Integrated and dynamic energy modelling of a regional system: A cost-optimized approach in the deep decarbonisation of the Province of Trento (Italy). (15th October 2020) - Viesi, Diego; Crema, Luigi; Mahbub, Md Shahriar; Verones, Sara; Brunelli, Roberto; Baggio, Paolo; Fauri, Maurizio; Prada, Alessandro; Bello, Andrea; Nodari, Benedetta; Silvestri, Silvia; Tomasi, Luca
Abstract: Since the Kyoto Protocol (1997), the European Union has fought against climate change adopting European, national and regional policies to decarbonise the economy. Moreover, the Paris Agreement (2015) calls 2050 solutions between -80% and -100% of greenhouse gas emissions compared with 1990. Regions have an important role in curbing CO2 emissions, and tailor-made strategies considering local energy demands, savings potentials and renewables must be elaborated factoring in the social and economic context. An "optimized smart energy system" approach is proposed, considering: (I) integration of electricity, thermal and transport sectors, (II) hourly variability of productions and demands, (III) coupling the EnergyPLAN software, to develop integrated and dynamic scenarios, with a multi-objective evolutionary algorithm, to identify solutions optimized both in terms of CO2 emissions and costs, including decision variables for all the three energy sectors simultaneously. The methodology is tested at the regional scale for the Province of Trento (Italy) analyzing a total of 30, 000 scenarios. Compared to the Baseline 2016, it is identified: (I) the strategic role of sector coupling among large hydroelectric production and electrification of thermal and transport demands (heat pumps, electric mobility), (II) slight increases in total annual cost, +14% for a -90% of CO2 emissions in 2050. Highlights: Regions have an important role in curbing CO2 emissions. Integration of electricity, thermal and transport sectors is required. Variability of energy productions and demands need to be considered. Multi-objective evolutionary algorithms allow to identify optimized solutions. In the case study a deep decarbonisation is achieved maintaining an overall stable cost.