eCite Digital Repository
Self-scheduling of a generating company with an EV load aggregator under an energy exchange strategy
Citation
Tavakoli, A and Negnevitsky, M and Saha, S and Haque, ME and Arif, MT and Contreras, J and Oo, A, Self-scheduling of a generating company with an EV load aggregator under an energy exchange strategy, IEEE Transactions on Smart Grid, 10, (4) pp. 4253-4264. ISSN 1949-3053 (2019) [Refereed Article]
Copyright Statement
Copyright 2018 IEEE.
DOI: doi:10.1109/TSG.2018.2854763
Abstract
This paper investigates an energy exchange strategy between a generating company (GenCO) and an electric vehicle load aggregator (EVLA) in the energy and ancillary services markets. The impact of the proposed strategy on the schedule of
generation, EV charging, payoff, and offer prices is discussed, especially when renewable energy and EV penetration grow. An optimal self-scheduling problem for a GenCO together with an EVLA and renewable generation units under an energy
exchange strategy is presented. In the proposed method, offer prices and EV tariffs under a price-maker approach are calculated by simulating the market operator clearing process and considering uncertainties corresponding to the renewable
forecasting errors and the driving patterns of EV owners. A stochastic intra-hour bi-level problem is developed for the upper and lower levels. In the upper level, a firm which owns conventional and wind generation plus EVLA maximizes the profit, while the lower-level problems correspond to the market clearings. The bi-level problem is solved as a mixed-integer linear program (MILP) by the CPLEX solver. Results show that the energy exchange strategy under flexible EV tariffs results in
an increase of the renewable energy penetration and the profitability of the GenCO.
Item Details
Item Type: | Refereed Article |
---|---|
Keywords: | energy exchange, renewable energy, electric vehicle, bi-level model, energy and ancillary services markets |
Research Division: | Engineering |
Research Group: | Electrical engineering |
Research Field: | Electrical energy generation (incl. renewables, excl. photovoltaics) |
Objective Division: | Energy |
Objective Group: | Energy storage, distribution and supply |
Objective Field: | Energy transmission and distribution (excl. hydrogen) |
UTAS Author: | Negnevitsky, M (Professor Michael Negnevitsky) |
ID Code: | 131235 |
Year Published: | 2019 |
Web of Science® Times Cited: | 8 |
Deposited By: | Engineering |
Deposited On: | 2019-03-07 |
Last Modified: | 2020-01-14 |
Downloads: | 0 |
Repository Staff Only: item control page