Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 51, Issue 12, Pages 2707-2714Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2010.06.006
Keywords
Orthogonal Experimental Design (OED); Locational Marginal Price; Probability Neural Network; Electricity price forecasting
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This paper proposes a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Probability Neural Network (PNN) and Orthogonal Experimental Design (OED), an Enhanced Probability Neural Network (EPNN) is proposed in the solving process. In this paper, the Locational Marginal Price (LMP), system load and temperature of PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday, and weekend. With the OED to smooth parameters in the EPNN, the forecasting error can be improved during the training process to promote the accuracy and reliability where even the spikes can be tracked closely. Simulation results show the effectiveness of the proposed EPNN to provide quality information in a price volatile environment. (C) 2010 Elsevier Ltd. All rights reserved.
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