This paper proposes a dynamic particle swarm optimization (PSO) algorithm for optimal generation rescheduling of a power system including renewable energy sources such as the solar and wind energy sources. The algorithm is to minimize total operating costs of this hybrid power system. The proposed dynamic PSO algorithm is one of the standard PSO algorithm variants, which modifies the acceleration coefficients of the cognitive and social components in the velocity update equation of the PSO algorithm as linear time-varying parameters. The acceleration coefficients are varied during the evolution process of the PSO algorithm to improve the global search capability of particles in the early stage of the optimization process and direct the global optima at the end stage. The dynamic PSO algorithm based optimal generation rescheduling of the power system with and without solar and wind powers is considered on the standard IEEE 30-bus 6-generator 41-transmission line test power system. The numerical results demonstrate the capabilities of the proposed algorithm to generate optimal solutions of the power system considering the renewable energy resources. The comparison with the standard PSO algorithm demonstrates the superiority of the proposed algorithm and confirms its potential to reschedule an optimal generation of the power system including the solar and wind energy sources.

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