Multi-objective optimization of air conditioning systems in residential buildings with an economic attitude

The use of fossil fuels for energy supply causes air pollution and environmental degradation factors, which itself causes climate change in the world. Therefore, researches are looking for ways to optimize energy consumption in the world. For this purpose, in this study, by optimizing the amount of energy consumption of air conditioning systems (ACS) in a residential building, it helps significantly in reducing the energy consumption of the building. For this purpose, a six residential building in 4 cities of Iran with different climates have been investigated. For this purpose, 5 design variables of summer clothing insulation level (SCIL), winter clothing insulation level (WCIL), ACS (40 different ACS), cooling thermostat temperature (CTT) and heating thermostat temperature (HTT) have been considered. The objective functions in this study are the cost of installing the air conditioning system (CIACS), the annual cost of bills (ACB) and the predicted percentage of dissatisfied (PPD). The effect of design factors on objective functions has been investigated by Morris’s sensitivity analysis. Three Energy Plus, JEPLUS and JEPLUS+EA software is used for optimization. For this purpose, non-dominant sorting genetic algorithm (NSGA-II) - is used for optimization. The optimization results after the calculations showed that Tehran's annual energy consumption has decreased by 81.3%, for Rasht by 63.64%, for Bandar Abbas by 82.66% and for Shahrekord by 77.2%. Also, the PPD for the cities of Tehran, Rasht, Bandar Abbas and Shahrekord improved by 44.42, 50.1, 31.1 and 56.3% respectively.