Pinch analysis is a physical insight-based
optimization technique, applicable to conservation problems for a
wide range of resources (such as energy, water, hydrogen, cooling
water, etc.). Principally, it has been applied to optimize the external
resource, to satisfy unmet demands in source-sink allocation problems,
with deterministic flows and deterministic quality parameters (such
as contamination concentration in water and hydrogen conservation
problems). However, in many applications, quality and flow parameters
of different sources may not be deterministic due to changes in environmental
as well as operational conditions (e.g., changes in product mix and/or
feed characteristics). In this paper, the applicability of pinch analysis
has been extended to resource conservation networks with uncertain
qualities and flows for the operation of individual sources and demands
with the desired reliability. The uncertainties in source quality
and source flows are incorporated through different probability distributions
with known means and standard deviations. The stochastic constraints,
due to uncertainties associated with flow and quality parameters of
the sources, are converted to deterministic equivalents by use of
chance-constrained programming. The resultant deterministic problem
is approximated to a linear programming problem in order to address
it through pinch analysis techniques. Applicability of the proposed
methodology is demonstrated for water and hydrogen conservation networks,
and the results are verified through Monte Carlo simulations.
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