Volatility in Electrical Load Forecasting for Long-term Horizon: An ARIMA-GARCH Approach

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Abstract

Electrical load forecasting in long-term horizon of power systems plays an important role for system planning and development. Load forecast in long-term horizon is represented as time-series. Thus, it is important to check the effect of volatility in the forecasted load time-series. In short, volatility in long-term horizon affects four main actions: risk management, long-term actions, reliability, and bets on future volatility. To check the effect of volatility in load series, this paper presents a univariate time series-based load forecasting technique for long-term horizon based on data corresponding to a U.S. independent system operator. The study employs ARIMA technique to forecast electrical load, and also the analyzes the ARCH and GARCH effects on the residual time-series.
Original languageEnglish
Title of host publication2016 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2016
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Print)978-1-5090-1970-0
DOIs
Publication statusPublished - 2016
EventPMAPS 2016: International Conference on Probabilistic Methods Applied to Power Systems - Beijing, China
Duration: 16 Oct 201620 Oct 2016

Conference

ConferencePMAPS 2016
CountryChina
CityBeijing
Period16/10/1620/10/16

Keywords

  • ARIMA
  • ARCH
  • GARCH
  • long-term load forecast
  • volatility

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