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    Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids

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    Peak_Loads_Shaving_in_a_Team_of_Cooperating_Smart_Buildings_Powered_Solar_PV-Based_Microgrids.pdf (5.897Mb)
    Date
    2021
    Author
    Ouammi, Ahmed
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    Abstract
    This paper presents a scheduling framework based algorithm for reducing/shaving the peak loads in a team of cooperating microgrids (TCM) powered smart buildings taking advantages of vehicle-to-building (V2B) concept and operational flexibilities of electric vehicles (EVs). Each microgrid includes a roof-top solar PV, energy storage system, EVs, loads, and advanced metering and communication infrastructure. The main objective is to formulate a constrained optimization problem embedded in a model predictive control (MPC) scheme to optimally control the operation of each microgrid to reduce/shave the peak load in case of occurrence, optimizing the power flows exchanges and energy storages, while ensuring a high quality of service to the EVs owners in each microgrid. The developed predictive model is implemented as a smart energy management based high-level control of the TCM to reduce/shave the peak loads and satisfy the EVs power demands through a coordination of the power exchanges between the microgrids. The algorithm has been tested through a case study to demonstrate its performance and effectiveness.
    DOI/handle
    http://dx.doi.org/10.1109/ACCESS.2021.3057458
    http://hdl.handle.net/10576/63184
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    • Center for Sustainable Development Research [‎338‎ items ]

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