An adaptive longterm electricity price forecasting modelling using Monte Carlo simulation

• Autorzy: Poullikkas A.
• Języki publikacji: EN

Abstrakty

EN

Accurate electricity price forecasting is of great importance for risk-analysis and decision-making in the electricity market. However, due to the characteristics of randomness and non-linearity associated with the electricity price series, it is difficult to build a precise forecasting model. If the electricity market price can be predicted properly, the generation companies and the load service entities as the main market participating entities can reduce their risks and further maximize their outcomes. In this work, adaptive longterm electricity price forecasting modelling using Monte Carlo simulation is proposed. The applicability of the prediction performance of the method is demonstrated for the case of electricity and oil price prediction, for vaious forecasting periods. Oil price prediction is an external factor for electricity price forecasting and is becoming very important in power systems running on oil derivatives. The proposed method could be useful for long term studies, evaluating the risk for financing since good electricity price forecast feeds into developing cost effective risk management plans for the participating companies in the electricity market and thus will help attract appropriate financing.

Słowa kluczowe

EN

electricity markets; electricity price forecasting; oil price forecasting

PL

rynki energii elektrycznej; prognozowanie cen energii elektrycznej; prognozowanie cen ropy naftowej

• Wydawca: Institute of Heat Engineering, Warsaw University of Technology
• Czasopismo: Journal of Power Technologies
• Rocznik: 2018
• Tom: Vol. 98, nr 3
• Strony: 267--273
• Opis fizyczny: Bibliogr. 27 poz., tab., wykr.

Twórcy

autor

Poullikkas A.

• Cyprus Energy Regulatory Authority, P.O. Box 24936, 1305 Nicosia, Cyprus

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).