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Model-based optimal start control strategy for multi-chiller plants in commercial buildings

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Chiller start control is to schedule chillers start-up operation, including how many chillers to be put into operation and when to start these chillers, for cooling down building internal temperature to a desired level before occupying. Chiller optimal start aims to find the most efficient way to schedule the chiller start operation for energy savings. Previous studies on chiller optimal start mainly focus on determining the pre-cooling lead time based only on initial outdoor and indoor temperatures without considering the impact of the recovery ability, i.e. the ability of the chillers to return the indoor air temperature to its set-point value. Different from previous studies, a new optimal start strategy is proposed in this article, which considers both the recovery ability and the cooling load condition as the optimizing variables. The new strategy is model-based and realized in two steps. The first step is to predict the building cooling load using a simplified building model, and identify a feasible set for the operating chiller number. The second step is to estimate the pre-cooling lead time using the simplified building model for each number inside the feasible range identified in the first step, and calculate the corresponding energy consumption. The number and its corresponding pre-cooling lead time which yields the least energy consumption constitute the optimal start operation. Practical application: The proposed strategy, validated through case studies, can be used in practical applications to select the optimal number of operating chillers and determine the associated pre-cooling lead time in order to achieve minimum energy consumption in the pre-cooling period. © 2010 The Chartered Institution of Building Services Engineers.
    Original languageEnglish
    Pages (from-to)113-129
    JournalBuilding Services Engineering Research and Technology
    Volume31
    Issue number2
    DOIs
    Publication statusPublished - May 2010

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

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