Global Dataset of Solar Power Plants: Multidimensional Integration and Analysis

The global expansion of renewable energy has increased the strategic importance of photovoltaic (PV) power plants and the demand for comprehensive, high-quality solar datasets to support energy planning, optimization, and data-driven applications. However, existing datasets are often constrained by limited attribute integration, incomplete information, and insufficient global coverage. This study presents a standardized, reliable, and multidimensional global dataset for photovoltaic power plant analysis, together with a largely reproducible and documented methodology that automates the collection, generation, and integration of heterogeneous solar-related data from multiple sources. Using this methodology, 27 geographic, topographic, logistical, climatic, and power-related attributes were integrated into a unified dataset comprising 58,978 photovoltaic plant records worldwide. Descriptive statistical analyses were performed to characterize the dataset and assess its informational richness and consistency. The results demonstrate that both the proposed methodology and the resulting dataset provide a robust foundation for photovoltaic energy research and decision-making across diverse application domains. By making this resource publicly available, this work facilitates reproducible research and supports the development of advanced analytical, predictive, and optimization models for academic, industrial, and policy-oriented applications.