Optimal Energy Management System of IoT-Enabled Large Building Considering Electric Vehicle Scheduling, Distributed Resources, and Demand Response Schemes

Fei Liu, Muhammad Shahzad*, Fazal Abbas, Hafiz Abdul Muqeet , Muhammad Hussain*, Bin Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)
96 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article number7448
JournalSensors
Volume22
Issue number19
Early online date30 Sept 2022
DOIs
Publication statusPublished - Oct 2022

Keywords

  • demand response
  • electric vehicle
  • energy management system
  • energy storage system
  • microgrids
  • smart grid

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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