Results vary considerably between months, although there is a clear trend to improve under lower solar angles, with a greater percentage gain in winter months.
- 01. Introduction
- 02. Algorithms in Solar Tracking Plants
- 03. Bifacial Tracking or tracking Bifacial Algorithm
- 04. Algorithm Functioning
- 05. Input Variables
- 06. Methodology
- 07. Anaytical Testing
- 07.1. Annual Results
- 07.2. Monthly Results
- 07.3. Climate Sensivity
- 07.4. Bifacial Gain
- 08. Combination with Diffuse Booster and Teamtrack
- 09. Experimental Testing
- 10. Conclusions
The use of bifacial photovoltaic modules has increased significantly since 2017, although the bifacial module technology is not new. The first bifacial cells at a lab-scale date back to the 1960s, whereas the technology was first marketed in 1981 by Isofotón, a Spain-based company ref. 1.
In the 90s, a number of sound barriers made up of bifacial modules in a portrait configuration (90 degrees) were installed in the Swiss city of Zurich, but it was not until the end of last decade that this technology became more popular on the marketplace. Nowadays, it is used in a large number of solar plants worldwide due to its greater energy efficiency, although it has also given rise to discussions and new prospects on how to enhance solar plant and tracker design in order to increase bifacial photovoltaic module performance.
In that sense, Soltec designed in 2015 the first solar tracker with bifacial panels for the La Silla plant ref. 2, carrying out since then multiple trials and tests, both a lab and experimental level ref. 3, with the aim to enhance tracker design and increase bifacial gain. The term “bifacial gain” refers to the amount of energy generated by the backside in relation to the frontside, considering the former is affected by various parameters such as albedo, tracker height, shadowing, module temperature and inter-row spacing. This time, Soltec’s Innovation Team went a step further to design a specific bifacial module algorithm capable of optimizing tracker position, thus increasing plant production ref. 4.
Solar tracking relies on astronomical algorithms or sensors. Soltec uses an astronomical algorithm developed in-house based on solar positioning data from NREL-SPA ref. 5, This algorithm sends information to the tracker with the aim of placing it at a particular angle depending on the Sun’s position. That is how the basic tracking algorithm works. However, with the aim to increase production, there are other algorithms, such as backtracking, TeamTrack in the case of Soltec, which are used to prevent shadowing between tracker rows in the early and late hours of the day, or the Diffuse Booster ref. 6 which uses weather information (forecast and onsite measurements) to enhance production when diffuse radiation is greater than direct radiation.
The bifacial tracking algorithm seeks to find the optimal solar tracker position in a photovoltaic plant by taking into account the total amount of front and rear radiation. Until now, tracking algorithms only considered front radiation to calculate the tracking angle, that is, they followed the sun in order to increase Global Plane Of Array (GPOA) irradiance. However, in the case of a plant with bifacial modules, it is possible that depending on the value of some specific parameters, that position might not be optimal for maximized production. In such cases, estimating Global Rear Irradiance (GRI) on the panel rear side plays a key role. Thus, Soltec’s bifacial tracking constitutes a step forward in bifacial technology implementation, in the sense that solar tracking is adapted to it.
This algorithm is used to determine the solar tracker angle at which the production of a particular bifacial module in a specific solar plant is maximized. To do that, the algorithm estimates power generation for a set of possible angles, choosing the optimal one. This estimation takes into account front and rear irradiance, as well as electrical module performance.
For each angle, the Electrical output Power (EP) is calculated as the sum of Electrical Power in the Front side (EPF) and Electrical Power in the Rear side (EPR), as shown in the following equation (1). EPF and EPR are obtained taking into account power conversion efficiency (η) and module bifaciality (BIF) for each side depending on GPOA and GRI, including an irradiation Mismatch Rear-side Factor (MRF), as shown in the equation below (2).
|Eq = EPF EPR||(1)|
|E = η GPOA η BIF GRI (1 – MRF)||(2)|
The GPOA is calculated using traditional methods ref. 7, whereas the GRI estimation is obtained with the application of ray-tracing techniques ref. 8 and 9 and comprehensive modeling. Global and diffuse horizontal irradiance are used as input data. The inclination angle as well as the tracker and scene geometry (descriptive plant parameters) are also used, including the surface reflectance colors and coefficients of all items. Simulations provide a module surface irradiance distribution which is then used to calculate the average GRI value and estimate the MRF ref. 10.
