Optimization of residential PV and water heating system's configration and operation using Multi-Objective Particle Swarm Optimization

Massive PV introduction induces difficult power supply-demand balance adjustment. As one of solutions, a PV system and a Solar Hot-Water Supply System which is a hybrid system of a Solar Thermal Water Heater and a Heat Pump Water Heater is combined. In optimization of these configuration, it is necessary to consider the optimization of multiple objectives such as cost and energy efficiency. However, it is difficult to satisfy these objectives simultaneously since these are trade-offs. In this paper, we conducted to find pareto optimal solutions by Multi-Objective Particle Swarm Optimization which is a kind of an evolutionary computing. To facilitate the solution search within the constraints conditions, we gave a flag to the excess and run-out of the heat storage amount. Thereby, we could find quasi-optimal solutions according to each objective, and conducted a search twice for solutions by Multi-Objective Particle Swarm Optimization with fixed configuration to find better solutions with respect to operation. As a result, the evaluation values of all objective functions are improved.