{"type":"ScholarlyArticle","title":"Aggregate Demand-Based Real-Time Pricing Mechanism for the Smart Grid: A Game-Theoretic Analysis","authors":[{"name":"Sambaran Bandyopadhyay","slug":"sambaran-bandyopadhyay","given":"Sambaran","family":"Bandyopadhyay","affiliation":""},{"name":"Ramasuri Narayanam","slug":"ramasuri-narayanam","given":"Ramasuri","family":"Narayanam","affiliation":""},{"name":"Ramachandra Kota","slug":"ramachandra-kota","given":"Ramachandra","family":"Kota","affiliation":""},{"name":"Pg Mohammad Iskandarbin Pg Hj Petra","slug":"pg-mohammad-iskandarbin-pg-hj-petra","given":"Pg Mohammad Iskandarbin Pg Hj","family":"Petra","affiliation":""},{"name":"Zainul Charbiwala","slug":"zainul-charbiwala","given":"Zainul","family":"Charbiwala","affiliation":""}],"abstract":"Managing peak energy demand is a critical problem for energy utilities. The energy costs for the peak periods form a major component of their overall costs. Real-time pricing mechanisms have been explored as a means of flattening the demand curve and reducing the energy costs. In this paper, we examine a model of ex-post real-time pricing mechanism that can be used by the utilities for this purpose. In particular, we study a convex piecewise linear cost function that modulates the price of energy based on the aggregate demand of the utility. We provide a game-theoretic analysis of the mechanism by constructing a non-cooperative game among the consumers of a utility wherein the cost to each consumer is decided by the pricing mechanism. We formally characterize the Nash equilibrium and other properties for two settings: (i) consumers have full flexibility in shifting their demand, and (ii) consumers can shift only a fraction of their demand at any time to another time.","doi":null,"url":"https://ijcai.org/proceedings/2015/362","pdf":"https://ijcai.org/proceedings/2015/0362.pdf","markdown":"https://ijcai.org/proceedings/2015/362.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/362","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Special Track on Computational Sustainability","track":"Special Track on Computational Sustainability","number":362,"pages":{"first":2554,"last":2559},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}