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Application of generalized neuron in electricity price forecasting

Mirzazad Barijough, S ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/PTC.2009.5282220
  3. Abstract:
  4. With recent deregulation in electricity industry, price forecasting has become the basis for this competitive market. The precision of this forecasting is essential in bidding strategies. So far, the artificial neural networks which can find an accurate relation between the historical data and the price have been used for this purpose. One major problem is that, they usually need a large number of training data and neurons either for complex function approximation and data fitting or classification and pattern recognition. As a result, the network topology has a significant impact on the network computational time and ability to learn and also to generate unseen data from training data. To overcome these problems, a new structure using generalized neurons (GN) is adapted in this paper. The proposed structure needs a smaller data set for training. So this property of GN can be very useful for price forecasting. The data such as historical prices are not available enough for most markets. The significance, viability and efficiency of the proposed approach, in electricity price forecasting, are shown using Ontario market data points and various GN models are compared. © 2009 IEEE
  5. Keywords:
  6. Back-propagation ; Generalized neuron ; Price forecasting ; Artificial Neural Network ; Bidding strategy ; Competitive markets ; Complex functions ; Computational time ; Data fittings ; Data sets ; Electricity industry ; Electricity price forecasting ; Historical data ; Market data ; Network topology ; New structures ; Ontario ; Significant impacts ; Training data ; Commerce ; Costs ; Deregulation ; Electric network topology ; Neural networks ; Neurons ; Pattern recognition ; Electric load forecasting
  7. Source: 2009 IEEE Bucharest PowerTech: Innovative Ideas Toward the Electrical Grid of the Future, 28 June 2009 through 2 July 2009, Bucharest ; 2009 ; 9781424422357 (ISBN)
  8. URL: http://ieeexplore.ieee.org/document/5282220/?reload=true