Introduce an Optimal Pricing Strategy Using the Parameter of "Contingency Analysis" Neplan Software in the Power MarketCase Study (Azerbaijan Electricity Network)
Subject Areas : journal of Artificial Intelligence in Electrical Engineering
Keywords: Artificial Neural Networks, Power market, Contingency Analysis,
Abstract :
Overall price optimization strategy in the deregulated electricity market is one of the most important challenges for the participants, In this paper, we used Contingency Analysis Module of NEPLAN Software, a strategy of pricing to market participants is depicted.Each of power plants according to their size and share of the Contingency Analysis should be considered in the price of its hour. In the second stage, each of the power plants and cross-border supplier required forecasts on price and load request for determined hours, that can be used Artificial Neural networks. Thus, an efficient integrated model of optimized pricing for participants in the power market is extracted. The result of this study in the Azerbaijan power network for the special day and hour checked and has been provided.
[1] Chary, D. M., “Contingency Analysis in Power Systems, Transfer Capability Computation and Enhancement Using Facts Devices in Deregulated Power System.” Ph.D. diss., Jawaharlal Nehru Technological University, 2011
[2] Wood, A. J.; Wallenberg, B. F., “Power Generation, Operation and Control”. 2nd ed., New York/USA: John Wiley& Sons, 1996, pp. 410-432.
[3] Mohamed, S. E. G.; Mohamed, A. Y., and Abdelrahim, Y. H., “Power System Contingency Analysis to detect Network Weaknesses”, Zaytoonah University International Engineering Conference on Design and Innovation in Infrastructure, Amman, Jordan, pp. I3-4 Jun., 2012.
[4] Contreras, J.; Espinola, R.; Nogales, F.J.; Conejo, A.J., “ARIMA models to predict next-day electricity prices,” IEEE Trans. on Power Syst., Aug. 2003, Vol. 18, No. 3 , pp.1014 – 1020.
[5] Hippert, H. S.; Pedreira, C. E.; Souza, R. C., “Neural networks for shortterm load forecasting: A review and evaluation,” IEEE Trans. Power Syst. Feb.2001, Vol.16, pp.44-55.
[6] Ramsay, B.; Wang, A. J., “A neural networks based estimator for electricity spot-pricing with particular reference to weekend and public holidays,” 1998, Vol.23, pp.47-57.
[7] Szkuta, B. R.; Sanabria, L. A.; Dillon, T. S., “Electricity price short-term forecasting using artifical neural networks,” IEEE Trans. on Power Syst. , Aug.1999, Vol.14, pp.851-857.
[8] Detailed statistic's Iranian electricity industry, especially the transfer of power in 2011, the publisher's TAVANIR Holding Company, Department of Human Resources and Research, published in August 2012.