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.

翻译：清洁能源的使用已成为全球趋势，其中太阳能光伏电站是这一能源转型的基石。为支撑其快速发展、优化能源利用并赋能广泛应用与服务，获取更精细、更详尽的太阳能数据至关重要。具体而言，现有数据集缺乏整合、存在显著空白且地理覆盖范围有限。相比之下，本研究提出了一套可靠、标准化且覆盖全球的多维度数据集。通过可复现的方法论和自动化流程，我们成功收集、生成并整合了地理、地形、物流、气候及电力属性等27项特征，这些特征对于全球光伏电站研究至关重要。基于对包含58,978条记录的汇编数据集进行描述性统计分析，原始数据已被转化为对能源行业有价值的信息。这证明了本产品作为知识发现来源的实用性，可公开供学术界和专业社区使用。