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Part of the book series: SpringerBriefs in Optimization ((BRIEFSOPTI))

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Abstract

Water scarcity and the cost of treating and recycling waste water both represent constraints in operating coal-fired power plants. As the capacity of thermoelectric power generation increases in the USA (the Energy Information Administration estimates that thermoelectric power generation will grow 22 % by 2030), so does the importance of managing the water used in these plants. In a clean coal-fired power plant, water is consumed in makeups (water added to a closed cycle due to evaporation or product loss), in blowdowns (water added during the cooling cycle due to liquid removal), and in the generation process itself. The amount of water consumed varies with two ambient weather factors: the dry-bulb temperature (temperature as measured by a thermometer shielded from moisture) and the humidity of the outside air, both of which are subject to significant uncertainty, and vary with the season and geographical region.

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Correspondence to Urmila Diwekar .

Notations

Notations

B :

blowdown losses

D :

drift losses

EL :

evaporation losses (EL)

f, h, and g i :

constraints using black-box models in Aspen Plus\(^{\rm \textregistered}\)

f(u):

initial uniform input distribution

\(\widehat{f(u)}\) :

probability density function of the updated input distribution

F :

FGD consumption

ME :

material and energy balance of the operating unit

\(N_{samp}\) :

number of samples taken

P :

amount of power generated

\(P^*\) :

fixed generation of electricity

\(p(u^*_j)\) :

probability density function for the output distribution corresponding to the initial uniform input distribution

Q :

total heat rejected by the cycle

x :

set of deterministic input parameters (design and operational conditions)

u :

set of uncertain weather conditions

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© 2015 Urmila Diwekar, Amy David

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Diwekar, U., David, A. (2015). Water Management Under Weather Uncertainty. In: BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems. SpringerBriefs in Optimization. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2282-6_5

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