MITIGATING RENEWABLE ENERGY GENERATION UNCERTAINTY BY DEADLINE DIFFERENTIATED PRICING

Electric vehicles are an important option to enable sustainable individual mobility. In order to lever-age this potential, electricity for charging of electric vehicles needs to be provided by local renewable energy sources. Information systems can enable an efficient coordination of demand and supply in this setting. Forecast errors regarding energy generation from these sources are common but can be ad-dressed by temporal flexibility of electric vehicle charging. We use a pricing scheme called deadline differentiated pricing that incentivizes customers to accept job shifting of their charging processes. This approach is applied on a specific use case: A city car park offers charging spots for electric vehicles that is supplied by both a local photovoltaic system and conventionally from the grid. We evaluate the impact of energy generation forecast errors on operator profits based on the formulation of a stochastic mixed-integer optimization problem and empirical mobility and generation data. We show that deadline differentiated pricing is resilient to inaccurate forecasts for photovoltaic energy generation. Deadline differentiated pricing increases profits in all investigated scenarios by at least 8% as compared to a simple pricing approach. Additionally, it can increase the share of charging demand covered by renewable energy by up to 17%