A Quantitative Method to Assess the Vehicle-To-Grid Feasibility of a Local Public Transport Company

In this paper, a quantitative model is implemented with the main goal of building a decision support tool to assess the feasibility of applying a Vehicle-To-Grid (V2G) service by a company operating a fleet of electric buses. The proposed model can calculate the energy that a vehicle within a depot can deliver back to the grid during periods of peak energy demand, based on the operational schedule that must be guaranteed (number of buses in service). After a presentation of the main features of V2G and the main benefits this technology can bring to the transportation company, the model structure, and related algorithms, as well as input and output data, are presented and discussed. To verify the effectiveness and validity of the proposed model, a case study related to the company that manages public transportation in the city of Milan, Italy, is described. 2 depots were analyzed considering the energy load during peak hours and the energy that could be injected into the grid considering the vehicles parked in the depot. From a quantitative point of view, V2G could feed about 7 MW to 10 MW into the grid, depending on the day of the week and time of day. Considering an average connection of 3 kW for a household, between 2,300 and 3,300 households could be served. In addition, an economic evaluation was performed considering energy trading: monthly, total revenues are 45,922 (sic) and total costs are 42,848 (sic); the economic benefit can be estimated at about 6.7% of total monthly revenues.

Automated summary

In this paper, a quantitative model is implemented to assess the feasibility of implementing a Vehicle-To-Grid (V2G) service by a company operating electric buses. The model calculates the energy that a vehicle within a depot can deliver back to the grid during peak demand periods based on the operational schedule. The paper also provides an economic evaluation of energy trading and estimates that V2G can supply about 7 to 10 MW of energy to the grid, serving approximately 2,300 to 3,300 households.