Optimal control and design for space-efficient rainwater harvesting and flood-mitigation systems
File(s)
Author(s)
Soh, Qiao Yan
Type
Thesis
Abstract
There is strong consensus that water stresses around the globe are increasing with rapid pace. Climate change is bringing about more extreme and unpredictable weather events, whilst urbanisation has been found to significantly alter the local water cycle which further compounds the impacts of climate change.
This thesis investigates future-proofing water management systems in urban areas. It has a specific focus on rainwater harvesting and flood-mitigation systems, as these multi-purpose systems have significant potential in addressing the water challenges expected in the near future. This study examines these issues through employing state-of-the-art computational methods in the development of accessible frameworks for optimising the design and operational policies of water management infrastructure.
A high-resolution simulation tool was developed to address the gap in existing simulation strategies in which short-term events, such as flash floods, were not captured. This was used to evaluate the system designs and operational strategies derived using an optimisation tool, also developed as part of this thesis, which was deliberately structured such that optimisation models can be built for any given system. These tools are novel in their scalability and accessibility, which are key contributions towards more effective strategies for designing efficient, multi-purpose water management systems.
Evaluated using real-world data from a residential estate in Singapore, the maximum level of improvement was found when the system design and control were optimised simultaneously. Under this framework, a system that is 20\% smaller than the existing configuration was found, which was able to both eliminate overflow events from historical rainfall days and increase the average harvested water yield by 176\%. This corresponds to a 48.6\% increase in the balance of savings, demonstrating substantial improvements to the system's demand fulfilment capabilities. Hence, optimisation-based design strategies can significantly increase the effectiveness of multi-purpose systems, which are key towards a sustainable water future.
This thesis investigates future-proofing water management systems in urban areas. It has a specific focus on rainwater harvesting and flood-mitigation systems, as these multi-purpose systems have significant potential in addressing the water challenges expected in the near future. This study examines these issues through employing state-of-the-art computational methods in the development of accessible frameworks for optimising the design and operational policies of water management infrastructure.
A high-resolution simulation tool was developed to address the gap in existing simulation strategies in which short-term events, such as flash floods, were not captured. This was used to evaluate the system designs and operational strategies derived using an optimisation tool, also developed as part of this thesis, which was deliberately structured such that optimisation models can be built for any given system. These tools are novel in their scalability and accessibility, which are key contributions towards more effective strategies for designing efficient, multi-purpose water management systems.
Evaluated using real-world data from a residential estate in Singapore, the maximum level of improvement was found when the system design and control were optimised simultaneously. Under this framework, a system that is 20\% smaller than the existing configuration was found, which was able to both eliminate overflow events from historical rainfall days and increase the average harvested water yield by 176\%. This corresponds to a 48.6\% increase in the balance of savings, demonstrating substantial improvements to the system's demand fulfilment capabilities. Hence, optimisation-based design strategies can significantly increase the effectiveness of multi-purpose systems, which are key towards a sustainable water future.
Version
Open Access
Date Issued
2023-12
Date Awarded
2024-05
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Shah, Nilay
Acha Izquierdo, Salvador
Sponsor
Singapore. National Research Foundation
Grant Number
L2NICTDF1-2017-3
Publisher Department
Department of Chemical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)