Assessing Solar Photovoltaic Efficiency and Reliability: A Data-Driven Analysis of Environmental and Inverter Factors

Mumtaz Anwar Khan

doi:10.69968/ijisem.2025v4i486-97

Authors

Mumtaz Anwar Khan Research Scholar, Computer Science and Technology, Sam Global University

DOI:

https://doi.org/10.69968/ijisem.2025v4i486-97

Keywords:

Solar Power Plant, Energy Yield, Regression Analysis, Elasticity Analysis

Abstract

The study delivers a thorough evaluation of the PV solar power plant performance, with a spotlight on energy generation, efficiency, and system's environmental impacts. A data-driven method has been introduced for this purpose and the high-resolution data of generation and weather covering the 33-day period has been scrutinized. The main performance indicators, i.e., the Performance Ratio (PR) and Power Conversion Efficiency (PCE), were computed. According to the research, the system reliability was extraordinarily high, as the inverter PR values remained consistently high (0.991–0.997), which implies that the energy produced was very close to the plant's nominal capacity. The PCE measurement indicated that the conversion from DC to AC was very good (PCE averages of about 9.77%). The use of correlation and multiple linear regression techniques led to confirming that the irradiation is the overwhelmingly primary factor that influences the AC power output, having a share of 92% in the whole AC power output variation ( ). The thermal aspect was acknowledged, although the analysis of the temperature coefficient led to the conclusion that there might be the heating of the module, but that heating has the least impact on the system efficiency. Besides, the elasticity and regression studies have shown the substantial influence of changes in irradiation and module temperature on power output. The results suggest that the photovoltaic power plant is not only operating-but-also-is-an-efficient-and-reliable-source-of-power and besides that, it is providing valuable data for system health monitoring, energy production improvement, and future operations and maintenance strategies designing.

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