A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis
A short-term load forecasting method based on load characteristics clustering and elastic net analysis is proposed in this paper. By analyzing and clustering the historical load characteristics, the annual days are classified and its clusters are specified, and the lack of pertinence of the types of...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2020-09-01
|
| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201905111 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850227396874076160 |
|---|---|
| author | Bingjie JIN Yong LIN Shuxin LUO Bin WEI Shucan ZHOU |
| author_facet | Bingjie JIN Yong LIN Shuxin LUO Bin WEI Shucan ZHOU |
| author_sort | Bingjie JIN |
| collection | DOAJ |
| description | A short-term load forecasting method based on load characteristics clustering and elastic net analysis is proposed in this paper. By analyzing and clustering the historical load characteristics, the annual days are classified and its clusters are specified, and the lack of pertinence of the types of the day cluster selection is avoided. At the same time, Elastic net analysis is adopted to identify and select the dominant factors for short-term load forecasting. Furthermore, the neural network forecasting model is established on the basis of input variable optimization. Taking the actual load of a city in Guangdong province as an example, the effectiveness of the proposed method in improving the daily load curve forecasting accuracy is verified by comparing with other methods. Results show that the model established is long-term effective, dispensing with repeated training, which is applicable for short-term load forecasting. |
| format | Article |
| id | doaj-art-fd22a2a57c5d486ea9ac259e6d04df2a |
| institution | OA Journals |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2020-09-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-fd22a2a57c5d486ea9ac259e6d04df2a2025-08-20T02:04:51ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492020-09-0153922122810.11930/j.issn.1004-9649.201905111zgdl-53-4-jinbingjieA Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net AnalysisBingjie JIN0Yong LIN1Shuxin LUO2Bin WEI3Shucan ZHOU4Power Grid Planning Center of Guangdong Power Grid Company, Guangzhou 510080, ChinaPower Grid Planning Center of Guangdong Power Grid Company, Guangzhou 510080, ChinaPower Grid Planning Center of Guangdong Power Grid Company, Guangzhou 510080, ChinaPower Grid Planning Center of Guangdong Power Grid Company, Guangzhou 510080, ChinaPower Grid Planning Center of Guangdong Power Grid Company, Guangzhou 510080, ChinaA short-term load forecasting method based on load characteristics clustering and elastic net analysis is proposed in this paper. By analyzing and clustering the historical load characteristics, the annual days are classified and its clusters are specified, and the lack of pertinence of the types of the day cluster selection is avoided. At the same time, Elastic net analysis is adopted to identify and select the dominant factors for short-term load forecasting. Furthermore, the neural network forecasting model is established on the basis of input variable optimization. Taking the actual load of a city in Guangdong province as an example, the effectiveness of the proposed method in improving the daily load curve forecasting accuracy is verified by comparing with other methods. Results show that the model established is long-term effective, dispensing with repeated training, which is applicable for short-term load forecasting.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201905111load characteristicsclusteringelastic netneural networkload forecasting |
| spellingShingle | Bingjie JIN Yong LIN Shuxin LUO Bin WEI Shucan ZHOU A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis Zhongguo dianli load characteristics clustering elastic net neural network load forecasting |
| title | A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis |
| title_full | A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis |
| title_fullStr | A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis |
| title_full_unstemmed | A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis |
| title_short | A Short-Term Load Forecasting Method Based on Load Curve Clustering and Elastic Net Analysis |
| title_sort | short term load forecasting method based on load curve clustering and elastic net analysis |
| topic | load characteristics clustering elastic net neural network load forecasting |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201905111 |
| work_keys_str_mv | AT bingjiejin ashorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT yonglin ashorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT shuxinluo ashorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT binwei ashorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT shucanzhou ashorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT bingjiejin shorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT yonglin shorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT shuxinluo shorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT binwei shorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis AT shucanzhou shorttermloadforecastingmethodbasedonloadcurveclusteringandelasticnetanalysis |