Dynamic multiobective optimization of power plant using PSO techniques

The Coordinate Control Scheme (CCS) requires references to provide control inputs to a power plant. The references are obtained by mapping the unit load demand to pressure set-point. In order to achieve the optimal power plant operation, the mapping should be optimized under a dynamic environment by considering the multiobjectives of the power system. In this paper, the multiobjective optimal power plant operation will be realized through the on-line optimal mapping between the dynamic unit load demand and pressure set-point using a modern heuristic method, the Particle Swarm Optimization (PSO). The multiobjective optimization is performed in the reference governor of a Fossil Fuel Power Unit (FFPU). Moreover, variations of the PSO technique, such as Hybrid PSO (HPSO), Evolutionary PSO (EPSO), and Constriction Factor Approach (CFA), will be introduced and the comparison will be made on the dynamic multiobjective optimization of a power plant.