TWI669590B - Maximum power tracking method for solar power generation system - Google Patents

Abstract

A method for tracking maximum power of a solar power generation system, which is implemented by a control circuit. The method includes the following steps: measuring the output current value and output voltage value of an initial operating point of a solar power generation system to obtain         ₁, V         ₁); Estimated illumination value G for a random guess          _guess Perform a simplified estimation operation to obtain a current illuminance value         GThe simplified estimation method operations include:         ,and         G=         G _{guess +} ｜         I _o -         I ₁ ｜ /          I           _sc among them,         I _o Is an estimated output current value,         I _sc ,         I _s ,         q,         k,         nand         TIs constant; according to the current illuminance value         GCalculate a maximum power point voltage         V _mpp ,among them,         ; And according to the maximum power point voltage value         V _mppPerform an alpha factor perturbation observation operation to determine a voltage command. The alpha factor perturbation observation operation includes:         ,         P(n-2) ＜         P(n-1) and         P(n) ＜         P(n-1), where ΔV          _pv (n) is the current voltage disturbance amount, Δ         V _pv (n-1) is the previous voltage disturbance amount, α is a constant less than 1 to reduce steady state oscillation,         P(n) is the current power value,         P(n-1) is the power value of the previous sampling,         P(n-2) is the power value of the first two samples.       

Description

Maximum power tracking method for solar power generation system

The present invention relates to a method for tracking maximum power of a solar power generation system, and more particularly to a method for tracking the maximum power of a solar power generation system by combining a simplified estimation method operation and an α-factor disturbance observation method operation.

The concept of environmental protection and sustainable development have become a global consensus. How to use existing energy more efficiently and actively develop new alternative energy are the top priorities of the engineering and technology community. The 21st United Nations Climate Change Conference (COP21), held in France in 2015, adopted the historically inclusive and legally binding carbon reduction agreement, the Paris Agreement, and all participating countries agreed to control greenhouse gas emissions in order to achieve pre-industrialization. By 2100, the average global temperature will not rise more than 2 ^o C, and strive to control the target within 1.5 ^o C. This shows that the degradation of the global environment, climate, and ecology due to greenhouse gas emissions has attracted worldwide attention, and issues such as green environmental protection and energy conservation and carbon reduction have received increasing attention from countries around the world. Therefore, how to reduce electricity consumption, improve energy conversion and use efficiency Reducing greenhouse gas emissions is a top priority.

For commercial solar power generation systems, based on cost and volume considerations, the improvement of solar cell utilization and conversion efficiency becomes extremely important. At present, the power generation efficiency of commercial solar cells is only about 20%. Because the electrical characteristics of solar cells are non-linear and there is a maximum power point, and their electrical characteristics are easily affected by the illuminance value and temperature, that is, the solar cells are in a certain fixed sunlight. There is a maximum power output point at both temperature and temperature. Therefore, how to capture the maximum output power of solar cells to maximize the cost-effectiveness of solar cells is an important issue for the development of solar power systems, which makes maximum power tracking (Maximum Power Point Tracking (MPPT) method plays a key role in high-efficiency solar power systems.

At present, many literatures have proposed tracking technology for maximum power of solar power generation systems. As the perturbation observation method and incremental conductance method of conventional technologies cannot quickly respond to environmental changes, it is very important to develop a method for fast maximum power tracking. The maximum power tracking technology in response to environmental changes can be divided into the following three categories:

I. Maximum power tracking method with changing steps:

The tracking method uses the distance between the current operating point and the maximum power point to determine the step size. When the operating point is close to the maximum power point, a smaller step amount is used, otherwise a larger step amount is used. The general tracking method uses the same fixed scale factor under all illuminances, but may produce a slower dynamic response when the illuminance changes, because the optimal values of the scale factors are not the same under different illuminance conditions. Some literatures use the power change as the feedback signal and use a proportional-integral controller to determine the size of the disturbance step. However, the proportional and integral parameters k _p and k _i also need to be adjusted, and some literatures have proposed successive approximation of the maximum power of the register. In the method, the size of the perturbation step is increased in a binary manner starting from the lowest bit. In order to track to the maximum power point, once the operating point passes the maximum power point, a monotonically decreasing step is adopted, but it is difficult to achieve due to complexity.

Second, the maximum power tracking method based on mathematical models and software calculations:

This method uses different mathematical models to calculate the maximum power point. Some literatures have proposed the one-dimensional Newton-Raphson method, and some literature have proposed the state estimation method to estimate the current illumination and temperature, and then use the parameters obtained. Calculate the actual maximum power point position. However, the above techniques all require accurate solar cell models and complicated calculations. In addition, the software calculation method can be used to develop the maximum power tracking technology that responds quickly to environmental changes, such as using particle swarm optimization, asymmetric fuzzy controllers, or fuzzy controllers in conjunction with neural networks to obtain appropriate perturbation steps. . However, the software-calculated maximum power tracking technology also requires more complex calculations and is not suitable for implementation with low-cost microcontrollers.

Three or two-stage maximum power tracking method:

The first stage of this method uses mathematical model analysis or software calculation to move the operating point near the maximum power point, and then uses the second stage to obtain the true maximum power point position. Some literatures suggest that the first stage can use Newton-Raphson, proportional short-circuit current method, ant colony method or beta method, while the second stage can use incremental conductance method, perturbation observation method or particle swarm method, two-stage method Although the maximum power tracking technology does not require accurate mathematical models and intelligent algorithms, its first-stage operation is still complicated.

