A Linear Programming Methodology to Quantify the Impact of PHEVs with V2G Capabilities on Distribution Systems

Abstract

The Smart Grid Initiative (SGI) encourages the integration of storage and peak-shaving technologies including plugin hybrid electric vehicles (PHEVs). PHEV sales in the US are expected to significantly increase primarily due to their potential to lower fuel costs by reducing fossil fuel consumption and to lower emissions. The rising penetration rate of these vehicles may however cause problems to utilities, especially as they may dramatically increase demand peaks if not managed properly. In this paper, a methodology is proposed to determine the impact of PHEV fleets with vehicle-to-grid (V2G) capabilities on electric distribution systems. The methodology relies on a probabilistic PHEV fleet characteristics model and a linear programming algorithm to determine the optimal charging patterns of the fleet vehicles, which are then used for utility peak-shaving purposes. Results for several scenarios show that a 30 % penetration level of V2G-capable PHEVs can be achieved without increasing peak load and without requiring any capacity update on the distribution infrastructure of the selected test system. Detailed results also show that daily load profiles would be modified for residential customers, and would stay closer to their average value than today.