Abstract
Electrification of the built environment is foreseen as a main driver for energy transition for more effective, electric renewable capacity firming. Direct and on-time use of electricity is the best way to integrate them, but the current energy demand of residential building stock is often mainly fuel-based. Switching from fuel to electric-driven heating systems could play a key role. Yet, it implies modifications in the building stock due to the change in the temperature of the supplied heat by new heat pumps compared to existing boilers and in power demand to the electricity meter. Conventional energy retrofitting scenarios are usually evaluated in terms of cost-effective energy saving, while the effects on the electrification and flexibility are neglected. In this paper, the improvement of the building envelope and the installations of electric-driven space heating and domestic hot water production systems is analyzed for 419 dwellings. The dwellings database was built by means of a survey among the students attending the Faculty of Architecture at Sapienza University of Rome. A set of key performance indicators were selected for energy and environmental performance. The changes in the energy flexibility led to the viable participation of all the dwellings to a demand response programme.
Highlights
Stagnation in energy efficiency improvements and up and down trends of carbon emissions call for ambitious targets
On the side of renewable energy, the European Commission set that the contribution of renewables in 2030 will cover 32% of final energy consumptions
By mid-century, this will change radically with the large-scale electrification of the energy system driven by the deployment of renewables and fully developed alternative fuel options [7]
Summary
Stagnation in energy efficiency improvements and up and down trends of carbon emissions call for ambitious targets. Large RES integration and control strategies are crucial for actual decarbonization at the national [8] as well as urban scale [9] It entails the deep testing and calibration of multi-energy flows modelling [10] to manage stochastic behavior of renewables. Buildings connected to the grid can be players by offering peak shaving or balancing services, and their value is weighted on the amount of flexible power for each single user It implies in building such a mechanism, the crucial role played by probabilistic modelling is beyond the design of the load profile for buildings [14]. Assessing the effects of energy retrofitting on flexibility is still missing and is investigated by the authors of the current paper by means of dedicated KPIs. Four indicators are built: (i) the energy consumption; (ii) renewable energy use; (iii) local carbon emissions; and (iv) flexible loads amount. Simulation scenarios provide the outcome of the new energy demand, its new proportion among fuel and electricity based, and the updated share between the aforementioned different flexible loads
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