An Optimal Energy Hub Management Integrated EVs and RES Based on Three-Stage Model Considering Various Uncertainties

In order to make significant progress in the operation of power systems and minimizing cost and air pollution, multi-carrier energy systems based on the economic and emission problem have been proposed by implementing various solutions and using different sources. In this study, an energy hub (EH) system includes a wind turbine (WT), photovoltaic (PV), and EVs that are exchanged energy with energy and reserve market considering energy, thermal, and gas demand response program is proposed. But these units due to uncertain behavior create a big problem in balancing between the demand and generated energy. Thus, the uncertainty of WT, PV, load, and electricity market price are modeled with Mont-Carlo method. Besides that, all parameters of the EVs with uncertainty behavior are modeled using a new method that classified EVs based on the capacity of the battery and other features. This method is employed a stochastic optimization approach to simplify the uncertainty modeling for increasing the system reliability. Hence, two objective functions, namely economic cost, and environmental cost are considered. Finally, a three-step strategy is introduced to solve the multi-objective problem as a single objective function. Finally, EH management performance is investigated by implementing the proposed method and elements.

Automated summary

In this study, an energy hub system is proposed to address the economic and emission problem in power systems. Uncertainties in wind turbine, photovoltaic, load, and electricity market price are modeled with a Mont-Carlo method. A new method is introduced to model the uncertainties of electric vehicles, simplifying the uncertainty modeling process to increase system reliability. Two objective functions, economic cost, and environmental cost, are considered, and a three-step strategy is introduced to solve the multi-objective problem.