In addition to a fast tracking speed and a small tracking loss, an excellent maximum power tracking method must also have the characteristics of soft implementation, low hardware complexity, good system compatibility, and easy expansion, including simple and convenient methods. It can be implemented with a low-cost microcontroller without the need for additional sensing devices and circuits (such as illuminance meters, thermometers, and conversion circuits). None of the above three types of maximum power tracking methods can be achieved. Therefore, a new need is urgently needed in the field. Maximum power tracking method.

One of the purposes of this case is to disclose a maximum power tracking method. The first stage is to use the simplified estimation method to estimate the current illumination of the sun, calculate the maximum power point voltage under this illumination and move the operating point to this voltage. In the second stage, the α-factor disturbance observation method is used to stably control the operating point at the maximum power point to achieve the purpose of fast maximum power tracking.

Another purpose of this case is a method of maximum power tracking, whose rise time and stability time in transient performance are significantly shorter than those of the fixed-step perturbation observation method and the variable-step perturbation observation method of the conventional technology. Transient and steady state response.

Another purpose of this case is to disclose a maximum power tracking method, in which the average tracking power loss is significantly reduced compared with the fixed-step perturbation observation method and the variable-step perturbation observation method of the conventional technology, and has good tracking efficiency.

Another purpose of this case is to disclose a method of maximum power tracking, which has good transient and steady state response. Compared with the fixed-step perturbation observation method and the variable-step perturbation observation method, the tracking speed is increased by 92.6%, respectively. And 87.5%, the tracking power loss also decreased by 85.85% and 76.7%, respectively.

To achieve the foregoing object, a maximum power tracking method is proposed, which is implemented by a control circuit. The maximum power tracking method includes the following steps: measuring the output current value and output voltage value of an initial operating point of a solar power generation system To obtain (I ₁ , V ₁ );

Perform a simplified estimation operation on the estimated illumination value G _guess of a random guess to obtain a current illumination value G. The simplified estimation operation includes:

,and

G=         G _{guess +} ｜         I _o -         I ₁ ｜ /          I           _sc

Among them, Io is an estimated output current value, and Isc, Is, q, k, n, and T are constants;

Calculate a maximum power point voltage value Vmpp according to the current illumination value G, where: ; And performing an alpha factor disturbance observation method operation to determine a voltage command according to the maximum power point voltage value Vmpp, the alpha factor disturbance observation method operation includes:

,

P (n-2) < P (n-1) and P (n) < P (n-1),

Among them, ΔV _pv (n) is the current voltage disturbance amount, Δ V _pv (n-1) is the previous voltage disturbance amount, α is a constant less than 1 to reduce steady state oscillation, and P (n) is the current power value , P (n-1) is the power value of the previous sampling, and P (n-2) is the power value of the previous two samplings.

In an embodiment, it further includes a power change threshold judgment step to re-perform the simplified estimation method operation to obtain a new estimation when a power change amount is greater than a preset power change threshold. Illuminance value G _guess .

In one embodiment, the preset power change threshold is 5% of the rated power.

In one embodiment, the control circuit includes: a boost converter having an input terminal, a control terminal, and an output terminal, the input terminal is used for coupling with a solar cell system, and the control terminal is used for A pulse width modulation signal is received, and the output terminal is used for coupling with a load; and a microcontroller is used to generate the voltage command and provide the pulse width modulation signal according to the voltage command.

In one embodiment, the microcontroller has a digital signal processor for performing an analog-to-digital conversion operation and a digital filtering operation on the current voltage and the current, respectively, and performing a proportional-integral operation according to the voltage command. A control operation and a pulse width modulation operation are performed to output the pulse width modulation signal.

In order to enable your review committee to better understand the structure, characteristics and purpose of this case, the drawings and detailed description of the preferred embodiments are attached as follows.

Please refer to FIG. 1, which shows a flowchart of steps in an embodiment of the maximum power tracking method in this case.

As shown in Figure 1, the maximum power tracking method in this case is implemented using a control circuit. The maximum power tracking method includes the following steps: measuring the output current value and output voltage value of an initial operating point of a solar power system Obtain (I ₁ , V ₁ ); (step a); perform a simplified estimation operation on the estimated illumination value G _guess of a random guess to obtain a current illumination value G , the simplified estimation operation includes:

,and

G=         G _{guess +} ｜         I _o -         I ₁ ｜ /          I           _sc

Among them, Io is an estimated output current value, and Isc, Is, q, k, n, and T are constants; (step b); calculating a maximum power point voltage value Vmpp according to the current illumination value G, where:

;as well as

Perform an alpha factor disturbance observation method operation to determine a voltage command according to the maximum power point voltage value V _mpp . The alpha factor disturbance observation method operation includes:

,

P (n-2) < P (n-1) and P (n) < P (n-1),

Among them, ΔV _pv (n) is the current voltage disturbance amount, Δ V _pv (n-1) is the previous voltage disturbance amount, α is a constant less than 1 to reduce steady state oscillation, and P (n) is the current power value , P (n-1) is the power value of the previous sampling, and P (n-2) is the power value of the previous two samplings.

Please refer to FIG. 2, which illustrates a flowchart of another embodiment of the maximum power tracking method according to the present invention.

As shown in FIG. 2, it further includes a power change threshold judgment step to re-perform the simplified estimation method operation when a power change amount is greater than a preset power change threshold to obtain a new estimation. Illuminance value G _guess .

The preset power change threshold is, for example, but not limited to, 5% of the rated power.

The following will explain the principle of this case:

Electrical characteristics of solar cells:

Please refer to FIG. 3, which shows a single diode equivalent circuit diagram of a solar cell.

