Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory
The forecast for photovoltaic (PV) power generation is of great significance for the operation and control of power system. In this paper, a short-term combination forecasting model for PV power based on similar day and cross entropy theory is proposed. The main influencing factors of PV power are a...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2018/6973297 |
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| author | Qi Wang Shunxiang Ji Minqiang Hu Wei Li Fusuo Liu Ling Zhu |
| author_facet | Qi Wang Shunxiang Ji Minqiang Hu Wei Li Fusuo Liu Ling Zhu |
| author_sort | Qi Wang |
| collection | DOAJ |
| description | The forecast for photovoltaic (PV) power generation is of great significance for the operation and control of power system. In this paper, a short-term combination forecasting model for PV power based on similar day and cross entropy theory is proposed. The main influencing factors of PV power are analyzed. From the perspective of entropy theory, considering distance entropy and grey relation entropy, a comprehensive index is proposed to select similar days. Then, the least square support vector machine (LSSVM), autoregressive and moving average (ARMA), and back propagation (BP) neural network are used to forecast PV power, respectively. The weights of three single forecasting methods are dynamically set by the cross entropy algorithm and the short-term combination forecasting model for PV power is established. The results show that this method can effectively improve the prediction accuracy of PV power and is of great significance to real-time economical dispatch. |
| format | Article |
| id | doaj-art-9d397a97687b487997be3c2fdff98f01 |
| institution | OA Journals |
| issn | 1110-662X 1687-529X |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-9d397a97687b487997be3c2fdff98f012025-08-20T02:20:19ZengWileyInternational Journal of Photoenergy1110-662X1687-529X2018-01-01201810.1155/2018/69732976973297Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy TheoryQi Wang0Shunxiang Ji1Minqiang Hu2Wei Li3Fusuo Liu4Ling Zhu5School of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaSchool of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaSchool of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaState Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, ChinaState Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, ChinaState Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, ChinaThe forecast for photovoltaic (PV) power generation is of great significance for the operation and control of power system. In this paper, a short-term combination forecasting model for PV power based on similar day and cross entropy theory is proposed. The main influencing factors of PV power are analyzed. From the perspective of entropy theory, considering distance entropy and grey relation entropy, a comprehensive index is proposed to select similar days. Then, the least square support vector machine (LSSVM), autoregressive and moving average (ARMA), and back propagation (BP) neural network are used to forecast PV power, respectively. The weights of three single forecasting methods are dynamically set by the cross entropy algorithm and the short-term combination forecasting model for PV power is established. The results show that this method can effectively improve the prediction accuracy of PV power and is of great significance to real-time economical dispatch.http://dx.doi.org/10.1155/2018/6973297 |
| spellingShingle | Qi Wang Shunxiang Ji Minqiang Hu Wei Li Fusuo Liu Ling Zhu Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory International Journal of Photoenergy |
| title | Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory |
| title_full | Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory |
| title_fullStr | Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory |
| title_full_unstemmed | Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory |
| title_short | Short-Term Photovoltaic Power Generation Combination Forecasting Method Based on Similar Day and Cross Entropy Theory |
| title_sort | short term photovoltaic power generation combination forecasting method based on similar day and cross entropy theory |
| url | http://dx.doi.org/10.1155/2018/6973297 |
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