Analysis of the impact of COVID-19 pandemics on the Italian industrial energy consumption

Energy system models for the analysis of future scenarios are mainly driven by the set of energy service demands which define the broad outlines of socio-economic development throughout the selected time horizon. Energy system optimization models serve as a valuable tool to of inquiry for relevant decision-making insights about the evolution of a Reference Energy System (RES) – a simplified representation of the complex and dynamic real-world interactions related to energy production and consumption – over medium-to-long-term time scales. Among such models, encompassing the four dimensions of Energy, Economy, Engineering and Environment – the so called “4Es” – those belonging to the TIMES framework represent a widespread choice for the exploration of contrasted future scenarios. In TIMES models, the proper modelling of energy service demands in all the final consumption sectors is one of the fundamental pillars to build credible scenarios, needed to generate a set of coherent set of demand growth rates. Indeed, once that drivers and elasticities are chosen and associated to the different energy service demands, TIMES can endogenously build demand curves for each energy service accounted for in the model. This thesis addresses the long-term effects of the Covid-19 pandemics on industrial production in Italy. Forecasts in 6 energy-intensive subsectors (Iron and Steel, Non-ferrous metals, Non-metallic minerals, Chemicals, Pulp and Paper, Other industries) are obtained through the application of Vector AutoRegressive models, to perform projections partly based on historical trends, without the need for external regressors. Results of the application of the method are computed in two cases, either considering or not the effects of the pandemics, showing a long-term reduction ranging from 3.5 ÷ 19.9 % in 2040, according to the subsector. A validation against the prescribed trends from the Italian Integrated National Energy and Climate Plan is also performed. As each industrial production trend acts itself as a driver in TIMES-Italia, the application to that model is presented to assess the impact on energy consumption forecasts. The results show how the long-term effects of the shock caused by the pandemics could lead, in the analyzed scenario, to a 10 % lower industrial energy consumption by 2040. This thesis addresses the long-term effects of the Covid-19 pandemics on industrial production in Italy. Forecasts in 6 energy-intensive subsectors (Iron and Steel, Non-ferrous metals, Non-metallic minerals, Chemicals, Pulp and Paper, Other industries) are obtained through the application of Vector AutoRegressive models, to perform projections partly based on historical trends, without the need for external regressors. Results of the application of the method are computed in two cases, either considering or not the effects of the pandemics, showing a long-term reduction ranging from 3.5 ÷ 19.9 % in 2040, according to the subsector. A validation against the prescribed trends from the Italian Integrated National Energy and Climate Plan is also performed. As each industrial production trend acts itself as a driver in TIMES-Italia, the application to that model is presented to assess the impact on energy consumption forecasts. The results show how the long-term effects of the shock caused by the pandemics could lead, in the analyzed scenario, to a 10 % lower industrial energy consumption by 2040.