As shown in the figure, the electrical characteristics of a solar cell are a non-linear power source, and no reverse current is allowed. Its voltage and current exhibit an exponential relationship. Therefore, when the output voltage of a solar cell changes, its output current also changes accordingly. According to the equivalent circuit, it can be known that the relationship between the output voltage and the current of the solar cell is shown in equation (1).

(1)

Among them, I _o is the output current of the solar cell, I _g is the photoelectric conversion current, I _S is the reverse saturation current of the diode, q is the carrier charge amount (1.602´10 ^-19 C), and R _S is the equivalent series resistance , V _o is the output voltage of the solar cell, n is the dielectric constant (between 1 and 2), k is the Boltzmann constant (1.38065´10 ^-23 J / ^o K), T is the absolute temperature value, and R _P is Equivalent parallel resistance.

The relationship between the photoelectric conversion current I _g and the illuminance value is shown in equation (2).

(2)

Among them, G is the illuminance value, the unit is W / m ² , and I _SC is the short-circuit current of the solar cell.

It is known from equation (2) that when the illuminance value G rises, the output electric energy of the semiconductor increases with the increase of the light energy of the semiconductor, and the photoelectric conversion current I _{g of the} solar cell also increases accordingly. In general, since the value of the parallel resistance of the solar cell is much larger than the value of the series resistance, equation (1) can be simplified into equation (3).

(3)

It is known from equation (3) that the output current I _{o of the} solar cell is almost directly proportional to the photoelectric conversion current I _g . Therefore, when the illumination value G increases, the output current I _{o of the} solar cell also increases.

In order to observe the influence on the output characteristic curve of the solar cell when the illuminance value and the ambient temperature value are changed, the equation (3) can be rewritten into the equation (4).

(4)

It is known from equation (4) that due to the natural logarithmic relationship, the output voltage V _{o of the} solar cell changes only slightly when the illumination value G rises.

Please refer to FIGS. 4a and 4b together, wherein FIG. 4a shows the current-voltage curves of the solar cell under different illumination values; and FIG. 4b shows the power-voltage curves of the solar cell under different illumination values.

Among them, the ambient temperature value is fixed at 25 ° C, and the different illuminance values are 200W / m ² , 400W / m ² , 600W / m ² , 800W / m ² and 1000W / m ² , as shown in the figure. The illuminance values are the five solar cell output curves drawn after the operation of equation (3), and the characteristic curves will change as the illuminance values change.

Please refer to Figs. 5a and 5b together. Fig. 5a shows the current-voltage curves of the solar cell at different temperature values; and Fig. 5b shows the power-voltage curves of the solar cell at different temperature values.

As shown in the figure, the output characteristic curve of the solar cell is also affected by the ambient temperature value. According to equation (3), when the ambient temperature value increases, the equivalent diode current decreases and the solar cell output current I _o slightly increases; And according to equation (4), the ambient temperature value is proportional to the output voltage V _o of the solar cell, but the output current I _{o of the} solar cell will also increase with the temperature value, and it will be affected much more than the output voltage. V _o , so the ambient temperature value has little effect on the solar cell output voltage V _o , but the equivalent series resistance across-voltage attenuation increases with the output current I _o , which causes the solar cell output voltage V _o to drop significantly. Its output power also decreases.

The hardware architecture of the solar maximum power tracking system adopted in this case:

Please refer to FIG. 6, which shows a schematic diagram of the control system architecture adopted in this case.

As shown in FIG. 6, the control system architecture adopted in this case includes a solar cell system 100, a boost converter 200, and a microcontroller 300.

The boost converter 200 has an input terminal, a control terminal, and an output terminal. The input terminal is used for coupling with the solar cell system 100. The control terminal is used for receiving a pulse width modulation signal. The output terminal is used for coupling with a load 400.

The micro-controller 300 has a digital signal processor for sampling, voltage-analog-to-digital conversion, and digital-filtering operations on the voltage and current output by the solar cell system 100, and then performing the maximum power tracking method to generate a The voltage command generates a duty cycle through a proportional-integral control operation and a pulse width modulation operation to control the boost converter 200 to achieve the purpose of maximum power tracking.

Among them, since the output voltage of the conventional solar battery system 100 is generally too low, the boost converter 200 is used to boost the output voltage of the solar battery system 100. The boost converter 200 is, for example, but not limited to Step-up DC-DC converter; the microcontroller 300 is implemented by, for example, but not limited to, a low-cost digital signal processor.

The maximum power tracking technology proposed in this case is based on a two-stage approach:

The first stage is to use the simplified estimation method to estimate the current illuminance of the solar cell, calculate the maximum power point voltage under this illuminance and move the operating point to this voltage, and the second stage uses the α factor disturbance observation method to move the operating point Stable control at the maximum power point to achieve the purpose of fast maximum power tracking.

Many documents mention the State Estimation method of solar cells. The basic principle is to observe the known information of the system to estimate other unknown information. The most widely used method is the Weighted Least Square (WLS) method. This mathematical model performs state estimation based on the numerical relationship between system measurement values and state variables, so it can accurately estimate the required system information.

To use the state estimation method to obtain the solar cell's illuminance and temperature under the current environment, the actual operation needs to measure the operating voltage and current of the two sets of solar cells, and it is easy to be interfered by inaccurate parameters or external noise. Causes an error in the estimated illuminance and temperature. In addition, in order to reduce the amount of error, iterative methods need to be used to converge the amount of error during the calculation. However, this method will greatly increase the computational complexity, making it difficult to use a microcontroller with a digital signal processor to implement. In addition, model parameter errors can make estimation difficult or even impossible to converge. Therefore, a simplified estimation method is proposed in this case to reduce the amount of calculation and avoid the problem of inconsistency.

