VECTORS

In the future, the way the power grid is currently managed will have to change radically. Indeed, pressing environmental problems and the path towards a sustainable economy will see the increasing use of renewable sources, cogeneration plants and smart loads, able to learn from the user habits and adapt to their needs. Current management and control strategies are already showing limitations in guaranteeing a constant high-quality of service (QoS) and maintaining stability. This hinders the potential of renewable resources and the energy management possibilities offered by new plants and smart devices. Also, significant shares of renewable sources cannot be further integrated in the grids with the current management strategies, as these types of sources cause severe instability problems due to their unreliability/uncontrollability. Advanced technological improvements are urgently needed to increase the renewable share and consequently boost the whole associated green economy. The overarching goal of this project is the development of new distributed control strategies capable of coping with these new challenging scenarios and tame the collective behavior of power grids via the joint action of distributed low- and high-level cooperative control techniques, preventing grid failures and faults, and promoting the development of a truly green economy. In this project, the power grid will be viewed as a complex evolving multi-agent system composed of a large number of different types of generators, loads and transmission lines. Despite uncertainties, fluctuations and disturbances, the grid must maintain a desired operating regime guaranteeing the required QoS to the final users, which must be very high in terms of voltage and frequency precision. While previous approaches have mostly focused on high-voltage grids, we will primarily focus on low-voltage microgrids. Namely, we will develop new models able to capture their complex dynamics including their interconnections with the distribution grid. We will then synthesize a cyberlayer of low and high level controllers capable of communicating and cooperating among each other. Such an architecture will be used to deploy automatic interventions for stabilization, renewable sources and advanced energy storage integration, and for preventing (or minimizing the impact of) possible anomalies or failures. The aim is to enhance the grid resilience to time-varying operating conditions due to dynamic loads and renewable generators. The grand challenge of the project will be achieved through the cooperation of a multidisciplinary consortium of 6 research units [Naples (NA), Padova (PD), Catania (CT), Pisa (PI), Benevento (BN), Torino (TO)] with complementary expertise and know-how on nonlinear control and the control of network systems, estimation and identification, power systems, modelling and network science. The workprogramme will be organized into 6 workpackages (WP). WP0 will deal with the project management and WP5 with the dissemination of the results. The remaining four WPs (from 1 to 4) will be devoted to the development of the proposed research activities. The set of algorithms we plan to develop will represent the backbone to foster and sustain the shift towards green energy, providing advancement in real-time control and management methods and a relevant progress in the rapidly evolving field of smart grids and microgrids.The project’s outcome will have an impact on both the scientific community studying distributed control approaches and the power system community. Also, it will be useful to Public Authorities and energy service companies to satisfy grid-stressing demand/response requests in real-time while guaranteeing safety at much lower costs. From the Society viewpoint, the project will ensure the improvement of the grid resiliency, the reduction of the environmental burden and reduction in CO2 emission together with lower energy consumer prices.Techniques and methods will be developed for multilayered network control, faults/failures prevention and mitigation, smart IoT loads and advanced storage modeling, and price-induced customers' behavioral characterization. The bridge between theory and practice will be at the core of the project that will use an experimental microgrid prototype in Pisa and advanced numerical simulation for validation and to drive interest from practitioners and industrialists alike. Well beyond the grid control problem, the project's scientific contribution will be general enough for the whole network science and control theoretic community and will enhance significantly the current state-of-the-art for analysis and control of complex networks such as transportation/logistic networks, and future cyber-physical agent coordination in smart cities.