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Scheduling and sizing of campus microgrid considering demand response and economic analysis

Bin, L ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.3390/s22166150
  3. Publisher: MDPI , 2022
  4. Abstract:
  5. Current energy systems face multiple problems related to inflation in energy prices, reduction of fossil fuels, and greenhouse gas emissions which are disturbing the comfort zone of energy consumers and the affordability of power for large commercial customers. These kinds of problems can be alleviated with the help of optimal planning of demand response policies and with distributed generators in the distribution system. The objective of this article is to give a strategic proposition of an energy management system for a campus microgrid (µG) to minimize the operating costs and to increase the self-consuming energy of the green distributed generators (DGs). To this end, a real-time based campus is considered that currently takes provision of its loads from the utility grid only. According to the proposed given scenario, it will contain solar panels and a wind turbine as non-dispatchable DGs while a diesel generator is considered as a dispatchable DG. It also incorporates an energy storage system with optimal sizing of BESS to tackle the multiple disturbances that arise from solar radiation. The resultant problem of linear mathematics was simulated and plotted in MATLAB with mixed-integer linear programming. Simulation results show that the proposed given model of energy management (EMS) minimizes the grid electricity costs by 668.8 CC/day ($) which is 36.6% of savings for the campus microgrid. The economic prognosis for the campus to give an optimum result for the UET Taxila, Campus was also analyzed. The general effect of a medium-sized solar PV installation on carbon emissions and energy consumption costs was also determined. The substantial environmental and economic benefits compared to the present situation have prompted the campus owners to invest in the DGs and to install large-scale energy storage. © 2022 by the authors
  6. Keywords:
  7. Batteries ; Distributed generation ; Prosumer market ; Battery storage ; Economic analysis ; Electric batteries ; Electric power transmission networks ; Energy management ; Energy management systems ; Energy utilization ; Fossil fuels ; Gas emissions ; Greenhouse gases ; Integer programming ; MATLAB ; Operating costs ; Smart power grids ; Solar panels ; Battery ; Campus microgrid ; Demand response ; Distributed generators ; Energy storage system ; Microgrid ; Prosume market ; Prosumer ; Smart grid ; Storage systems ; Distributed power generation ; Carbon ; Computer Simulation ; Electricity ; Solar Energy
  8. Source: Sensors ; Volume 22, Issue 16 , 2022 ; 14248220 (ISSN)
  9. URL: https://www.mdpi.com/1424-8220/22/16/6150