Reactive Power Market Simulation: A Particle Swarm Optimization Approach

This paper deals with the application of Particle Swarm Optimization algorithm (PSO) for reactive power scheduling in deregulated power system.  Reactive power procurement is modeled as a security constraint optimal power flow incorporating voltage stability problem. The model attempts to  minimize cost of reactive power procurement and energy losses as a main objective while technical criteria and voltage stability margin, in special, are  treated as soft constraints. From mathematical points of view, reactive power market can be expressed as a nonlinear optimization problem. Thus  PSO, as a powerful heuristic algorithm, is implemented to find equilibrium point of the reactive power market. Reactive power market is simulated over the IEEE30 bus system and obtained results are compared with another evolutionary programming such as genetic algorithm (GA) in terms of  quantity and precision. Results show that the PSO has a good potential to converge to better feasible solution in less iteration and it can be successfully used for reactive power optimization in restructured environments.

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