An agent-based approach to virtual power plants of wind generators and electric vehicles
An agent-based approach to virtual power plants of wind generators and electric vehicles
Wind power is gaining in significance as an important renewable source of clean energy. However, due to their inherent uncertainty, wind generators are often unable to participate in the forward electricity markets like the more predictable and controllable conventional generators. Given this, virtual power plants (VPPs) are being advocated as a solution for increasing the reliability of such intermittent renewable sources. In this paper, we take this idea further by considering VPPs as coalitions of wind generators and electric vehicles, where wind generators seek to use electric vehicles (EVs) as a storage medium to overcome the vagaries of generation. Using electric vehicles in this manner has the advantage that, since the number of EVs is increasing rapidly, no initial investment in dedicated storage is needed. In more detail, we first formally model the VPP and then, through an operational model based on linear programming, we show how the supply to the Grid and storage in the EV batteries can be scheduled to increase the profit of the VPP, while also paying for the storage using a novel scheme. The feasibility of our approach is examined through a realistic case-study, using real wind power generation data, corresponding electricity market prices and electric vehicles’ characteristics.
1314-1322
Vasirani, M.
09d5a301-d0d1-42f3-8cd8-ccb3dfc30872
Kota, R.
533595f6-c1bc-48fc-b661-fa08aa69daf8
Cavalcante, R.L.G.
f0e12e72-9fd8-4599-ac09-19cd2e887d31
Ossowski, S
f893bbde-7db0-4cb0-a92e-02fbaa0253f7
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
2013
Vasirani, M.
09d5a301-d0d1-42f3-8cd8-ccb3dfc30872
Kota, R.
533595f6-c1bc-48fc-b661-fa08aa69daf8
Cavalcante, R.L.G.
f0e12e72-9fd8-4599-ac09-19cd2e887d31
Ossowski, S
f893bbde-7db0-4cb0-a92e-02fbaa0253f7
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Vasirani, M., Kota, R., Cavalcante, R.L.G., Ossowski, S and Jennings, N.R.
(2013)
An agent-based approach to virtual power plants of wind generators and electric vehicles.
IEEE Transactions on Smart Grid, 4 (3), .
Abstract
Wind power is gaining in significance as an important renewable source of clean energy. However, due to their inherent uncertainty, wind generators are often unable to participate in the forward electricity markets like the more predictable and controllable conventional generators. Given this, virtual power plants (VPPs) are being advocated as a solution for increasing the reliability of such intermittent renewable sources. In this paper, we take this idea further by considering VPPs as coalitions of wind generators and electric vehicles, where wind generators seek to use electric vehicles (EVs) as a storage medium to overcome the vagaries of generation. Using electric vehicles in this manner has the advantage that, since the number of EVs is increasing rapidly, no initial investment in dedicated storage is needed. In more detail, we first formally model the VPP and then, through an operational model based on linear programming, we show how the supply to the Grid and storage in the EV batteries can be scheduled to increase the profit of the VPP, while also paying for the storage using a novel scheme. The feasibility of our approach is examined through a realistic case-study, using real wind power generation data, corresponding electricity market prices and electric vehicles’ characteristics.
Text
vkcoj_v4.pdf
- Author's Original
Text
06518218.pdf
- Other
More information
Published date: 2013
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 351001
URI: http://eprints.soton.ac.uk/id/eprint/351001
ISSN: 1949-3053
PURE UUID: 2eb4bfc9-5cc8-4b61-8f9d-26906d35db2b
Catalogue record
Date deposited: 12 Apr 2013 10:56
Last modified: 14 Mar 2024 13:34
Export record
Contributors
Author:
M. Vasirani
Author:
R. Kota
Author:
R.L.G. Cavalcante
Author:
S Ossowski
Author:
N.R. Jennings
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics