Multi-criteria ranking of renewable energy alternatives for smart grids using expert-weighted TOPSIS

Introduction High penetration of renewable energy sources increases operational variability and planning uncertainty in smart grids. Transparent prioritization of technologies is required before detailed sizing and dispatch analysis. Methods A decision support framework based on expert weighted Technique for Order Preference by Similarity to Ideal Solution is applied. Four alternatives, solar PV, wind, hydropower, and biomass, are assessed using four criteria: efficiency, cost, emissions, and resource availability. Criteria weights from pairwise comparisons are 0.562, 0.254, 0.125, and 0.059. Results Closeness coefficients from the weighted normalized matrix rank the options as follows: solar PV (0.9211), wind (0.6220), hydropower (0.3759), and biomass (0.0253). Sensitivity analysis with ±30% weight variation and equal weighting preserves the ranking. Discussion The framework is shown to be transparent, robust, and easy to replicate. Adaptation to other regions is enabled through updated local data and stakeholder defined weights.