Pu, Fangwei (2019) Optimizing storage tank size in rainwater harvesting (RWH) systems based on daily demand and supply matching. Masters thesis, Concordia University.
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Abstract
Under current published guidelines for Rainwater Harvesting (RWH) systems, sizing procedure for rainwater tanks is based on annual climate data, which might underestimate the performance of RWH system and lead to oversized tanks. The aim of this study is to promote compact sizing of RWH systems such that RWH systems could be deployable for more situations.
To effectively evaluate the optimal size of rainwater storage tanks, this study proposes to consider the matching of demand and supply on a daily basis. A performance evaluation method, based on daily climate conditions, is developed. The approach and its effectiveness are demonstrated by various water demand scenarios for residential buildings.
The comparison between fulfillment rates for RWH systems with rainwater tanks sized using the annual method and those sized using the daily method showed that the annual method may oversize rainwater storage tanks of RWH systems. The performance analysis with consideration of extreme climates illustrates the daily method can be adopted to size the tanks for extremely wet areas.
The scope of this study is limited residential buildings with a wide variety of water consumption patterns. The uncertainty of the sizing approach reduces for office buildings, where the water consumption is more predictable.
By adopting this method, oversized rainwater tanks and biased performance evaluation of RWH systems can be largely avoided, and more practical recommendations on RWH systems at initial design stage can be offered.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Pu, Fangwei |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Building Engineering |
Date: | August 2019 |
Thesis Supervisor(s): | Lee, Bruno |
ID Code: | 985919 |
Deposited By: | Fangwei Pu |
Deposited On: | 05 Feb 2020 14:03 |
Last Modified: | 05 Feb 2020 14:03 |
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