Multi-Objective Optimization of Integrated Energy Systems Considering Renewable Energy Uncertainty and Electric Vehicles

In this study, the multi-objective optimization considering renewable energy uncertainty and electric vehicles (EVs) is proposed for regional integrated energy systems (RIES), which can balance the economy and environmental friendliness of the system. Firstly, the influence of factors such as disordered access and charging/discharging of EVs on system operation is considered, an orderly charging and discharging model of EVs is established according to the driving laws. Then, a robust optimization model with polyhedral uncertainty set is constructed to handle the uncertainty of renewable energy output. Moreover, the minimizing operation cost and carbon emissions is developed as the multi-objective function, and the carbon emission penalty factor is introduced to convert the multi-objective into single objective solution. Finally, the validation is carried out by an actual RIES. The case studies verify the proposed method can well balance the economy and environmental protection of the system, and enhance robustness against the uncertainty while realizing the economic and optimal operation of the system.