IEC TS 61 724 2 Edition 1 0 201 6 1 0 TECHNICAL SPECIFICATION Photovoltaic system performance – Part 2 Capacity evaluation method IE C T S 6 1 7 2 4 2 2 0 1 6 1 0 (e n ) ® THIS PUBLICATION IS COPYRIGH[.]
General
To define the temperature dependence of a photovoltaic (PV) system's power output, it is essential to consider two key aspects: first, the relationship between weather conditions and module temperature, and second, how the power output varies as a function of module temperature.
Module temperature can be directly measured using a sensor on the back of the module, as outlined in IEC 61829 or Annex B of IEC 61724-1:2016, or with a calibrated infrared camera This temperature is influenced by both weather conditions and the quality of installation, as improper module installation or poor mounting design can lead to higher operating temperatures than expected To accurately assess module operating temperature, ambient temperature and wind speed can be utilized to calculate an expected average Additionally, measurements from IEC 61853-2 can enhance the model for determining module temperature based on ambient conditions.
Example heat transfer model to calculate expected cell operating
This section introduces a heat transfer model that has shown promising results, but it is essential for practitioners to select the model that aligns best with their specific circumstances It is crucial to utilize consistent heat transfer models when establishing capacity performance targets and reference conditions.
The module and cell temperatures may be described by Equations (A 1 ) and (A.3):
Tm = Gmeas ã [e ( a + b ã WS ) ][°C m 2 /W] + Ta (A 1 ) where
Tm is the calculated module back surface temperature (°C);
Gmeas is the measured POA irradiance (W/m 2 );
Ta is the measured ambient temperature (°C);
WS is the wind speed corrected to 1 0 m height (m/s); a is the module glazing coefficient (see Table A 1 ); b is the forced convection glazing coefficient (s/m); e is the natural logarithm base
WS is the the wind speed corrected to a 1 0 m height or to the height that is relevant to the power model;
WSmeas is the as measured wind speed;
H is the height used by performance model (m) (typically 1 0 m);
Hmeas is the above grade anemometer height (m);
I EC TS 61 724-2: 201 6 © I EC 201 6 – 23 – α is the resistance coefficient for ground cover or the Hellmann exponent
The conductive temperature drop between the module's back surface and interior PV cell can then be calculated from Equation (A 3)
Tc = Tm + ( Gmeas /1 000 W/m 2 ) ã dTcond [°C] (A.3) where
Tc is the calculated cell temperature (°C); dTcond is the conduction temperature coefficient to determine the difference between module surface and cell centre (°C)
The coefficients a, b, and dTcond are essential for establishing temperature dependence and can be obtained from experimental data or referenced from literature for comparable configurations, as shown in Table A.1 If the wind speed data used for measurements and modeling are collected at the same height, the wind speed correction in Equation (A.2) can be disregarded.
Table A.1 – Empirically determined coefficients used to predict module temperature
M odu le type M ou nt a b
Gl ass/cel l/gl ass Open rack − 3, 47 − 0, 059 4 3
Gl ass/cel l/gl ass Cl ose roof m ount − 2, 98 − 0, 047 1 1
Gl ass/cel l/pol ymer sheet Open rack − 3, 56 − 0, 075 0 3
Gl ass/cel l/pol ymer sheet I nsul ated back − 2, 81 − 0, 045 5 0
Pol ymer/thi n -film/steel Open rack − 3, 58 − 0, 1 1 3 3
N OTE Wi n d speed was measu red at th e stan d ard meteorolog ical hei g ht of 1 0 m
The Hellmann coefficient is influenced by both air stability and terrain shape It is advisable to choose values from Table A.2, and the uncertainty analysis must assess how sensitive the final results are to the selected values from Table A.2 or any other model assumptions.
Table A.2 – Hellmann coefficient, α , for correction of wind speed according to measured height, if values in Table A.1 are used
U n stabl e ai r above flat open coast 0, 1 1
N eu tral ai r above fl at open coast 0, 1 6
U n stabl e ai r above hu man inhabi ted areas 0, 27
N eu tral ai r above hu man i nhabi ted areas 0, 34
Stabl e ai r above flat open coast 0, 40
Stabl e ai r above hu man inh abited areas 0, 60
In certain designs, temperature coefficients can significantly vary with wind direction Therefore, accurately measuring wind direction and adjusting the temperature model accordingly can enhance the precision of the testing process.
To accurately measure the back-of-module temperature, it is essential to define the system and test boundaries Once these parameters are established, only Equation (A.3) is required, with Tm set to the measured temperature Proper measurement of the back-of-module temperature should follow the specified guidelines.
The evaluation of junction temperature can be conducted using IEC 60904-5, but this method poses challenges for continuously operating systems, as it relies on measured open-circuit voltage This approach may not accurately reflect the actual rear surface temperature due to rapid fluctuations caused by changes in irradiance from high wind and cloud movement Therefore, it is crucial to assess the electrical output power of the system under stable irradiation conditions, as outlined in the filtering criteria in Table 1.
