Multi-objective Optimization Scheduling of Photovoltaic Thermal Power Units Based on Electric Vehicles: An Improved NSGA-II Algorithm

With the rapid popularization of new energy and electric vehicles, the uncontrolled charging and discharging behavior resulting from the integration of renewable energy generation (RGs) and electric vehicles can have an impact on the stable operation of the power grid. This paper combines the traditional unit commitment (UC) model with the integration of plug-in electric vehicles (PEVs) and photovoltaic generation (PV) to form a new super multi-objective problem model. This model takes into account the objective functions of generation cost and carbon emissions associated with UC, as well as a deviation function that simulates satisfaction of users with electric vehicle charging load in real-world scenarios. In order to address this kind of multi-objective optimization problem, an improved hybrid Levy flight and NSGA-II algorithm is developed. The enhanced NSGA-II algorithm was compared with two other algorithms on the same model. Experimental results show that the enhanced NSGA-II algorithm reduces the model’s energy requirements and performs better than the other two, thus proving its effectiveness.