An optimization model for siting and sizing of vehicle-to-grid facilities in a microgrid

In this paper, we propose a new optimization model for investment planning for Vehicle-to-Grid (V2G) technology in a microgrid. The V2G technology allows the microgrid to take advantage of temporal arbitrage in the electricity market, and hence, improve economic viability of electric vehicles. We present both a mathematical model and a custom solution methodology for this problem. The proposed stochastic model is a very large-scale mixed-integer nonlinear programming problem, and thereby, we develop an algorithm that provides high-quality solutions. A case study for 14-node and 37-node microgrid test systems for a planning horizon of five years is presented, and a thorough sensitivity analysis for effects of uncertainty, investors preferred payback period, market price fluctuations and electric vehicles arrival and departure rates is discussed. The simulation results show that investing in the V2G technology can considerably improve the long-term economics of the microgrid, but the obtained profit and the payback period can vary from one plan to another.