Electricity Price Forecasting for Nord Pool Data

Rita Beigaite, Tomas Krilavicius, Ka Lok Man

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

22 Citations (Scopus)

Abstract

In many countries deregulation of power markets was undertaken to create a more efficient market. As a result, electricity now can be purchased and sold across areas and countries more easily. For participants of electricity market it is beneficial to forecast future prices in order to optimize risks and profits as well as make future plans. A number of various methods is applied for solving this problem. However, the accuracy of forecasts is not sufficient as market spot price of electricity has features such as seasonality, spikes or high volatility. Furthermore, diverse approaches work differently with distinct countries (markets). In this paper we discuss our experiments with electricity spot price data of Lithuania's price zone in Nord Pool power market. Day-ahead forecasts are made using Seasonal Naïve, Exponential smoothing, Artificial Neural Networks.

Original languageEnglish
Title of host publication2018 International Conference on Platform Technology and Service, PlatCon 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647103
DOIs
Publication statusPublished - 25 Sept 2018
Event2018 International Conference on Platform Technology and Service, PlatCon 2018 - Jeju, Korea, Republic of
Duration: 29 Jan 201831 Jan 2018

Publication series

Name2018 International Conference on Platform Technology and Service, PlatCon 2018

Conference

Conference2018 International Conference on Platform Technology and Service, PlatCon 2018
Country/TerritoryKorea, Republic of
CityJeju
Period29/01/1831/01/18

Keywords

  • electricity spot price
  • forecasting

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