A New Approach for Allocation and Sizing of Multiple Active Power-Line Conditioners

In this paper, a particle swarm optimization (PSO) algorithm is developed for allocation and sizing of multiple active power-line conditioners (APLCs) in power systems. The utilized objective function comprises four factors as total harmonic distortion, total size of active power-line conditioners (APLCs), harmonic transmission-line loss, and motor load loss. To evaluate the capability of the proposed method, the IEEE 18-bus test system is employed and investigated in three different cases. These cases are based on the assumption of continuous/discrete and limited/unlimited size for APLCs, requiring the optimization method to solve discrete/nondiscrete nonlinear problems. Therefore, in addition to PSO, an integer nonlinear optimizer (discrete PSO called DPSO) algorithm is also developed. Simulation results are compared with results obtained by genetic algorithm as well as with nonlinear programming (discrete nonlinear programming). It is demonstrated that analytical methods enjoy higher accuracy in smooth objective functions while they are not accurate enough in practical situations where nonsmooth objective functions are involved. If improper initial solutions are provided, achieving optimized results cannot be guaranteed by using analytical approaches. It is also shown that heuristic algorithms due to their randomness characteristics are more useful in practical cases where a number of local minima are present. Simulation results confirmed the capability and effectiveness of the proposed PSO-based algorithm in the allocation and sizing of multiple APLCs in a test power system compared with analytical methods and other heuristic algorithms.