This document provides a primer on fuel quality analysis for combustion power plants. It discusses the importance of proper fuel sampling and testing to understand a power plant's primary energy input. The summary discusses common issues with fuel analysis, including inaccurate or incomplete samples and tests, as well as errors in analysis reports. It provides guidance on ensuring accurate fuel analysis, including recommended sampling techniques and types of tests to provide the most useful information for power plant operations and optimization.
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Primer on Fuel Quality Analysis
01/01/2015 | Una Nowling, PE
Fuel quality is vitally important for combustion power plants, yet fuel quality testing is still uncommon and analyses often incorrect. Improved knowledge about the primary energy
input to your power plant will help maximize your potential for improved operation and reduced generation costs.
Back in the “good old days” of the power industry, fuel was cheap, fuel supplies were fairly constant, air emissions regulations were loose, and power plant coffee was as
dark as sin and worse for you. Since those days the power industry has seen tremendous change in every way—save for the coffee.
In those same good old days, fuel quality testing wasn’t given serious attention. So-called “short proximate” analyses were conducted monthly, but a full analysis might
not have been done since the day the local beauty queen broke a champagne bottle on the turbine casing. Even when analyses were done, they were often rife with
errors, ranging from simple typographical and mathematical errors, to blatant sloppiness. When I started my career in the power industry more than 20 years ago, I
wondered how a power plant could pay so much for an analysis containing so many significant errors, and thus I learned to devote considerable time to checking for,
advising upon, and fixing such errors.
One would hope that in this era of massively instrumented and logged modern power plants—struggling to cut costs while meeting performance, operations and
maintenance, reliability, and emissions targets—that our fuel quality sampling and testing practices would significantly improve. Unfortunately, that does not seem to be
the case, and as a result the power engineer is frequently called upon to review the fuel quality data assumptions and analyses that are conducted.
How serious is this problem? In my career I’ve reviewed well over 10,000 fuel quality samples, and I would estimate that perhaps 1 in 10 has a significant error that
prevents a full and accurate analysis of the fuel without engineering judgment to correct the error. For example, I recently received 12 coal quality analyses from a power
plant, and three of that 12—25%—featured some significant error or omission.
To help you avoid such problems, this article provides tips and guidelines for ensuring that you and your power plant staff have the best possible knowledge about your
fuels.
It All Begins with Sampling
Understanding where, how, and when the fuel sample is collected will provide information on how representative that sample is of your average fuel quality.
Unfortunately, fuel sampling is often considered just another messy chore, where someone takes a quick scoop of a coal pile with a bucket and pronounces “mission
accomplished.” Unfortunately, this will often yield an inaccurate sample, especially as it may be possible that no one really knows what coal or coals are mixed together in
that particular region of the pile.
A better way of sampling is to take directly from the train during the unloading process (Figure 1). Even better is to take small samples of coal from five or more train
cars, as they are being unloaded, and mix the samples together to produce a composite coal for analysis. If sampling is being conducted during a performance test
(Figure 2), the best method is often to collect equal samples at each of the coal feeders and combine these to create the composite sample.
2. (http://www.powermag.com/wp-
content/uploads/2015/01/PWR_010115_FuelAnalysis_Fig1.jpg)
1. What’s really on that train? Not having an accurate measure of your fuel quality is like grocery shopping blindfolded. Courtesy: Una Nowling
(http://www.powermag.com/wp-
content/uploads/2015/01/PWR_010115_FuelAnalysis_Fig2.jpg)
2. Ignorance is not bliss. The wrong coal was delivered for a test burn, and no analysis was done to provide operators with a warning. By Day 4, a clinker approximately 10 x 20 x 4 feet formed on
the freeboard area, falling during turndown and destroying the bottom ash hopper. Courtesy: Una Nowling
For the best sampling guidelines, refer to the engineering standards in use in your country. For the U.S. this would be the American Society for Testing and Materials
(ASTM) standards. Good examples of sampling standards include ASTM D 2234/D 2234M-07 for belt samples, D 6883-04 for sampling from stockpiles and delivery
vehicles, and D 4596-99 for mine samples.
Which Tests Should Be Conducted?
After a representative sample has been safely collected, the next step is determining what tests should be performed upon the sample. The answer to this depends upon
what your goals are for attempting to solve fuel quality–related problems at your power plant. Here’s a look at the typical coal analyses, in order from least to most
complete, and what impacts they can help predict:
■ The most basic analysis, a “short proximate,” will typically consist of the heating value, moisture, ash, and sulfur in the fuel. This is a barely acceptable analysis, which
will only allow one to make general estimates about the plant performance.
■ A full proximate analysis will add volatile matter and fixed carbon to the results, which can be useful for determining unburned carbon, CO production, coal fineness
requirements, excess air requirements, and the like.
■ An ultimate analysis will provide the carbon, hydrogen, nitrogen, sulfur, ash, moisture, oxygen, and (sometimes) chlorine. With this analysis one can determine
combustion air and flue gas calculations, calculate boiler efficiency, estimate NO production, and estimate boiler tube corrosion rates.
■ An ash mineral analysis will provide a breakdown of the minerals contained in the ash on an elemental scale. An ash mineral analysis will assist in predicting slagging
and fouling in the boiler, ash erosion and corrosion, ash resistivity for collection in electrostatic precipitators, and more.
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The process of checking the analyses of the fuels you’ve tested is made simplest by developing a spreadsheet of all fuel analyses that are received, and then developing
macros to perform the checks discussed in this article. This sort of exercise can be a good project for engineering interns, and can help instill an awareness of the
importance of fuel quality early in their careers. For more advanced efforts, one could employ an Access database, or even a web- or cloud-based intranet database to
create an intelligent fuels library that is accessible fleetwide. In the long run, the cost of increasing your awareness of the diet of your power plant is relatively small but
has the potential to yield significant benefits.
How Many Errors Did You Find?
Here are all of the problems with the coal analysis presented in the sidebar:
■ The proximate analysis only sums to 98%.
■ The ultimate analysis appears to be on a dry basis instead of as-received, because summing everything save the moisture and chlorine equals 100%.
■ The net calorific value in kcal/kg is greater than the gross calorific value.
■ The conversion between kcal/kg and Btu/lb is incorrect.
■ A Dulong analysis of the as-given ultimate analysis yields 13,150 Btu/lb—nearly 1,000 Btu/lb greater than given.
■ The sulfur content of 3.3% is externally inconsistent for a Colombian coal; it should be less than 2%.
■ A typographical error invalidates the ash initial deformation temperature.
■ The ash hemispherical temperature is greater than the ash fluid temperature.
■ Minor error: The oxygen value does not have measurement units. ■
— Una Nowling, PE (nowlinguc@bv.com) is the technology lead for fuels at Black & Veatch. She has worked on fuels-related issues and analyses at more than 550
different units over 21 years, specializing in coal, natural gas, and biofuels. She is also an adjunct professor of mechanical engineering at University of Missouri-Kansas
City.
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