Principle of simplified estimation method:

First, it is assumed that the ambient temperature remains the same during the first estimation of the illuminance. Then the system only needs to measure the voltage and current of a group of solar cells, and substitute equation (2) into equation (3) to reduce the microcontroller. The amount of calculation, ignoring the equivalent series resistance R _S and the parallel resistance R _P , the relationship between the output current and voltage of the solar cell, as shown in equation (5)

(5)

Among them, I _o is the output current of the solar cell, G is the illuminance value, I _SC is the short-circuit current of the solar cell, I _S is the reverse saturation current of the diode, q is the carrier charge amount (1.602´10 ^-19 C), V _o is the output voltage of the solar cell, n is the dielectric constant (between 1 and 2), k is the Boltzmann constant (1.38065´10 ^-23 J / ^o K), and T is the absolute temperature value.

Then randomly guess the current illuminance of the solar cell, substitute equation (5) to get the output current value of the solar cell under the current illuminance, subtract it from the actual measured output current value, and then divide the difference between the two by the solar cell. The short-circuit current I _{sc is} the difference between the actual illuminance and the estimated illuminance, thereby achieving the purpose of estimating the current illuminance of the solar cell. The necessary condition for using this method is that the measurement point of the first sampling should be on the left half of the solar cell output power vs. voltage characteristic curve.

Please refer to FIG. 7, which is a schematic diagram showing the error of illumination estimation under different voltages and temperatures.

As shown in the figure, when the measurement point is below the voltage of 10V, the temperature change has little effect on the estimated illuminance, and the amount of error is less than 5´10 ^-4 . Therefore, the more accurate illuminance value can be estimated, and the actual temperature It needs to be calculated when the operating point is stable at the maximum power.

Please refer to FIG. 4b together. As shown in the figure, the output power-voltage characteristics of the solar cell under different illumination levels are different, and the maximum power point voltage is also different.

Please refer to FIGS. 8a and 8b together, where FIG. 8a shows output power voltage curves at different illuminances from 100W / m ² to 1000W / m ² , and FIG. 8b shows a fitting curve between the illuminance value and the maximum power point voltage .

In order to find out the relationship between the maximum power point voltage and the illuminance, the output power-voltage curve graphs with different illuminances of 100W / m ² to 1000W / m ² are plotted every 100W / m ² in an analog manner, and each Position of the maximum power point under illumination.

As shown in Figure 8a, because the position of the maximum power point voltage is different under different illumination, the curve fitting method is used here to take the illumination value G as the independent variable, and the maximum power point voltage V _mpp as the strain number. Draw the G-Vmax curve.

The G-Vmax curve uses the polyfit function provided by MATLAB to fit a one-variable cubic polynomial, as shown in equation (6).

(6)

Among them, G is the illuminance value, the unit is W / m ² , and V _mpp is the maximum power point voltage value.

As shown in Figure 8b, the fitting curve shows that equation (6) is very close to the actual maximum power point voltage. Therefore, when the illumination value is estimated, it can be substituted into equation (6) to obtain the maximum value under this illumination value. Power point voltage value, and move the system voltage command operating point to this point.

The principle of a factor perturbation observation method :

In order to avoid the fixed-step perturbation observation method to oscillate back and forth near the maximum power point, the variable-step perturbation observation method needs to be used to improve it. Many literatures have proposed various variable-step perturbation observation methods. More complicated.

This case is based on the spirit of the variable step perturbation observation method, using the a-factor perturbation observation method, and the relationship is shown in equation (7).

(7)

Among them, Δ V _pv ( n ) is the current voltage disturbance amount, Δ V _pv ( n -1) is the previous voltage disturbance amount, α is a set a factor, and the a factor needs to be less than 1 to reduce the voltage disturbance amount. Reduce the problem of steady state oscillations.

Equation (7) is simpler than other methods to ensure fast system response. However, this method needs to satisfy conditional equations (8) and (9), as shown below.

(8)

(9)

The parameters of the above two conditional expressions are defined as P (n) is the current power value, P (n-1) is the power value of the previous sampling, and P (n-2) is the power value of the previous two samplings.

Please refer to FIGS. 9a and 9b together, where FIG. 9a shows that the tracking path crosses the maximum power point from the left half plane of the PV curve to the right half plane, and FIG. 9b shows that the tracking path crosses the right half plane of the PV curve Maximum power point to the left half plane.

As shown in the figure, both of the above conditions cross the maximum power point. When the operating point passes the maximum power point, it means that the current operating point is located near the maximum power point. In order to eliminate the fixed-step disturbance observation method, it oscillates around the maximum power point. In this case, after the maximum power point is passed, the voltage disturbance is multiplied by a factor less than 1 to reduce the degree of disturbance to achieve the purpose of improving the accuracy of steady-state tracking.

Among them, the a-factor perturbation observation method first samples the solar cell voltage and current value through a microcontroller and calculates its power value. Then it determines whether conditional equation (8) and conditional equation (9) are true and determines whether the voltage perturbation must be changed. The size of the amount is finally calculated by using the basic principle of the perturbation observation method and the current operating point position to calculate the required voltage change amount and covering the current value with the previous value. The above process can be repeated to achieve the purpose of maximum power tracking. This part For the sake of knowing the technology, I will not repeat them here.

