دورية أكاديمية
Day-Ahead Nonparametric Probabilistic Forecasting of Photovoltaic Power Generation Based on the LSTM-QRA Ensemble Model
| العنوان: | Day-Ahead Nonparametric Probabilistic Forecasting of Photovoltaic Power Generation Based on the LSTM-QRA Ensemble Model |
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| المؤلفون: | Fei Mei, Jiaqi Gu, Jixiang Lu, Jinjun Lu, Jiatang Zhang, Yuhan Jiang, Tian Shi, Jianyong Zheng |
| المصدر: | IEEE Access, Vol 8, Pp 166138-166149 (2020) |
| بيانات النشر: | IEEE, 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Electrical engineering. Electronics. Nuclear engineering |
| مصطلحات موضوعية: | Probabilistic forecasting, photovoltaic output, quantile regression averaging (QRA), long short-term memory (LSTM), interval prediction, nonparametric forecasting, Electrical engineering. Electronics. Nuclear engineering, TK1-9971 |
| الوصف: | With the rapid growth of photovoltaic (PV) power in recent years, the stability of system operation, the performance of system contingency analysis as well as the power quality of the power grid are threatened by the inherent uncertainty and fluctuation of PV output. It is necessary to have the knowledge of PV output characteristics for reliable power system dispatching. Day-ahead PV power forecasting is an effective support for achieving optimal dispatching. Probabilistic forecasting can describe the uncertainty that is difficult to depict by deterministic forecasting, and the forecasting results are more comprehensive. An ensemble nonparametric probabilistic forecasting model of PV output is proposed based on the traditional deterministic forecasting method. Quantile regression averaging (QRA) is used to ensemble a group of independent long short-term memory (LSTM) deterministic forecasting models for obtaining the probabilistic forecasting of PV output. Real measured data are used to verify the effectiveness of this nonparametric probabilistic forecasting model. Additionally, in comparison with the benchmark methods, LSTM-QRA has higher prediction performance due to the better forecasting accuracy of independent deterministic forecasts. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2169-3536 61044741 |
| Relation: | https://ieeexplore.ieee.org/document/9186100/; https://doaj.org/toc/2169-3536 |
| DOI: | 10.1109/ACCESS.2020.3021581 |
| URL الوصول: | https://doaj.org/article/7d227e61044741988b27ffba27402908 |
| رقم الأكسشن: | edsdoj.7d227e61044741988b27ffba27402908 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 21693536 61044741 |
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| DOI: | 10.1109/ACCESS.2020.3021581 |