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A Stackelberg game-theoretic approach to optimal real-time pricing for the smart grid

Meng, Fan-Lin and Zeng, Xiao-Jun (2013) 'A Stackelberg game-theoretic approach to optimal real-time pricing for the smart grid.' Soft Computing, 17 (12). pp. 2365-2380. ISSN 1432-7643

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This paper proposes a Stackelberg game approach to maximize the profit of the electricity retailer (utility company) and minimize the payment bills of its customers. The electricity retailer determines the retail price through the proposed smart energy pricing scheme to optimally adjust the real-time pricing with the aim to maximize its profit. The price information is sent to the customers through a smart meter. According to the announced price, the customers can automatically manage the energy use of appliances in the households by the proposed optimal electricity consumption scheduling system with the aim to minimize their electricity bills. We model the interactions between the retailer and its electricity customers as a 1-leader, N-follower Stackelberg game. At the leader’s side, i.e., for the retailer, we adopt genetic algorithms to maximize its profit while at the followers’ side, i.e., for customers, we develop an analytical solution to the linear programming problem to minimize their bills. Simulation results show that the proposed approach is beneficial for both the customers and the retailer.

Item Type: Article
Uncontrolled Keywords: Stackelberg game; Real-time pricing; Energy consumption scheduling; Genetic algorithms; Smart grid
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 08 Jul 2021 15:21
Last Modified: 23 Sep 2022 19:31

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