The Performance Ratio (PR) indicator is commonly used to assess the maintenance status and efficiency of photovoltaic farms. Although PR and other indicators like AR or EPI aim to measure the performance of installations, their usefulness is very limited. Let’s take a closer look at why PR is not the best tool for evaluating the condition of a solar farm and the potential pitfalls associated with its use.
Introduction
The condition of a photovoltaic farm directly depends on the quality of its maintenance, which in turn relies on the accuracy of detecting installation issues. At first glance, indicators like PR seem to be an ideal measurement tool. However, a deeper analysis reveals that discrepancies in their results can reach up to 10 percentage points. This means that both a PR of 100% and 90% may not trigger a reaction from maintenance managers (O&M). Such a wide margin of uncertainty can lead to unnoticed energy losses and impact the profitability of the installation.
Why is PR not reliable?
Below, we present 8 main reasons why the Performance Ratio indicator is not a sufficient tool for monitoring the efficiency of photovoltaic farms.
1. Irradiance Sensor
The PR calculation is based on readings from the weather station that measure irradiance. Different types of sensors are used in photovoltaic farms, creating a risk of inconsistent measurements. The key difference lies in using Reference Cell sensors versus pyranometers. Readings from these devices can vary significantly. The Reference Cell is more accurate as it measures irradiance in the plane of the PV modules (Plane of Array – POA), which better reflects the impact of sunlight on energy generation. Differences in sensor class and calibration accuracy also fall into this category.
Therefore, the use of different measurement methods may be surprising. However, it’s important to note that some farms don’t have weather stations at all. In such cases, any sensor is better than none, but striving for more accurate solutions is always beneficial.
2. Inverter capacity and Power Clipping
The PR indicator does not account for inverter capacity. When the AC power reaches its maximum level, the PR value is reduced. While this situation does not require intervention, it distorts the PR value. This phenomenon can go unnoticed, especially when PR is analyzed over longer periods (monthly, quarterly, or yearly). While tools like PVSyst can account for this phenomenon over the long term, it’s worth noting that it makes interpreting the result challenging, which may desensitize the response to this parameter’s variability.
3. Long measurements periods
PR is usually calculated on an annual, sometimes quarterly or monthly basis, allowing for comparison with historical values. However, such a long measurement period can mask small but significant anomalies. As a result, important issues may go unnoticed, leading to energy losses of around 5-7%. Daily measurement can be used, but it is subject to high variability due to the influence of several factors described in this article. Thus, averaging results over longer periods, while seemingly providing a sense of stability, can actually lead to negligence. On one hand, averaging stabilizes the indicator’s value, but on the other, it accumulates the errors inherent in this method.
It should also be noted that with such long assessment periods, response to potential issues is naturally not quick, limiting the effectiveness of corrective and optimization actions.
4. Averaging the indicator for entire solar farm
Like long measurement periods, averaging PR for the entire farm masks problems in individual components of the installation. To illustrate this issue, let’s consider a simplified scenario. Imagine a 1 MWp farm where one string has stopped working. The loss is just 1.4% of total production, which is unlikely to be detected based on PR. If we shift our focus from technicalities to financial aspects, we quickly notice that even this level of loss is significant from the perspective of margin and return on investment.
5. Inverter efficiency
The Performance Ratio only considers the DC side of the installation, ignoring other crucial aspects such as inverter efficiency. For example, modern devices achieve efficiencies of around 97-98%, but if an older installation is in the portfolio, its efficiency may be lower. Therefore, the absolute PR value for each of these farms will mean something different.
6. Shutdown and curtailment periods
Power restrictions imposed by the grid have a significant impact on PR. In the case of power surpluses in the grid, these restrictions are becoming more frequent and harder to manage. Besides distorting the PR value, there is also a problem with proper reporting and settlement with the Asset Owner when PR is reduced due to factors beyond O&M’s control.
7. PV module temperature
The basic PR indicator does not account for the impact of PV module temperature, which significantly affects production efficiency. This causes PR to be higher in autumn and winter than in summer. While it is possible to use PR temperature corrected, this requires more complex calculations, which are often overlooked.
8. PV module degradation
Over time, PV modules lose their efficiency, affecting PR. Although this is a natural process, an older farm will show lower values. Therefore, in the case of farms with varying operation times, comparing indicators can be misleading, as low values may not reflect the actual technical condition of the installation.
EPI and PR Target — Do they solve the problem?
Modern indicators like EPI or PR Target attempt to correct PR’s shortcomings but still rely on assumptions and averages that do not reflect the real situation. While they seem to be a step forward, their use does not eliminate the issue of measurement uncertainty.
Conclusion
Typical performance indicators like PR have their limitations, mainly due to averaging results, long assessment periods, and interpretation based on model and historical data. To effectively monitor photovoltaic farms, a more detailed, data driven infrastructure analysis is needed, considering operating conditions and all circumstances in real time. This approach provides a very accurate measure, free from significant uncertainty errors, while also being straightforward in interpreting the solar farm’s condition and necessary interventions. This is the key to achieving higher efficiency and minimizing energy losses.
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