The environmental sustainability of the global economic growth is one of the most important challenges of our times. The transition from a fossil-fuel based energy system towards one dominated by renewable energy sources has been recognized as the most effective solution to find a balance between the growth in energy demand and the necessity to reduce greenhouse gas emissions. However, to take full advantage from carbon free energy sources, a transition is required not only in the way energy is generated, but also in how it is consumed and managed. In particular, electrification of harder-to-abate sectors, namely building and transportation sectors, is expected to become the main cause of energy demand growth in the near future. Indeed, increasing the installation of electrical devices to cover buildings thermal load, as for example heat pumps and air conditioners, and spread of electric vehicles are the cornerstones actions of the energy policy of all the developed countries. In this foreseen context, dominated by volatile distributed generation and unexpected demand fluctuations due to electric vehicles charging, a transformation from a centralized to a decentralized energy management paradigm is needed to ensure high quality, reliable, resilient and cost-effective service provision. Moreover, electric grids should evolve and become smarter and more flexible to accommodate the bi-directional flows of energy and data and face sudden unbalances. Digitalization together with integration of distributed flexibility sources are expected to play a crucial role in the effective implementation of new intelligent energy management systems and in enabling demand response program at the end-user level. In this work, these aspects are analyzed to provide a comprehensive solution to the aforementioned issues. In particular, the focus is on the development of optimal deterministic design and control frameworks for local microgrid, where stationary and mobile energy storage devices, namely batteries, thermal energy storage and electric vehicles, as well as controllable loads and generators are installed to enhance the flexibility of system with renewables. Considering the mutual influence between sizing and control targets, mobile and stationary energy storage technologies are analyzed for different hybrid renewable energy system configurations. Moreover, a novel methodology to include uncertainties in a deterministic Model Predictive Control strategy is also shown. The results obtained show that the methodology proposed to optimally integrate stationary and mobile energy storage systems with programmable load for demand side management strategies allows both industrial and residential users to adapt their consumption profiles according to some predefined requirements. In this way, they may act as prosumers, i.e. providers of distributed energy storage within the grid, with techno-economic and environmental benefits both from the grid and their own point of view.

Enhancement of renewable energy penetration and grid reliability through optimal integration of stationary and mobile energy storage systems and distributed energy generation

SANTARELLI, MARINA
2021

Abstract

The environmental sustainability of the global economic growth is one of the most important challenges of our times. The transition from a fossil-fuel based energy system towards one dominated by renewable energy sources has been recognized as the most effective solution to find a balance between the growth in energy demand and the necessity to reduce greenhouse gas emissions. However, to take full advantage from carbon free energy sources, a transition is required not only in the way energy is generated, but also in how it is consumed and managed. In particular, electrification of harder-to-abate sectors, namely building and transportation sectors, is expected to become the main cause of energy demand growth in the near future. Indeed, increasing the installation of electrical devices to cover buildings thermal load, as for example heat pumps and air conditioners, and spread of electric vehicles are the cornerstones actions of the energy policy of all the developed countries. In this foreseen context, dominated by volatile distributed generation and unexpected demand fluctuations due to electric vehicles charging, a transformation from a centralized to a decentralized energy management paradigm is needed to ensure high quality, reliable, resilient and cost-effective service provision. Moreover, electric grids should evolve and become smarter and more flexible to accommodate the bi-directional flows of energy and data and face sudden unbalances. Digitalization together with integration of distributed flexibility sources are expected to play a crucial role in the effective implementation of new intelligent energy management systems and in enabling demand response program at the end-user level. In this work, these aspects are analyzed to provide a comprehensive solution to the aforementioned issues. In particular, the focus is on the development of optimal deterministic design and control frameworks for local microgrid, where stationary and mobile energy storage devices, namely batteries, thermal energy storage and electric vehicles, as well as controllable loads and generators are installed to enhance the flexibility of system with renewables. Considering the mutual influence between sizing and control targets, mobile and stationary energy storage technologies are analyzed for different hybrid renewable energy system configurations. Moreover, a novel methodology to include uncertainties in a deterministic Model Predictive Control strategy is also shown. The results obtained show that the methodology proposed to optimally integrate stationary and mobile energy storage systems with programmable load for demand side management strategies allows both industrial and residential users to adapt their consumption profiles according to some predefined requirements. In this way, they may act as prosumers, i.e. providers of distributed energy storage within the grid, with techno-economic and environmental benefits both from the grid and their own point of view.
2021
Inglese
MULONE, VINCENZO
BARTOLUCCI, LORENZO
Università degli Studi di Roma "Tor Vergata"
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/296444
Il codice NBN di questa tesi è URN:NBN:IT:UNIROMA2-296444