@inproceedings{34461,
  keywords = {Demand response, Distributed control, TCLs, Smart thermostats},
  author = {Bingqing Chen and Jonathan Francis and Marco Pritoni and Soummya Kar and Mario Berg{\'e}s},
  title = {COHORT: Coordination of Heterogeneous Thermostatically Controlled Loads for Demand Flexibility},
  abstract = {<p>Demand flexibility is increasingly important for power grids. Careful coordination of thermostatically controlled loads (TCLs) can modulate energy demand, decrease operating costs, and increase grid resiliency. We propose a novel distributed control framework for the Coordination Of HeterOgeneous Residential Thermostatically controlled loads (COHORT). COHORT is a practical, scalable, and versatile solution that coordinates a population of TCLs to jointly optimize a grid-level objective, while satisfying each TCL{\textquoteright}s end-use requirements and operational constraints. To achieve that, we decompose the grid-scale problem into subproblems and coordinate their solutions to find the global optimum using the alternating direction method of multipliers (ADMM). The TCLs{\textquoteright} local problems are distributed to and computed in parallel at each TCL, making COHORT highly scalable and privacy-preserving. While each TCL poses combinatorial and non-convex constraints, we characterize these constraints as a convex set through relaxation, thereby making COHORT computationally viable over long planning horizons. After coordination, each TCL is responsible for its own control and tracks the agreed-upon power trajectory with its preferred strategy. In this work, we translate continuous power back to discrete on/off actuation, using pulse width modulation. COHORT is generalizable to a wide range of grid objectives, which we demonstrate through three distinct use cases: generation following, minimizing ramping, and peak load curtailment. In a notable experiment, we validated our approach through a hardware-in-the-loop simulation, including a real-world air conditioner (AC) controlled via a smart thermostat, and simulated instances of ACs modeled after real-world data traces. During the 15-day experimental period, COHORT reduced daily peak loads by an average of 12.5\% and maintained comfortable temperatures.</p>},
  year = {2020},
  booktitle = {Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation},
  journal = {Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation},
  series = {Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation},
  month = {11/2020},
  institution = {ACM},
  publisher = {ACM},
  address = {Virtual Event JapanNew York, NY, USA},
  isbn = {9781450380614},
  url = {https://dl.acm.org/doi/proceedings/10.1145/3408308https://dl.acm.org/doi/10.1145/3408308.3427980https://dl.acm.org/doi/pdf/10.1145/3408308.3427980},
  doi = {10.1145/340830810.1145/3408308.3427980},
  language = {eng},
}