Case study - Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company

Abstract

In this paper, an application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired thermal power-generating company is presented. Results show that there is immense potential not only for significant cost savings but also for reduced logistics between different coal source–power plant pairs. The target plant load factor at each power plant can be achieved without the need of any imported coal which would not only save precious foreign exchange, but also reduce the logistics involved in the import of coal and transport to power plants. Sensitivity analyses have also been performed with varying coal supply and coal quality levels. The issue of greenhouse gas (GHG) emissions from coal-fired power plants has also been addressed. The trade-off between the optimal total cost and GHG emission targets has been explored. Results show that it is possible to significantly reduce carbon footprints with a marginal increase in the optimal total cost and without the need of import of coal. However, if it is desired to further reduce GHG emission targets, optimal total costs rise substantially with imported coal gradually substituting domestic coal. It is believed that the results presented in this paper would provide a fresh perspective with regard to the allocation and movement of coal. Finally, recommendations and concluding remarks are presented.