Frontiers in Energy Research (Feb 2023)

Optimal control of renewable energy communities with controllable assets

  • Samy Aittahar,
  • Miguel Manuel de Villena,
  • Guillaume Derval,
  • Michael Castronovo,
  • Ioannis Boukas,
  • Quentin Gemine,
  • Damien Ernst,
  • Damien Ernst

DOI
https://doi.org/10.3389/fenrg.2023.879041
Journal volume & issue
Vol. 11

Abstract

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Introduction: The control of Renewable Energy Communities (REC) with controllable assets (e.g., batteries) can be formalised as an optimal control problem. This paper proposes a generic formulation for such a problem whereby the electricity generated by the community members is redistributed using repartition keys. These keys represent the fraction of the surplus of local electricity production (i.e., electricity generated within the community but not consumed by any community member) to be allocated to each community member. This formalisation enables us to jointly optimise the controllable assets and the repartition keys, minimising the combined total value of the electricity bills of the members.Methods: To perform this optimisation, we propose two algorithms aimed at solving an optimal open-loop control problem in a receding horizon fashion. Moreover, we also propose another approximated algorithm which only optimises the controllable assets (as opposed to optimising both controllable assets and repartition keys). We test these algorithms on Renewable Energy Communities control problems constructed from synthetic data, inspired from a real-life case of REC.Results: Our results show that the combined total value of the electricity bills of the members is greatly reduced when simultaneously optimising the controllable assets and the repartition keys (i.e., the first two algorithms proposed).Discussion: These findings strongly advocate the need for algorithms that adopt a more holistic standpoint when it comes to controlling energy systems such as renewable energy communities, co-optimising or jointly optimising them from both a traditional (very granular) control standpoint and a larger economic perspective.

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