Energy Hub optimal sizing in the smart grid; machine learning approach

The interests in “Energy Hub” (EH) and “Smart Grid” (SG) concepts have been increasing, in recent years. The synergy effect of the coupling between electricity and natural gas grids and utilizing intelligent technologies for communicating, may change energy management in the future. A new solution entitling “Smart Energy Hub” (S. E. Hub) that models a multi-carrier energy system in a SG environment studied in this paper. Moreover, the optimal size of CHP, auxiliary boiler, absorption chiller, and also transformer unit as main elements of a S. E. Hub is determined. Authors proposed a comprehensive cost and benefit analysis to optimize these elements and apply Reinforcement Learning (RL) algorithm for solving the optimization problem. To confirm the proposed method, a residential customer has been investigated as an S. E. Hub in a dynamic electricity pricing market.