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dc.contributor.authorFleming, Sean
dc.date.accessioned2021-09-13T16:49:44Z
dc.date.available2021-09-13T16:49:44Z
dc.date.issued2021-09-13T16:49:44Z
dc.identifier.urihttp://hdl.handle.net/10222/80806
dc.description.abstractIn parallel to growing building electrification initiatives, the cost of lithium-ion batteries has fallen by over 85% since 2010. These factors have driven interest in using lithium-ion batteries to reduce demand charges in commercial and industrial buildings. The research objective was to develop new models and control strategies for using batteries for demand charge management in Nova Scotia’s commercial and industrial sector with basic monthly billing data for peak demand prediction. This research used four years of 15 minute electrical load data for 248 commercial buildings, across eight building categories, from Nova Scotia Power to explore the relationships between the peak demand, average load and monthly load factor of a building and the potential for demand savings, categories of buildings that are of interest, and the peak demand prediction accuracy with basic monthly billing data. A new MATLAB battery model was developed to perform iterative demand reduction simulations across a range of battery capacities, inverter power rates, and demand reduction targets. New visualization methods were developed to sort results by both building size and load factor so trends between buildings load characteristics and demand savings results can be identified quickly. Key findings of the research were that buildings with an average monthly load factor under 40% and an average load of less than 50 kW are the best candidates for using a battery in a demand charge management application. There were limited opportunities in the Hotel and Utility categories because of the high average loads and average monthly load factors. While in the Commercial, Retail, and Industrial there are strong opportunities for demand charge reduction, provided the buildings meet the average load and average monthly load factor guidelines above. Finally, there are diminishing returns for demand savings with larger battery pack sizes. Smaller battery packs offer the most demand savings per unit of battery capacity and the largest percentage of total demand reduction per unit of battery capacity.en_US
dc.language.isoenen_US
dc.subjectenergy storageen_US
dc.subjectbatteriesen_US
dc.subjectdemand charge managementen_US
dc.subjectpeak shavingen_US
dc.subjectbatteryen_US
dc.titleModelling Energy Storage for Demand Charge Mitigation in Commercial Buildings to Develop Standardized Design Guidelinesen_US
dc.date.defence2021-08-17
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.contributor.degreeMaster of Applied Scienceen_US
dc.contributor.external-examinerDr. Tim Littleen_US
dc.contributor.graduate-coordinatorFarid Taherien_US
dc.contributor.thesis-readerDr. Darrel Domanen_US
dc.contributor.thesis-supervisorDr. Lukas Swanen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.copyright-releaseNot Applicableen_US
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