Evaluation of the Effectiveness of Solar Array Simulators in Reproducing the Characteristics of Photovoltaic Modules
Abstract
:1. Introduction
2. Solar Array Simulator
2.1. Power Stage
2.2. Control Stage
2.3. Graphical Supervision Interface
2.4. Common Characteristics of SASs
- An internal algorithm that generates an I–V points table based on input parameters of the PV module, such as open-circuit voltage (), short-circuit current (), current at maximum power point (), and voltage at maximum power point (). This feature allows for a quick and easy approximation of the curve without the need for a computer to perform the simulation;
- An algorithm that allows the user to define a custom table of points to determine the I–V curve (user-defined lookup table). This feature enables users to have full control over the simulation and create specific tables for their project needs. Additionally, custom tables can be stored in the system’s internal memory, making it easy to access and reuse in future simulations;
- A shading mode that allows for simulation of shadow conditions, enabling the evaluation of their impact on the energy production of PV systems. The list mode is used to generate a list of operation points of the I–V curve of a PV module under different conditions, which is essential for determining the module’s efficiency in different situations.
3. Methodology and Characterization of the Evaluated SAS
- Steady-state operation: In this scenario, the SASs are tested under stable operating conditions, considering PV modules subject to constant solar irradiation and a constant temperature. By doing so, it becomes possible to evaluate how the sources respond and follow the global maximum power point (GMPP) in a steady state.
- Shading-induced curve change: This scenario simulates a situation where part of the PV module is shaded, resulting in a change in its characteristic power curve. By doing so, it becomes possible to assess how emulating sources respond to this change and whether they can properly track the new maximum power point.
- Performance during curve transitions: In this scenario, rapid and smooth transitions between different operating points of the PV module are considered. This can occur, for example, due to rapid changes in solar irradiation or ambient temperature. By doing so, it becomes possible to analyze whether emulating sources can accurately follow these transitions and capture variations in the GMPP.
Characterization of the Evaluated Emulating Sources
- SAS A is an emulating source equipped with a built-in 16-bit digital control, along with voltage and current measurement circuits. According to the manufacturer, this source is particularly suitable for real-time analysis of maximum power point tracking (MPPT) and for the monitoring of inverter tracking. However, this source does not allow the user to modify the internal control gains. The results obtained with SAS A are graphically represented in blue in the following sections of this work.
- SAS B is a fully programmable emulating source. Its dynamics are determined by the control gains imposed by the user in the graphical supervision interface, allowing for the digital adjustment of properties such as voltage, current, and power. Additionally, this source offers adjustable simulation of internal resistance. The multiprocessing architecture of SAS B enables not only the combination of different control profiles but also real-time data processing. The results obtained with SAS B are graphically represented in red in the following sections of this work.
4. Equipment and Settings Used to Evaluate Emulating Sources
4.1. Configuration 1: RC Load
4.2. Configuration 2: Buck–Boost Converter
5. Results
5.1. Steady-State Behavior of SAS
5.1.1. Results of SASs in Measurements with the Buck–Boost Converter Duty Cycle Varied Linearly
5.1.2. Steady-State Performance Evaluation
5.2. Transient Behavior of SASs
5.2.1. Transient Behavior for Source Connected in Buck–Boost Converter with Fixed Duty Cycle
5.2.2. Transient for Source Connected to RC Load
5.2.3. Transient with GMPPT
- CASE 1—Converter control with regular response time: In this application, the the control loop for the converter input voltage (voltage at the output of the emulated source) was designed that the system had zero error in a steady state, a crossover frequency of 3 kHz, a phase margin of 67.1°, and infinite gain margin. For this purpose, a PI controller with gains of = and = was used. The crossover frequency was selected to be ten times lower than the switching frequency, a common practice in static converters with only one control loop.
- CASE 2—Converter control with slow response time: In this application, the gains of the PI controller were decreased to reduce the system’s crossover frequency, making its dynamics slower. For this purpose, a PI controller with gains of = and = was used.
5.2.4. Evaluation of Transient Results
6. Conclusions
- Regarding static analysis, the analyzed SAS showed inaccuracies in the knee region and in the nonlinear region of the I–V curve, especially when configured to emulate only one module. However, it was observed that increasing the number of modules tended to significantly reduce inaccuracies.
