###### Abstract
Except that mentioned in the previous paragraph, most of the relevant literature studies the small-scale-building-type CCHP; most of the literature does not consider selling electricity to the main grid, which reduces the flexibility of parallel exchange of electricity between the mains and also weakens the advantages of the microgrid in peak saving and valley filling. Considering these reasons, this work studied a large-scale CCHP combined with renewable energy generators and considered the parallel connection of the mains, allowing the exchange of power with the main grid. In this way, the advantages of CCHP can be used to cut peaks and fill valleys, reduce operating costs, and make the entire system more flexible in power-generation scheduling. Therefore, this research considered energy-storage equipment in the model in addition to the basic equipment in CCHP including the gas turbine (GT), gas boiler (GB), absorption chiller (AC), and electric chiller (EC) as well as the electricity-storage device (ES) and heating-storage device (HT). In addition, in order to more efficiently find the optimal solution to the CCHP problem, ref. [17] proposed the following electric load (FEL) and following thermal load (FTL) strategies. These two strategies are based on the electric energy load or thermal energy load of the current period, respectively, to adjust the power generation of the gas-turbine generator during the period so that the generated power just meets the electrical load or thermal energy load. However, when most scholars adopted these two strategies in the past, they did not consider energy-storage equipment [17; 18; 19], which does not meet the requirements of the energy-storage equipment for dispatching energy supply in the CCHP system proposed in this study, and assumed that the over-produced energy would be used by other users. In this study, the experimental case in Taiwan is located in the subtropical climate zone, where the demand for thermal energy load in winter is not as high as that of temperate or frigid regions at higher latitudes, so the FTL is relatively unsuitable. Therefore, this research only adopted the concept of FEL to make the gas-turbine generator meet at least a certain proportion of the electric energy load during this period and cancel the assumptions mentioned above to be closer to the real situation. The CCHP optimization problem requires establishing a mathematical model under the constraints of the energy balance and the operation mode of each unit to pursue the maximum benefit of each objective. Most of early scholars studied the optimization of CCHP on the single-objective problem of optimizing for achieving the lowest cost [15]. Since then, with the rise of environmental awareness, topics of CCHP research have begun to focus on environmental-protection aspects such as lowering carbon emissions and increasing the energy conversion rate and transformed the optimization problem into a multi-objective issue [20]. In recent years, the combination of CCHP and renewable energy is the developing trend because the development of renewable energy is becoming more and more mature. Thus, several algorithms are proposed to solve the related problems [21; 22; 23; 24; 25]. [PERSON] et al. considered the space constraints of CCHP units, wind power generation, and solar power generation units, hoping to obtain the best unit combination in a limited space, and adopted a multi-objective swarm algorithm based on particle-swarm optimization (PSO) to solve the problem [23]. [PERSON] et al. combined CCHP and solar power generation, using solar collectors to store solar thermal energy and targeting life cycle assessment, and optimized the problem by genetic algorithm (GA) [24]. [PERSON] et al. took the CCHP of island operation as a model and considered the influence of the location of renewable energy devices, such as the angle of solar panel installation and the height of wind turbines,which was solved by an evolutionary algorithm: the preference-inspired coevolutionary algorithm [25].