A cloud computing framework on demand side management game in smart energy hubs. (January 2015)

• Record Type: Journal Article
• Authors: Sheikhi, Aras; Rayati, Mohammad; Bahrami, Shahab; Ranjbar, Ali Mohammad; Sattari, Sourena
• Is Part Of: International journal of electrical power & energy systems. Volume 64(2015:Jan.)
• Page Start: 1007
• Page End: 1016
• Publication Date: 2015-01
• Subjects: Cloud computing (CC) -- Demand side management (DSM) -- Game theory -- Smart Energy Hub (S.E. Hub) -- Smart grid (SG); Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2014.08.020
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Here, users with strict energy consumption scheduling can actively participate in DSM. A proposed game among S.E. Hubs results optimum energy consumption strategy. The strategies reduce individual energy cost and peak to average ratio. Cloud computing infrastructure is suggested in smart grid. Abstract: The presence of energy hubs in the future vision of energy networks creates an opportunity for electrical engineers to move toward more efficient energy systems. At the same time, it is envisioned that smart grid can cover the natural gas network in the near future. This paper modifies the classic Energy Hub model to present an upgraded model in the smart environment entitling "Smart Energy Hub". Supporting real time, two-way communication between utility companies and smart energy hubs, and allowing intelligent infrastructures at both ends to manage power consumption necessitates large-scale real-time computing capabilities to handle the communication and the storage of huge transferable data. To manage communications to large numbers of endpoints in a secure, scalable and highly-available environment, in this paper we provide a cloud computing framework for a group of smart energy hubs. Then, we use game theory to model the demand side management among the smart energy hubs. Simulation results confirm that at the Nash equilibrium, peak to average ratio of the total electricity demand reduces significantly and at the same time the hubs will pay less considerably for their energy bill.