The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Parallel cooperative micro-particle swarm optimization: A master-slave model
Applied Soft Computing
A new fitness estimation strategy for particle swarm optimization
Information Sciences: an International Journal
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In this paper, Message Passing Interface (MPI) based parallel computation and particle swarm optimization (PSO) algorithm are combined to form the parallel particle swarm optimization (PPSO) method for solving the dynamic optimal reactive power dispatch (DORPD) problem in power systems. In the proposed algorithm, the DORPD problem is divided into smaller ones, which can be carried out concurrently by multi-processors. This method is evaluated on a group of IEEE power systems test cases with time-varying loads in which the control of the generator terminal voltages, tap position of transformers and reactive power sources are involved to minimize the transmission power loss and the costs of adjusting the control devices. The simulation results demonstrate the accuracy of the PPSO algorithm and its capability of greatly reducing the runtimes of the DORPD programs.