Modeling Analysis of Electric Vehicle Penetration Scenario using Dynamic Optimal Power Generation Mix Model with High Temporal Resolution

After the Fukushima nuclear accident, Japanese power generation planning needs to be reassessed to reflect technical developments on both the power supply and demand sides. The Fukushima nuclear accident has complicated the position of nuclear energy in Japan's long-term power generation mix due to public acceptance and other associated issues such as nuclear waste management. There is a need for more studies concerning the peak grid integration of variable renewables such as PV and wind power, which are expected to potentially replace nuclear energy. On the power demand side, the anticipated future introduction of electric vehicles (EVs) and plug-in hybrid vehicle (PHEV) will have an impact on grid management in the electric power system. In this context, it is important to develop a computational tool to comprehensively analyze the optimal power generation mix and organize it in a consistent way. This paper develops a dynamic high time-resolution optimal power generation mix model as large-scale linear programming model with 18 million constraints and 8 million endogenous variables. It then analyzes the optimal deployment of variable renewables (VR) and EVs with the future possible nuclear scenario and CO2 regulation policy in Japan taken into consideration. In the calculated optimal solutions, EVs play an important role in integrating variable renewables and treating the imbalance in VR surplus output.