A novel complex system approach for the determination of renewable energy sources impact on electricity infrastructures

The increasing environmental awareness, associated with the increasing demand and price of fossil fuels, is leading to the implementation of novel energy models based on renewable energy sources (RES) and sustainable mobility. However, the actual physical and economic models on which power system management rules are based on, are not able to properly manage the high amount of unwanted power fluctuations introduced by RES power generation. For such reason, major issues has been pointed out in term of energy security and access, inspiring changes in methods and paradigms associated to energy supply management. Moreover, the transaction towards an emission free mobility must be based on the interaction between RES generation and Electric Vehicles (EV) mobility, pointing out the need of a new approach able to combine mobility and energy supply infrastructures. In order to describe and model power systems with an high amount of RES generation, is important to indicate that such systems are made by a great number of microscopical interacting elements which behave in a stochastic way. For this reason, these systems can not easily be described in a deterministic way, but must be described by a statistical representation of the system observables. In this thesis, a novel approach based on statistical mechanics methods is presented, able to model the impact of such sources over the system. By using such approach, has been possible to evaluate the possible impact of such sources in terms of power system stability and sustainable mobility

Vehicle electrification: technologies, challenges and a global perspective for smart grids

Nowadays, due to economic and climate concerns, the private transportation sector is shifting for the vehicle electrification, mainly supported by electric and hybrid plug-in vehicles. For this new reality, new challenges about operation modes are emerging, demanding a cooperative and dynamic operation with the electrical power grid, guaranteeing a stable integration without omitting the power quality for the grid-side and for the vehicle-side. Besides the operation modes, new attractive and complementary technologies are offered by the vehicle electrification in the context of smart grids, which are valid for both on-board and off-board systems. In this perspective, this book chapter presents a global perspective and deals with challenges for the vehicle electrification, covering the key technologies toward a sustainable future. Among others, the flowing topics are covered: (1) Overview of power electronics structures for battery charging systems, including on-board and off-board systems; (2) State-of-the-art of communication technologies for application in the context of vehicular electrification, smart grids and smart homes; (3) Challenges and opportunities concerning wireless power transfer with bidirectional interface to the electrical grid; (4) Future perspectives about bidirectional power transfer between electric vehicles (vehicle-to-vehicle operation mode); (5) Unified technologies, allowing to combine functionalities of a bidirectional interface with the electrical grid and motor driver based on a single system; and (6) Smart grids and smart homes scenarios and accessible opportunities about operation modes.Fundação para a Ciência e Tecnologia (FCT

Integrated modelling framework for the analysis of demand side management strategies in urban energy systems

Influenced by environmental concerns and rapid urbanisation, cities are changing the way they historically have produced, distributed and consumed energy. In the next decades, cities will have to increasingly adapt their energy infrastructure if new low carbon and smart technologies are to be effectively integrated. In this context, advanced planning tools can become crucial to successfully design these future urban energy systems. However, it is not only important to analyse how urban energy infrastructure will look like in the future, but also how they will be operated. Advanced energy management strategies can increase the operational efficiency, therefore reducing energy consumption, CO2 emissions, operational costs and network investments. However, the design and analysis of these energy management strategies are difficult to perform at an urban scale considering the spatial and temporal resolution and the diversity in users energy requirements. This thesis proposes a novel integrated modelling framework to analyse flexible transport and heating energy demand and assess different demand-side management strategies in urban energy systems. With a combination of agent-based simulation and multi-objective optimisation models, this framework is tested using two case studies. The first one focuses on transport electrification and the integration of electric vehicles through smart charging strategies in an urban area in London, UK. The results of this analysis show that final consumer costs and carbon emissions reductions (compared to a base case) are in the range of 4.3-45.0% and 2.8-3.9% respectively in a daily basis, depending on the type of tariff and electricity generation mix considered. These reductions consider a control strategy where the peak demand is constrained so the capacity of the system is not affected. In the second case study, focused on heat electrification, the coordination of a group of heat pumps is analysed, using different scheduling strategies. In this case, final consumer costs and carbon emissions can be reduced in the range of 4-41% and 0.02-0.7% respectively on a daily basis. In this case, peak demand can be reduced in the range of 51-62% with respect to the baseline. These case studies highlight the importance of the spatial and temporal characterisation of the energy demand, and the level of flexibility users can provide to the system when considering a heterogeneous set of users with different technologies, energy requirements and behaviours. In both studies, trade-offs between the environmental and economic performance of demand-side management strategies are assessed using a multi-objective optimisation approach. Finally, further applications of the integrated modelling framework are described to highlight its potential as a decision-making support tool in sustainable and smart urban energy systems.Open Acces