Optimal placement of UPFC using security constraint Hybrid PSO algorithm

The Hybrid Particle Swarm Optimization (HPSO), combination of Genetic Algorithm (GA) and Adaptive PSO (APSO), is developed for the different sets of constraint power flow analysis with the UPFC. The breeding and subpopulation procedure which are applied in GA are merged into APSO for the proposed security constraint Hybrid PSO (SCHPSO) algorithm to obtain new search space into the current individual. The UPFC is modeled considering actual losses of power transmission in UPFC, switching losses of the two converters of UPFC and losses of the coupling transformers. The multi-objective optimization problem is converted to a single objective minimization problem providing proper weighting factors and the unique objective function is formulated considering practical security constraints. Six groups of line flows are set for the UPFC at different locations to obtain optimal placement of the UPFC under security constraints. For both ill-conditioned and IEEE standard systems, the SCHPSO algorithm is compared with other techniques and the proposed SCHPSO algorithm shows the best performances for all cases.