Optimal sizing of a solar thermal building installation using particle swarm optimization

In recent years the domestic energy management has become a non-trivial task as the number of energy sources and system components involved have increased, and all components have to operate coordinately in order to maximize global efficiency measures.In this paper a methodology is presented for finding the optimal size of the main components for a solar thermal system where particular attention is given to the optimization framework. The use of the PSO (particle swarm optimization) algorithm is proposed and the results obtained are compared with a GA (genetic algorithm) solution. Further, the relative influence of certain system parameters on the optimal configuration is investigated by means of a sensitivity analysis where the size of the collector is shown to have the greatest influence on all main output quantities while the size of the auxiliary power unit presents a relatively small influence on the solution.Finally, it is demonstrated that the accurate sizing of the energy components is necessary to minimize the energy consumption and cost of installation, while maximizing the solar fraction. The proposed methodology is shown to successfully solve the problem

► Solar combisystem for heating and hot water preparation of mid-sized building.
► System component optimization and comparison between PSO and GA algorithm results.
► Energy use strongly depends on heating set-point temperature during day.
► Sensitivity of solution dominated by solar collector, followed by storage tank size.