Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.energy.2011.04.020
DC FieldValue
dc.titleA linear diversity constraint - Application to scheduling in microgrids
dc.contributor.authorNaraharisetti, P.K.
dc.contributor.authorKarimi, I.A.
dc.contributor.authorAnand, A.
dc.contributor.authorLee, D.-Y.
dc.date.accessioned2014-06-16T09:29:45Z
dc.date.available2014-06-16T09:29:45Z
dc.date.issued2011-07
dc.identifier.citationNaraharisetti, P.K., Karimi, I.A., Anand, A., Lee, D.-Y. (2011-07). A linear diversity constraint - Application to scheduling in microgrids. Energy 36 (7) : 4235-4243. ScholarBank@NUS Repository. https://doi.org/10.1016/j.energy.2011.04.020
dc.identifier.issn03605442
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/54306
dc.description.abstractMicrogrids usually operate in disparate locations and may not be connected to the national grid. The potential sources of electricity in microgrids are wind farms, solar energy, biomass, tidal energy, among others. However, microgrids that are connected to the national grid are gaining importance, because they can supply electricity to the national grid when they have an excess and buy from it when they are in shortage. Such a symbiotic relationship with the national grid helps reduce investment in storage capacity and minimizes other operational costs. In this work, we develop a mathematical model MILP - (mixed integer linear programming) for scheduling operations in microgrids connected to the national grid. We allow several realistic features such as time constraints for the purchase/sale of power from/to the national grid; round trip efficiency of batteries; hydrogen generation, and limits on storage and retrieval rates from batteries/hydrogen tanks/natural gas tanks. Furthermore, to maintain diversity in the generation of electricity from multiple resources, we develop and impose a novel linear diversity constraint on the production schedule without sacrificing the ease of schedule implementation. © 2011 Elsevier Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.energy.2011.04.020
dc.sourceScopus
dc.subjectMicrogrids
dc.subjectMILP
dc.subjectOptimization
dc.subjectRenewable energy
dc.subjectScheduling
dc.typeArticle
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.contributor.departmentSINGAPORE-MIT ALLIANCE
dc.contributor.departmentCIVIL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1016/j.energy.2011.04.020
dc.description.sourcetitleEnergy
dc.description.volume36
dc.description.issue7
dc.description.page4235-4243
dc.description.codenENEYD
dc.identifier.isiut000293115600034
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