Owing to the limitation of single objective optimization configuration of the distributed combined cooling heating and power (DCCHP) system, the multi-objective optimization configuration of the system was carried out from the aspects of energy efficiency and economy. Taking the maximum primary energy saving (PES) and minimum annual cost (AC) as the objective functions, three key parameters of gas turbine capacity, absorption refrigeration ratio and gas turbine minimum load rate were selected as decision variables. Nondominated sorting genetic algorithm II (NSGA-II) was used to optimize the system with multi-objective, and subsequently Pareto optimal solutions were obtained. With the aid of ideal point method, the optimal capacity configuration of the system was selected. For the case of an energy supply system of a hotel, optimized results show that under the given parameters, the optimal PES is 0.6788 and the minimum AC is 2.1309 million yuan in consideration of both energy efficiency and economy.
Keywords Distributed combined cooling heating and power, multi-objective optimization, non-dominated sorting genetic algorithm