Abstract
Aiming at the control variables of reactive power optimization are discrete, and some parameters in the standard particle swarm optimization (PSO) algorithm need to be predefined by test, so the algorithm's practicability is restricted. For these reasons, an adaptive particle swarm optimization (APSO) algorithm is proposed by the authors. APSO introduces the self-adaptive tuning strategy and boundary constraint conditions can find the global optimal solution and solve the discrete variables. The reactive power optimization results of the standard IEEE-30-bus power system show that APSO is efficient than standard PSO. The global convergence accuracy and convergence stability is obviously improved compared with that of PSO.
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