Aspiration
Being able to predict and simulate the leading causes of variation in heat rates which are key factors in measuring the overall efficiency of the power plant.
Approach
We acquire, clean, transform, and integrate power plant equipments from sources like inspection data points, sensors data (caloric value, excess O2, ash content, CO content, flow rate, voltage), and maintenance post-event data (damage classes, maintenance types, planned v.s. unplanned events, maintenance actions). Then we use machine learning to do Root Cause Analysis to identify “important features” or variables that affected the heat rate to find the best most important parameters that gives the highest overall efficiency.