Integrated PV Charging of EV Fleet Based on Dynamic Energy Prices and Offer of Reserves

TL;DR

This paper presents a MILP-based energy management system for EV fleet charging using PV and dynamic grid tariffs, optimizing costs and grid support through a unified approach.

Contribution

It introduces a comprehensive MILP model that integrates PV-based EV charging, grid reserve offers, and network constraints into a single receding-horizon optimization.

Findings

Cost reduction of 31% to 650% compared to traditional policies

Effective support for grid regulation via vehicle-to-grid technology

Incorporation of distribution constraints prevents grid overloading

Abstract

Workplace charging of electric vehicles (EV) from photovoltaic (PV) panels installed on an office building can provide several benefits. This includes the local production and use of PV energy for charging the EV and making use of dynamic tariffs from the grid to schedule the energy exchange with the grid. The long parking time of EV at the workplace provide the chance for the EV to support the grid via vehicle-to-grid technology, the use of a single EV charger for charging several EV by multiplexing and the offer of ancillary services to the grid for up and down regulation. Further, distribution network constraints can be considered to limit the power and prevent the overloading of the grid. A single MILP formulation that considers all the above applications has been proposed in this paper for a charging a fleet of EVs from PV. The MILP is implemented as a receding-horizon model predictive energy management system. Numerical simulation based on market and PV data in Austin, Texas have shown 31% to 650% reduction in the cost of EV charging when compared to immediate and average rate charging policies.