Why are I-V curves important in photovoltaic efficiency?
I-V curves are essential for evaluating the electrical performance of solar panels and determining their maximum power point. These curves represent the relationship between current (I) and voltage (V) of a photovoltaic module under specific irradiance and temperature conditions. This analysis is widely used by companies and laboratories that offer operation and maintenance services for photovoltaic plants.
Issues in solar panel performance
Solar panels can experience low performance due to factors such as partial shading, hotspots, dirt, deterioration, bypass diode failures, poor design, and limited maintenance [1]. According to a report by the American company Raptor Maps, anomalies in photovoltaic systems have doubled between 2019 and 2022—mainly those related to cells and diodes—projecting a 6% anomaly rate for large-scale solar systems by 2025 [2]. In some cases, figures as high as 12.1% have been reported [3].
Economic impact of photovoltaic system failures
Average annual losses are approximately $3,350 per megawatt, highlighting the need for more frequent inspections by owners and operators of these assets.
Machine Learning in I-V curve analysis: A growing trend
Optimized anomaly diagnosis with AI.
Machine learning is increasingly being used to enhance the accuracy and efficiency of I-V curve evaluations in solar panel monitoring [4]. In this context, companies like Huawei have introduced innovative products such as the Smart I-V Curve Diagnosis 3.0 system, which can detect up to 14 types of anomalies, ensuring faster inspections with 100% accuracy [3]. Additionally, real-time monitoring with machine learning shows great potential for early prediction and detection of deficiencies.
ITIC-GROUP success stories: innovation in the photovoltaic sector
At ITIC-GROUP, we have extensive experience and the capacity to meet diverse needs within the photovoltaic sector. We have collaborated with multiple photovoltaic solar farms, delivering valuable insights through fault identification using I-V curve analysis, which improves performance.
Our I-V curve services
ITIC-GROUP employs sophisticated equipment capable of supporting any photovoltaic capacity in the Americas, including both monofacial and bifacial panels.
We are currently developing our own machine learning models to assist in anomaly detection and provide a more precise evaluation of I-V curves, optimizing solar panel efficiency and maintenance.
Contact us in Peru
Contact us in Peru
Get in touch with ITIC Group in Peru for certifications, inspections, and testing.
Contact us in USA
Contact us in USA
Get in touch with ITIC Group in USA for certifications, inspections, and testing.
References
[1] K. Hasan, S. B. Yousuf, M. S. H. K. Tushar, B. K. Das, P. Das, and M. S. Islam, “Effects of different environmental and operational factors on the PV performance: A comprehensive review,” Energy Sci. Eng., vol. 10, no. 2, pp. 656–675, Feb. 2022, doi: 10.1002/ESE3.1043.
[2] B. Santos, “Raptor Maps indicates the growing problem of low performance in photovoltaic systems,” PV magazine, 2023. https://www.pv-magazine.es/2023/03/07/raptor-maps-senala-el-creciente-problema-del-bajo-rendimiento-de-los-sistemas-fotovoltaicos/ (accessed Feb. 18, 2025).
[3] “What is Smart I-V Curve Diagnosis?,” Ambiente Soluciones. https://ambientesoluciones.com/portal/noticias-de-actualidad/que-es-el-diagnostico-inteligente-de-la-curva-i-v (accessed Feb. 18, 2025).
[4] E. Stanzani et al., “Application of Machine Learning to Predict I-V Characteristics of PV Modules Based on Steady-State Solar Simulator,” Jun. 2024, doi: 10.20944/PREPRINTS202406.0748.V1.
- Aníbal Alviz Meza.
- ITIC-GROUP
