A Multiarmed Bandit Incentive Mechanism for Crowdsourcing Demand Response in Smart Grids


  • Shweta Jain Indian Institute of Science, Bangalore
  • Balakrishnan Narayanaswamy University of California, San Diego
  • Y. Narahari Indian Institute of Science, Bangalore




Multiarmed Bandits, Mechanism Design, Smart Grids


Demand response is a critical part of renewable integration and energy cost reduction goals across the world. Motivated by the need to reduce costs arising from electricity shortage and renewable energy fluctuations, we propose a novel multiarmed bandit mechanism for demand response (MAB-MDR) which makes monetary offers to strategic consumers who have unknown response characteristics, to incetivize reduction in demand. Our work is inspired by a novel connection we make to crowdsourcing mechanisms. The proposed mechanism incorporates realistic features of the demand response problem including time varying and quadratic cost function. The mechanism marries auctions, that allow users to report their preferences, with online algorithms, that allow distribution companies to learn user-specific parameters. We show that MAB-MDR is dominant strategy incentive compatible, individually rational, and achieves sublinear regret. Such mechanisms can be effectively deployed in smart grids using new information and control architecture innovations and lead to welcome savings in energy costs.




How to Cite

Jain, S., Narayanaswamy, B., & Narahari, Y. (2014). A Multiarmed Bandit Incentive Mechanism for Crowdsourcing Demand Response in Smart Grids. Proceedings of the AAAI Conference on Artificial Intelligence, 28(1). https://doi.org/10.1609/aaai.v28i1.8806



AAAI Technical Track: Game Theory and Economic Paradigms