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Optimal energy management system of IoT-Enabled large building considering electric vehicle scheduling, distributed resources, and demand response schemes

Fei, L ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.3390/s22197448
  3. Publisher: MDPI , 2022
  4. Abstract:
  5. In the energy system, various sources are used to fulfill the energy demand of large buildings. The energy management of large-scale buildings is very important. The proposed system comprises solar PVs, energy storage systems, and electric vehicles. Demand response (DR) schemes are considered in various studies, but the analysis of the impact of dynamic DR on operational cost has been ignored. So, in this paper, renewable energy resources and storages are integrated considering the demand response strategies such as real-time pricing (RTP), critical peak pricing (CPP), and time of use (ToU). The proposed system is mapped in a linear model and simulated in MATLAB using linear programming (LP). Different case studies are investigated considering the dynamic demand response schemes. Among different schemes, results based on real-time pricing (58% saving) show more saving as compared to the CPP and ToU. The obtained results reduced the operational cost and greenhouse gas (GHG) emissions, which shows the efficacy of the model. © 2022 by the authors
  6. Keywords:
  7. Demand response ; Electric vehicle ; Energy management system ; Microgrids ; Cost benefit analysis ; Electric power transmission networks ; Electric vehicles ; Energy management ; Energy storage ; Gas emissions ; Greenhouse gases ; Linear programming ; MATLAB ; Renewable energy resources ; Scheduling ; Smart power grids ; Dynamic demand response ; Energy storage system ; Large buildings ; Microgrid ; Optimal energy ; Real time pricing ; Smart grid ; Storage systems ; Time of use ; Energy management systems
  8. Source: Sensors ; Volume 22, Issue 19 , 2022 ; 14248220 (ISSN)
  9. URL: https://www.mdpi.com/1424-8220/22/19/7448