This method can be achieved whether the tracking is started from the short-circuit current terminal or the open-circuit voltage terminal. When the conditional equation (8) and the conditional equation (9) are not met, it means that the current operating point is still a distance from the maximum power point, so the maximum value can be used. Voltage disturbance to reduce transient tracking time. From the above, it can be known that the a-factor perturbation observation method effectively retains the advantages of fast transient response and high steady-state tracking accuracy, thereby enabling the system to produce a stable and high-power output and obtain the best results.

Please refer to Figs. 10a and 10b together. Fig. 10a shows the tracking diagram of the maximum power tracking method in this case, and Fig. 10b shows the tracking diagram of the maximum power tracking method in this case when the illuminance and temperature change.

As shown in Figure 10a, this case is to first measure the output current value and output voltage value of an initial operating point of a solar power generation system to obtain (I ₁ , V ₁ ), and set the sampling operating point on the solar characteristic curve. The left half (point V _{1 in the} figure). At this time, the error of the ambient temperature has little effect on the estimated illuminance. Then, a random guess of the estimated illuminance value G _{guess is made} , and a simplified type estimation of the estimated illuminance value G _{guess is} performed. Normal operation to obtain a current illumination value G.

Calculate a maximum power point voltage value V _mpp according to the current illuminance value G , and move the operating point to the maximum power point voltage value V _mpp (point A in the figure), and perform a calculation based on the maximum power point voltage value V _mpp . The α factor disturbs the observation method operation. At this time, the operating point will converge between the three points A, B, and C in the figure.

When the operating point is stable at the maximum power point, it is determined whether the current illumination value G has changed. That is, when the power change amount is greater than a preset power change threshold (for example, but not limited to 5% of the rated power), it means that the current illuminance value G is changed. At this time, the calculation is repeated to obtain a current illuminance value G and a maximum power point. The voltage value V _mpp and the subsequent alpha factor perturbation observation method operation to determine a voltage command (ie, points D to F in the figure).

If the current illuminance value G has not changed, the output voltage V _O , current I _O and the current illuminance value G at the current operating point are substituted into equation (10) to obtain a current temperature value T.

(10)

The current temperature value T will be used to calculate the current illuminance value G when the illuminance changes next time. Repeatedly performing the above steps can achieve the purpose of maximum power tracking in this case.

10b, assuming the initial value of the illumination system of 1000W / m ^2, over time decreased to 300W / m ^2, and finally increased to 700W / m ^2, and the system temperature ranges from 25 ° C to 35 ° C .

When the time is t ₀ , the maximum power tracking method in this case will first randomly guess an estimated illuminance value G _guess . Since the preset operating point of the system is located on the left side of the solar characteristic curve, the impact of temperature contrast estimation at this point will not affect Large, so even if the preset temperature is not equal to the actual temperature, the maximum power tracking method in this case can still estimate the accurate current illumination value G.

When the time is t ₁ , the maximum power tracking method in this case will calculate a maximum power point voltage value V _mpp according to the current illuminance value G , and perform an alpha factor disturbance observation method operation between time t ₂ and t _i In order to stabilize the operating point at the maximum power point.

When assuming t _i α factor perturbation and observation method has entered the steady state, the maximum power point tracking method in this case will be switched to the temperature estimation mode in time t _i, no detection current illuminance value G will be changed using the equation ( 10) Find a current temperature value T and record it (shown as t _i to t _{j in the} figure).

If the current illuminance value G changes, the maximum power tracking method in this case will recalculate to obtain a current illuminance value G, a maximum power point voltage value V _mpp, and subsequent alpha factor disturbance observation method operations to determine a voltage command, and Use the recorded current temperature value T as the actual temperature value at this moment (as shown in the interval _{tj in the} figure).

Since the system temperature generally does not change instantaneously, this assumption should be valid on a practical system. By repeatedly performing the above steps, the goal of maximum power tracking in this case can be achieved.

The case with Comparison of known technologies:

The maximum power tracking method proposed in this case is compared with the fixed-step perturbation observation method and the variable-step perturbation observation method of the conventional technology to verify the feasibility and performance improvement of the case.

The input source for the actual test in this case was the TerraSAS ETS 600X8 D-PVE solar cell simulator introduced by AMETEK to simulate the solar cell model LDK-85 introduced by LDK Solar. The electrical specifications are shown in Table 1.

Table 1 Maximum power P _mpp 85 W Open circuit voltage V _OC 21.6 V Short-circuit current I _SC 5.28 A Maximum power point voltage V _mpp 17.3V Maximum power point current I _mpp 4.93A

After the solar cell module has passed through 7 series and 1 parallel, the corresponding experimental parameter specifications are shown in Table 2.

Table 2 Maximum power P _mpp 595 W Open circuit voltage V _OC 152.2 V Short-circuit current I _SC 5.28 A Maximum power point voltage V _mpp 121.1V Maximum power point current I _mpp 4.93A

Among them, the power stage circuit is a step-up converter, and the control stage circuit uses the dsPIC33FJ16GS502 digital signal microcontroller introduced by Microchip as the control core to regulate the duty cycle of the step-up converter power switch to track the maximum power of the system. For the purpose, the load side uses the 63108A electronic load introduced by Chroma, and it is operated in a constant voltage mode and stabilized to 200V for actual testing. The measurement waveform part uses the MSO2024 oscilloscope introduced by Tektronix, and a solar simulator is used. The provided man-machine interface records the experimental data.

In order to verify the correctness of the maximum power tracking method in this case, a 600W maximum power tracking circuit was actually completed in this case. In addition to verifying its feasibility by using experimental results, it also uses the fixed step perturbation observation method and variable step of the conventional technology. The perturbation observation method is compared to highlight the performance of the novel solar maximum power tracking method in this case.

