Optimal control of renewable energy communities with controllable assets

Author:

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

Abstract

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.

Funder

Université de Liège

Publisher

Frontiers Media SA

Subject

Economics and Econometrics,Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

Reference36 articles.

1. The theory of dynamic programming

2. Real-time bidding strategies from micro-grids using reinforcement learning;Boukas,2018

3. Subhour simulation of a microgrid of all-electric nzebs based on Italian market rules;Ciocia,2020

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