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Explicit Reward Mechanisms for Local Flexibility in Renewable Energy Communities

Thomas Stegen, Julien Allard, Noé Diffels, François Vallée, Mevludin Glavic, Zacharie De Grève, Bertrand Cornélusse

TL;DR

This paper tackles maximizing local arbitrage in Renewable Energy Communities while preserving user privacy by introducing a decentralized, iterative coordination between a Community Operator and members. Its method, ECFlexIt, splits decisions between participants and CO, and uses regulatory Keys of Repartition (KoRs) to fairly allocate activated flexibility, with three concrete KoR rules (Equal, Prorate, Cascade). The study models EVs, water boilers, and heat pumps as storage-like assets and validates on a 20-household case showing the decentralized approach closely matches centralized optima, with deviations as low as around 3.22–3.5% and notable grid efficiency gains when flexibility is activated. The work demonstrates that privacy-preserving, incentive-aware coordination can unlock substantial local flexibility, especially from thermal loads, while keeping computational and data-sharing overhead manageable for real-world deployment.

Abstract

Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes.

Explicit Reward Mechanisms for Local Flexibility in Renewable Energy Communities

TL;DR

This paper tackles maximizing local arbitrage in Renewable Energy Communities while preserving user privacy by introducing a decentralized, iterative coordination between a Community Operator and members. Its method, ECFlexIt, splits decisions between participants and CO, and uses regulatory Keys of Repartition (KoRs) to fairly allocate activated flexibility, with three concrete KoR rules (Equal, Prorate, Cascade). The study models EVs, water boilers, and heat pumps as storage-like assets and validates on a 20-household case showing the decentralized approach closely matches centralized optima, with deviations as low as around 3.22–3.5% and notable grid efficiency gains when flexibility is activated. The work demonstrates that privacy-preserving, incentive-aware coordination can unlock substantial local flexibility, especially from thermal loads, while keeping computational and data-sharing overhead manageable for real-world deployment.

Abstract

Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes.
Paper Structure (18 sections, 5 equations, 3 figures, 4 tables, 2 algorithms)

This paper contains 18 sections, 5 equations, 3 figures, 4 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Framework and key assumptions
  3. Flexible load models
  4. Repartition keys
  5. Equal Key
  6. Prorate Key
  7. Cascade Key
  8. Centralized Flexibility Activation Problem
  9. Baseline problem (SoloFix)
  10. Individual self-consumption problem (SoloFlex)
  11. Non-flexible community problem (ECFix)
  12. Prioritization of individual self-consumption (ECFlex')
  13. Proposed decentralized resolution approach
  14. Case Study and Results
  15. Preserving privacy does not imply high benefits loss
  16. ...and 3 more sections

Figures (3)

  • Figure 1: Equivalent battery models of the four domestic flexible equipments considered.
  • Figure 2: Total benefits over the SoloFix model
  • Figure 3: Individualization of the benefits compared to the community with fixed consumption