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Moment Constrained Optimal Transport for Thermostatically Controlled Loads

Title: Moment Constrained Optimal Transport for Thermostatically Controlled Loads
Authors: Le Corre, Thomas; Cardinal, Julien; Bušić, Ana
Contributors: Département d'informatique - ENS-PSL (DI-ENS); École normale supérieure - Paris (ENS-PSL); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS); Apprentissage, graphes et optimisation distribuée (ARGO); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de Paris; Institut National de Recherche en Informatique et en Automatique (Inria); Laboratory of Information, Network and Communication Sciences (LINCS); Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom Paris (IMT)-Sorbonne Université (SU); ANR-22-PETA-0004,AI-NRGY,Distributed AI-based architecture of future energy systems integrating very large amounts of distributed sources(2022)
Source: https://hal.science/hal-05226794 ; 2025.
Publisher Information: CCSD
Publication Year: 2025
Subject Terms: [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
Description: Controlling large populations of thermostatically controlled loads (TCLs), such as water heaters, poses significant challenges due to the need to balance global constraints (e.g., grid stability) with individual requirements (e.g., physical limits and quality of service). In this work, we introduce a novel framework based on Moment Constrained Optimal Transport (MCOT) for distributed control of TCLs. By formulating the control problem as an optimal transport problem with moment constraints, our approach integrates global consumption constraints and physical feasibility conditions into the control design. This problem with high (or infinite) dimensionality can be reduced to a much lower finite-dimensional problem. The structure of this problem allows for computing the gradient with Monte Carlo methods by generating trajectories of TCLs. Contrary to all previous work, in our MCOT framework, it is possible to choose the sampling law, which considerably speeds up the calculations. This algorithm mitigates the need for extensive state-space discretization and significantly reduces computational complexity compared to existing methods. Numerical experiments in a water heater case study demonstrate that our MCOT-based method effectively coordinates TCLs under various constraints. We further extend our approach to an online setting, illustrating its practical applicability on simulated data from the SMACH (Multi-agent Simulation of Human Activity in the Household) platform.
Document Type: report
Language: English
Availability: https://hal.science/hal-05226794; https://hal.science/hal-05226794v1/document; https://hal.science/hal-05226794v1/file/MCOT_Water_Heaters_CDC_2025%20%2810%29.pdf
Rights: https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.32C6DDEF
Database: BASE