Smart Power Grid and Cloud Computing

Časopis: RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Volume, no: 24 , 1

ISSN: 1364-0321

Stranice: 566-577

Link: https://www.sciencedirect.com/science/article/abs/pii/S136403211300227X

Apstrakt:
As a consequence of rapidly increased CO2 emissions, humanity is facing global warming. Electricity generation accounts for almost half of the emission; besides, conventional electrical production based on fossil fuel is becoming more and more expensive. One approach to significantly slow down global warming is to drive our society away from the current fossil fuel fiesta and use only renewable power such as solar and wind energy. Another approach is to improve the management of energy production, transmission, and distribution. Part of the latter solution is on the supply side, where one possible solution is to develop continent-wide smart power grids and energy storage systems. However, an equally important part of the solution is on the demand side, where technologies and applications that can work with this type of unpredictable energy consumption are becoming necessary. The smart power grid with new sources of data, fast growth of information, and proactive management requires new strategy for business and operational management. In this paper we discuss how Cloud computing model can be used for developing Smart Grid solutions. The Cloud computing model is based on the delivery of computing as a service, whereby storage, software and information are provided to computers and other devices as a commodity over the Internet. The advantages of Cloud computing – reduced costs, increased storage, on-demand performance, and better flexibility – have motivated many companies in recent years to move their IT operations to the cloud; the same advantages can be used to achieve the most important future goals of a large-scale Smart Grid, such as energy savings, two-way communication, and demand resource management.
Ključne reči: Smart power grid, Information and communication technology, Cloud computing, Renewable energy sources, Energy efficiency