A new evolutionary optimization algorithm for optimal power flow in a power system involving unified power flow controller

作者：Niknam Taher^*; Narimani Mohammad Rasoul; Farjah Ebrahim; Bahmani Firouzi Bahman

来源：Energy Education Science and Technology Part A: Energy Science and Research , 2012, 29(2): 901-912.

• Optimal power flow
• Fuzzy adaptive particle swarm optimization
• evolutionary algorithm
• Unified Power Flow Controller

This paper presents an efficient and reliable evolutionary based approach to minimize the generator fuel cost in power systems involve Unified Power Flow Controller (UPFC). Putting the UPFC in electrical network may assist the system in operating within its physical limits and reduce total generation cost associated with out-of merit order caused by constrained transmission. The proposed approach employs a New Adaptive Particle Swarm Optimization (NAPSO) algorithm for optimal setting of Optimal Power Flow (OPF) problem control and optimal parameter of UPFC variables simultaneously. Finding the optimal values of control variables for a UPFC device is a complex optimization problem which cannot be easily solved, therefore it needs to a strong algorithm for solving. Unlike the other heuristic techniques, NAPSO has a flexible and well-balanced mechanism to enhance and adapt to the global and local exploration abilities. Also, this paper proposes a new model for UPFC in power system calculation. The proposed model has a better convergence and requires less CPU time compared to traditional models. The results are promising and show the effectiveness and robustness of the proposed approach and illustrate how transmission usage is affected when UPFC is utilized.

• 出版日期2012-7