In the actual measurement, each method updates the maximum power tracking command once in 0.2 seconds. Among them, the fixed-step disturbance observation method and the variable-step disturbance observation method of the conventional technology test the condition of the standard uniform test condition (STC). , And the new solar maximum power tracking method in this case adds a test for illumination change.

( One ) Observation of fixed step perturbation observation method of conventional techniques:

Please refer to FIGS. 11a and 11b together, where FIG. 11a shows the measured waveforms of the tracking voltage and current of the fixed step perturbation observation method of the conventional technology; FIG. 11b shows the fixed step perturbation of the conventional technology Measured waveform of the tracking power of the observation method.

Under the same system specifications, the fixed step perturbation observation method performs the best performance evaluation when Δ V _cmd = 4 V, so the step command Δ V _cmd for voltage fluctuation is set to 4 V for actual measurement.

As shown in the figure, with a uniform illumination of 1000 W / m ² and a temperature of 25˚C, the actual measurement results show that the fixed-step perturbation observation method of the conventional technique has a rise time of 5.4 seconds and a stabilization time of 6.6 seconds. The average state power is 580.52 W, the steady-state tracking power accuracy is 98.4%, the tracking power loss is 8669.1 J, and the average tracking power loss is 173.38 W.

( two) Measured changes in the conventional technique:

Please refer to Figs. 12a and 12b together. Fig. 12a shows the measured waveforms of the tracking voltage and current of the step change perturbation observation method of the conventional technology; Fig. 12b shows the step change perturbations of the conventional technology. Measured waveform of the tracking power of the observation method.

Under the same system specifications, the variable-step disturbance observation method performs best when the scale factor M = 1.4, so the M value is set to 1.4 for actual measurement.

As shown in the figure, under the condition of uniform illumination of 1000 W / m ² and measured temperature of 25˚C, the actual measurement results show that the variation of the conventional technique is stepwise disturbance observation method with a rise time of 3.2 seconds and a settling time of 4.2 seconds. The average state power is 597.02 W, the steady-state tracking power accuracy is 99.84%, the tracking power loss is 5259.5 J, and the average tracking power loss is 105.19 W.

(3) Actual measurement results in this case:

The actual measurement in this case is divided into two parts. The first part is the measurement of uniform illumination and the second part is the measurement of changing illumination.

Please refer to FIGS. 13a and 13b together. FIG. 13a shows the measured waveforms of the tracking voltage and current of the uniform illuminance in this case; and FIG. 13b shows the measured waveforms of the tracking power of the uniform illuminance in this case.

As shown in the figure, under the condition of uniform illuminance of 1000 W / m ² and measured temperature of 25 ° C, the actual measurement results show that the rise time of this case is 0.4 seconds, the settling time is 1.4 seconds, and the steady-state average power It is 597.66 W, the steady-state tracking power accuracy is 99.95%, the tracking power loss is 1227.3 J, and the average tracking power loss is 24.54 W.

Please refer to Figs. 14a and 14b together, where Fig. 14a shows the measured waveforms of the tracking voltage and current with varying illuminance in this case; and Fig. 14b shows the measured waveforms of the tracking power with varying illuminance in this case.

As shown in the figure, the measured part of the illuminance changes, after the illuminance changes from 1000 W / m ² to 300 W / m ^{2 and} finally rises to 700 W / m ² , and the temperature changes from 25˚C to 35˚C and finally In the case of a decrease of 30˚C, the actual measurement results show that after the instantaneous change in illumination, the current operating point and the temperature estimated by the system can be used to jump to the vicinity of the current maximum power point for the Alpha factor disturbance observation method.

Please refer to FIGS. 15a to 15f together, where FIG. 15a shows the change tracking performance diagram of the case at 1000 W / m ² illuminance and 31˚C temperature; FIG. 15b shows the case at 1000 W / m ² illuminance and 35˚ track the performance of change of temperature C; Figure 15c illustrates a case in which 300 W / m ^2, and illumination variations 35˚C track the performance of the temperature; Figure 15d illustrates a case in which 300 W / m ² illumination and temperature 32˚C Figure 15e shows the change tracking performance of the case at 300 W / m ² illuminance and 30 ； C temperature; Figure 15f shows the change of the case at 700 W / m ² illuminance and 30˚C temperature Track performance graphs.

As shown in the figure, the tracking performance of this case under various illuminance and temperature conditions has a steady-state tracking accuracy higher than 99.58%. The experimental results are roughly the same as the simulation results, so the fast maximum power tracking technology proposed in this case can be verified. feasibility.

(4) Comparison and analysis:

Table 3 shows the simulation and measurement results of the fixed-step perturbation observation method of the conventional technique.

table 3 Fixed-step perturbation observation Simulation results Experimental results Rise Time 5 seconds 5.4 seconds stable schedule 6.2 seconds 6.6 seconds Steady state average power 597.41 W 580.52 W Steady-state tracking accuracy 99.68% 98.4% Tracking power loss 6763.7 J 8669.1 J Average tracking power loss 135.27 W 173.38 W

Table 4 shows the simulation and actual measurement results of the variation step of the conventional technique.

