Data-driven framework for boiler performance monitoring

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.