摘要详情

ID / 提交时间

26 / 2021-09-28 23:47:45

标题

A Customer Baseline Measurement Method for Residential User of Demand Response

关键字

主题及专题

AI-driven technology > Intelligent Anomaly Detection, Fault Diagnosis and Prognostics

状态

全文录用

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

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.

重要日期

会议日期

07月11日

2023

至

08月18日

2023
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

报告提交截止日期

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