Global Dataset of Solar Power Plants: Multidimensional Integration and Analysis

TL;DR

This paper presents a comprehensive, standardized global dataset of nearly 59,000 solar power plants, integrating multiple data dimensions to support research and development in solar energy.

Contribution

It introduces a novel, reproducible methodology to compile a multidimensional, global solar plant dataset with 27 attributes, filling gaps in existing data sources.

Findings

The dataset includes 58,978 records with geographic, topographic, climate, and logistical data.

Descriptive analysis demonstrates the dataset's potential for knowledge discovery.

The dataset is publicly available for academic and professional use.

Abstract

The use of clean energy is a global trend, with solar photovoltaic plants serving as a cornerstone of this energy transition. To support this rapid growth, optimize energy utilization, and enable a wide range of applications and services, it is essential to have access to more sophisticated and detailed solar data. Specifically, existing datasets lack integration, contain significant gaps, and have limited geographic coverage. In contrast, this study proposes a reliable, standardized, and multidimensional dataset with a global scope. Through a reproducible methodology and automated processes, we have successfully collected, generated, and combined 27 attributes of geographic, topographic, logistical, climate, and power nature, which are critical for the study of photovoltaic plants worldwide. Based on descriptive statistical analysis of the 58,978 records comprising the compiled dataset, the raw data have been transformed into valuable information for the energy sector. This demonstrates the utility of this product as a source of knowledge discovery, publicly available to the academic and professional communities.