A community energy management system for smart microgrids

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

doi:10.1016/j.epsr.2022.107959

A community energy management system for smart microgrids

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

Computer Science

Research output: Contribution to journal › Article › peer-review

59 Downloads (Pure)

Abstract

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 language	English
Article number	107959
Number of pages	14
Journal	Electric Power Systems Research
Volume	209
Early online date	9 Apr 2022
DOIs	https://doi.org/10.1016/j.epsr.2022.107959
Publication status	Published - Aug 2022

Bibliographical note

Funding Information:
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.

Keywords

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

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.epsr.2022.107959Licence: Creative Commons: Attribution (CC BY)

verban2022communityFinal published version, 3.84 MBLicence: Creative Commons: Attribution (CC BY)

Cite this

@article{618ce49e6bb0411fa64d16885847d1e5,

title = "A community energy management system for smart microgrids",

abstract = "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.",

keywords = "Smart microgrid, Community energy management system, Cyber-physical systems, Edge computing, Internet of things, Displaced communities",

author = "Nandor Verba and Nixon, {Jonathan Daniel} and Elena Gaura and Dias, {Leonardo Alves} and Alison Halford",

note = "Funding Information: 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: {\textcopyright} 2022 Elsevier B.V.",

year = "2022",

month = aug,

doi = "10.1016/j.epsr.2022.107959",

language = "English",

volume = "209",

journal = "Electric Power Systems Research",

issn = "0378-7796",

publisher = "Elsevier",

}

TY - JOUR

T1 - A community energy management system for smart microgrids

AU - Verba, Nandor

AU - Nixon, Jonathan Daniel

AU - Gaura, Elena

AU - Dias, Leonardo Alves

AU - Halford, Alison

N1 - Funding Information: 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.

PY - 2022/8

Y1 - 2022/8

N2 - 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.

AB - 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.

KW - Smart microgrid

KW - Community energy management system

KW - Cyber-physical systems

KW - Edge computing

KW - Internet of things

KW - Displaced communities

UR - http://www.scopus.com/inward/record.url?scp=85127730992&partnerID=8YFLogxK

U2 - 10.1016/j.epsr.2022.107959

DO - 10.1016/j.epsr.2022.107959

M3 - Article

SN - 0378-7796

VL - 209

JO - Electric Power Systems Research

JF - Electric Power Systems Research

M1 - 107959

ER -

A community energy management system for smart microgrids

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this