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Optimal management of energy sharing in a community of buildings using a model predictive control

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Vand, Behrang
dc.contributor.author Ruusu, Reino
dc.contributor.author Hasan, Ala
dc.contributor.author Manrique Delgado, Benjamin
dc.date.accessioned 2021-05-19T06:30:50Z
dc.date.available 2021-05-19T06:30:50Z
dc.date.issued 2021-07-01
dc.identifier.citation Vand , B , Ruusu , R , Hasan , A & Manrique Delgado , B 2021 , ' Optimal management of energy sharing in a community of buildings using a model predictive control ' , Energy Conversion and Management , vol. 239 , 114178 . https://doi.org/10.1016/j.enconman.2021.114178 en
dc.identifier.issn 0196-8904
dc.identifier.issn 1879-2227
dc.identifier.other PURE UUID: b1db46db-2ab5-4c68-ba84-67529c93cb64
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/b1db46db-2ab5-4c68-ba84-67529c93cb64
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85105340291&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/62845798/ENG_Vand_et_al_Optimal_management_of_energy_sharing_Energy_Conversion_and_Management.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/107563
dc.description Funding Information: The first author is supported by a personal grant from The Finnish Foundation for Technology Promotion/The Foundations' Post Doc Pool. This paper was partly funded by two Academy of Finland projects: “Advanced Energy Matching for Zero-Energy Buildings in Future Smart Hybrid Networks 2014-2018, Decision no. 277680” and the Strategic Research Council (SRC) project “Smart Energy Transition (SET) – Realizing Its Potential for Sustainable Growth for Finland’s Second Century, Decision no. 314325”. The work is connected to the authors’ participation in the IEA-EBC Annex 67 – Energy Flexible Buildings (http://www.annex67.org/). Publisher Copyright: © 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
dc.description.abstract Exporting generated electricity by on-site renewable energy systems from buildings to the grid is only slightly profitable in many countries. Therefore, it is required to investigate the benefits of sharing generated energy in a microgrid within a community of buildings. Exploiting the benefits of peer-to-peer energy exchange between prosumers in a community can make the best use of the on-site generation while reducing their bills. This study elaborates the potential of energy management to minimize the electricity cost of a community consisted of multiple buildings and connected to a microgrid. To implement this, an energy management system is designed based on non-linear economic model predictive control and successive linear programming for sharing the on-site surplus generated electricity between the buildings in the community. Four buildings are simulated and studied as an example of a small community. These buildings are dissimilar in their age, thermal mass, insulation, heating system and on-site renewable energy systems. It is shown that considering the community of buildings as a single entity, the novel model predictive control can be efficiently used for minimizing the energy cost of the community that has various sources of energy generation, conversion and storage, including significant non-linear interactions. Three different scenarios of the energy management system for the studied community are investigated, and the results indicate that the annual electricity energy cost for single buildings can be reduced by 3.0% to 87.9%, depending on the building and its systems, and by 5.4% to 7.7% on the community level. en
dc.format.extent 18
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Energy Conversion and Management en
dc.relation.ispartofseries Volume 239 en
dc.rights openAccess en
dc.title Optimal management of energy sharing in a community of buildings using a model predictive control en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Edinburgh Napier University
dc.contributor.department VTT Technical Research Centre of Finland
dc.contributor.department Department of Mechanical Engineering
dc.subject.keyword Energy management system
dc.subject.keyword Energy sharing
dc.subject.keyword Microgrid
dc.subject.keyword Model predictive control
dc.subject.keyword Non-linear optimization
dc.identifier.urn URN:NBN:fi:aalto-202105196827
dc.identifier.doi 10.1016/j.enconman.2021.114178
dc.type.version publishedVersion

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