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Author:

Bai, Y. (Bai, Y..) | Zhang, W. (Zhang, W..) | Yu, T. (Yu, T..) | Wang, J. (Wang, J..) | Deng, G. (Deng, G..) | Yan, J. (Yan, J..) | Liu, J. (Liu, J..)

Indexed by:

EI Scopus SCIE

Abstract:

The problems of continuous rise in global power consumption, gradual increase in the peak–valley difference of power systems, and continuous expansion of renewable energy penetration have caused the power system regulation to shift from the traditional supply side to demand side. Buildings have huge power consumption and great energy flexibility, making them one of the most important units on the demand side of a power system. This study performed a detailed review of 183 literatures on flexible energy resources. The review has been carried out from the supply and demand side and demand response strategy side. Based on the results of the analysis and discussion, we proposed seven general quantitative models of flexibility for commonly used flexible resources, which lays the foundation for the flexibility evaluation of the building electric energy flexible system (BEEFS) and implementation of demand response strategies. In addition, the optimization techniques commonly used in demand response strategies are analyzed to achieve different goals. The results show that the combination of these strategies and optimization techniques can achieve the goals of reducing operating costs (OCs) by 4%–42%, reducing peak power (PP) by 15%–96%, and improving renewable energy consumption rate (RECR) by 6%–70%. This study constructs an overall framework for the flexibility quantification of building electric energy systems, which can be further expanded in the future. In the process of interaction between the building and the grid, appropriate demand response strategies and optimization techniques need to be selected according to the types and characteristics of flexible resources to achieve the goals in the demand response process. © 2023

Keyword:

Flexible energy system Renewable energy Demand response strategies Optimization techniques Quantitative model

Author Community:

  • [ 1 ] [Bai Y.]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zhang W.]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Yu T.]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Wang J.]Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Deng G.]China Academy of Building Research, Beijing, 100013, China
  • [ 6 ] [Yan J.]National Energy Conservation Center, Beijing, 100045, China
  • [ 7 ] [Liu J.]National Energy Conservation Center, Beijing, 100045, China

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Source :

Journal of Building Engineering

ISSN: 2352-7102

Year: 2023

Volume: 68

6 . 4 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 20

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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