Integration of a sustainability paradigm in energy system models

The awareness matured in recent years towards the necessity of climate change mitigation is leading to a change in priorities across all the sectors of the economy, especially in industrial production and power generation. The current paradigm in place for the solution of the problem is to abate greenhouse gases emissions. Nonetheless, from a social and economic perspective, a sharp transition could bring non-negligible issues in terms of energy reliability and affordability. In this context, the relevance of computer-aided techniques, such as energy system models, plays a crucial role. The goal behind energy system models is to provide a set of least-cost solutions for the development of the technology mix to achieve prescribed environmental targets, such as CO2 emission reduction. Several aspects, like environmental footprint, energy security and human health risks, are completely unaccounted for in the currently existing modelling frameworks. Each of those aspects requires the accounting of several dimensions that can fall inside the wide definition of sustainability. The aim of this thesis is dual. First of all, a metric for the evaluation of the overall sustainability level of an energy scenario is proposed. Given the trend towards an ever-higher electrification of energy end-uses, the work has been concentrated on the power sector. All the modelled technologies were characterized by a set of parameters regarding life cycle impacts and other energy issues-related indicators. Those parameters and their ability to represent the system sustainability are validated with several simulations coming from the TIMES bottom-up energy model generator, achieving higher scores for low carbon scenarios. The second goal of this work is to improve the traditional energy system modeling paradigm based on emission-constrained economic, shifting it from a mainly economic-oriented algorithm to a combined sustainability-economic optimization. The environment in which this procedure is applied is TEMOA: an open source, energy system optimization modeling framework. Inside TEMOA, the same sustainability metrics applied ex-post in the previous phase is endogenously integrated, accounting for that either as a model constraint or as a component of the final objective function. In this multi-objective optimization context, the user has the possibility to decide the level of priority of the two components, thanks to a weighted sum approach. The modified objective function is applied to a simplified version of the TEMOA-Italy model. Results show how it is possible to prioritize the sustainability evaluation of the scenarios limiting the economic expenditure, thanks to an optimized configuration of the energy mix