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
Optimizing Anomaly Diagnosis with AI
Using machine learning models is a trend among companies seeking to increase the accuracy and efficiency of I-V curve evaluation during solar panel monitoring [4]. In this context, companies like Huawei have launched innovative products such as the Smart I-V Curve Diagnosis 3.0 system, which can detect 14 types of anomalies, ensuring inspections in less time and with 100% accuracy [3]. Furthermore, real-time monitoring through machine learning offers significant potential for predicting and detecting early deficiencies.
Success Stories at ITIC-GROUP: Innovation in the Photovoltaic Sector
At ITIC-GROUP, we have extensive experience and capabilities to address diverse needs in the photovoltaic sector. We have worked with multiple photovoltaic solar plants, providing valuable information by identifying faults through I-V curve analysis, which enables enhanced performance.
Our I-V Curve Services
At ITIC-GROUP, we possess sophisticated equipment capable of covering any photovoltaic capacity in the Americas region, addressing monofacial and bifacial panels.
We are currently developing machine learning models to assist our technicians in detecting anomalies and ensuring more accurate I-V curve evaluations, thereby optimizing the efficiency and maintenance of solar panels.
Contact us in Colombia
Contact us in Colombia
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Contact us in USA
Contact us in USA
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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