2. Smart Grid

All over the world, electrical power systems are encountering radical change stimulated by the urgent need to decarbonize electricity supply, to swap aging resources and to make effective application of swiftly evolving information and communication technologies (ICTs). All of these goals converge toward one direction; ‘Smart Grid.’ The Smart Grid can be described as the transparent, seamless, and instantaneous two-way delivery of energy information, enabling the electricity industry to better manage energy delivery and transmission and empowering consumers to have more control over energy decisions. Basically, the vision of Smart Grid is to provide much better visibility to lower-voltage networks as well as to permit the involvement of consumers in the function of the power system, mostly through smart meters and Smart Homes. A Smart Grid incorporates the features of advanced ICTs to convey real-time information and facilitate the almost instantaneous stability of supply and demand on the electrical grid. The operational data collected by Smart Grid and its sub-systems will allow system operators to quickly recognize the best line of attack to protect against attacks, susceptibility, and so on, sourced by a variety of incidents. However, Smart Grid initially depends upon knowing and researching key performance components and developing the proper education program to equip current and future workforce with the knowledge and skills for exploitation of this greatly advanced system. The aim of this chapter is to provide a basic discussion of the Smart Grid concept, evolution and components of Smart Grid, environmental impacts of Smart Grid and then in some detail, to describe the technologies that are required for its realization. Even though the Smart Grid concept is not yet fully defined, the chapter will be helpful in describing the key enabling technologies and thus allowing the reader to play a part in the debate over the future of the Smart Grid. The chapter concludes with the experimental description and results of developing a hybrid prediction method for solar power which is applicable to successfully implement the ‘Smart Grid.’