Optimization of dynamic poly-generation system and evaluation of system performance in building application

Abstract

A decentralized small-scale poly-generation system has attracted lots of attention nowadays. In this study, the poly-generation system is optimized and evaluated for the building application. To reduce the high computational cost of dynamic simulation and multi-objective global optimization process, a hybrid simulation model has been newly proposed. The new hybrid model is developed with the validation and verification of each system component. Based on the developed model, the meta-model is optimized for improving the multi-criteria indices (energy, environment, and economy). For the optimization, the critical design variables are selected as the rated electrical power of the prime mover, the volume of thermal storage system, the cooling/heating capacity ratio supplied by electrically driven systems, and maximum heat power from the storage system. As a result of optimization and decision making, the most effective point from Pareto frontier is determined. In addition, sensitivity analysis and feasibility evaluation are conducted to investigate the effectiveness of the poly-generation system when integrated with the building in South Korea. The results show that primary energy consumption is reduced by 22.9%, CO2 emissions by 14.2%, and annualized total cost by 6.0%, respectively. Through the specific economic investigation, the payback year is calculated as 6.2. Finally, the performance that greatly affects multi-criteria indices is further discussed in terms of utilization rate, load coverage, and self-sufficiency ratio.