Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61189
Title: Analysis of an air-cooled chiller replacement project using a probabilistic approach for energy performance contracts
Authors: Lee, P
Lam, PTI 
Lee, WL 
Chan, EHW 
Keywords: Chiller replacement
ESCO
Monte Carlo simulation
Performance contracting
Issue Date: 2016
Publisher: Pergamon Press
Source: Applied energy, 2016, v. 171, p. 415-428 How to cite?
Journal: Applied energy 
Abstract: Replacement of air-cooled chillers with water-cooled chillers for air-conditioning plants in existing buildings can yield a significant amount of energy savings, especially in a sub-tropical climate. However, due to variations in weather conditions and building operation patterns, the amount of actual energy saving is often uncertain in these retrofits. These uncertainties impose a risk of saving shortfalls when Energy Service Companies (ESCOs) guarantee building owners for a certain amount of energy savings in Energy Performance Contracting (EPC) projects. This study presents a probabilistic approach to estimating a range of possible energy savings with the associated confidence levels for chiller replacement in existing buildings, taking into account the annual variations in the influential parameters affecting energy savings. The influential factors include building cooling loads, system control and operation systems, as well as chiller plant characteristics. The proposed approach involves: the use of correlation analysis for identifying influential parameters; EnergyPlus for simulating energy use of chiller plant; and a Monte Carlo approach for simulating the probability of post-retrofit energy savings. A commercial building where the air-cooled chillers were replaced with water-cooled chillers is used to illustrate the proposed approach. Results show that the variations in annual energy savings for chiller replacement projects can be estimated with a defined degree of certainty. In the case study project, the possible annual energy savings during the post-retrofit period range from 1,149,000 kWh (37.6% of baseline consumption) to 1,504,000 kWh (49.2% of ditto) at 90% statistical significance. The risk mitigation measures for this type of energy retrofit are discussed as well.
URI: http://hdl.handle.net/10397/61189
ISSN: 0306-2619
EISSN: 1872-9118
DOI: 10.1016/j.apenergy.2016.03.035
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