# Coordination of resources at the edge of the electricity grid: systematic review and taxonomy

arXiv: https://arxiv.org/abs/2202.03786 · HTML: https://mlsanity.com/paper/2202.03786/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Feb 2022.

## Built on by (most cited first, 4 of 4)

- [Centralised rehearsal of decentralised cooperation: Multi-agent reinforcement learning for the scalable coordination of residential energy flexibility](https://mlsanity.com/paper/2305.18875/) (2023)
- [Home Electricity Data Generator (HEDGE): An open-access tool for the generation of electric vehicle, residential demand, and PV generation profiles](https://mlsanity.com/paper/2310.01661/) (2023)
- [Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problems](https://mlsanity.com/paper/2404.15583/) (2024)
- [Data Model Design for Explainable Machine Learning-based Electricity Applications](https://mlsanity.com/paper/2505.23607/) (2025)

## Abstract (arXiv)

This paper proposes a novel taxonomy of coordination strategies for distributed energy resources at the edge of the electricity grid, based on a systematic analysis of key literature trends. The coordination of distributed energy resources such as decentralised generation and flexibility sources is critical for decarbonising electricity and achieving climate goals. The literature on the topic is growing exponentially; however, there is ambiguity in the terminology used to date. We seek to resolve this lack of clarity by synthesising the categories of coordination strategies in a novel exhaustive, mutually exclusive taxonomy based on agency, information and game type. The relevance of these concepts in the literature is illustrated through a systematic literature review of 84,741 publications using a structured topic search query. Then 93 selected coordination strategies are analysed in more detail and mapped onto this framework. Clarity on structural assumptions is key for selecting appropriate coordination strategies for differing contexts within energy systems. We argue that a plurality of complementary strategies is needed to coordinate energy systems' different components and achieve deep decarbonisation.