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Reactive Power Planning using Swarm Evolutionary Techniques

Reactive power planning is known to be challenging issues for optimization. It refers to the adequate size and position of reactive power resources for regular working conditions as well as in the anticipation of a power system vulnerability or interruption. The problem of imaginary power drafting aims to streamline the active power losses subject to different system constraints. In the deregulated electricity sector, ancillary resources such as frequency control, network control and system restart are necessary to monitor the system’s frequency, stability, security, voltage profile, and to ensure generation and transmission. One of the auxiliary services used to sustain the voltage profile by delivering or absorbing reactive power is voltage control and imaginary power control. This paper compares four different swarm evolutionary algorithms to streamline imaginary power in the power system network. Different algorithms used in this paper are Particle swarm optimization, Butterworth particle swarm optimization, Random drift particle swarm optimization, and Eagleset Strategic particle swarm optimization. In the study it was found that RDPSO gave the best result in reference to reduction in losses followed by ESPSO, BPSO and PSO respectively.