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Peer-to-peer aggregation for dynamic adjustments in power demand

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Abstract

Energy demand-side management becomes a well-established approach in the Smart Power Grid. Aggregation of consumption information is a critical operation performed by most demand-side energy management mechanisms as it provides information about the required adjustment of power demand. However, a centralized demand-side energy management approach controlled exclusively by utility companies is not always scalable, robust and aligned to the privacy requirements of consumers. A large amount of end-user consumption information is aggregated continuously in centralized approaches. This paper introduces an alternative demand-side energy management scheme: ALMA, the Adaptive Load Management by Aggregation. In ALMA, consumers adjust their demand by selecting between different incentivized demand-options based on aggregate consumption information provided by peer-to-peer aggregation mechanisms. The feasibility of dynamic adjustment in power demand is evaluated and confirmed analytically using data from the current reality and practice of Smart Power Grids.

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Notes

  1. Accessible at: http://www.dehems.eu/ (last accessed: May 2012)

  2. Some of the stakeholders involved are the Bonneville Power Administration, PacifiCorp, Portland General Electric, the City of Port Angeles and Clallam County Public Utility District #1. Industrial collaborators include Invensys Controls, Whirlpool Corporation and IBM Thomas J. Watson Research Center.

  3. Feeders are circuits of the distribution system that connect substations with end-consumers. They run along streets or underground and power the distribution transformers at or near the consumer premises.

  4. In the context of the Olympic Peninsula Project, the marginal price is the change in the total price as a result of a unit change in demand.

  5. Available at: https://svn.pnl.gov/olypen (last accessed: May 2012)

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Acknowledgments

This research is partially funded by the NLNet foundation, the NWO project “RobuSmart: Increasing the robustness of Smart Grids through distributed energy generation: a complex network approach”, grant number 647.000.001 and the European Institute of Technology project: “Smart Grid Value Modelling”. The authors would like to thank Donald J. Hammerstrom, Ronald B. Melton and David P. Chassin for providing access to the data of the Olympic Peninsula Smart Grid Demonstration Project. Furthermore, authors are grateful to Mark Yao and Ron Ambrosio for their intuition about the use of this data.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    Evangelos Pournaras

  2. Department of Multi-actor Systems, Delft University of Technology, Jaffalaan 5, 2628 BX, Delft, The Netherlands

    Martijn Warnier & Frances M. T. Brazier

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  1. Evangelos Pournaras
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  2. Martijn Warnier
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  3. Frances M. T. Brazier
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Correspondence to Evangelos Pournaras.

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Pournaras, E., Warnier, M. & Brazier, F.M.T. Peer-to-peer aggregation for dynamic adjustments in power demand. Peer-to-Peer Netw. Appl. 8, 189–202 (2015). https://doi.org/10.1007/s12083-013-0246-y

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