A community energy management system for smart microgrids

Nandor Verba, Jonathan Daniel Nixon, Elena Gaura, Leonardo Alves Dias, Alison Halford

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
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Community micro-grid energy projects are needed to drive de-carbonisation and increase equity of energy systems among displaced communities. However, micro-grid solutions are often inflexible and lack functionality to respond to displaced community energy needs and ensure the long-term sustainability of interventions. This paper explores the use of fog-computing retrofit architectures deployed on community micro-grid infrastructures to enable flexible demand management to improve service delivery and longevity. A micro-services solution is proposed that decouples components increasing resilience and testability while allowing hybrid edge-cloud deployments. The architecture is outlined and demonstrated for a micro-grid providing energy to two nurseries and a playground in Kigeme refugee camp, Rwanda. To enact the community priorities within the demand management system, modified Genetic Algorithm (GA) methods are outlined and tested for different use-case scenarios. The performance of the modified GA methods are then compared with a pre-existing battery protect controller and an alternative deterministic (space-shared) energy manager model. A modified search space GA method was required for GA to outperform both the existing battery controller and proposed deterministic method in terms of achieving the highest utility function in almost every use-case. The results further showed how simple community priorities can be set and used to enact control on the system in 24h timeframes that are in line with the local decision-making context.
Original languageEnglish
Article number107959
Number of pages15
JournalElectric Power Systems Research
Early online date9 Apr 2022
Publication statusPublished - Aug 2022

Bibliographical note

© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).


The authors would like to acknowledge the financial support of the Engineering and Physical Science Research Council (EPSRC) for funding the Humanitarian Engineering and Energy for Displacement (HEED) project as part of the Global Challenges Research Fund (EP/P029531/1). The authors would like to acknowledge and thank project delivery partners Practical Action and Scene Connect for their significant role in co-ordinating in-camp activities and providing technical inputs and tools. We would also like to recognise the support of MIDIMAR (Ministry of Disaster Management and Refugees) and UNHCR (United Nations High Commissioner for Refugees) and the contributions of the Global Plan of Action, Chatham House, and the RE4R (Renewable Energy for Refugees) Project (a partnership between Practical Action and UNHCR, supported by the IKEA Foundation). Funding Information: This research was funded under the Humanitarian Engineering and Energy for Displacement (HEED) project financed by Research Councils UK (EP/P029531/1). Publisher Copyright: © 2022 Elsevier B.V.


  • Smart microgrid
  • Community energy management system
  • Cyber-physical systems
  • Edge computing
  • Internet of things
  • Displaced communities


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