Introducing a novel strategy for sizing the prime mover of a CCHP system by multi-objective optimization

Using the combined cooling, heating and power generation (CCHP) systems is one of the most efficient ways to improve the performance of the systems which operate by combustion of fossil fuels. One of the first and important steps in implementation of CCHP system is the sizing of its prime mover. It is usually done based on the maximum power demand. Considering life cycle costs (LCC), annual carbon dioxide emission (ACDE) and annual average of efficiency (AAE) as the objective functions, a novel strategy for sizing the prime mover of a CCHP system was introduced for a residential complex including 72 same buildings each consisting of 7 same units. Pareto optimal frontier (POF) and final optimum solution were found by Non-dominated sorting genetic algorithm II (NSGA-II) method and TOPSIS. The results showed that the best strategy for sizing the prime mover was based on 86.6% of maximum required electrical power, which in this case, the ACDE and AAE improved up to 14.3 and 0.37%, respectively, while LCC increased 15.4%.