Smart Garage Development Problem: Model Formulation and Solution Approach

Abstract

Plug-in electric vehicles (PEVs) are becoming increasingly popular. In the next several years, all major vehicle manufacturers will introduce PEVs, either as battery electric vehicles (BEVs), such as the Nissan Leaf, or plug-in hybrid electric vehicles (PHEVs) with a dual powertrain, such as the General Motors Volt and the Toyota Prius. This new generation of vehicles relies on electricity as a power source and a battery as an energy storage medium. Naturally, for PEVs, refueling occurs when the battery connects to an electrical outlet linked to a distribution network. The primary objective of this paper is to study optimal locations for building facilities (i.e., smart garages) that will maximize integrated benefits from the transportation system (i.e., parking fee) and the electric power system [i.e., revenue from vehicle-to-building (V2B) services]. A deterministic smart garage development problem (SGDP) is formulated and modeled as a bilevel program and solved by using a genetic algorithm. The results of a simple numerical example show the sensitivity of the model results with respect to parameters, including PEV penetration rate and battery capacity.