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

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journal contribution
submitted on 2023-08-30, 06:28 and posted on 2023-10-15, 08:40 authored by Ahmed Ouammi

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.

Other Information

Published in: IEEE Access
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1109/access.2021.3057458

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

IEEE

Publication Year

  • 2021

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Qatar University
  • College of Arts and Sciences - QU
  • Center for Sustainable Development - CAS