The performance of photovoltaic (PV) module is mainly influenced by in-plane irradiance and module temperature parameters. At any site, variations of in-plane irradiance and module temperature depends on local weather parameters and these weather parameters vary significantly over large geographical area. The most frequently occurred value of in-plane irradiance and module temperature has major contribution in energy generation. In this manner, calculation of performance ratio (PR) based on most frequent operating condition (MFOC) will give an accurate indication of performance under local climatic conditions. Thus, estimation of MFOC is important and its mapping over a large geographical area will be useful for PV systems performance assessment. The objective of present study is to map MFOC of PV module across India. For this purpose, a new scheme of climate classification has been developed. The 58 different sites have been selected and weather data of each site has been used to estimate irradiance, module temperature, and output power, which are analyzed to identify MFOC. The estimation MFOC has been verified with experimental data. Based on present study, seven MFOC have been found for India. Results show that the PR under MFOC is lower than the conventional PR by up to 4%.

光伏 (PV) 组件的性能主要受面内辐照度和组件温度参数的影响。在任何地点，面内辐照度和模块温度的变化取决于当地的天气参数，而这些天气参数在大的地理区域内变化很大。面内辐照度和模块温度最常出现的值对能量产生有重大贡献。以这种方式，基于最频繁操作条件 (MFOC) 的性能比 (PR) 计算将给出当地气候条件下性能的准确指示。因此，MFOC 的估计很重要，它在大地理区域上的映射将有助于光伏系统性能评估。本研究的目的是绘制整个印度光伏组件的 MFOC。以此目的，已经制定了一种新的气候分类方案。选择了 58 个不同的站点，并使用每个站点的天气数据来估计辐照度、模块温度和输出功率，并对其进行分析以识别 MFOC。估计 MFOC 已经用实验数据进行了验证。根据目前的研究，已为印度发现了七个 MFOC。结果表明，MFOC 下的 PR 比常规 PR 低 4%。