A dual-objective trade-off approach to decide the optimum design parameters for internal cooling load calculation

Abstract

The building design cooling load is the basis of sizing the air-conditioning equipment, but the extreme values are always used as the referenced design parameters for occupants, lighting and equipment respectively without considering the relationship between the internal load sources which will result in an oversized equipment. Based on the measured data in existing buildings, the Copula function is used to explore the joint occurrence probability of the internal disturbances. In view of the deviation of the calculated cooling load from the extreme cooling load, the unguaranteed rate is established. Aiming to balance the maximum joint probability and the minimum unguaranteed rate, a dual-objective trade-off approach with the genetic algorithm and TOPSIS method is proposed to seek the optimum solution from the Pareto Fronts to provide references for internal load design parameters. The results show that there is a big deviation between the design values and trade-off results, especially the recommended values of lighting power density in the design standards are at least 26% higher than the trade-off results. And the energy consumption for internal disturbances can be at least reduced by 12.1% using the trade-off approach.