Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data
Load forecasting is critical for management and security of smart grid system. Traditional methods are usually on the basis of historical power consumption data, and the popularization of multi-meter integration technology makes analysis of integrated energy consumption data more efficient. Towards...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2021-10-01
|
| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103108 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850051686719029248 |
|---|---|
| author | Xingang WANG Binruo ZHU Zhen GU |
| author_facet | Xingang WANG Binruo ZHU Zhen GU |
| author_sort | Xingang WANG |
| collection | DOAJ |
| description | Load forecasting is critical for management and security of smart grid system. Traditional methods are usually on the basis of historical power consumption data, and the popularization of multi-meter integration technology makes analysis of integrated energy consumption data more efficient. Towards the issue of load forecasting, with water/power/gas consumption data collected by integrated smart meter as features, two mid-and-long term power consumption forecasting methods are proposed: gaussian process regression (GPR) and relevance vector regression (RVR). Experimental results show the superiority of the proposed method and the significance of integrated energy consumption data for load forecasting problem. |
| format | Article |
| id | doaj-art-d79a7c4abe1845f787c38759fa1d3d27 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2021-10-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-d79a7c4abe1845f787c38759fa1d3d272025-08-20T02:53:03ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492021-10-01541021121610.11930/j.issn.1004-9649.202103108wangxingangMid-and-Long Term Load Forecasting Based on Integrated Power Consumption DataXingang WANG0Binruo ZHU1Zhen GU2Electric Power Research Institute of State Grid Shanghai Electric Power Company, Shanghai 200051, ChinaElectric Power Research Institute of State Grid Shanghai Electric Power Company, Shanghai 200051, ChinaElectric Power Research Institute of State Grid Shanghai Electric Power Company, Shanghai 200051, ChinaLoad forecasting is critical for management and security of smart grid system. Traditional methods are usually on the basis of historical power consumption data, and the popularization of multi-meter integration technology makes analysis of integrated energy consumption data more efficient. Towards the issue of load forecasting, with water/power/gas consumption data collected by integrated smart meter as features, two mid-and-long term power consumption forecasting methods are proposed: gaussian process regression (GPR) and relevance vector regression (RVR). Experimental results show the superiority of the proposed method and the significance of integrated energy consumption data for load forecasting problem.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103108power consumption forecastingmulti-meter integrationprobabilistic modeltime series |
| spellingShingle | Xingang WANG Binruo ZHU Zhen GU Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data Zhongguo dianli power consumption forecasting multi-meter integration probabilistic model time series |
| title | Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data |
| title_full | Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data |
| title_fullStr | Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data |
| title_full_unstemmed | Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data |
| title_short | Mid-and-Long Term Load Forecasting Based on Integrated Power Consumption Data |
| title_sort | mid and long term load forecasting based on integrated power consumption data |
| topic | power consumption forecasting multi-meter integration probabilistic model time series |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103108 |
| work_keys_str_mv | AT xingangwang midandlongtermloadforecastingbasedonintegratedpowerconsumptiondata AT binruozhu midandlongtermloadforecastingbasedonintegratedpowerconsumptiondata AT zhengu midandlongtermloadforecastingbasedonintegratedpowerconsumptiondata |