Additionally, the power coefficient relating the cell temperature to the relative change in system output is defined and the power is corrected according to Equation (A.4)
CFTcell is the operating temperature cell correction factor; δ is the PV power − cell temperature coefficient taken from the product literature
(note that this coefficient has a negative value (1 /°C));
Tc is the cell temperature calculated from measured meteorological conditions using a heat transfer model or from measured module temperature;
TTRC refers to the cell temperature linked to the target reference conditions (TRC) It is essential to calculate TTRC using the same model employed to establish the target power for the specified TRC.
Annex B (informative) Example of model for system power
General
The model for the electrical power output of a system can be fairly simple or complex A simple example is given here.
Example model
In the context of implementing a linear assumption, the plant power is defined by Equation (B.1) The correction factor for irradiance, as outlined in Equation (B.2), incorporates the effects of module temperature based on a linear temperature correction assumption.
PPred = ( PPredTarg ) ⋅ ( Gmeas / GTRC ) + Pzero ⋅ (1 – Gmeas / GTRC ) (B 1 ) where
PPred is the predicted power;
PPredTarg is the predicted power at targeted conditions;
Gmeas is the measured irradiance;
GTRC is the rating irradiance used to specify the target power;
Pzero is the (negative) intercept often observed when plotting the output power as a function of irradiance when inverters require a minimum power input to function
Adding a temperature correction to Equation (B.1 ) and neglecting the Pzero term results in the following relationship to predict power from measured irradiance and cell temperatures:
PPred = ( PPredTarg ) ⋅ ( Gmeas / GTRC ) ⋅ [1 + δ ( TC – TTRC )] (B.2) where δ is the temperature coefficient taken from the product literature;
TTRC is the cell temperature calculated by the thermal model at the TRC conditions;
TC is the cell temperature calculated for each measurement point (see Annex A for an example of how this may be calculated)
See 6 3 4 for use of Equation (B.2) in calculating the correction factor
Annex C (informative) Inconsistent array orientation
The orientation of an array may vary because of:
• unintentional variation due to tracker malfunction or misalignment for part of an array;
• intentional variation to follow the local terrain in an uncontrolled way;
• intentional variation to specified orientations, such as on a roof with two different orientations
Defining methods for dealing with each of these situations is outside of the scope of this document The purpose of this annex to provide guidance rather than specific methods
An energy test is typically defined based on a specific orientation, indicating that it should be conducted according to the designed orientation However, applying this capacity test to the designed orientation rather than the installed orientation may result in an inaccurate evaluation of the system.
To optimize the performance of a solar array, irradiance sensors should be strategically placed to align with the array's configuration In larger systems with less controlled alignment, it may be advantageous to install sensors for each section of the plant The selection of the number and locations of these sensors should account for various orientations, and the data collected must be weighted according to the proportion of modules in each orientation This approach ensures an accurate assessment of the average irradiance experienced by the array under evaluation, and all details should be mutually agreed upon by the involved parties.
Typically, the test is not conducted when a tracker is malfunctioning; however, if an array is misaligned, the previously outlined strategy can be implemented.
When different parts of a system are oriented differently and connected to separate inverters, it is advisable to conduct tests on each part individually Conversely, if multiple arrays with varying orientations are linked to a single inverter, the irradiance measurements must be adjusted to account for the proportions of each array's orientation.
I EC 60904-5, Photovoltaic devices – Part 5: Determination of the equivalent cell temperature (ECT) of photovoltaic (PV) devices by the open-circuit voltage method
I EC TS 61 724-3, Photovoltaic system performance – Part 3: Energy evaluation method
IEC 61 829, Photovoltaic (PV) array – On-site measurement of current-voltage characteristics
IEC 61 853-2, Photovoltaic (PV) module performance testing and energy rating – Part 2: Spectral response, incidence angle and module operating temperature measurements
IEC 62446-1 , Photovoltaic (PV) systems – Requirements for testing, documentation and maintenance – Part 1 Grid connected – Documentation, commissioning tests and inspection ISO 5725, Accuracy (trueness and precision) of measurement methods and results
Photovoltaic Array Performance Model, D.L King, W E Boyson, J A Kratochvill, Sandia Report SAND2004-3535, 2004 prod sandia gov/techlib/access-control cgi/2004/043535 pdf Sandia’s PV Performance Modeling Collaborative, https: //pvpmc.sandia gov/
IEA PVPS (Photovoltaic Power Systems Programme of the I nternational Energy Agency) Task1 3 (Performance and Reliability of Photovoltaic Systems), http: //iea- pvps.org/index php?idW
ASTM E2848-1 3, Standard test method for reporting photovoltaic non-concentrator system performance
A Fundamentals Approach to (PV) Plant Capacity Testing, T A Dierauf, S Kurtz, E Riley, B Bourne, EU PVSEC 201 4 Paper 5AO_7_1 _A