Photovoltaic Power Generation Research Based on Multidimensional Indicators

A 1% increase in PV generation could reduce China's power sector carbon emissions by 2.05% by 2035. This dataset likely contains results from a framework combining forecasting, optimization, and carbon assessment using PCA, t-SNE, and PSO. The data was uploaded by Pengying Fan in April 2026.

Use Cases

• Forecast photovoltaic power generation based on the multidimensional indicator system
• Optimize regional energy planning based on the described framework combining forecasting and assessment
• Assess carbon emission reduction potential based on the reported 1% PV increase scenario
• Validate model performance based on the reported R²=0.9975 metric

Strengths

• Model achieved a high R² value of 0.9975
• Framework integrates power forecasting, optimization, and carbon assessment
• Analysis quantifies a specific impact: 1% PV increase reduces sector emissions by 2.05% by 2035

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data may reflect geographic bias inherent to the China-focused analysis

Provenance

Source

figshare

Collection Method

Framework combining a multidimensional indicator system, PCA, t-SNE, and PSO

Freshness

Last updated 2026-04-29 05:57:30

Geography

China