4.7 Article

Optimal Operation Analysis of Integrated Community Energy System Considering the Uncertainty of Demand Response

期刊

IEEE TRANSACTIONS ON POWER SYSTEMS
卷 36, 期 4, 页码 3681-3691

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2021.3051720

关键词

Load management; Uncertainty; Natural gas; Load modeling; Cogeneration; Cooling; Ice; Integrated community energy system; energy hub; price incentives; uncertainty; demand response

资金

  1. Regional Innovation and Development Joint Fund of National Natural Science Foundation of China [U19A20106]
  2. Fundamental Research Funds for the Central Universities of China [PA2020GDSK0098]

向作者/读者索取更多资源

This study proposes a demand response uncertainty model based on price incentives and constructs an energy coupling matrix for integrated community energy systems. By optimizing the operating model, it effectively reduces system operating costs, improves the load profile, and achieves a win-win situation for both energy companies and users.
Propose a demand response uncertainty model based on price incentives, describe the relationship between the incentive price and the demand response coefficient. Constructed energy coupling matrices for integrated community energy systems considering demand response based on traditional energy hub models. The uncertainty of the demand response is depicted using the interval approach. Considering the load characteristics and various constraints of the integrated community energy system, optimized operating model with the goal of minimizing operating costs. Using an example of an integrated community energy system for a campus, considering multiple operating scenarios to investigate the effect of integrated demand response under different approaches, the impact of price incentives and incentive schemes on integrated community energy systems. The results show that compared with the traditional method, this method effectively reduces system operating costs and improves the load profile, which helps to achieve a win-win situation for both energy companies and users.

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