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首页 > 过刊浏览>2023年第46卷第11期 >56-68. DOI:10.11835/j.issn.1000.582X.2023.11.006
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一种基于差分隐私的峰谷分时电价激励方案
作者:
作者单位:

1.国网四川省电力公司电力科学研究院，成都 610072;2.重庆大学 大数据与软件学院，重庆 400030

作者简介:

庞博（1994—），男，硕士，主要从事隐私计算应用研究，（Email）pang-bo@outlook.com。

通讯作者:

胡春强, 男，博士，教授，（Email）chu@cqu.edu.cn。

中图分类号:

TP311

基金项目:

国网四川省电力公司科技项目（SGSCDK00LYJS2200130）。


An incentive scheme of peak-valley price based on differential privacy
Author:
Affiliation:

1.Electric Power Research Institute of State Grid Sichuan Electric Power Company, Chengdu 610072, P. R. China;2.School of Big Data & Software Engineering, Chongqing University, Chongqing 400030, P. R. China

Fund Project:

Supported by State Grid Sichuan Power Company Science and Technology Project (SGSCDK00LYJS2200130).

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    摘要:

    针对智能电网系统峰值负荷差值过大、电力供给短缺等问题，提出了基于差分隐私的峰谷分时电价激励方案。方案将差分隐私和峰谷分时电价模型进行结合，在保证用户数据隐私的前提下对峰谷分时电价的定价策略进行优化。通过施行差异化的电价策略对用户的用电行为进行引导，激励用户形成错峰用电习惯，进而实现电力系统整体用电负荷的均衡。最后，通过实验对引入差分隐私后的数据效用进行分析，并对所提机制的运行效果进行评估。实验表明，本方案在实现电网整体用电负荷削峰填谷的同时对用户的数据隐私进行了保护。

    Abstract:

    To solve the problems of significant peak load variations and power supply shortages within smart grid systems, this paper proposes an incentive scheme for peak and off-peak time-of-use (TOU) pricing based on differential privacy. The scheme integrates differential privacy with the peak-valley TOU model, optimizing pricing strategies while safeguarding user data privacy. Differentiated pricing schemes are implemented to influence users’ behavior of electricity consumption, encouraging off-peak consumption habits and achieving a balanced power load across the system. Experimental analysis assesses the data utility following the introduction of differential privacy, evaluating the operation effectiveness of the proposed mechanism. Results show that this scheme successfully achieves load balancing throughout the whole power network while protecting user data privacy.

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庞博,张凌浩,滕予非,常政威,唐超,胡春强,刘泽伟,王宝琳.一种基于差分隐私的峰谷分时电价激励方案[J].重庆大学学报,2023,46(11):56-68.

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  • 收稿日期:2023-07-31
  • 在线发布日期: 2023-11-28
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