- Regarding dynamic analysis, the analyzed SASs faced difficulties in following the reference curves during transitions. Their dynamic characteristics (resulting from the control system) and their slew-rate limitations ended up generating behaviors divergent from what is expected for PV modules. This limitation is especially critical when evaluating model-based MPPT algorithms, since the ability to quickly identify the maximum power point after a change in the I–V curve is crucial for the efficiency of this class of algorithms.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Parameter | SAS A | SAS B |
---|---|---|
Power | 0–5 kW | 0–10 kW |
Current | 0–8.5 A | 0–13 A |
Maximum output voltage | 600 V | 1000 V |
Curve storage | 100 * | 1000 |
Point capacity | 128 | 64 |
Voltage rms ripple | 0.11% ** | 0.40% ** |
Peak voltage noise | 1.50 V | 1.50 V |
Parameter | Description | Value |
---|---|---|
Maximum output power | 4000 W | |
Maximum input voltage | 500 V | |
Maximum output voltage | 500 V | |
Input current ripple | 0.2% | |
Output current ripple | 0.04% | |
Switching frequency | 20 kHz |
Parameter | Description | Value |
---|---|---|
L | Inductance | 6 mH |
Maximum current through inductor | 25 A | |
Electrolytic capacitors (input) | 470 μF | |
Electrolytic capacitors (output) | 330 μF | |
to | Polyester capacitors (high-frequency decoupling) | 4.7 μF |
to | Bus discharge resistors | 20 k |
Curve | Curve 1 200 W/m2 | Curve 2 400 W/m2 | Curve 3 600 W/m2 | Curve 4 800 W/m2 | Curve 5 1 kW/m2 |
---|---|---|---|---|---|
SAS A | 7.1760 | 7.9615 | 8.1349 | 9.8986 | 12.9918 |
SAS B | 4.4700 | 8.4491 | 5.5101 | 9.4378 | 9.8855 |
Curve | Curve 1 200 W/m2 | Curve 2 400 W/m2 | Curve 3 600 W/m2 | Curve 4 800 W/m2 | Curve 5 1 kW/m2 |
---|---|---|---|---|---|
SAS A | 0.0027 | 0.0028 | 0.0029 | 0.0035 | 0.0045 |
SAS B | 0.0017 | 0.0027 | 0.0022 | 0.0029 | 0.0031 |
Curve | Curve 1 200 W/m2 | Curve 2 400 W/m2 | Curve 3 600 W/m2 | Curve 4 800 W/m2 | Curve 5 1 kW/m2 |
---|---|---|---|---|---|
SAS A | 5.3046 | 4.3502 | 5.0178 | 3.9010 | 3.0319 |
SAS B | 1.3504 | 1.6747 | 2.1754 | 1.5903 | 1.5471 |
Curve | Curve 1 200 W/m2 | Curve 2 400 W/m2 | Curve 3 600 W/m2 | Curve 4 800 W/m2 | Curve 5 1 kW/m2 |
---|---|---|---|---|---|
SAS A | 0.0016 | 0.0013 | 0.0014 | 0.0012 | 0.0010 |
SAS B | 0.0006 | 0.0006 | 0.0007 | 0.0006 | 0.0006 |
# | Resistance () | Capacitance (mF) | Time Constant (ms) |
---|---|---|---|
1 | 2.66 | 4.70 | 12.50 |
2 | 2.66 | 9.40 | 25.06 |
3 | 2.66 | 14.10 | 37.59 |
4 | 2.66 | 18.80 | 50.12 |
5 | 2.66 | 23.50 | 62.65 |
6 | 2.66 | 28.20 | 75.18 |
7 | 2.66 | 32.90 | 87.71 |
8 | 2.66 | 37.60 | 100.24 |
9 | 2.66 | 42.30 | 112.77 |
10 | 2.66 | 47.00 | 125.30 |
11 | 3.43 | 47.00 | 161.11 |
12 | 4.80 | 47.00 | 225.60 |
13 | 8.00 | 47.00 | 376.00 |
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Cavalcante Junior, V.M.; Neto, R.C.; Barbosa, E.J.; Bradaschia, F.; Cavalcanti, M.C.; Azevedo, G.M.d.S. Evaluation of the Effectiveness of Solar Array Simulators in Reproducing the Characteristics of Photovoltaic Modules. Sustainability 2024, 16, 6932. https://doi.org/10.3390/su16166932
Cavalcante Junior VM, Neto RC, Barbosa EJ, Bradaschia F, Cavalcanti MC, Azevedo GMdS. Evaluation of the Effectiveness of Solar Array Simulators in Reproducing the Characteristics of Photovoltaic Modules. Sustainability. 2024; 16(16):6932. https://doi.org/10.3390/su16166932
Chicago/Turabian StyleCavalcante Junior, Valdemar Moreira, Rafael C. Neto, Eduardo José Barbosa, Fabrício Bradaschia, Marcelo Cabral Cavalcanti, and Gustavo Medeiros de Souza Azevedo. 2024. "Evaluation of the Effectiveness of Solar Array Simulators in Reproducing the Characteristics of Photovoltaic Modules" Sustainability 16, no. 16: 6932. https://doi.org/10.3390/su16166932
APA StyleCavalcante Junior, V. M., Neto, R. C., Barbosa, E. J., Bradaschia, F., Cavalcanti, M. C., & Azevedo, G. M. d. S. (2024). Evaluation of the Effectiveness of Solar Array Simulators in Reproducing the Characteristics of Photovoltaic Modules. Sustainability, 16(16), 6932. https://doi.org/10.3390/su16166932