An adaptive longterm electricity price forecasting modelling using Monte Carlo simulation

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.