{"id":1263,"date":"2013-09-17T09:15:42","date_gmt":"2013-09-17T13:15:42","guid":{"rendered":"http:\/\/admin.acceleratingscience.com\/?p=1263"},"modified":"2025-08-21T15:48:13","modified_gmt":"2025-08-21T15:48:13","slug":"using-line-elemental-coal-analyzer-reduce-power-outages","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/mining\/using-line-elemental-coal-analyzer-reduce-power-outages\/","title":{"rendered":"Using an On-Line Elemental Coal Analyzer to Reduce Power Outages"},"content":{"rendered":"

Officials at a Utah-based power generation plant wanted to reduce the number of forced outages caused by slagging — the molten or partial melting pasty ash deposits in their boiler. They believed that a low ash fusion temperature was causing slagging which impacted their boiler performance \u2013 which in turn reduced operating efficiency and availability, and prompted unplanned unit outages. In order to estimate the ash fusion temperatures in the coal<\/a> being sent to the power plant they needed to measure the ash constituents whose proportions determine ash fusion. They installed a Prompt Gamma Neutron Activation Analysis (PGNAA) online coal analyzer<\/a> in their yard which could provide minute-by-minute analysis of Silicon Dioxide (SiO2), Aluminum Oxide (Al2O3), Iron Oxide (Fe2O3), Calcium Oxide (CaO), Titanium Dioxide (TiO2), Potassium Oxide (K2O), and Sodium Oxide (Na2O) in the ash. \u00a0\u00a0They hoped that the analyzer could help them blend coals of differing ash composition, so they could keep the blended coal\u2019s ash softening temperature above 2175degrees F.<\/p>\n

\"Power

Power Plant<\/p><\/div>\n

The plant managers, working with consultants, were able to correlate the ash softening temperature of the coal feeding the station with the forced outage rate due to slagging for a particular unit. The plant had also developed an understanding of the relationships between certain coal ash minerals and the softening temperature of the ash. They developed formulas to estimate the ash softening temperature of the coal blend as a function of the components of the ash. They realized they could use the PGNAA analyzer to measure the chemistry of the six major ash components and then control the ash softening temperature. They set up a process to take advantage of the known chemistry of the components:<\/p>\n

    \n
  1. Coal is delivered by tandem truck to the site and is discharged at the blending system truck dump where it is stored in one of three stockpiles.<\/li>\n
  2. Coal from the three piles is reclaimed as a blend and conveyed to the screening transfer building.<\/li>\n
  3. The coal is then conveyed to a second transfer tower and on to a surge bin ahead of the storage barn feed belt.<\/li>\n
  4. Coal from a second truck dump also discharges into the surge bin.<\/li>\n
  5. Coal from the surge bin is then conveyed to the storage barn.<\/li>\n<\/ol>\n

    The on-line elemental analyzer<\/a>, installed on the storage barn feed belt where it can be used to control the blend of coal from the three stock piles, monitors the quality of the coal dumped at the direct feed truck dump.\u00a0 Then:<\/p>\n

      \n
    1. The sampled coal from the primary sampler discharges directly into the feed hopper on the analyzer.<\/li>\n
    2. The analyzer controls the feed of coal through the analyzer and the sample system with a variable speed belt and discharges it, via a chute, into the sample crusher.<\/li>\n
    3. The crusher discharges coal on to the secondary feeder belt.<\/li>\n
    4. A two way cross-belt secondary sampler located on the secondary feed belt allows two samples to be collected from the belt in separate sample containers.<\/li>\n
    5. The secondary feed belt discharges reject coal onto the sample reject conveyor which transports it back to the barn feed conveyor.<\/li>\n<\/ol>\n

      Because the analyzer controls the geometry of the coal flowing through it, the best possible accuracy can be achieved. Samples were analyzed for moisture, ash, sulfur, ash oxides, and ash fusion temperatures. The results of the test showed that the precision of the PGNAA analysis of ash, sulfur and ash oxides, compared to their requirements, was exceptional. A much-improved estimate of ash softening temperature was also achieved. The minute-by-minute data from the analyzer allowed the plant to supply more consistent coal blends to the units and allowed the plant to maximize the ash softening temperature of the blend, while reducing the need for more expensive, high fusion coals. With a more reliable coal blend, the station has re-gained electrical generation capacity and more consistently achieved the maximum rated capacity of the plant. If operating problems occur, they can be immediately determined whether or not there is a coal quality issue. If not, the plant can quickly move on to identify the true source of the problem and fix it. There is less potential for lost generation because both quality and equipment problems are identified and addressed sooner. Read the coal analyzing abstract<\/a>, including validation test results, to further see how an on-line coal analyzer can control the ash softening temperature of the blended coal in order to reduce outages and improve plant efficiency.<\/p>\n","protected":false},"excerpt":{"rendered":"

      Officials at a Utah-based power generation plant wanted to reduce the number of forced outages caused by slagging — the molten or partial melting pasty ash deposits in their boiler. They believed that a low ash fusion temperature was causing slagging which impacted their boiler performance \u2013 which in turn reduced operating efficiency and availability,<\/p>\n","protected":false},"author":67,"featured_media":1262,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_monsterinsights_skip_tracking":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[9,6,36,10],"tags":[31,113,143,183,16,184],"division":[],"class_list":{"0":"post-1263","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-coal","8":"category-elemental-geochemical-analysis","9":"category-material-handling","10":"category-mineral-processing","11":"tag-coal-2","12":"tag-coal-analyzer","13":"tag-coal-ash","14":"tag-elemental-analysis-of-coal","15":"tag-mining-2","16":"tag-power-outage","17":"entry"},"_selected_authors":[768],"_selected_reviewers":[],"acf":[],"yoast_head":"\nUsing 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