Supplementary file 1_Multi-criteria ranking of renewable energy alternatives for smart gri

Supplementary file 1 by Wenfeng Geng presents a decision support framework for prioritizing renewable energy technologies in smart grids. The framework applies an expert-weighted TOPSIS method to rank four alternatives—solar PV, wind, hydropower, and biomass—based on four criteria. The dataset, last updated on 2026-04-30, is a 19.7 KB DOCX file containing the methodology and results, including closeness coefficients and sensitivity analysis.

Use Cases

• Ranking renewable energy technology alternatives for smart grid planning based on the described efficiency, cost, emissions, and resource availability criteria.
• Conducting sensitivity analysis on technology prioritization based on the described ±30% weight variation and equal weighting scenarios.
• Replicating or adapting the expert-weighted TOPSIS decision framework for other regions using updated local data and stakeholder-defined weights.

Strengths

• The methodology is explicitly described, applying a TOPSIS framework with four criteria and four alternatives.
• Results include specific closeness coefficients for ranking: solar PV (0.9211), wind (0.6220), hydropower (0.3759), and biomass (0.0253).
• Sensitivity analysis with ±30% weight variation and equal weighting was performed, demonstrating the ranking's robustness.

Limitations

• The dataset is a 19.7 KB DOCX file, indicating a very limited scope, likely a supplementary document rather than a primary data table.
• Row count and column-level documentation are unknown, which may limit suitability assessment for direct computational use.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

Wenfeng Geng via figshare

Collection Method

A decision support framework based on expert-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).

Freshness

Last updated 2026-04-30 05:24:15; freshness should be verified.