Multi-objective optimization of combined cooling, heating and power system integrated with solar and geothermal energies

The aim of this study is to optimize the integrated performance of a hybrid combined cooling, heating, and power system driven by natural gas as well as solar and geothermal energy resources from the energy, economy, and emission perspectives. A basic natural gas system with a prime mover unit, absorption chiller, and electricity and thermal storage components is coupled with solar photovoltaic panels and a ground source heat pump. A multi-objective optimization method is proposed and employed to optimize the configurations of the hybrid system and thereby achieve optimal performances using non-dominated sorting genetic algorithm II. Accordingly, the variable output ratio of ground source heat pump is optimized to match the heat to electricity ratios between the system and users. The hybrid system's schemes of a specific case building that operates in different modes are optimized and compared; these schemes include following electric load, following thermal load, and following hybrid load. The impacts of natural gas and grid electricity prices on system performance are investigated. The results demonstrate that the configurations of the hybrid system that operates using the following electric load strategy achieves better performances than other modes. The proposed optimization method herein can be effective in optimizing the configurations of a hybrid system and consequently improve system performances.