A Non-intrusive Air Conditioning Load Accurate Perception System for Source-load-storage Coordination Optimization

GU Wei; XUE Honglin; DUAN Jing; WANG Di; ZHANG Jianliang; HUO Meiru; GAO Yinghao; LI Xiang

doi:10.19725/j.cnki.1007-2322.2023.0333

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A Non-intrusive Air Conditioning Load Accurate Perception System for Source-load-storage Coordination Optimization

更新时间：2025-12-11

- A Non-intrusive Air Conditioning Load Accurate Perception System for Source-load-storage Coordination Optimization
- Issue 6, Pages: 1153-1161(2025)
- 作者机构：
  
  1. 国网山西省电力公司信息通信分公司,山西省,太原市,030000
  2. 华北电力大学电气与电子工程学院，北京市昌平区,102206
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0333
  CLC：
- Published：2025
- 稿件说明：
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GU Wei, XUE Honglin, DUAN Jing, et al. A Non-intrusive Air Conditioning Load Accurate Perception System for Source-load-storage Coordination Optimization[J]. 2025, (6): 1153-1161.
DOI：

GU Wei, XUE Honglin, DUAN Jing, et al. A Non-intrusive Air Conditioning Load Accurate Perception System for Source-load-storage Coordination Optimization[J]. 2025, (6): 1153-1161. DOI： 10.19725/j.cnki.1007-2322.2023.0333.

摘要

推进源荷储互动并参与电力市场有利于各类资源的协调开发和配置。但需求侧可调资源的定量分析方式未考虑弹性负荷的随机性，由于空调负荷数量多且可控性强，研究面向源荷储协调优化的非侵入式空调负荷精准感知系统。首先针对全面感知需求侧负荷导致资源浪费的问题，基于小波变换分析空调负荷的暂态特性，实现类空调负荷的事件检测；然后基于特征工程对空调负荷稳态特性的一致性以及与其他负荷的差异性进行结构化表征，与随机森林进行结合构建空调负荷专用辨识模型。最后通过空调负荷调节潜力评估模型实时分析区域内空调的可调容量。利用公开数据集以及实际采集数据进行仿真分析，感知结果验证了系统的准确性和有效性。

Abstract

The promotion of the source-load-storage interaction and participation in the power market facilitates the coordinated development and allocation of various resources. However

the randomness of elastic load is not considered in the quantitative analysis of demand-side adjustable resources. Considering the abundant quantity and strong controllability of air conditioning loads

we investigate a non-intrusive air conditioning load accurate perception system for source-load-storage coordination optimization in this paper. Firstly

to address the issue of wasted computing power caused by full perception of demand-side loads

the event detection of air conditioning load is realized by wavelet transform through analyzing the transient characteristics of air conditioning load. Secondly

the consistency of steady-state characteristics of air conditioning loads and the difference of other loads are structurally expressed through feature engineering

enabling the construction of an exclusive identification model for air conditioning loads through a combination with random forests. Finally

the adjustable capacity of air conditioning in the area is analyzed in real-time through the potential assessment model for air conditioning load regulation. The system’s accuracy and effectiveness are verified through simulation using publicly datasets and actual collected data.

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references

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