Table 4 Variable step perturbation observation Simulation results Experimental results Rise Time 4.2 seconds 3.2 seconds stable schedule 4.8 seconds 4.2 seconds Steady state average power 599.33 W 597.02 W Steady-state tracking accuracy 100% 99.84% Tracking power loss 5428.5 J 5259.5 J Average tracking power loss 108.57 W 105.19 W

The simulation and actual measurement results in this case are shown in Table 5.

table 5 This case Simulation results Experimental results Rise Time 0.4 seconds 0.4 seconds stable schedule 1.2 seconds 1.4 seconds Steady state average power 599.31 W 597.66 W Steady-state tracking accuracy 100% 99.95% Tracking power loss 532.93 J 1227.3 J Average tracking power loss 10.66 W 24.54 W

It can be seen from the above table that the simulation and actual measurement results of the maximum power tracking technology are not too different, so the correctness of the proposed tracking method can be verified.

From the actual measurement results, it can be known that the fixed stepped disturbance observation method cannot meet the trade-off problem of rise time and steady-state tracking accuracy at the same time because the step size is fixed. Therefore, the fixed stepped disturbance observation method has a rise time. , Stability time, and accuracy of steady-state tracking are inferior to the other two; while the variable-step perturbation observation method can successfully overcome the trade-off problem of the fixed-step perturbation observation method, it also generates the design problem of the scale factor M If the M value is too large, the system will be unstable. Conversely, if the M value is too small, the transient response will be too slow. The ideal value of the scale factor M is also different under different illumination levels, so the change step The perturbation observation method must be designed for different solar power generation systems. The ideal value of the scale factor M can only be applied to the specific solar cell curve, which increases the design difficulty; and the maximum power tracking method in this case can solve the above two methods. Although the problem can only be applied to specific curves, the transient and steady state performance is good, so the best performance improvement is obtained.

As shown in Table 6, the rise time in this case was reduced by 5 seconds compared to the fixed-step disturbance observation method, compared with the variable-step disturbance observation method by 2.8 seconds, and the tracking speed was increased by 92.6% and 87.5%, respectively; the stabilization time Compared with the fixed step perturbation observation method, it is reduced by 5.2 seconds, and compared with the variable step perturbation observation method, it is reduced by 2.8 seconds.

Table 6 Fixed-step perturbation observation Variable step perturbation observation This case Rise Time 5.4 seconds 3.2 seconds 0.4 seconds stable schedule 6.6 seconds 4.2 seconds 1.4 seconds

As shown in Table 7, in the steady state part, the fixed-step perturbation observation method will oscillate near the maximum power point after entering the steady state. Its steady-state average power is only 580.52 W, and the steady-state tracking accuracy is 98.4%. The variable step type perturbation observation method adds a variable step, and no oscillation occurs at the maximum power point, so the steady-state tracking accuracy is increased to 99.84%; the steady-state tracking accuracy of this case is 99.95%, which has the best steady-state response.

Table 7 Fixed-step perturbation observation Variable step perturbation observation This case Steady state average power 580.52 W 597.02 W 597.66 W Steady-state tracking accuracy 98.4% 99.84% 99.95%

As shown in Table 8, in the part of tracking power loss, because the step design of the fixed step disturbance observation method must consider the trade-off between transient and steady-state response performance, it is impossible to take into account both performances, and the average tracking power loss is more. The variable-step disturbance observation method has a better transient and steady-state response, so its average tracking power loss is reduced by 39.3% compared with the fixed-step disturbance observation method; and the case has good transient and steady-state. Response, so its average tracking power loss is the lowest of the three methods, which is 85.85% lower than the fixed-step perturbation observation method and 76.7% lower than the variable-step perturbation observation method, so the overall performance is the best.

Table 8 Fixed-step perturbation observation Variable step perturbation observation This case Tracking power loss 8669.1 J 5259.5 J 1227.3 J Average tracking power loss 173.38 W 105.19 W 24.54 W

In summary, the experimental results confirm that compared with the fixed-step perturbation observation method and the variable-step perturbation observation method, the tracking speed in this case has been increased by 92.6% and 87.5%, respectively; in addition, the tracking power loss has also been reduced by 85.85% And 76.7%.

With the design disclosed above, this case has the following advantages:

1. The maximum power tracking method disclosed in this case uses the first stage to use the simplified estimation method to estimate the current illuminance of the solar cell, calculate the maximum power point voltage under this illuminance and move the operating point to this voltage. In the second stage, the α-factor disturbance observation method is used to stably control the operating point at the maximum power point to achieve the purpose of fast maximum power tracking.

2. The maximum power tracking method disclosed in this case has a significantly shorter rise time and stable time in the transient performance than the fixed-step perturbation observation method and the variable-step perturbation observation method of the conventional technology. State response.

3. The maximum power tracking method disclosed in this case has an average tracking power loss that is significantly reduced compared to the fixed step perturbation observation method and variable step perturbation observation method of conventional technology, and has good tracking efficiency.

4. The maximum power tracking method disclosed in this case has good transient and steady-state response. Compared with the fixed-step perturbation observation method and the variable-step perturbation observation method, the tracking speed is increased by 92.6% and 87.5%, respectively. The tracking power loss also decreased by 85.85% and 76.7%, respectively.

What is disclosed in this case is a preferred embodiment. For example, any local changes or modifications that are derived from the technical ideas of this case and are easily inferred by those who are familiar with the technology, do not depart from the scope of patent rights in this case.

In summary, regardless of the purpose, method and effect, this case shows that it is very different from the conventional technology, and that its first invention is practical, and it is also in line with the patent requirements of the invention. Granting patents will benefit society and feel good.

100‧‧‧solar battery system

200‧‧‧Boost Converter

300‧‧‧Microcontroller

400‧‧‧ load

Step a‧‧‧ measures the output current value and output voltage value of an initial operating point of a solar power generation system to obtain (I ₁ , V ₁ ).

Step b‧‧‧ performs a simplified estimation operation on the estimated illuminance value G _guess of a random guess to obtain a current illuminance value G.

