A Customer Baseline Measurement Method for Residential User of Demand Response
编号:292 访问权限:仅限参会人 更新:2021-12-03 10:57:52 浏览:514次 张贴报告

报告开始:2021年12月17日 14:30(Asia/Shanghai)

报告时间:5min

所在会场:[Z] Poster Session [Z6] Poster Session 6: AI-driven technology

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摘要
 One of the most important challenges for DR revenue is the calculation of customer baseline load. In this paper a novel CBL (Customer Baseline Load )  calculation method and it’s correction based on error evaluation is proposed theoretically and empirically. A dataset consisting of 2135 residential customers from China is utilized for the case study to test the performance of the algorithm in actual conditions using accuracy and bias metrics. The case study results show that load data is non-stationary, and the baseline method of grey theory can well adapt to this feature. The model proposed in this paper can effectively improve the accuracy of demand response load baseline measurement. The average error is decreased from 6.09% to 3.56%. At the same time, it can also provide data support for adjustable load to participate in market-oriented transactions.
 
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报告人
Feixiang gong
China Electric Power Research Institute

稿件作者
Feixiang gong China Electric Power Research Institute
Yuting Xu China Electric Power Research Institute
Songsong Chen China Electric Power Research Institute
Dezhi Li China Electric Power Research Institute
Shiming Tian China Electric Power Research Institute
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    2023

    08月18日

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  • 11月10日 2021

    初稿截稿日期

  • 12月10日 2021

    注册截止日期

  • 12月11日 2021

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主办单位
IEEE IAS
承办单位
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST
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