Application of MCDM technique for selection of fuel in power plant

Abstract

This paper presents a thermodynamics-assisted Multi-Criteria Decision Making (MCDM) technique for selecting the optimal fuel alternative in a thermal power station. The study incorporates three MCDM methods: Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), and Additive Ratio Assessment (ARAS) for the analysis. To determine the qualitative and quantitative criteria that influence fuel selection, the weight of each criterion is calculated using the entropy method. The MCDM techniques are then applied to rank the available fuels based on their thermodynamic parameters. The results of the analysis indicate that sample number 33, followed by sample number 24, are the best alternatives for replacing the currently used coal. These samples have grade values of 0.0301794 and 0.0276172, respectively, according to GRA method. Furthermore, Spearman's rank correlation coefficient reveals that GRA is the most reliable method for ranking among the three techniques, with a correlation coefficient of 0.99164, which is the highest among all three methods. To validate the robustness of the results, the weights of beneficiary attributes are varied from 50% to 80% using the GRA method. It is observed that the ranking remains consistent despite the changes in weights. Overall, this study demonstrates the effectiveness of using thermodynamics-assisted MCDM techniques in selecting the optimal running fuel for a thermal power station. Based on the grey relational grade, GRA assesses the strength of correlation between several variables. The GRA method proves to be reliable and consistent in determining the rankings, providing valuable insights for decision-making in the fuel selection process.