This book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids.
From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response).
In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility.
This book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids.
From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response).
In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility.
