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25 April 2023 Demand response baseline load optimization based on process monitoring: the case of an enterprise in Xi'an
YuZhuo Zhang, JinFeng Wang, HaiFeng Zheng, Min Cao, YueLong Jia, Jie Ma, ZhengMou Ren, XiaoChen Sun
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Proceedings Volume 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022); 125981U (2023) https://doi.org/10.1117/12.2672991
Event: Eighth International Conference on Energy Materials and Electrical Engineering (ICMEE 2022), 2022, Guangzhou, China
Abstract
On the basis of fully considering the monitoring needs of the demand response process, combined with the basis of electric energy data acquisition and industrial load characteristics, this paper proposes a demand response baseline demand suitable for process monitoring, establishes an improved demand response baseline load model, and analyzes an example. Specifically, based on the analysis and comparison of the existing baseline load algorithms, a baseline load algorithm for process monitoring is proposed. The user load is clustered first, and then the matching day method is used to improve the accuracy of the baseline load algorithm. The results show that, the method established in this paper is very effective in fitting the baseline load of users with strong periodicity.
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YuZhuo Zhang, JinFeng Wang, HaiFeng Zheng, Min Cao, YueLong Jia, Jie Ma, ZhengMou Ren, and XiaoChen Sun "Demand response baseline load optimization based on process monitoring: the case of an enterprise in Xi'an", Proc. SPIE 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022), 125981U (25 April 2023); https://doi.org/10.1117/12.2672991
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KEYWORDS
Data processing
Binary data
Data modeling
Power grids
Data centers
Statistical analysis
Statistical methods
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