Physical sensors correctly measure fuel consumption at thermal power plants, but complete sensing is not always economically viable. To solve this challenge, machine learning models are used to predict next-day consumption. Doing so makes it possible to consider operational issues and asset maintenance to determine dispatch order. This presentation will highlight the novel methods being used to predict fuel consumption and costs at thermal power plants.