Optimization of charging strategies for electric vehicles in PowerMatcher-driven smart energy grids

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Abstract

A crucial challenge in future smart energy grids is the large-scale coordination of distributed energy demand and generation. The well-known PowerMatcher is a promising approach that integrates demand and supply exibility in the operation of the electricity system through dynamic pricing and a hierarchical bidding coordination scheme. However, as the PowerMatcher focuses on short-term coordination of demand and supply, it cannot fully exploit the exibility of e.g. electric vehicles over longer periods of time. In this paper, we propose an extension of the PowerMatcher comprising a planning module, which provides coordinated predictions of demand/price over longer times as input to the users for determining their short-term bids. The optimal short-term bidding strategy minimizing a user's costs is then formulated as a Stochastic Dynamic Programming (SDP) problem. We derive an analytic solution for this SDP problem leading to a simple short-term bidding strategy. Numerical results using real-world data show a substantial performance improvement compared to the standard PowerMatcher, without significant additional complexity.
Original languageUndefined
Title of host publicationProceedings 9th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools 2015
EditorsW. Knottenbelt, K. Wolter, A. Busic, M. Gribaudo, P. Reinecke
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1-8
Number of pages8
ISBN (Print)978-1-63190-096-9
DOIs
Publication statusPublished - 2015
Event9th EAI International Conference on Performance Evaluation Methodologies and Tools 2015 - Berlin, Germany
Duration: 14 Dec 201516 Dec 2015
Conference number: 9
http://archive.valuetools.org/2015/show/home

Publication series

Name
PublisherACM

Conference

Conference9th EAI International Conference on Performance Evaluation Methodologies and Tools 2015
Abbreviated titleVALUETOOLS 2015
CountryGermany
CityBerlin
Period14/12/1516/12/15
Internet address

Keywords

  • EWI-26827
  • PowerMatcher
  • Electric vehicles
  • METIS-316836
  • Smart Grids
  • Market-based coordination
  • IR-99668
  • Stochastic dynamic programming

Cite this

Kempker, P., van Dijk, N. M., Scheinhardt, W. R. W., van den Berg, H. L., & Hurink, J. L. (2015). Optimization of charging strategies for electric vehicles in PowerMatcher-driven smart energy grids. In W. Knottenbelt, K. Wolter, A. Busic, M. Gribaudo, & P. Reinecke (Eds.), Proceedings 9th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools 2015 (pp. 1-8). New York: Association for Computing Machinery (ACM). https://doi.org/10.4108/eai.4-1-2016.151091
Kempker, Pia ; van Dijk, N.M. ; Scheinhardt, Willem R.W. ; van den Berg, Hans Leo ; Hurink, Johann L. / Optimization of charging strategies for electric vehicles in PowerMatcher-driven smart energy grids. Proceedings 9th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools 2015. editor / W. Knottenbelt ; K. Wolter ; A. Busic ; M. Gribaudo ; P. Reinecke. New York : Association for Computing Machinery (ACM), 2015. pp. 1-8
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abstract = "A crucial challenge in future smart energy grids is the large-scale coordination of distributed energy demand and generation. The well-known PowerMatcher is a promising approach that integrates demand and supply exibility in the operation of the electricity system through dynamic pricing and a hierarchical bidding coordination scheme. However, as the PowerMatcher focuses on short-term coordination of demand and supply, it cannot fully exploit the exibility of e.g. electric vehicles over longer periods of time. In this paper, we propose an extension of the PowerMatcher comprising a planning module, which provides coordinated predictions of demand/price over longer times as input to the users for determining their short-term bids. The optimal short-term bidding strategy minimizing a user's costs is then formulated as a Stochastic Dynamic Programming (SDP) problem. We derive an analytic solution for this SDP problem leading to a simple short-term bidding strategy. Numerical results using real-world data show a substantial performance improvement compared to the standard PowerMatcher, without significant additional complexity.",
keywords = "EWI-26827, PowerMatcher, Electric vehicles, METIS-316836, Smart Grids, Market-based coordination, IR-99668, Stochastic dynamic programming",
author = "Pia Kempker and {van Dijk}, N.M. and Scheinhardt, {Willem R.W.} and {van den Berg}, {Hans Leo} and Hurink, {Johann L.}",
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Kempker, P, van Dijk, NM, Scheinhardt, WRW, van den Berg, HL & Hurink, JL 2015, Optimization of charging strategies for electric vehicles in PowerMatcher-driven smart energy grids. in W Knottenbelt, K Wolter, A Busic, M Gribaudo & P Reinecke (eds), Proceedings 9th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools 2015. Association for Computing Machinery (ACM), New York, pp. 1-8, 9th EAI International Conference on Performance Evaluation Methodologies and Tools 2015, Berlin, Germany, 14/12/15. https://doi.org/10.4108/eai.4-1-2016.151091

Optimization of charging strategies for electric vehicles in PowerMatcher-driven smart energy grids. / Kempker, Pia; van Dijk, N.M.; Scheinhardt, Willem R.W.; van den Berg, Hans Leo; Hurink, Johann L.

Proceedings 9th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools 2015. ed. / W. Knottenbelt; K. Wolter; A. Busic; M. Gribaudo; P. Reinecke. New York : Association for Computing Machinery (ACM), 2015. p. 1-8.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - A crucial challenge in future smart energy grids is the large-scale coordination of distributed energy demand and generation. The well-known PowerMatcher is a promising approach that integrates demand and supply exibility in the operation of the electricity system through dynamic pricing and a hierarchical bidding coordination scheme. However, as the PowerMatcher focuses on short-term coordination of demand and supply, it cannot fully exploit the exibility of e.g. electric vehicles over longer periods of time. In this paper, we propose an extension of the PowerMatcher comprising a planning module, which provides coordinated predictions of demand/price over longer times as input to the users for determining their short-term bids. The optimal short-term bidding strategy minimizing a user's costs is then formulated as a Stochastic Dynamic Programming (SDP) problem. We derive an analytic solution for this SDP problem leading to a simple short-term bidding strategy. Numerical results using real-world data show a substantial performance improvement compared to the standard PowerMatcher, without significant additional complexity.

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A2 - Busic, A.

A2 - Gribaudo, M.

A2 - Reinecke, P.

PB - Association for Computing Machinery (ACM)

CY - New York

ER -

Kempker P, van Dijk NM, Scheinhardt WRW, van den Berg HL, Hurink JL. Optimization of charging strategies for electric vehicles in PowerMatcher-driven smart energy grids. In Knottenbelt W, Wolter K, Busic A, Gribaudo M, Reinecke P, editors, Proceedings 9th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools 2015. New York: Association for Computing Machinery (ACM). 2015. p. 1-8 https://doi.org/10.4108/eai.4-1-2016.151091