - Xu,Zhao

PY - 2009

Y1 - 2009

N2 - The research on allocation of FACTS devices has attracted quite a lot interests from various aspects. In this paper, a hybrid model is proposed to optimise the number, location as well as the parameter settings of static Var compensator (SVC) deployed in large–scale power systems. The model utilises the result of vulnerability assessment for determining the candidate locations. A hybrid optimisation method including two stages is proposed to find out the optimal solution of SVC in large– scale planning problem. In the first stage, a conventional genetic algorithm (GA) is exploited to generate a candidate solution pool. Then in the second stage, the candidates are presented to a linear planning model to investigate the system optimal loadability, hence the optimal solution for SVC planning can be achieved. The method is presented to IEEE 300–bus system.

AB - The research on allocation of FACTS devices has attracted quite a lot interests from various aspects. In this paper, a hybrid model is proposed to optimise the number, location as well as the parameter settings of static Var compensator (SVC) deployed in large–scale power systems. The model utilises the result of vulnerability assessment for determining the candidate locations. A hybrid optimisation method including two stages is proposed to find out the optimal solution of SVC in large– scale planning problem. In the first stage, a conventional genetic algorithm (GA) is exploited to generate a candidate solution pool. Then in the second stage, the candidates are presented to a linear planning model to investigate the system optimal loadability, hence the optimal solution for SVC planning can be achieved. The method is presented to IEEE 300–bus system.

BT - Proceedings of APSCOM'09

T2 - Proceedings of APSCOM'09

ER -