Research on capacity and strategy optimization of combined cooling, heating and power systems with solar photovoltaic and multiple energy storage

Combined cooling, heating and power systems can exploit renewable energy and significantly improve the comprehensive benefit of energy supply systems. Moreover, the stability and economy of these systems are mainly affected by the operation strategy and the capacity allocation scheme of each device. Therefore, a novel hourly dynamic simulation model is established to obtain the optimal capacity allocation scheme. The novelty is that it considers the reduction in CO2, NOx and SO2 emissions. The variable load operation characteristics of the main devices are considered. With the operation strategy of following the electrical load and following the thermal load, the model is solved by nondominated sorting genetic algorithm II with the optimization objectives, including economy, environment and energy savings. The technique for order preference by similarity to an ideal solution method is used as a multiobjective decision method. As a result, with the following the electrical load strategy, the pollutant emission reduction rate is 74.86%, the primary energy savings rate is 36.83%, the annual cost savings rate is 13.04%, and the comprehensive index is 54.89%. When the electrical cooling ratio is 0.8, it is 0.29% higher than the pollutant emission reduction rate without mixed refrigeration and 0.63% higher than the primary energy savings rate. When the optimal capacity of the photovoltaic system is configured, the pollutant emission reduction rate increases by 5.13%, the primary energy savings rate increases by 15.59%, the annual cost savings rate increases by 7.48%, and the comprehensive index increases by 7.51%. Therefore, the novel model and optimization algorithm are reliable and feasible for addressing the system capacity configuration improving system operation stability.