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...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2021-10-01
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| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103108 |
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| Summary: | 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. |
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| ISSN: | 1004-9649 |