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A refrigerated gas plant (RGP) faces operational challenges on
three fronts namely: 1) at the plant inlet, fluctuations in flow
rate and composition caused by multiple feed gas streams; 2) within
RGP, unscheduled shutdowns due to equipment malfunction; 3) at the
outlet, strict product specifications enforced by the customers.
These challenges force RGP to improve its efficiency in order to
sustain profitability. An identified area for improvement is during
operational planning. This type of planning poses a short-term and
continuous scheduling problem in which preconfigured setpoints are
directly implemented by regulatory controllers. While this practice
is currently accepted, economic benefits can be further realized by
frequent reevaluation of plant states through real-time
optimization (RTO). Since scheduling is performed at a much larger
time-scale (days-weeks) as compared with RTO (hours-days),
integration of these two automation layers is difficult. This book
discusses an efficient approach for integration of scheduling and
RTO in the RGP.
Space-time modeling of atmospheric pollutants has been actively
attempted by many workers, including Kyriakidis (1999) who
successfully integrated the deterministic trend m(t) and the
probabilistic residual R(t) components of a random variable RV Z(t)
through a stochastic simulation approach. However, many of the
spatiotemporal studies carried a major assumption that the temporal
aspect is fully understood and thus focused primarily on spatial
modeling. The main objective of this work is concerned with
evaluating the accuracy and suitability of the techniques used for
modeling the temporal phenomena. Various statistical methodologies,
i.e., linear regression, kriging and stochastic simulation, were
performed in the case of predicting tropospheric ozone
concentrations in Calgary, Alberta for 1998-2000. It should be
emphasized that the more accurate the temporal modeling is
performed at various environmental monitoring stations, the higher
the probability of success in estimating ozone values at unknown
locations. Therefore, exhaustive studies of ozone phenomena must be
carried out at as many cities in Canada as possible.
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