Version 1
: Received: 2 April 2024 / Approved: 2 April 2024 / Online: 2 April 2024 (13:06:32 CEST)
How to cite:
D’Amico, G.; Karagrigoriou, A.; Vigna, V. Forecasting the Power Generation Mix in Italy Based on Grey Markov Models. Preprints2024, 2024040194. https://doi.org/10.20944/preprints202404.0194.v1
D’Amico, G.; Karagrigoriou, A.; Vigna, V. Forecasting the Power Generation Mix in Italy Based on Grey Markov Models. Preprints 2024, 2024040194. https://doi.org/10.20944/preprints202404.0194.v1
D’Amico, G.; Karagrigoriou, A.; Vigna, V. Forecasting the Power Generation Mix in Italy Based on Grey Markov Models. Preprints2024, 2024040194. https://doi.org/10.20944/preprints202404.0194.v1
APA Style
D’Amico, G., Karagrigoriou, A., & Vigna, V. (2024). Forecasting the Power Generation Mix in Italy Based on Grey Markov Models. Preprints. https://doi.org/10.20944/preprints202404.0194.v1
Chicago/Turabian Style
D’Amico, G., Alex Karagrigoriou and Veronica Vigna. 2024 "Forecasting the Power Generation Mix in Italy Based on Grey Markov Models" Preprints. https://doi.org/10.20944/preprints202404.0194.v1
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
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
