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AuthorAchour, Yasmine
AuthorOuammi, Ahmed
AuthorZejli, Driss
Available date2024-08-15T04:48:37Z
Publication Date2021
Publication NameIEEE Access
ResourceScopus
ISSN21693536
URIhttp://dx.doi.org/10.1109/ACCESS.2021.3132895
URIhttp://hdl.handle.net/10576/57729
AbstractThis paper presents an effective solution to manage the power flows exchanges in a campus integrated microgrid for peak reduction/shaving purposes. The campus integrated microgrid is composed of photovoltaic parking shades, an energy storage system, electric vehicles and bikes, loads, an advanced metering infrastructure, and a smart control unit. The latter is based on Model Predictive Control (MPC) whose objective is to reduce/shave the peak load of the campus while satisfying the Energy Storage System ESS, electrical Vehicles (EVs) and Electrical Bikes (EBs) state of charge. The proposed strategy aims to take the advantage of combining storage and photovoltaic (PV) systems to Vehicle to Campus (V2C) and Bike to Campus (B2C) concepts to support the microgrid to pay the minimum billing power while ensuring a good service quality to the EVs and EBs users. For that, the integration of the renewable energy sources and the different storage systems into the microgrid is modeled, and the MPC-based optimization framework is formulated. Besides, the results related to the application of the MPC to real case studies are presented, integrating the effects of static and dynamic weighting factors on the microgrid operation.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCampus integrated microgrid
demand response
electric bikes
electric vehicles
model predictive control
peak reduction
renewable energy
TitleModel Predictive Control Based Demand Response Scheme for Peak Demand Reduction in a Smart Campus Integrated Microgrid
TypeArticle
Pagination162765-162778
Volume Number9
dc.accessType Open Access


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