Optimum pricing of smart home appliances based on carbon emission and system cost

Abstract

Concurrent optimization of two different objective functions is a prominent subject in power systems. A model based on a multi-objective mixed-integer program is presented for smart home scheduling with economic and environmental considerations. One of the objective functions minimizes the operational cost of the building, whereas, the other one minimizes the carbon release. To solve the suggested multi-objective problem, the ɛ-constraint technique and the weighted addition method are utilized. Therefore, to choose the desirable win–win approach from the achieved effective outcomes, a min–max composition of fuzzy is used in order to obtain desirable evaluation results. The CPLEX solver of the GAMS is used to solve the suggested problem. In addition, to assess the effectiveness of the suggested model, ɛ-constraint technique and the weighted addition method case studies have been used. In a comparison of the achieved results, it is seen that by incorporating the ɛ-constraint technique, the overall operational cost of the smart home is 28.57% lower when economically optimizing the model. Also, by environmentally optimizing the model, 7.63% less carbon was emitted. Moreover, using the weighted addition method demonstrates a decrease of 28.76% and 11.37% from economic and environmental viewpoints, respectively. The simulation results show that to minimize carbon release, the building’s electrical power control system prefers utilizing CHP over the boiler.