Siemens aims to increase plant efficiency

A Siemens researcher at work.

Siemens is researching analytical methods that would enable coal-fired power plants and biogas plants to be operated more efficiently, the company reports.

This would enable power plant operators to better match their combustion parameters to the grade of the fuel. Feasibility has already been demonstrated in the laboratory, and the first pilot plant is scheduled for 2011. The method’s use in biogas plants is currently under investigation.

The efficiency of a coal-fired power plant is dependent on the quality of the fuel, which varies as a function of its region of origin, for example. Coal with a low calorific value reduces the output of the power plant, so that the amount of coal in the combustion chamber must be increased. Exhaust gas treatment could also be optimized if the exact sulfur content were known for each load of coal.

Furthermore, slag formation — one reason that power plants must undergo regular maintenance — could be better controlled.

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Such analyses are time-consuming, however. To determine the calorific value, for instance, the coal is burned in a colorimeter and the heat released is measured. One alternative is infrared spectroscopy. This method is based on the fact that molecules emit characteristic light spectra when irradiated with infrared light. These spectra provide information about the chemical bonds in the sample, from which certain elements or substance groups can be deduced.

The researchers of Siemens Corporate Technology (CT) can therefore not only determine the carbon, sulfur and water content of the sample, but they can also deduce the calorific value directly from the type of bonds. In order to offer an economic solution, they use relatively inexpensive spectrometers that operate in the near-infrared wavelength region (NIR). Their spectra are difficult to analyze, however, because the signals originating from individual types of bonds overlap. Siemens CT has therefore used statistical mathematical methods to develop a process that uses reference measurements of known samples to identify characteristic curve shapes for the elements sought.
 

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