Optimal Operation of a Plug-In Electric Vehicle Parking Lot in the Energy Market Considering the Technical, Social, and Geographical Aspects

Abstract

This chapter studies the optimal operation problem of a parking lot in the energy market modelling the drivers' behavior based on the social and geographical factors including the drivers' income level, the distance between the PEVs and parking lot, and the driving routes. The driving routes of plug-in electric vehicles (PEVs) are modelled considering the minimum and maximum traffic speed limits and the real latitude and longitude of area around Marina City vertical parking lot in Chicago, IL 60654. Herein, the parking lot is supplied by the renewable energy sources, and it has the capability of bilateral energy transaction with the energy market through the electrical distribution system and with the PEVs using the vehicle-to-grid (V2G) and grid-to-vehicle (G2V) services. In this study, the problem is formulated as a mixed integer linear programming (MILP) problem, and it is solved for different PEV types including Tesla Model S, Citroën C-Zero, Volkswagen e-Up, and Renault Kangoo Z.E., multiple PEV penetration levels, and diverse social classes of drivers. It is proven that the driver's social class, the PEV's type, and even the PEV penetration level can affect the problem outcomes. In other words, the unrealistic value of these parameters may have a significant impact on the maximum profit of parking lot, the optimal operation of energy sources, and the optimal value of incentive. Therefore, the parking lot owner is recommended to specify them before solving the problem to avoid achieving any misleading result.