Light-Weight Stackelberg Game Theoretic Demand Response Scheme for Massive Smart Manufacturing Systems

As Internet-of-Things (IoT) technology emerges, smart manufacturing has recently attracted a large amount of attention. Smart manufacturing leads to smart energy management because of its significant operating expenditure savings. However, it is believed that centralized energy management of IoT devices will impose critically large overhead since massive numbers of IoT devices are expected to be deployed. Therefore, distributed energy management or demand response (DR) is deemed to be a better solution for emerging massive smart manufacturing systems. There have been a significant number of distributed DR algorithms, including Stackelberg game theoretic approaches. However, the Stackelberg game theoretic approaches require a large number of iterations to reach Nash equilibrium, which in turn necessitates communication overheads among IoT devices. This communication overhead causes a large amount of energy consumption as well as delay. In this paper, we propose a light-weight DR scheme based on the Stackelberg model without iterations for the massive smart manufacturing systems. The proposed scheme manages energy consumption based on a non-iterative Stackelberg model and historical real-time pricing. To the best of our knowledge, our approach is the first technique that considers communication overheads for the DR technique. The performance evaluation demonstrates that the proposed scheme shifts operations to avoid peak loads, and the electricity bill is significantly reduced, operations occur at preferred times, and communication energy consumption and delay are minimized.