To design the algorithm, Soltec took into account some descriptive plant parameters which influence bifacial module production and, in turn, tracker position.
Soltec also considered other parameters and variables obtained during plant operation, such as the following:
- Global and diffuse horizontal irradiance: The algorithm uses solar irradiance data to calculate the GPOA and GRI of upcoming intervals. Such data is obtained from weather forecasts and then validated by means of plant sensors so as to enhance accuracy.
- Albedo (percentage of radiation reflected by a surface in relation to the irradiation it receives): The algorithm uses the plant soil albedo value established beforehand for each month. In the case of soils with a dynamic albedo, the system also allows an external configuration which favors increased efficiency and online updates.
The algorithm processes descriptive photovoltaic plant parameters as well as operating variables, albedo and irradiation, to calculate the optimal angle at which bifacial generation is maximized. With the aim to optimize algorithm effectiveness, detailed modeling of the plant’s operating mode and geometry is carried out during a preliminary phase known as “Adjustment Phase”, where key performance parameters are calculated. Later, during the Operation Phase, the algorithm is used to calculate the deviation angle in relation to the monofacial tracking position, integrating the obtained value within the remaining plant performance algorithms (e.g. TeamTrack) in order to maximize gain under various environmental conditions.
It applies to 1-in-portrait and 2-in-portrait trackers. Due to a highly detailed geometrical plant modeling, it is optimized for application to soils with a dynamic albedo, as well as for Albedo Enhance Materials (AEM), including an update of the reflection surface area dirt level. Since the algorithm was designed for 50-MW plants, in the case of plants with a greater power output, it should be applied to modules or subfields of less than 50 MW. It is compatible with all commercial bifacial modules, regardless of the number of cells (72, 78), transparency, technology, frameless and framed.
The performance and gain of the bifacial tracking algorithm depends on the following:
- Weather conditions: level of irradiation and percentage of diffuse radiation.
- Accuracy of weather forecast.
- Site latitude.
- Soil albedo.
Testing carried out by Soltec aims to quantify the power output gain obtained with this algorithm by combining all above-mentioned variables. Tests were carried out in three different latitudes: Mediterranean, Equatorial and Northern, for a 50-MW plant and albedo levels of 20%, 30% and 40%. Obtained results can be seen below on tables 1, 2 and 3:
Being Δ Total = annual gain, Δ Period = gain for activation period and Δ Max hour = Maximum value reached in 1 hour.
|Albedo %||Δ Total kWh/kWp/year(%)||Δ Period %||Δ Max hour %|
|Albedo %||Δ Total kWh/kWp/year(%)||Δ Period %||Δ Max hour %|
|Albedo %||Δ Total kWh/kWp/year(%)||Δ Period %||Δ Max hour %|
Results in the tables show that the algorithm is able to increase plant power generation around 0.10% in Mediterranean latitudes, with an albedo of 30%. As for Northern sites with the same albedo, the increase amounts to 0.12%. In the case of Equatorial sites, there is a substantial increase under conditions of high albedo (40%), with a gain of 0.11%.
The differentiating element of this algorithm is its capacity to adapt to climate conditions based on weather forecast information. Results show that, with a few exceptions in the Equatorial case, the lower the percentage of extra diffuse energy generated, the higher the bifacial tracking, as shown in the following graph, where penalties due to frontside disorientation are lower. However, this absolute increase is not so evident when the percentage gain is assessed, due to lower irradiation levels under these conditions.
