Cited by 109Building Energy and Comfort OptimizationIntegrated Energy Systems OptimizationSmart Grid Energy Management

Gigawatt-hour scale savings on a budget of zero: Deep reinforcement learning based optimal control of hot water systems

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Kazmi, Hussain, Mehmood, Fahad, Lodeweyckx, Stefan, Driesen, Johan·2018·Energy

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Crossref · 10.1016/j.energy.2017.12.019

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  • Kazmi et al. used deep RL to achieve a scalable 20% reduction of energy while requiring only three sensors.

    “For control, Kazmi et al. [417] used deep RL to achieve a scalable 20% reduction of energy while requiring only three sensors: air temperature, water temperature, and energy use (see also Section 5.3 for similarly substantial gains in datacenter cooling).”

    From Tackling climate change with machine learning (2023) · cites this paper as [417]

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Research works printed but not linked: 2

  1. Afram, A. a.-S. (2014). Review of modeling methods for HVAC systems. Applied Thermal Engineering 67.1, 507-519.
  2. Gal, Y. R. (2016). Improving PILCO with bayesian neural network dynamics models. Data-Efficient Machine Learning workshop. Vol. 951.

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Authors
Kazmi, H., Mehmood, F., Lodeweyckx, S., & Driesen, J.
Affiliations
  • KU Leuven (BE)
  • Lahore University of Management Sciences (PK)
Corresponding author
Kazmi, Hussain
Venue
Energy
Publisher
Elsevier BV
Published
2018-02
Volume
144
Pages
159-168
ISSN
0360-5442 (ISSN-L)
OpenAlex
W2774636080
Cited by
109
References
41
Citations by year
2026: 3 · 2025: 14 · 2024: 13 · 2023: 14 · 2022: 14 · 2021: 19 · 2020: 14 · 2019: 14 · 2018: 4
FWCI
7.70
Type
journal article
Language
en
Open access
Locations
  • Energy (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Lirias (submittedVersion, other-oa)
  • HAL (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • arXiv (Cornell University)
Funders
Agentschap Innoveren en Ondernemen
Topics
  • Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
Keywords
domestic hot water heating, deep reinforcement learning, optimal control, energy consumption reduction, occupant comfort, model-free learning, hot water storage tank, residential energy efficiency, building energy efficiency

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