Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response

Yuwei Cao; Liying Wang; Shigong Jiang; Weihong Yang; Ming Zeng; Xiaopeng Guo

doi:10.1016/j.gloei.2020.11.003

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Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response

Solving Crisis | 更新时间：2026-07-15

- Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response
- Global Energy Interconnection Vol. 3, Issue 5, Pages: 430-441(2020)
- 作者机构：
  
  1. School of Economics and Management, North China Electric Power University,Beijing,China,102206
  2. State Grid Economic and Technological Research Institute Co.,Beijing,China,102209
- 作者简介：
- 基金信息：
- DOI：10.1016/j.gloei.2020.11.003
  CLC：
- Online First：09 December 2020，
  
  Published：09 December 2020
- 稿件说明：
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Yuwei Cao, Liying Wang, Shigong Jiang, et al. Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response[J]. Global Energy Interconnection, 2020, 3(5): 430-441.
DOI：

Yuwei Cao, Liying Wang, Shigong Jiang, et al. Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response[J]. Global Energy Interconnection, 2020, 3(5): 430-441. DOI： 10.1016/j.gloei.2020.11.003.

摘要

Abstract

In a multi-energy collaboration system

cooling

heating

electricity

and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation

they can significantly improve their individual operating efficiency and overall economic benefits. Demand response

as a multi-energy supply and demand balance method

can further improve system flexibility and economy. Therefore

a multi-energy cooperative system optimization model has been proposed

which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis

a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation

the model has been verified

and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.

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