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Increasing Use of Renewable Energy by Coalition Formation of Renewable Generators and Energy Stores

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Multi-Agent Systems and Agreement Technologies (EUMAS 2016, AT 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10207))

Abstract

Renewable sources are not used to their full potential for electricity generation. Unpredictability of solar and wind power forces renewable generators to bid conservative generation amounts in a day-ahead market in order to avoid fees for failure to provide generation. In this paper we propose an approach to increase the use of renewable sources, which allows renewable generators to hedge against generation unpredictability by forming coalitions with energy stores. Inside these coalitions renewable generators purchase availability of energy stores to generate power when needed. Renewable generators use this availability to avoid fees for failure to provide committed generation whenever the current generation is lower than the committed value. We experimentally show that our approach allows renewable generators to commit to 100% of the predicted generation, thus increasing the use of renewable sources. We also show that our approach generates profit incentives for both renewable generators and energy stores to form coalitions.

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Acknowledgments

This work was supported by the US National Science Foundation via Award No. CNS-1544705.

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Correspondence to Pavel Janovsky .

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Janovsky, P., DeLoach, S.A. (2017). Increasing Use of Renewable Energy by Coalition Formation of Renewable Generators and Energy Stores. In: Criado Pacheco, N., Carrascosa, C., Osman, N., Julián Inglada, V. (eds) Multi-Agent Systems and Agreement Technologies. EUMAS AT 2016 2016. Lecture Notes in Computer Science(), vol 10207. Springer, Cham. https://doi.org/10.1007/978-3-319-59294-7_12

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  • DOI: https://doi.org/10.1007/978-3-319-59294-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59293-0

  • Online ISBN: 978-3-319-59294-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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