Setpoint Tracking with Partially Observed Loads

Antoine Lesage-Landry, Joshua A. Taylor

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


We use online convex optimization for setpoint tracking with uncertain, flexible loads. We consider full feedback from the loads, bandit feedback, and two intermediate types of feedback, partial bandit where a subset of the loads are individually observed and the rest are observed in aggregate, and Bernoulli feedback where in each round the aggregator receives either full or bandit feedback according to a known probability. We give sublinear regret bounds in all cases. We numerically evaluate our algorithms on examples with thermostatically controlled loads and electric vehicles.

Original languageEnglish (US)
Article number8288694
Pages (from-to)5615-5627
Number of pages13
JournalIEEE Transactions on Power Systems
Issue number5
StatePublished - Sep 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


  • Demand response
  • electric vehicles
  • online convex optimization
  • thermostatically controlled loads


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