A Non-intrusive Appliances Load Monitoring Method Based on Hourly Smart Meter Data
文献类型：会议论文
| 作者 | Song CH(宋纯贺)1,3 ; Wang ZF(王忠锋)1,3; Liu, Shuji2; Xu, Libo2; Zhou, Dapeng2; Zeng P(曾鹏)1,3
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| 出版日期 | 2019 |
| 会议日期 | October 18-20, 2019 |
| 会议地点 | Changsha, China |
| 关键词 | Smart grid Non-intrusive appliances load monitoring Peak load |
| 页码 | 785-799 |
| 英文摘要 | Peak load management is very important for the electric power system. This paper analyzes the impact of residential swimming pool pumps (RSPPs) on the peak load. First, this paper analyzes the challenges of non-intrusive energy consumption estimation for SPPs. Second, a novel reference-based change-point (RCP) model is proposed for non-intrusive SPPs energy consumption estimation. The advantages of the proposed RCP model are that it does not require high sampling rate data or prior information of the appliance. We show that during pool season, under the assumption that the ratio of base loads (defined as the power consumption which is independent of the outdoor temperature) of houses with and with PPs remains the same during no-pool season and pool season, 6.3% of the total energy is consumed by PPs, while under the assumption that for houses with and without PPs, the ratio of base loads is equal to the ratio of the temperature-dependent power consumption during pool season, 9.08% of the total energy is consumed by PPs. Furthermore, we show that by shifting PPs activity period, under the first assumption, at least 1.27% of peak demand can be reduced, while under the second assumption, at least 4.53% of peak demand can be reduced. |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 9th International Conference on Computer Engineering and Networks, CENet2019
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| 会议录出版者 | Springer |
| 会议录出版地 | Berlin |
| 语种 | 英语 |
| ISSN号 | 2194-5357 |
| ISBN号 | 978-981-15-3752-3 |
| 源URL | [http://ir.sia.cn/handle/173321/27374]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 通讯作者 | Song CH(宋纯贺) |
| 作者单位 | 1.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Song CH,Wang ZF,Liu, Shuji,et al. A Non-intrusive Appliances Load Monitoring Method Based on Hourly Smart Meter Data[C]. 见:. Changsha, China. October 18-20, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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