Data-driven framework for boiler performance monitoring

Riku-Pekka Nikula, Mika Ruusunen and Kauko Leiviskä

Applied Energy, 2016, vol. 183, issue C, 1374-1388

Abstract: The energy industry is striving for cost-efficient production with low emissions. The efficiency of energy conversion processes is one of the most important factors affecting the path to such a goal. This paper provides a framework for the monitoring of steam boiler operation in power stations. The framework is based on the use of historical process data as a reference for real-time operation. The actual boiler efficiency is monitored together with its expected efficiency, which is an estimate of the highest historical efficiency in the corresponding process state, based on a data-driven model. In the presented approach, the process state is defined on the basis of variables that have the strongest correlation with boiler efficiency according to information-theoretic variable ranking. Boiler performance is monitored using a statistical process control chart for the difference between the expected and actual efficiencies. The framework was tested using data from a circulating fluidised bed boiler and from a corner-fired boiler. The results revealed that the strongest correlations between process variables and boiler efficiency are substantially consistent in both cases. Moreover, the framework provides a novel measure for boiler performance enhancement.

Keywords: Efficiency; Information theory; Statistical process control; Steam boiler; System identification (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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DOI: 10.1016/j.apenergy.2016.09.072

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