Menu-Based Pricing for Charging of Electric Vehicles With Vehicle-to-Grid Service

Abstract

The paper considers a bidirectional power flow model of the electric vehicles (EVs) in a charging station. The EVs can inject energies by discharging via a Vehicle-to-Grid (V2G) service which can enhance the profits of the charging station. However, frequent charging and discharging degrade battery life. A proper compensation needs to be paid to the users to participate in the V2G service. We propose a menu-based pricing scheme, where the charging station selects a price for each arriving user for the amount of battery utilization, the total energy, and the time (deadline) that the EV will stay. The user can accept one of the contracts or rejects all depending on their utilities. The charging station can serve users using a combination of the renewable energy and the conventional energy bought from the grid. We show that though there exists a profit maximizing price which maximizes the social welfare, it provides no surplus to the users if the charging station is aware of the utilities of the users. If the charging station is not aware of the exact utilities, the social welfare maximizing price may not maximize the expected profit. In fact, it can give a zero profit. We propose a pricing strategy which provides a guaranteed fixed profit to the charging station and it also maximizes the expected profit for a wide range of utility functions. Our analysis shows that when the harvested renewable energy is small the users have higher incentives for the V2G service. We, numerically, show that the charging station's profit and the user's surplus both increase as V2G service is efficiently utilized by the pricing mechanism.

Control of Charging of Electric Vehicles Through Menu-Based Pricing

“…Following this work, we have considered the case where the EVs can inject energies by discharging via a Vehicle-to-Grid (V2G) service which can enhance the profits of the charging station [25].…”

Dynamic Pricing for Electric Vehicle Charging—A Literature Review

“…In Reference [97], Ghosh and Aggarwal describe the integration of the battery usage in the price menus from Reference [82] (see also Section 3.4.4). Thus, users get different price offers for different deadlines, different amounts of charged energy and different battery utilization.…”

“…Many works employ utility functions in the amount of charged energy. It is usually assumed that the utility function is increasing and concave (Some works assume that the utility function is strictly increasing and/or strictly concave) [70,78,86,90,97,99]. The concavity of the function reflects the law of diminishing marginal utility.…”

“…with user specific parameters δ n and β n . In Reference [97], a utility function in the battery utilization B (in terms of the amount of energy, which is discharged and charged in addition to the requested amount of energy) is used. It is assumed that the utility (actually, it can be seen as disutility) of a user n in the battery utilization is linear:…”

Multi-Layer Event-Based Vehicle-to-Grid (V2G) Scheduling With Short Term Predictive Capability Within a Modular Aggregator Control Structure

“…Also aimed at minimising the charging costs of individual EVs is the work presented in [19] where a resolution of 10 minutes was identified as the best compromise between precision and computational cost. In [20] EV users are offered a variety of contracts when connecting to a V2G network stating how much energy will be charged, how much will be made available for V2G as well as the charging costs and compensation for V2G participation. Such an approach gives a lot of control to the EV user but adds significant complexity and constraints to the scheduling process.…”