Multi-objective sizing optimisation of a solar-thermal system integrated with a solar-hydrogen combined heat and power system, using genetic algorithm

Abstract

A sizing multi-objective optimisation using the genetic algorithm is performed on a solar-hydrogen combined heat and power system integrated with solar-thermal collectors (SH CHP-ST) to supply both power and heat (i.e. hot water demand) to an application. A solar-hydrogen system is a renewable system with hydrogen-based storage consisting of an electrolyser, a hydrogen tank, and a fuel cell. The fuel cell generates heat while producing power that can be recovered. The heat collected from the fuel cell can be integrated with the heat supply of a renewable solar-thermal system consisting of an evacuated tube collector and a hot water storage tank. A simulation module to model the operation of the whole system is implemented in MATLAB. Energy demands and meteorological data for a remote household located in southeast Australia are considered. The sizes of the main components of the system are optimised with the objectives of maximising the overall reliability of the system, minimising the levelised cost of energy, and minimising the percentage of excess energy from the PV that is not utilised. The results show that the electric reliability of the optimal solutions in favour is always equal to 100%. The maximum thermal reliability that could be obtained is around 96%. A trade-off between the cost of energy and percentage of wasted power from PV is found.