Optimal Operation of Electric Vehicle Charging Station Based on 100% Renewable Energy for Supplying Cryptocurrency Mining Farm and Critical Loads in Off-Grid and Grid-Tied States

This research proposes a novel method for utilizing renewable energies in electric vehicle charging stations. In the proposed method, the required energy for charging the electric vehicles, the needed energy for supplying the cryptocurrency mining farm as well as the energy for supplying the critical loads of the upstream grid are afforded by 100% renewable resources, and the electric vehicle parking station (i.e., charging station) receives no energy from the utility grid. In this model, the uncertainty of renewable energies and the mismatch between generation and demand are resolved by optimal charging-discharging of electric vehicles. While the utility grid is available, the electric vehicles are fully charged, the cryptocurrency mining farm continues operation at full capacity, and excess renewable energy is sent to the upstream grid to supply the critical loads. The critical loads are supplied from two directions of the grid and parking station. During an outage or blackout of the utility grid, the critical loads are fully supplied by an electric vehicle parking station. In this situation, the cryptocurrency miners are modeled as a responsive load. In the off-grid operation, the proposed planning manages the energy of cryptocurrency miners as well as the charging-discharging pattern of electric vehicles for reaching two objectives of fully charging all the electric vehicles and fully supplying the critical loads. If there is any surplus of energy, it is used to run the cryptocurrency miners. In the proposed model, since no energy is received from the utility grid, the issues related to cryptocurrency mining are inconsequential. The objective function of the proposed method is to minimize the number of discharge cycles on electric vehicles to avoid battery degradation. The problem is formulated as mixed integer linear programming and solved by GAMS software. The wind and solar energy uncertainty are incorporated in the model and an optimal charging-discharging pattern is designed for electric vehicles to confirm feasible operation under all energy variations.