An Investigation of V2G Profitability with Robust Optimization and Bidding Price Heuristics

Abstract

Over the last years the number of Electric Vehicles (EVs) has been growing more than expected, and a massive growth is foreseen for the next decade. An increase of consumption due to EV charging is then expected, with possible drawbacks, like undesired peaks, for distribution and transmission system operators. However, EVs are indeed storage systems, and, therefore, they can be employed to provide flexibility to the power system: this is known as the Vehicle-to-Grid (V2G) concept. This paper aims at investigating a V2G control strategy for the EV charging stations in a public or private parking lot, in order to provide flexibility services by participating in the Ancillary Service Market (ASM).The energy to be exchanged on the ASM, and also on the Day-Ahead Market (DAM), is obtained by solving an optimal control problem that maximizes the EV charging station operator's daily profit while ensuring the desired minimum State of Charge (SoC) of each EV at the end of the recharge. The cycling aging of EV batteries is considered in particular via the price of the discharged energy. The problem is formulated in a robust way to take into account uncertainties on ASM bid acceptance. The bidding prices on the ASM act as problem inputs, and therefore have to be suitably chosen. The different heuristic strategies proposed here for this choice are based on an analysis performed on one-year data of the Italian ASM. The mixed heuristic and robust approach yields different economic results, depending on the adopted bidding price strategy. The results provide interesting input for further developments of business cases for V2G applications.