A Novel Demand Response Potential Assessment Method for Industrial Users

2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI:10.1109/ICCS56273.2022.9988549

Shaofeng Guan, Huidan Zhuo, Kuangli Yang

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引用次数: 2

Abstract

Power companies or load aggregators can reasonably call demand-side resources through accurate user demand response potential assessment, which can improve the effect of demand response implementation and reduce the load peak-to-valley difference of the power system. Therefore, based on Gaussian process regression, this paper proposes a demand response potential evaluation method for industrial users with large power consumption and strong load regularity. A feature extraction model of industrial user interruptible load based on time series decomposition algorithm, a demand response user willingness model and an industrial user demand response potential evaluation model based on Gaussian process regression are established. Finally, the actual demand response data of a local industrial user is compared with the proposed demand response potential evaluation method. The results show that the proposed method can more accurately evaluate the demand response potential of industrial users, and reasonably call the industrial user resources on the demand side for power companies or load aggregators.

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一种新的工业用户需求响应潜力评估方法

电力公司或负荷聚合商可以通过对用户需求响应潜力的准确评估，合理调用需求侧资源，提高需求响应实施效果，减小电力系统负荷峰谷差。因此，本文基于高斯过程回归，提出了一种用电大、负荷规律性强的工业用户需求响应潜力评价方法。建立了基于时间序列分解算法的工业用户可中断负荷特征提取模型、需求响应用户意愿模型和基于高斯过程回归的工业用户需求响应潜力评价模型。最后，将某本地工业用户的实际需求响应数据与所提出的需求响应潜力评价方法进行对比。结果表明，该方法能够更准确地评估工业用户的需求响应潜力，为电力公司或负荷聚合商合理调用需求侧的工业用户资源。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 IEEE 2nd International Conference on Computer Systems (ICCS)

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