考虑需求响应和条件风险价值的综合能源系统优化调度

刘英培; 单泓元; 信明垚; 秦浩然

doi:10.19725/j.cnki.1007-2322.2024.0224

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考虑需求响应和条件风险价值的综合能源系统优化调度

能源互联网 | 更新时间：2026-10-19

- 考虑需求响应和条件风险价值的综合能源系统优化调度
- Optimal Scheduling of Integrated Energy Systems Considering Demand Response and Conditional Value at Risk
- 现代电力 2026年43卷第5期页码：1045-1052
- 作者机构：
  
  华北电力大学电气与电子工程学院,河北省,保定市,071003
- 作者简介：
  
  刘英培(1982)，女，博士，副教授，研究方向为新能源发电并网技术、综合能源系统优化等，E-mail：liuyingpei_123@126.com
  单泓元(2000)，男，硕士研究生，通信作者，研究方向为综合能源系统优化调度， E-mail：1215005988@qq.com
- 基金信息：
  
  国家自然科学基金项目(51607069)。
- DOI：10.19725/j.cnki.1007-2322.2024.0224
  中图分类号： 5
- 纸质出版：2026
- 稿件说明：
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刘英培, 单泓元, 信明垚, 等. 考虑需求响应和条件风险价值的综合能源系统优化调度[J]. 现代电力, 2026,43(5):1045-1052.

LIU Yingpei, SHAN Hongyuan, XIN Mingyao, et al. Optimal Scheduling of Integrated Energy Systems Considering Demand Response and Conditional Value at Risk[J]. 2026, 43(5): 1045-1052.
刘英培, 单泓元, 信明垚, 等. 考虑需求响应和条件风险价值的综合能源系统优化调度[J]. 现代电力, 2026,43(5):1045-1052. DOI： 10.19725/j.cnki.1007-2322.2024.0224.

LIU Yingpei, SHAN Hongyuan, XIN Mingyao, et al. Optimal Scheduling of Integrated Energy Systems Considering Demand Response and Conditional Value at Risk[J]. 2026, 43(5): 1045-1052. DOI： 10.19725/j.cnki.1007-2322.2024.0224.

摘要

为降低系统碳排放量，平抑负荷曲线，减少源–荷不确定性带来的潜在风险，提出一种考虑需求响应和条件风险价值的综合能源系统优化调度模型。首先，在源侧建立一种包含阶梯式绿色证书机制的碳–绿联合交易机制，在负荷侧引入多能源价格引导的需求响应模型。其次，引入条件风险价值理论，从失负荷和需求响应调度偏差两个角度量化源–荷不确定性给系统带来的潜在风险。然后，建立综合考虑碳–绿联合交易机制、需求响应模型和条件风险价值的优化调度模型。最后，通过算例分析与论证的结果表明：模型具有减少系统碳排放量、负荷峰谷差的作用，引入条件风险价值后，决策者需要综合考虑系统的经济性和安全性，制定更合理的优化调度方案。

Abstract

To reduce carbon emissions

flatten load curves

and mitigate potential risks stemming from source-load uncertainties

an optimal scheduling model for the integrated energy system (IES) that incorporates demand response (DR) and conditional value at risk (CVaR) is proposed. Firstly

a carbon-green joint trading mechanism that incorporates a tiered green certificate mechanism is proposed on the source side

and a DR model guided by multiple energy prices on the load side is introduced into the model. Furthermore

the CVaR theory is introduced to quantify the potential risks brought by source-load uncertainty to the system from the perspectives of load loss and DR scheduling deviation. Subsequently

an optimized scheduling model is developed that comprehensively considers the carbon-green joint trading mechanism

DR model

and CVaR. Finally

the results indicate that the model effectively reduces system carbon emissions and mitigates the peak-to-trough difference in load profiles through case analysis and demonstration. With the introduction of CVaR

decision-makers are required to balance the economic and security aspects of the system

thereby enabling them to select a more rational optimization scheduling strategy.

关键词

Keywords

references

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