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Hydraulic plant generation forecasting in Colombian power market using ANFIS

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  • Moreno, Julián

Abstract

In this paper an ANFIS model is proposed to forecast the monthly ideal generation of an agent with a hydraulic plant within the Colombian power market. The proposed model considers several factors as the plant's reservoir level, the expected hydraulic contributions of the rivers which feed it, and the expected weather conditions represented by the SST anomaly forecast in Nio 3.4 zone. The fitness of such model is measured with real data of a particular agent from period 2002-2007 and it is compared against a multiple linear regression model. The obtained results show a considerable decrease of the mean percentage error, which is an evidence of its validity and possible application to other agents.

Suggested Citation

  • Moreno, Julián, 2009. "Hydraulic plant generation forecasting in Colombian power market using ANFIS," Energy Economics, Elsevier, vol. 31(3), pages 450-455, May.
    • Handle: RePEc:eee:eneeco:v:31:y:2009:i:3:p:450-455
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    Cited by:

    1. Monteiro, Claudio & Ramirez-Rosado, Ignacio J. & Fernandez-Jimenez, L. Alfredo, 2013. "Short-term forecasting model for electric power production of small-hydro power plants," Renewable Energy, Elsevier, vol. 50(C), pages 387-394.
    2. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    3. Lihki Rubio & Keyla Alba, 2022. "Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model," Mathematics, MDPI, vol. 10(13), pages 1-21, June.
    4. Claudia Condemi & Loretta Mastroeni & Pierluigi Vellucci, 2021. "The impact of Clean Spark Spread expectations on storage hydropower generation," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1111-1146, December.

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