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Demonstration of Intelligent HVAC Load Management With Deep Reinforcement Learning: Real-World Experience of Machine Learning in Demand Control

Yan Du, Fangxing Li, Kuldeep Kurte, Peter L. Munk, Helia Zandi

2022IEEE Power and Energy Magazine34 citationsDOIOpen Access PDF

Abstract

Buildings account for 40&#x0025; of total primary energy consumption and 30&#x0025; of all CO<sub>2</sub> emissions worldwide. A large portion of building energy consumption is due to heating, ventilation, and air-conditioning (HVAC) systems. In the summer, for example, more than 50&#x0025; of a building&#x2019;s electricity consumption is used for cooling. With proper energy management, buildings can provide load shifting, peak shaving, frequency regulation, and many other demand response services.

Topics & Concepts

HVACLoad managementAir conditioningDemand responseBuilding management systemElectricityEnergy consumptionReinforcement learningEnergy managementArchitectural engineeringBuilding automationPeaking power plantAutomotive engineeringConsumption (sociology)Ventilation (architecture)Cooling loadComputer sciencePeak demandEngineeringControl (management)Energy (signal processing)Electrical engineeringRenewable energyMechanical engineeringArtificial intelligenceDistributed generationPhysicsMathematicsStatisticsSociologySocial scienceThermodynamicsSmart Grid Energy ManagementBuilding Energy and Comfort OptimizationEnergy Load and Power Forecasting
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