Fuel Cost Optimization of Coal-Fired Power Plants using Coal Blending Proportions

In this paper, we aim to explore the possibility of optimizing the fuel cost of power plants using a mixed-integer linear programming model that considers coal blending proportion. Since there are various grades of coal at varying prices, the right optimal blending of various grades is required to get an optimal proportion as required by the power plant. The model considers various factors including coal source, mode of transportation, quality of coal, Gross Calorific Value (GCV), blending proportion, and so forth. The study's findings may help the power sector take optimized decisions based on multiple parameters. The outcome of this proposed research shows that there is enough scope for fuel cost-saving and reduced logistic costs between the source and power plant pair.