Titolo della tesi: Energy Transition Pathways of Urban Districts Towards Sustainable and Fully Electric Operations: A Techno-Economic Optimization Approach
Clean energy transition and mitigation of global warming are two of the most impressive social, technological and financial challenges that humanity has faced. Limiting and possibly stopping the global temperature rise is of uttermost importance to slow down and in the long term possibly reverse the negative effects of global warming. In this context, the energy sector is the one that contributes the most to $CO_2$ emissions and thus the one that requires the most important efforts to achieve carbon neutrality. The clean energy transition from fossil to renewable energy sources entails tremendous efforts and strong changes in society, and a formidable complex change in the technology that humans are using to produce, handle and store electricity and heat. Central production from thermal power plants and dispatch to users is rapidly shifting to local production from renewable energy sources. Small plants with fluctuations in production result in increasing problems with the interaction with the power grid and require time-dependent digital twins to forecast production and load, manage storage systems, dispatch and interaction with the power grids, entailing in the future also the possibility of managing and shifting the load according to the availability of Renewable Energy Sources (RESs). Developing digital twins is essential in this scenario, as they can help in the design, techno-economic optimization and management of complex energy systems.
In this dissertation, the development, validation and test of complex models for various distributed energy systems via in-house codes (pyRES), commercial software (TRNSYS) and open-source software (EnergyPlus), are discussed together with the implementation of multi-objective optimization algorithms and various strategies for design and power flow control. In addition to the energy supply systems, methods and frameworks were developed for estimating the energy consumption of urban districts.
These models were then applied to real scenarios and evaluated in different test cases. One test case is an urban district in Germany consisting of 240 buildings in which profiling and estimation of energy consumption are automated and analyzed. One of the central aspects of the clean energy transition is the fact that the proposed solutions need to comply with the local conditions, often struggling against complex legal requirements and social aspects. To this end, another district as a test case is used to evaluate the performance of distributed energy systems in the historical city center of Rome, Italy where local heritage preservation laws cause limitations in the flexibility of the energy system.
The optimal transition results show that the digitally developed and optimized energy system can reduce the purchased energy from the grid, primary energy consumption, $CO_2$ emissions and generation cost by 68.2\%, 55.7\%, 56.0\% and 48.9\% respectively. Further results highlight the feasibility of the decarbonization of the heating sector through electrification by employing heat pumps. The optimal quantity and size of heat pumps reveal the required energy system configuration to minimize the load and generation mismatches.