Power Plant Performance Monitoring Using Statistical Methodology Approach

The paper sets out problems experienced in current power plant performance calculation methodology. With changes in the electricity market and the increased role of computer control and diagnostic system, the previous methodology is fast becoming obsolete. Several key factors are highlighted (for example, reference values and corrective curves) which may lead to highly imprecise and inadequate evaluations of plant performance and, especially, operator behavior. It is important to bear in mind the systemic changes on the energy market. The current methodology focuses on controlling factors impacting power generating efficiency whereas the modern market is more complex and real costs are largely dependent on other variable costs, such as environmental fees, equipment wearing costs and the energy trading market. Statistical analysis of data is proposed as a modification of the current methodology. As most heat rate calculation is done on-line, it is possible to analyze this data in detail and apply, for example, PCA (Principle Component Analysis) and linear (and nonlinear) regression, thereby enabling a more accurate determination of the influence of principle process parameters on heat rate deviation. The article presents sample results of comprehensive analysis (two cases from different plants) of two twin units (heat rate calculation and process data analysis from a 12-month period) which to demonstrate the clear need to modify and update the old performance calculation approach.