Game-Theoretic Market-Driven Smart Home Scheduling Considering Energy Balancing

• Published in: IEEE systems journal Vol. 11; no. 2; pp. 910 - 921
• Main Authors: Yang Liu, Shiyan Hu, Han Huang, Ranjan, Rajiv, Zomaya, Albert Y., Lizhe Wang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Communities; Customers; Dynamic pricing; Electric appliances; Electric utilities; Electricity; Electricity consumption; electricity market; energy balancing; Energy conservation; Energy consumption; Game theory; Games; Generators; Home appliances; Household appliances; Infrastructure; Markets; Pricing; Residential energy; Scheduling; Smart buildings; smart home scheduling; Smart homes; Utilities
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2015.2418032

In a smart community infrastructure that consists of multiple smart homes, smart controllers schedule various home appliances to balance energy consumption and reduce electricity bills of customers. In this paper, the impact of the smart home scheduling to the electricity market is analyzed with a new smart-home-aware bi-level market model. In this model, the customers schedule home appliances for bill reduction at the community level, whereas aggregators minimize the energy purchasing expense from utilities at the market level, both of which consider the smart home scheduling impacts. A game-theoretic algorithm is proposed to solve this formulation that handles the bidirectional influence between both levels. Comparing with the electricity market without smart home scheduling, our proposed infrastructure balances the energy load through reducing the peak-to-average ratio by up to 35.9%, whereas the average customer bill is reduced by up to 34.3%.