Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Forecasting the Power Generation Mix in Italy Based on Grey Markov Models

Version 1 : Received: 2 April 2024 / Approved: 2 April 2024 / Online: 2 April 2024 (13:06:32 CEST)

A peer-reviewed article of this Preprint also exists.

D’Amico, G.; Karagrigoriou, A.; Vigna, V. Forecasting the Power Generation Mix in Italy Based on Grey Markov Models. Energies 2024, 17, 2184. D’Amico, G.; Karagrigoriou, A.; Vigna, V. Forecasting the Power Generation Mix in Italy Based on Grey Markov Models. Energies 2024, 17, 2184.

Abstract

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which provides powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.

Keywords

Markov Chain; Grey Model; Energy Mix; Electricity

Subject

Computer Science and Mathematics, Applied Mathematics

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