Step c‧‧‧ calculates a maximum power point voltage value V _mpp according to the current illumination value G.

Step d‧‧‧ performs an alpha factor disturbance observation method operation according to the maximum power point voltage value V _mpp to determine a voltage command.

Step e‧‧‧ performs an alpha factor disturbance observation method operation according to the maximum power point voltage value V _mpp to determine a voltage command.

FIG. 1 is a flowchart illustrating steps of an embodiment of the maximum power tracking method in this case. FIG. 2 is a flowchart illustrating steps of another embodiment of the maximum power tracking method. FIG. 3 shows a single diode equivalent circuit diagram of a solar cell. FIG. 4a shows current-voltage curves of solar cells under different illumination values; FIG. 4b shows power-voltage curves of solar cells under different illumination values. FIG. 5a shows current-voltage curves of the solar cell at different temperature values; FIG. 5b shows power-voltage curves of the solar cell at different temperature values. FIG. 6 is a schematic diagram of a control system architecture adopted in this case. FIG. 7 is a schematic diagram showing the error of illumination estimation under different voltages and temperatures. FIG. 8 a shows output power voltage curves at different illuminances from 100 W / m ² to 1000 W / m ² . FIG. 8b shows a fitting curve of the illuminance value and the maximum power point voltage. FIG. 9a shows that the tracking path crosses the maximum power point from the left half plane of the PV curve to the right half plane. FIG. 9b shows that the tracking path crosses the maximum power point from the right half plane of the PV curve to the left half plane. FIG. 10a is a schematic diagram of the maximum power tracking method in this case. FIG. 10b is a schematic diagram illustrating the tracking of the maximum power tracking method in this case when the illuminance and temperature are changed. FIG. 11 a shows the measured waveforms of the tracking voltage and current of the fixed step perturbation observation method of the conventional technique. FIG. 11b shows the measured waveforms of the tracking power of the conventional fixed-step disturbance observation method. FIG. 12a shows the measured waveforms of the tracking voltage and current of the step change disturbance observation method of the conventional technique. FIG. 12b is a waveform diagram of the measured power of the tracking power of the step change disturbance observation method of the conventional technique. Figure 13a shows the measured waveforms of the tracking voltage and current of the uniform illuminance in this case. FIG. 13b shows the measured waveform of the tracking power of the uniform illuminance in this case. Figure 14a shows the measured waveforms of the tracking voltage and current with varying illuminance in this case. FIG. 14b shows the measured waveforms of the tracking power with varying illuminance in this case. Figure 15a shows the change tracking performance of this case at 1000 W / m ² illuminance and 31 ° C temperature. Figure 15b shows the change tracking performance of the case at 1000 W / m ² illuminance and 35 ° C temperature. Figure 15c shows the change tracking performance of the case at 300 W / m ² illumination and 35 ° C temperature. Figure 15d shows the change tracking performance of the case at 300 W / m ² illuminance and 32 ° C temperature. Fig. 15e shows the change tracking performance of the case at 300 W / m ² illuminance and 30 ° C temperature. Figure 15f shows the change tracking performance of this case at 700 W / m ² illuminance and 30 ° C temperature.

Claims (5)

A method for tracking maximum power of a solar power generation system, which is implemented by using a control circuit. The method includes the following steps: measuring an output current value and an output voltage value of an initial operating point of a solar power generation system to obtain (I ₁ , V ₁ ); performing a simplified estimation method operation on the estimated illuminance value G _guess of a random guess to obtain a current illumination value G , the simplified estimation method operation includes: And G = G _{guess +} | I _o - I ₁ | / I _sc , where I _o is an estimated output current value, and I _sc , I _s , q , k , n and T are constants; The illuminance value G calculates a maximum power point voltage value V _mpp , where V _mpp = 43.59 × G ³ -99.88 × G ² + 87.49 × G +92.75; and moves the system voltage command operating point to the maximum power point voltage value V _mpp to perform an alpha factor perturbation observation method to determine a voltage command. The alpha factor perturbation observation method operations include: Δ V _pv ( n ) = α × Δ V _pv ( n -1), P (n-2) < P (n-1) and P (n) < P (n-1), where ΔV _pv (n) is the current voltage disturbance amount, Δ V _pv (n-1) is the previous voltage disturbance amount, α It is a constant less than 1 to reduce steady state oscillation. P (n) is the current power value, P (n-1) is the power value of the previous sampling, and P (n-2) is the power value of the previous two samplings. The maximum power tracking method for a solar power generation system according to item 1 of the scope of patent application, further comprising a power change threshold judgment step to re-implement the simplified type when a power change is greater than a preset power change threshold. An estimation operation is performed to obtain a new said estimated illumination value G _guess . According to the maximum power tracking method of the solar power generation system described in item 2 of the patent application scope, the preset power change threshold is 5% of the rated power. The maximum power tracking method for a solar power generation system according to item 1 of the patent application scope, wherein the control circuit includes: a boost converter having an input terminal, a control terminal, and an output terminal. The input terminal is used for Coupled to a solar cell system, the control end is used to receive a pulse width modulation signal, and the output end is used to be coupled to a load; and a microcontroller is used to generate the voltage command and The voltage command provides this pulse width modulated signal. The maximum power tracking method for a solar power generation system according to item 4 of the scope of patent application, wherein the microcontroller has a digital signal processor for performing an analog-to-digital conversion operation on the current voltage and the current current, and a Digital filtering operation, and performing a proportional-integral control operation and a pulse width modulation operation according to the voltage command to output the pulse width modulation signal.