Optimal Operating Rules for Joint System of Water Supply Reservoir and Seawater Desalination Plant using Genetic Programming
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- @MastersThesis{oai:repository.ust.hk:1783.1-81383,
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author = "Yi Yang",
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title = "Optimal Operating Rules for Joint System of Water
Supply Reservoir and Seawater Desalination Plant using
Genetic Programming",
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year = "2015",
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school = "HKUST",
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type = "M.Phil",
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address = "Hong Kong",
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month = jul,
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keywords = "genetic algorithms, genetic programming, water-supply,
saline water conversion, water resources development,
water reuse",
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bibsource = "OAI-PMH server at repository.ust.hk",
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language = "English",
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oai = "oai:repository.ust.hk:1783.1-81383",
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URL = "https://doi.org/10.14711/thesis-b1514746",
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URL = "http://repository.ust.hk/ir/bitstream/1783.1-81383/1/th_redirect.html",
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size = "115 pages",
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abstract = "Due to climate change, population growth and
industrial development, there is increasing scarcity of
freshwater resources amidst rising demands. In view of
this, many coastal places are resorting to seawater
desalination as a means of supplementing existing
supplies from reservoirs. However, doing so introduces
a tradeoff between water supply reliability and cost,
as seawater desalination is relatively expensive
because of its high energy consumption. Although some
studies have been done to combine seawater desalination
with other options like reservoir and wastewater reuse
for supplying high water demand, they either emphasize
too much on economic cost rather than system operation,
or lack quantitative investigation into the operation
of an integrated or joint system. Thus, a comprehensive
model for the operation of a joint system to
systematically optimise both water supply reliability
and economic efficiency is required. In this study, an
optimisation model for the operation of a joint system
of a single reservoir and seawater desalination plant
was developed for urban water supply. The model aimed
to maximise water supply reliability while constraining
cost. Taking into account the existing storage of water
in the reservoir, the demand for water by various
sectors, and current and forecast future inflows to the
reservoir, two operating rules that interact with each
other were optimised for guiding the operation of the
reservoir and seawater desalination plant. Upon
attaining the optimal functions, both operational cost
and capital cost were calculated on an annual basis for
analysis. To solve the above operation model, a genetic
programming (GP) iterative tool was designed for the
joint system. Using the GPLAB toolbox in MATLAB,
genetic programming was applied in an iterative fashion
to generate optimal operational rules to govern the
releases from the reservoir and water production rates
of the desalination plant. In this manner, GP was
empowered to optimise the two rules simultaneously,
which would not be possible if using GP in a
conventional way. Results were obtained for a
semi-hypothetical case study in California and analysed
to prove the advantage of the joint system and
applicability of genetic programming for the purposes
of this study. The fitness value was found to have
improved by 33percent after 83 iterations in the
baseline case. It was demonstrated that due to the
assumption that the volume data of current inflows and
demands were affected by their volume data one and two
time periods before thus forecasting information might
be indirectly incorporated into the functions by the
incorporation of these variables into the functions.
The complex functions generated by the model can be
easily calculated using computer programs. The capital
cost consisted of 1/3 of the total cost with an
equilibrium point at around 500 million dollars per
month when it was allocated to each month. But the
water demands were too high to be fully met (70percent
met), leading to large budget carry overs. In terms of
the reservoir performance, the reservoir storage was
drawn down before every inflow peak. If the budget was
not enough for this expensive way of desalinating
water, it had to depend more on releasing water from
the reservoir, whose inflows fluctuated in all time
periods. As the capacity of desalination plant
increases, demand plays a more important role in
deciding how much water to be released from the
reservoir. The scale expansion of the existing seawater
desalination plant could be a very effective but costly
way to solve water scarcity problems in coastal city
water supply cases, while increasing the reservoir
capacity is the most efficient way to reducing water
shortages. And the fitness value kept increasing by
83.05percent when the reservoir capacity went up from
3000 million m$^{3}$ in the baseline case to 5000
million m$^{3}$. But still future work needs to be done
to incorporate more scenarios to prove the advantage of
the joint operation model together with the GP
iterative tool.",
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notes = "oai:repository.ust.hk:1783.1-81383",
- }
Genetic Programming entries for
Yi Yang
Citations