Integrated PV Charging of EV Fleet Based on Energy Prices, V2G and Offer of Reserves

Journal article (2019)

Authors

G.R. Chandra Mouli DC systems, Energy conversion & Storage - EEMCS
Mahdi Kefayati The University of Texas at Austin
Ross Baldick The University of Texas at Austin
P. Bauer DC systems, Energy conversion & Storage - EEMCS
Research Group
DC systems, Energy conversion & Storage (EEMCS) (TU Delft)
Copyright: © 2019 G.R. Chandra Mouli, Mahdi Kefayati, Ross Baldick, P. Bauer
DOI
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https://doi.org/10.1109/TSG.2017.2763683
Scheduling Smart grids Electric vehicle Distribution system Smart charging Charging station Photovoltaic system Regulation services
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Published Date

2019

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

DC systems, Energy conversion & Storage

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 at the workplace provides the chance for the EV to support the grid via vehicle-to-grid technology, the use of a single EV charger for charging several EVs 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 mixed integer linear programming (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 simulations based on market and PV data in Austin, Texas have shown 32% to 651% reduction in the net cost of EV charging from PV when compared to immediate and average rate charging policies.