Optimal Operation of Residential Energy Hubs Considering Optimized Capacity of Photovoltaic-based Renewable Energy Systems

The deployment of multi-carrier energy systems, which are called energy hubs, is one of the most recent and useful strategies in the field of energy systems. The reliability of energy systems and their operation cost and efficiency could be improved by applying the concepts of energy hubs. The simultaneous management of electrical consumptions and heat demands by the concepts of energy hub would be effective. The energy management of residential energy hubs has received a great deal of attention because the energy consumption of the residential sector is significant in the amount of global energy consumption of the world. There is a knowledge gap in developing a new method simultaneously considering optimal operation and optimal allocation of photovoltaic units in residential energy hubs. This paper tries to fill this knowledge gap. Integrating the optimal planning and optimal scheduling of residential energy hubs could improve the system cost and other features. Considering the capacity of the photovoltaic unit as one of the decision variables in the proposed optimization problem besides other operation and scheduling decision variables is one of the most important contributions of this research. The proposed method is applied to a residential energy hub, including the controllable and uncontrollable appliances, combined heat and power units, plug-in hybrid electric vehicles, heating loads, photovoltaic units, and heat storage systems. The proposed optimization problem is solved by the genetic algorithm in MATLAB. Different case studies are analyzed to assess the impacts of photovoltaic units’ capacity, energy storage systems, and simultaneous optimization of planning and operation decision variables. The test results illustrate the advantages of the simultaneous optimization of operation and capacity of the photovoltaic unit in the proposed method. It is inferred from the comparative test results that by applying the proposed method, it is possible to improve the operation cost and efficiency of energy systems, while the constraints of customer satisfaction are concerned. It is revealed that an around 5% improvement in the daily cost of the studied residential energy hub could be achieved compared to conventional studies. The sensitivity analysis is performed to investigate how energy storage systems besides photovoltaic units influence the residential energy hubs.