Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends

Dongsu Kim, Jongman Lee, Sunglok Do, Pedro J. Mago, Kwang Ho Lee, Heejin Cho

    Research output: Contribution to journalReview articlepeer-review

    30 Citations (Scopus)

    Abstract

    Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas emissions, which may significantly impact climate change. Heating, ventilation, and air-conditioning (HVAC) systems are among the most significant contributors to global primary energy consumption and carbon gas emissions. Furthermore, HVAC energy demand is expected to rise in the future. Therefore, advancements in HVAC systems’ performance and design would be critical for mitigating worldwide energy and environmental concerns. To make such advancements, energy modeling and model predictive control (MPC) play an imperative role in designing and operating HVAC systems effectively. Building energy simulations and analysis techniques effectively implement HVAC control schemes in the building system design and operation phases, and thus provide quantitative insights into the behaviors of the HVAC energy flow for architects and engineers. Extensive research and advanced HVAC modeling/control techniques have emerged to provide better solutions in response to the issues. This study reviews building energy modeling techniques and state-of-the-art updates of MPC in HVAC applications based on the most recent research articles (e.g., from MDPI’s and Elsevier’s databases). For the review process, the investigation of relevant keywords and context-based collected data is first carried out to overview their frequency and distribution comprehensively. Then, this review study narrows the topic selection and search scopes to focus on relevant research papers and extract relevant information and outcomes. Finally, a systematic review approach is adopted based on the collected review and research papers to overview the advancements in building system modeling and MPC technologies. This study reveals that advanced building energy modeling is crucial in implementing the MPC-based control and operation design to reduce building energy consumption and cost. This paper presents the details of major modeling techniques, including white-box, grey-box, and black-box modeling approaches. This paper also provides future insights into the advanced HVAC control and operation design for researchers in relevant research and practical fields.

    Original languageEnglish
    Article number7231
    JournalEnergies
    Volume15
    Issue number19
    DOIs
    Publication statusPublished - 2022 Oct

    Bibliographical note

    Publisher Copyright:
    © 2022 by the authors.

    Keywords

    • HVAC model predictive control (MPC)
    • advanced HVAC technology
    • black-box model
    • building HVAC optimization
    • building energy modeling
    • grey-box model
    • white-box model

    ASJC Scopus subject areas

    • Renewable Energy, Sustainability and the Environment
    • Fuel Technology
    • Engineering (miscellaneous)
    • Energy Engineering and Power Technology
    • Energy (miscellaneous)
    • Control and Optimization
    • Electrical and Electronic Engineering

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