Why is accurate performance assessment of decentralized PV systems a must?

Assessing solar photovoltaic (PV) performance is crucial to ensure optimal plant operation and financial feasibility. This is relevant for any scale - on the wide spectrum of grid connected PV systems from residential size to solar fields. A whole field of applied mathematics has developed to address this issue, with multiple researchers engaging in model optimizations to find the best possible tools and models to assess PV performance. There is a variety of tools for the task - such as onsite weather sensors, satellites, regional weather stations and novel algorithmic solutions - all essentially utilized for calculating PV performance at various levels of accuracy.

Fig.1 The performance assessment map is based on the work by SunSpec Alliance and the San Jose State University (2014).

Basic-level performance assessment for Solar PV

At the basic level, solar PV performance can be assessed using commonly available tools. Manual review of inverter or utility energy meter readings and comparing them with historical monthly averages of the same system is one approach. Alternatively, using performance modeling tools such as PVSyst, PVSol, and PVWatts offers a better independent benchmark for monthly performance. These methods typically achieve 80-85% accuracy on a monthly resolution and about 90-95% accuracy on an annual resolution, sufficient for financial reports.

Another straightforward technique is peak system power measurement, a simplified way to measure the Power Performance Index (PPI). This method provides a fair estimate of system performance during the month with about 85% accuracy and can even be utilized daily, albeit with lower accuracy. Lastly, it is common to compare normalized energy output of a system with nearby PV systems - which can bring about 80-90% accuracy on monthly scale. These methods are typical for residential and small commercial segments due to their low cost and simplicity, making them adequate for basic financial reports but not for professional Operation and Maintenance (O&M) requirements.

Advanced-level PV performance assessment

Advanced-level PV performance measurement can be achieved with independent tools, including onsite weather sensors, satellites, and regional weather sensors. These tools calculate performance indicators such as Performance Ratio (PR), Power Performance Index (PPI), and Energy Performance Index (EPI) with varying accuracy levels. High-tier onsite weather sensors enable 95% accuracy on daily resolution (with temperature correction), while lower-tier sensors and satellites offer around 85-90% daily accuracy. Regional weather stations may be less accurate but still provide daily resolution necessary for professional operation & maintenance (O&M). Incorporating these advanced tools and real-time weather data into energy management systems is crucial. Accurate PV performance assessment ensures that energy production forecasts are reliable, which in turn supports effective decision-making for grid management and energy distribution. By leveraging advanced PV performance assessment tools, energy management systems can better predict and manage solar energy contributions, ensuring consistent and dependable energy production.

Expert-level PV performance assessment

Solar PV performance assessment at the expert level involves a combination of high-tier weather sensing hardware and sophisticated software tools. This hardware, equipped with irradiance sensors, temperature sensors, and wind speed meters, is meticulously calibrated to ensure real-time accuracy. The sensors are combined with advanced software that incorporates proprietary algorithms, and increasingly, artificial intelligence (AI), to analyze and predict solar performance under varying environmental conditions. By continuously adjusting based on live data, these tools can achieve daily resolution accuracy rates as high as 95-98%. This level of precision is particularly important for utility-scale solar PV systems, where even minor anomalies, such as soiling or equipment degradation, can impact energy output and operational efficiency.

However, the integration of high-tier weather sensing technology comes at a significant cost. The hardware required for expert-level performance assessment is expensive to install and maintain, and the software often demands custom calibration labor and licensing fees. Additionally, the use of AI-driven analytics requires costly computing and continuous updates to ensure the algorithms remain optimized for changing conditions. Due to the high financial investment, these solutions are most commonly found in large-scale utility PV projects, where the return on investment (ROI) justifies the expenditure. In smaller-scale or C&I solar PV systems, more cost-effective alternatives are typically used, often with lower accuracy and fewer real-time capabilities.

Novel methods: high accuracy PV performance measurement

New methods for high-accuracy PV performance assessment are being developed with the goal of achieving top-tier accuracy at lower costs. These methods often combine various techniques to optimize results. For instance, some approaches merge affordable satellite data with regional ground-based weather stations to deliver accurate performance insights at a fraction of traditional costs. Another innovative example involves using IoT networks of uncalibrated sensors from surrounding areas to estimate environmental conditions impacting PV systems. Additionally, advanced AI algorithms are increasingly employed to fine-tune these diverse data sources, enabling more precise monitoring without expensive hardware setups. These hybrid solutions are paving the way for more cost-effective and scalable solar PV performance assessments.

Soltell is proud to be part of the global effort to optimize solar PV energy finance, operations, and integration. With innovative Sensorless technology, we deliver high-precision performance measurement without the need for external weather sensors. The solution embedding the technology provides key metrics such as the Energy Performance Index (EPI), Power Performance Index (PPI), Soiling Ratio (SR), and Availability, all with impressive accuracy. By simplifying performance assessment and improving data-driven decision-making, Soltell is helping to streamline the efficiency and financial sustainability of solar energy projects worldwide.

In addition, Soltell's SysMap solution provides the proprietary Intactness Index (Intact), which offers a superior quantitative approach to assessing PV performance. It combines technical assessment for components of a photovoltaic system with quantitative performance indicators using proprietary algorithms. This proprietary indicator is significantly more accurate than monthly performance models based on seasonal averages, which can have a monthly deviation of ±20% due to weather variations and model inaccuracies. The Intactness index is also superior to other performance indexes used across the decentralized energy resources (DERs) industry such as remote sensing approach and reliance on regional weather sensors.

Fig.2 Energy Performance Index via Sensorless technology detecting chemical staining, which can't be identified with hardware sensors. Measurement of a 150kW rooftop PV system in an industrial area, during and after a chemical staining event affecting the modules.

In summary, Soltell's Sensorless technology enables the cost-effective application of proprietary algorithms to residential and commercial PV plants, achieving an uncertainty level of 2-6% on daily resolution. This results in a performance assessment accuracy level of 94-98%, enabling superb industrial automation with priority-enabling ratings and predictive maintenance capabilitie comparable to high-tier automation tools.

Interested in Sensorless technology for measuring PV performance and integrating it into an energy management software or a service application? Fill-in the demo request to get more details.