Mutagenic effluents from a coal-fired power plant:  short-term variations and relation to power load and other load-dependent emissions

Victorin, Katarina; Jantunen, Matti; A, Itkonen; Ahlborg, Ulf G.; Staahlberg, Margareta.; Honkasalo, Sirpa.

doi:10.1021/es00146a014

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…On the other hand, the variability of the daily load curve for the U.K. is shown as being affected by the climate change because of the seasons . There is scarce literature available about individual plant load variation, only for a 300 MW plant, daily variations on steam flows are studied in ref . Finally, one more reference suggests that the power demand can be adjusted to a normal distribution with a standard deviation equal to 1 / 3 of the mean .…”

Section: Model Of the Pc Processmentioning

confidence: 99%

Stochastic Simulation of Pulverized Coal (PC) Processes

2010

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An increasing population and electricity demand in the U.S. require capacity expansion of power systems. The National Energy Technology Laboratory (NETL), U.S. Department of Energy (DOE), has invested considerable efforts on research and development to improve the design and simulation of these power plants. Incorporation of novel process synthesis techniques and realistic simulation methodologies yield optimal flowsheet configurations and accurate estimation of their performance parameters. To provide a better estimation of such performance indicators, simulation models should predict the process behavior based on not only deterministic values of well-known input parameters but also uncertain variables associated with simulation assumptions. In this work, the stochastic simulation of a load-following pulverized coal (PC) power plant takes into account the variation of three input variables, namely, atmospheric air temperature, atmospheric air humidity, and generation load. These uncertain variables are characterized with probability density functions (pdfs) obtained from available atmospheric and electrical energy generation data. The stochastic simulation is carried out by obtaining a sample of values from the pdfs that generates a set of scenarios under which the model is run. An efficient sampling technique [Hammersley sequence sampling (HSS)] guarantees a set of scenarios uniformly distributed throughout the uncertain variable range. Then, each model run generates results on performance parameters as cycle efficiency, carbon emissions, sulfur emissions, and water consumption that are statistically analyzed after all runs are completed. Among these parameters, water consumption is of importance because an increasing demand has been observed mostly in arid regions of the country and, therefore, constrains the operability of the processes. This water consumption is significantly affected by atmospheric uncertainties. The original deterministic process model simulation was designed in Aspen Plus, and a CAPE-OPEN compliant stochastic simulation capability is employed to run the uncertainty analysis. Initially, the influences of atmospheric conditions and load change on the performance parameters are analyzed separately to understand their individual influences on the process, and then their simultaneous variation is analyzed to generate more realistic estimations of the process performance.

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Section: Model Of the Pc Processmentioning

confidence: 99%

Stochastic Simulation of Pulverized Coal (PC) Processes

2010

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“…As cooling occurs, relatively involatile compounds, including many polycyclic aromatic hydrocarbons (PAHs) and their derivatives, condense on the surfaces of ambient particles (1-3). PAHs and their derivatives, extracted from sampled airborne particulate matter, are both carcinogenic and mutagenic (4)(5)(6)(7)(8).…”

Section: Introductionmentioning

confidence: 99%