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Discrete Fourier Transform based approach to forecast monthly peak load

Beiraghi, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/APPEEC.2011.5748585
  3. Abstract:
  4. This paper presents a new method in order to predict the monthly electricity peak load of a country based on the prediction of Discrete Fourier Transform (DFT) of monthly peak electricity demand variation using the ARIMA methodology. For validation, the result of this method was used to predict monthly peak load variation of the recent two years in Iranian national grid. The primary goal of this article is to show the application and implementation of Discrete Fourier Transform to predict monthly variation of electricity peak load in national electric power systems. Furthermore, it is elaborated to demonstrate the benefits and shortcomings of DFT approach comparing to the commonly used methodologies known by time series approximation. Comparing the predicted and real value of monthly peak load in the recent years indicates a good and reliable prediction by the new applied methodology
  5. Keywords:
  6. ARIMA method ; Discrete Fourier Transform ; Load forecasting ; National Grid ; Peak electricity demand ; Peak load ; Real values ; Series approximations ; Discrete Fourier transforms ; Electric power systems ; Electricity ; Forecasting ; Time series ; Electric load forecasting
  7. Source: Asia-Pacific Power and Energy Engineering Conference, APPEEC ; 2011 ; 21574839 (ISSN) ; 9781424462551 (ISBN)
  8. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5748585