Particle Swarm Optimization for Robust Power Management in DC Prosumer Microgrids with Battery

Abstract

Power prosumers with rooftop solar panels have risen in recent times. They easily integrate into DC microgrids, due to the nature of their output - DC. Therefore, it is important to study DC prosumer grids. Power management is crucial to the efficient and economic operation of microgrids. In this paper, the power management task of a DC prosumer microgrid is tackled using the Particle Swarm Optimization algorithm in Pyswarm. The task is developed mathematically as a constrained optimization problem with the objective of minimizing the grid's operating cost. The equality constraints of the optimization problem are handled using the Penalty Function approach. Using a six-bus DC microgrid, investigations are carried out on the effect of the penalty parameter on three metrics - objective function value, magnitude of violation and time to reach a solution. Results show that among the penalty parameter values considered for the solution to the power management problem of the six-bus system, and with respect to the three metrics, penalty parameter values le+1 and le+7 are most suitable. Furthermore, studies on the effect of swarm size on the three metrics show that a swarm size between 200 and 250 is ideal.