Optimal Operation of Residential Battery Energy Storage Systems under COVID-19 Load Changes
dc.contributor.author | Hijazi, Zahraa | |
dc.contributor.advisor | Hong, Junho | |
dc.contributor.advisor | Su, Wencong | |
dc.date.accessioned | 2024-07-09T20:50:50Z | |
dc.date.available | 2025-07-09 16:50:51 | en |
dc.date.issued | 2024-12-20 | |
dc.date.submitted | 2024-06-24 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/194075 | |
dc.description.abstract | Over the past few years as COVID-19 was declared a worldwide pandemic that resulted in loadchanges and an increase in residential loads, utilities have faced increasing challenges in maintainingload balance. Because out-of-home activities were limited, daily residential electricityconsumption increased by about 12â30% with variable peak hours. In addition, battery energystorage systems (BESSs) became more affordable, and thus higher storage system adoption rateswere witnessed. This variation created uncertainties for electric grid operators. The objective ofthis research is to present a utility perspective of the optimal operation of residential battery storagesystems to maximize utility benefits without jeopardizing grid resilience and stability. This isaccomplished by formulating an objective function to minimize distribution and generation losses,generation fuel prices, market fuel prices, generation at peak time, and battery operation cost and tomaximize battery capacity. Furthermore, to study the optimal locations for batteries on a distributioncircuit, a trial-and-error approach was considered that takes into account grid infrastructure. Amixed-integer linear programming (MILP) method has been developed and implemented for thesepurposes. A residential utility circuit has been selected for a case study. The circuit includes 315buses and 100 battery energy storage systems without the connection of other distributed energyresources (DERs), e.g., photovoltaic and wind. Assuming that the batteries are charging overnight,the results show that energy costs can be reduced by 10% and losses can decrease by 17% by optimallyoperating batteries to support increased load demand. In addition, it resulted in improvedvoltage profiles with the lowest voltage of 0.95 p.u., reduced distribution losses to 1.5% and foundthe optimal batteries deployment locations which happens to be closer to the end of the circuit. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Battery energy storage system | en_US |
dc.subject | Distributed energy resources | en_US |
dc.subject | Mixed-integer linear programming | en_US |
dc.subject | Wholesale energy market | en_US |
dc.subject | Optimization | en_US |
dc.subject.other | Electrical and Computer Engineering | en_US |
dc.title | Optimal Operation of Residential Battery Energy Storage Systems under COVID-19 Load Changes | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | Doctor of Engineering (DEng) | en_US |
dc.description.thesisdegreediscipline | College of Engineering & Computer Science | en_US |
dc.description.thesisdegreegrantor | University of Michigan-Dearborn | en_US |
dc.contributor.committeemember | Wang, Mengqi | |
dc.contributor.committeemember | Nuqu, Reynaldo | |
dc.identifier.uniqname | zahijazi | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/194075/1/Hijazi_Dissertation_Optimal_Operation.pdf | en |
dc.identifier.doi | https://dx.doi.org/10.7302/23520 | |
dc.description.mapping | 4747e415-ebc0-42de-9b6b-96a7df57693f | en_US |
dc.identifier.orcid | 0009-0007-1141-5892 | en_US |
dc.description.filedescription | Description of Hijazi_Dissertation_Optimal_Operation.pdf : Dissertation | |
dc.working.doi | 10.7302/23520 | en_US |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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