Phd in ENERGY AND ENVIRONMENT

Thesis title: Ottimizzazione energetica e riqualificazione architettonica, impiantistica nel social housing

The urgent need for a sustainable energy transition requires a strategic rethink of the building sector, which is responsible for about 40% of global energy consumption and a significant share of CO2 emissions. In this context, the Public Housing Sector (ERP) shows structural and energy vulnerabilities that require innovative and systemic interventions. The inadequacy of the building envelope and existing systems is a primary critical issue, negatively affecting both consumption and comfort. The aim of this study is to explore solutions for energy optimisation and retrofitting through the integration of advanced technologies. The analysis initially focuses on a case study applied to the Tor Bella Monaca district of Rome, with the aim of evaluating effective strategies for reducing consumption and emissions through the use of renewable energy sources and energy storage systems. The introduction of renewable energy communities and intelligent management strategies is a key element of the research, with the aim of guaranteeing a model that can be replicated at urban and regional level. The methodological approach is based on a combination of advanced energy modelling, multi-scenario simulations and the application of machine learning techniques to optimise consumption management. The first step is the construction of a digital representative building, developed through advanced statistical analysis and on-site surveys. The data collected includes architectural characteristics, thermal performance and existing equipment configuration. The digital representative building was developed based on a detailed analysis of the existing building stock in the Tor Bella Monaca district, identifying key parameters such as geometry, construction materials, thermal characteristics and average energy consumption. The modelling was carried out using advanced energy simulation software, allowing comparative evaluations between different intervention strategies. Six technological transformation scenarios were developed, including the integration of photovoltaic systems, heat pumps and thermal and electrical storage systems. The analysis uses Key Performance Indicators (KPIs) to quantify the consumption of non-renewable primary energy, the level of energy self-sufficiency and the reduction of CO2 emissions. In addition, the impact of climate change, energy demand management and possible optimisations in the operation of plant systems were considered to maximise overall efficiency. The integration of machine learning techniques allows the development of predictive models to forecast the future consumption of the analysed buildings based on historical data. Multi-scenario simulation allows the impact of each solution to be assessed, identifying the most effective configurations from an energy and economic point of view. The simulations highlight the key role of renewable technologies in reducing the environmental impact of ERP buildings. The implementation of thermal and electrical storage systems improves the flexibility of the energy system, reducing dependence on fossil fuels and ensuring greater stability of the local grid. Furthermore, the adoption of advanced control strategies based on artificial intelligence algorithms improves the management of energy production and consumption, increasing local self-consumption and reducing network losses. The economic analysis has shown that although the retrofit requires a significant initial investment, it guarantees a positive economic return in terms of reduced energy costs and increased asset value of the buildings. The creation of renewable energy communities under the ERP can lead to a 30-50% reduction in non-renewable primary energy consumption, making a significant contribution to decarbonisation targets. In addition, the integration of smart grid solutions and advanced monitoring systems will facilitate optimised management of energy resources and encourage greater end-user participation in the energy transition. Another key aspect of research is the optimisation of construction site processes to reduce environmental impact and improve energy efficiency during the construction and renovation phases. Sustainable resource management is a key factor, with particular emphasis on using certified and recycled materials, optimising transport and reducing material waste. At the same time, on-site energy efficiency can be improved through the use of low-consumption machinery, electrification of operations and the use of temporary facilities powered by renewable energy sources. It is also essential to continuously monitor the environmental footprint, using digital technologies and BIM to control energy consumption and waste production. The implementation of advanced site management strategies, combined with the use of innovative construction methods such as prefabrication and the use of advanced materials, allows for a significant reduction in the CO2 emissions associated with the construction process. These measures are essential to ensure a limited environmental impact and to align the construction sector with the sustainability objectives set at European level. Research shows that the introduction of renewable energy communities in the ERP sector can be an effective strategy for reducing energy inequalities and improving urban sustainability. The analysis suggests that a combined approach of technological interventions and smart management strategies can lead to a significant increase in energy efficiency, contributing to the achievement of the European Union's decarbonisation objectives. The results highlight the importance of a multidisciplinary approach to the design and management of energy retrofitting interventions. The combination of advanced modelling, artificial intelligence techniques and energy community management provides a replicable methodological framework for future applications in other high-density urban contexts. Furthermore, the interaction between incentive policies, regulatory frameworks and innovative technologies plays a crucial role in ensuring the scalability and economic sustainability of the proposed solutions. The research opens up new perspectives for the development of integrated energy optimisation strategies in social housing, laying the foundations for the adoption of data-based management models and the interoperability of local energy networks.