3.8 Proceedings Paper

Probabilistic optimal design and on-site adaptive commissioning of building air-conditioning systems concerning uncertainties

Journal

INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS
Volume 158, Issue -, Pages 2725-2730

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.egypro.2019.02.029

Keywords

Probabilistic optimal design; uncertainty analysis; adaptive commissioning; air-conditioning system; building energy saving

Categories

Funding

  1. Research Grant Council (RGC) of the Hong Kong SAR [152079/18E]
  2. Hong Kong Polytechnic University [1-ZVG7]

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Sizing of building air-conditioning systems is a critical issue in design practice concerning the building energy consumption in operation and risk of being undersized. In current practice, chillers and pumps are often oversized due to the rough consideration of uncertainties using safety factor to avoid the risk of being undersized, which results in significant energy waste in operation. In addition, the current design and commissioning do not provide means and flexibility for the air-conditioning systems to minimize their energy consumption when the systems are found oversized in operation. This paper presents a novel design and commissioning approach, consisting of probabilistic optimal design and on-site adaptive commissioning, for building airconditioning systems to maximize their energy savings in operation. The probabilistic optimal design of an air-conditioning system involves two parts. One is probabilistic optimal design of chillers considering uncertainties, one is probabilistic optimal design of water circulation system considering uncertainties and the flexibility of on-site adaptive commissioning. Monte Carlo simulation is used to quantify uncertainties in system design and operation process. The on-site adaptive commissioning method has alternative commissioning schemes developed to maximize the energy saving based on the actual situation. A case study is performed to test and validate this new design and commissioning approach. Results show that about 20% energy saving could be achieved when the system is oversized by 20%, compared to conventional design and commissioning methods. (C) 2019 The Authors. Published by Elsevier Ltd.

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