An emotional neural network based approach for wind power prediction
Accurate wind power forecasting is vital for the integration of wind power into the grid. Emotional neural network (ENN)——a new type of neural network which could be used to model complex systems and patterns, was used to forecast wind power. To prevent ENN from stucking in locally optimal solution...
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| Main Author: | |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2017-03-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017005/ |
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| Summary: | Accurate wind power forecasting is vital for the integration of wind power into the grid. Emotional neural network (ENN)——a new type of neural network which could be used to model complex systems and patterns, was used to forecast wind power. To prevent ENN from stucking in locally optimal solution in the process of training, genetic algorithm was proposed to train ENN. The root-mean-square and the standard deviation of the forecast errors were also adopted to measure the accuracy and reliability of the forecast to test the performance of ENN. The results demonstrate that, compared with artificial neural network, ENN can improve the accuracy and reliability of the forecast by 3.8% and 46% respectively. |
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| ISSN: | 1000-0801 |