Table 4 compares the impact of standard and bifacial tracking on the bifacial gain, the latter being the extra percentage of production of the bifacial module compared to that of a monofacial module. The bifacial gain increase translates into an economic gain for the plant, which in this particular case was calculated for a price of €50 per MWh. The results obtained are shown in the following table:
The bifacial tracking algorithm is compatible with other Soltec algorithms, more specifically, the ‘Diffuse Booster’, an algorithm capable of maximizing module generation when the diffuse radiation percentage is greater than the direct radiation percentage, as well as TeamTrack, capable of increasing plant generation in up to 6.2%.
Upon completion of analytical testing, Soltec launched some experimental testing on its test field in Murcia (Mediterranean latitude) with the aim to doublecheck simulation results and determine practical algorithm performance. To do that, two solar trackers were compared, one using the algorithm and the other a traditional tracking mode of monofacial modules. The difference in tracking angle behaviour is shown below.
Using the operational algorithm for an entire month contributed to an overall improvement of 0.183%, with a mean of 1.48%, a percentile 90 of 4.95% and a maximum value of 9.33%. Gain during the activation period was 0.37%.
Bifacial tracking was also tested at BiTEC California, with AEM [poster ref. – point 4] obtaining an algorithm gain compared to regular solar tracking of 1.64%. Another conclusion reached is the excellent sensitivity to weather forecasts of the algorithm.
After a reliability analysis carried out by the weather specialist contractor, the average diffuse ratio error was measured at 5.7%, with a hit rate of 89%, translating into an average angle error of 1.57º.
In that regard, the annual gain estimate is also sensitive to the selected meteorological year, especially considering that the impact of small diffuse variations is not negligible.
Total algorithm gain is potentially 0.29% (0.41% during activation period), and due to weather forecast inaccuracies, the total gain obtained in the end amounted to 0.18%. Using the same parameters as before, i.e. for a 50 MW plant in Mediterranean latitude, we can estimate an economic gain for a Mediterranean latitude site, under albedo conditions of 30%, of €6,192 annually.
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ref. 2 A.Di Stefano, G. Leotta, F. Bizzarri. “La Silla PV plant as a utility-scale side-by-side test for innovative modules technologies”. 33rd European Photovoltaic Solar Energy Conference and Exhibition EUPVSEC2017 September 2017 Amsterdam. Proc 6CO.14.1 p.p 1978 – 1982, online reference: https://www.eupvsec-proceedings.com/proceedings?paper=44211
ref. 3 J.Guerrero-Pérez, I. Muñoz Benavente, J.Navarro, The Bifacial Year, Soltec White Paper, online reference https://soltec.com/wp-content/uploads/2019/11/BiTEC-whitepaper-4_en.pdf
ref. 4 J. Guerero-Perez, A.Ros Gomez, Tracking Algorithms for Improving Bifacial Modules Energy Yield with Albedo Enhance Materials and Agrivoltaics, Poster THU – E – 06 SiliconPv 11-14 April 2023 Delft
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ref. 6 Magnus Herz et all, 5.3% Diffuse Booster, Soltec White papers, online reference https://lab.soltec com/5-3-diffuse-booster/#02
ref. 7 R. Perez, P. Ineichen, R. Seals, J. Michalsky, R. Stewart. Modeling Daylight Availability and Irradiance Component from Direct and Global Irradiance. Solar Energy 44, no 5, pp 271-289, 1990.
ref. 8 Stein et al. 2019. Bifacial Photovoltaic Performance Optimization Using Ray Tracing and High Performance Computing, Keynote presentation at Photonics North, Quebec City, Canada. https://pvpmc.sandia.gov/download/7213/
ref. 9 Ayala Pelaez, C. Deline, P. Greenberg, J. S. Stein, and R. K. Kostuk, “Model and Validation of Single-Axis Tracking with Bifacial PV”, IEEE J. Photovoltaics, vol. 9, no. 3, 2019. https://ieeexplore.ieee.org/abstract/document/8644027
ref. 10 Chris Deline et all, Bifacial PV System Mismatch Loss Estimation and Parametrization, PVSEC2019 Marsella September 2019. https://www.nrel.gov/docs/fy19osti/74831.pdf
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