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Forecasting the electricity market using neural network and gray wolf algorithm
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Mohamad Ferdosian   , Hamid Abdi * , Saied Kharati , Shahram Karimi |
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Abstract: (2563 Views) |
| The electricity market in the world today is scientifically recognized and it is becoming more competitive every day. In the meantime, the price forecasting tool helps market participants gain more profit. The purpose of the present study is to extend the neural network and optimize it by gray wolf algorithm to predict electricity market price. Since traditional and neural network models have always used probabilistic methods to increase prediction accuracy, this model has tried to ignore these by introducing a new method to require less time for prediction. One of the issues that always affects the prediction accuracy is the existence of critical and sudden cases in the system, which will be controlled in this research using efficient methods. The proposed model uses Nordic electricity market information, but it is obviously applicable to any other market. Finally, to illustrate the accuracy of this model, a comparison is made between it and one of the traditional methods. |
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| Keywords: Gray wolf algorithm, price prediction, neural network |
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Full-Text [PDF 2436 kb]
(957 Downloads)
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Type of Study: Research |
Subject:
Electrical Engineering
Received: 2019/10/20 | Accepted: 2019/09/21 | Published: 2020/10/2
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