Srishti Agarwal
Rukmini Devi Institute of Advanced Studies (Guru Gobind Singh Indraprastha University, Delhi)
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http://doi.org/10.37648/ijrst.v14i02.009
Power plants operate with high capital intensity, complex regulatory risk, and volatile fuel markets. Conventional ratio or regressionâ€based assessments often struggle with short samples, missing values, and mixed monotone criteria. This paper proposes an Improved Gray Correlative Analysis (IGCA) framework—combining grey normalization, entropy weights, and an optimally tuned distinguishing coefficient—to evaluate the short-to-medium-term financial condition of power plants. We synthesize methodological advances in Grey System Theory between 2013–2023, including inscribed-core GRA for improved discrimination, entropy-based weighting, and sensitivity to the distinguishing coefficient. We then offer a step-by-step protocol and an illustrative application to a small portfolio of thermal plants using standard financial ratios (liquidity, leverage, coverage, profitability, cash-flow strength, and capex burden). Comparative analysis shows that IGCA preserves rankings found by classical GRA and TOPSIS while increasing separation among alternatives—supporting clearer decisions for lenders, regulators, and owners.
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