One approach to temperature distribution control in thermal power plant boilers
Optimization of the combustion control process in a tangentially fired pulverized coal boiler, to achieve uniform temperature distribution, is discussed in the paper. This issue is even more critical in those thermal power plants which are not equipped with modern systems for combustion enhancement,...
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| Vydané v: | Automatika Ročník 61; číslo 2; s. 273 - 283 |
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| Hlavní autori: | , , |
| Médium: | Journal Article Paper |
| Jazyk: | English |
| Vydavateľské údaje: |
Ljubljana
Taylor & Francis
02.04.2020
Taylor & Francis Ltd KoREMA - Hrvatsko društvo za komunikacije,računarstvo, elektroniku, mjerenja i automatiku Taylor & Francis Group |
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| ISSN: | 0005-1144, 1848-3380 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Optimization of the combustion control process in a tangentially fired pulverized coal boiler, to achieve uniform temperature distribution, is discussed in the paper. This issue is even more critical in those thermal power plants which are not equipped with modern systems for combustion enhancement, such as low NOx burners. Research has shown that the temperature distribution inside the boiler of such power plant can be controlled by adjusting firing, through coal redistribution among the mills. Furthermore, disturbed flame symmetry (i.e. non-uniform temperature distribution in the boiler) is reflected in a large difference between the output temperatures measured on the left and right sides of the boiler. Given the non-stationary conditions typical of thermal power plant boilers, an adaptive control approach is proposed, based on PI controllers which are very popular in industry and widely accepted. Self-tuning of the PI controllers is based on dynamic model parameters derived applying the weighted recursive least squares (WRLS) method to real data recorded at Nikola Tesla B thermal power plant in Serbia, whose nominal power is 650 MW. The same model was later used to test the proposed control approach. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 239870 |
| ISSN: | 0005-1144 1848-3380 |
| DOI: | 10.1080/00051144.2020.1733792 |