A non-dominated sorting genetic approach using elite crossover for the combined cooling, heating, and power system with three energy storages

In this paper, the cooling, thermal and electrical energy storages are integrated into the combined cooling, heating, and power (CCHP) system to improve its energy utilization efficiency. Eight scenarios with or without electrical energy storage (EES) are investigated for the CCHP system. Furthermore, a non-dominated sorting genetic approach using elite crossover is presented for the eight scenarios. The elite crossover enables the individuals with non-domination rank 1 to converge towards the Pareto front of each scenario, and the other crossover helps the individuals with larger ranks to search in wide regions. In addition, an elimination strategy is used to exclude the individuals in crowded regions, which is beneficial for obtaining diversified solutions for each scenario instead of similar ones. For the four scenarios where selling electricity to grid is allowed, their energy, economy and environment function values are higher than those of the separate production scenarios, and the two scenarios with EES are 1.5997% and 2.6495%, respectively, higher than the two scenarios without EES. For the four scenarios where selling electricity to grid is forbidden, the two scenarios with EES can provide feasible solutions while the others fail. The two scenarios with EES achieve 72.1202% and 80.5804% total growths, respectively, for the separate production scenarios.