An adaptive longterm electricity price forecasting modelling using Monte Carlo simulation

  • Andreas Poullikkas


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 tobuild a precise forecasting model. If the electricity market price can be predicted properly, the generation companies and theload service entities as the main market participating entities can reduce their risks and further maximize their outcomes. Inthis work, adaptive longterm electricity price forecasting modelling using Monte Carlo simulation is proposed. The applicabilityof the prediction performance of the method is demonstrated for the case of electricity and oil price prediction, for vaiousforecasting periods. Oil price prediction is an external factor for electricity price forecasting and is becoming very important inpower systems running on oil derivatives. The proposed method could be useful for long term studies, evaluating the risk forfinancing since good electricity price forecast feeds into developing cost effective risk management plans for the participatingcompanies in the electricity market and thus will help attract appropriate financing.

Author Biography

Andreas Poullikkas


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How to Cite
POULLIKKAS, Andreas. An adaptive longterm electricity price forecasting modelling using Monte Carlo simulation. Journal of Power Technologies, [S.l.], v. 98, n. 3, p. 267–273, nov. 2018. ISSN 2083-4195. Available at: <>. Date accessed: 13 apr. 2024.
Policy, Economy and Society


electricity markets; electricity price forecasting; oil price forecasting

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