
1.华北电力大学电气与电子工程学院,北京市 102206
2.国网河北省电力有限公司,河北省石家庄市 050000
Received:21 May 2025,
Revised:2025-09-14,
Online First:12 December 2025,
Published:25 September 2026
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莫鑫蓬,郑顺林,张旭东等.不完全信息下考虑锚定-棘轮效应的综合需求响应优化建模[J].电力系统自动化,2026,50(18):80-96.
MO Xinpeng,ZHENG Shunlin,ZHANG Xudong,et al.Optimization Modeling of Integrated Demand Response Considering Anchoring and Ratchet Effects Under Incomplete Information[J].Automation of Electric Power Systems,2026,50(18):80-96.
莫鑫蓬,郑顺林,张旭东等.不完全信息下考虑锚定-棘轮效应的综合需求响应优化建模[J].电力系统自动化,2026,50(18):80-96. DOI: 10.7500/AEPS20250521009.
MO Xinpeng,ZHENG Shunlin,ZHANG Xudong,et al.Optimization Modeling of Integrated Demand Response Considering Anchoring and Ratchet Effects Under Incomplete Information[J].Automation of Electric Power Systems,2026,50(18):80-96. DOI: 10.7500/AEPS20250521009.
综合需求响应(IDR)是新型电力系统背景下实现供需平衡的有效手段。为提高IDR用户响应模型的准确性
以便综合能源系统服务商(IESP)制定更为经济有效的激励策略,文中考虑了用户锚定效应和棘轮效应对其响应行为的影响。首先,建立锚定效应矩阵以实现用户锚定效应的有效建模。然后,通过在传统用户模型中引入棘轮系数实现了用户棘轮效应的有效建模。同时,建立了考虑不完全信息的IESP优化模型。该模型基于极大似然理论和牛顿迭代原理,解决了因用户棘轮系数不可观测所带来的不完全信息。所提模型被建立为一个以用户、IESP为主体的双层优化问题,并被转化为一个单层优化问题进行求解。仿真结果表明,所提模型能够提高用户参与IDR的效益、减少IESP成本以及降低电网功率不平衡风险,不仅能有效表征用户的锚定效应和棘轮效应,还能够处理用户侧的不完全信息。
Integrated demand response (IDR) serves as an effective means to achieve the supply-demand balance in the context of the new power system. To improve the accuracy of user response models for IDR and enable integrated energy system providers (IESPs) to formulate more economical and efficient incentive strategies
this paper incorporates the influences of users’ anchoring effect and ratchet effect on their response behaviors. First
an anchoring effect matrix is established to effectively model the user anchoring effect. Then
ratchet coefficients are introduced into the conventional user response model to characterize the ratchet effect. Meanwhile
an IESP optimization model considering incomplete information is constructed. Based on the maximum likelihood theory and the Newton iteration principle
the proposed model addresses the incomplete information problem caused by the unobservability of user ratchet coefficients. The proposed model is established as a bi-level optimization problem with users and IESPs as the two decision-making subjects
which is further transformed into a single-level optimization problem for solution. Simulation results demonstrate that the proposed model can improve the benefits of users participating in IDR
cut down the operational cost of IESPs
and mitigate the power imbalance risk of the power grid. It can not only effectively characterize users’ anchoring and ratchet effects but also efficiently handle the incomplete information on the user side.
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