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Long-term electricity demand forecasting via ordinal regression analysis: the case of Greece

Angelopoulos Dimitrios, Psarras John E., Siskos, Yannis

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URIhttp://purl.tuc.gr/dl/dias/93214083-0753-4F34-B7C0-C12322305B6A-
Identifierhttps://ieeexplore.ieee.org/document/7981153/-
Identifierhttps://doi.org/10.1109/PTC.2017.7981153-
Languageen-
TitleLong-term electricity demand forecasting via ordinal regression analysis: the case of Greeceen
CreatorAngelopoulos Dimitriosen
CreatorPsarras John E.en
CreatorSiskos, Yannisen
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryElectricity demand forecasting constitutes a critical process in the operation and planning procedures of power networks that highly affects the decisions of utility providers and energy policy makers. Accurate forecasting is vital in reducing costs, related to excess electricity storage and infrastructures, and achieving enhanced power security and stability. A novel modeling approach for long-term electricity demand forecasting is introduced via the application of ordinal regression analysis. Annual forecasts of the total net electricity demand in the Greek interconnected power system are provided for the years 2016-2025. The Gross Domestic Product (GDP) has been identified as the greatest influential parameter on the evolution of electricity demand. Furthermore, the forecasting model has achieved a minimum Mean Absolute Percentage Error (MAPE) of 2.14%. The extracted forecasts indicate a constant increase of the total net electricity demand in Greece as a result of the expected economic growth during the upcoming years. en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-04-25-
Date of Publication2017-
SubjectElectricity demand forecastingen
SubjectGreeceen
SubjectNon-linear optimizationen
SubjectOrdinal regressionen
Bibliographic CitationD. Angelopoulos, J. Psarras and Y. Siskos, "Long-term electricity demand forecasting via ordinal regression analysis: The case of Greece," in IEEE Manchester PowerTech, 2017. doi : 10.1109/PTC.2017.7981153en

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