 Consumer preference–enabled intelligent energy management for smart cities using game theoretic social tieShen Wang, Jun Wu and Yutao Zhang International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 4, 1550147718773235 Abstract: In smart cities, balanced energy usage is a classic scheduling target in decision-making of power systems. To handle multiple energy consumers, energy management is usually built based on game theory. Despite their effectiveness, they do not consider consumer preferences, which are however important in developing salient scheduling frameworks. For the first time, this work explores consumer preference–based social networking in computing-optimized schedules to facilitate the incorporation in energy management. We propose the consumer preference driven intelligent energy management technique for smart cities using game theoretic social tie. In our technique, social communities are constructed based on the preference of electricity usage. To support dynamic decisions in the consumer preference–induced game, community pricing strategy is adjusted during each time period through leveraging cooperative game theory. The simulation results demonstrate the effectiveness and efficiency of the proposed intelligent energy management technique. Keywords: Smart cities; energy management; consumer preference; social tie; game theory; demand response (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:4:p:1550147718773235 Access Statistics for this article More articles in International Journal of Distributed Sensor Networks |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.