TWI600997B - A solar power system maximum power tracking device - Google Patents

Description

Maximum power tracking device for solar power generation system

The present invention relates to a maximum power tracking device for a solar power generation system, and more particularly to a maximum power tracking device that utilizes a deterministic cuckoo bird search method to gradually converge one of the output voltages of a solar cell to a power maximizing voltage.

As industrial development consumes a large amount of coal, oil and fossil fuels, energy shortages are emerging; on the other hand, increasing carbon dioxide emissions also cause global climate change, damage to animal and plant habitats and global warming. These phenomena all indicate that human damage to the earth will affect the living environment of human beings. If the situation is serious, it may threaten the survival of human beings. Therefore, in order to reduce the damage to the global environment, we must find new and clean energy, which is the green energy, including geothermal energy, tidal energy, wind energy, bio-energy and solar energy. Among them, solar energy is one of the most important green energy sources at present, because solar energy is low-pollution, does not require fuel costs, and is an inexhaustible source of energy.

Solar energy revenue growth rate of 12% in 2014, up to 1 trillion US$ 61 billion, is mainly due to the fact that today's solar cell power generation efficiency has been much higher than before, coupled with low production costs, so how to effectively apply solar energy has become an important Question. Among green energy sources, solar energy is the most convenient and clean energy source, but the current power generation efficiency of commercial solar cells is still not ideal, and the sunlight is not a full-illumination state and the surrounding green trees or buildings. Both may affect the intensity of sunlight and cause changes in the battery power-voltage characteristic curve of solar energy. In order to maintain the optimal output state of the solar cell, it is necessary to find the position of the maximum power output point of the solar cell. This technique is called maximum power. Tracking (Maximum Power Point Tracking, MPPT) technology.

Common maximum power tracking control technologies include open circuit voltage method, short circuit current method, direct measurement method, disturbance observation method and incremental conductance method. Since all kinds of maximum power tracking control technologies have their advantages and disadvantages, users must evaluate them to find the best control technology for the system. The research direction of solar cell maximum power tracking algorithm can be divided into two parts:

1. Since the maximum power tracking algorithm generates power loss during transient tracking, how to have an ideal transient response becomes an important issue in order to reduce the ability to track power loss and improve external environmental changes.

2. When operating in steady state, the solar power system must avoid the algorithm oscillating near the maximum power point and accurately place the operating point at the maximum power point position to improve the overall output efficiency, thereby reducing the tracking loss. Therefore, how to accurately find the maximum power point of the solar cell is also an indispensable part of the solar power generation system.

It can be clearly seen from the above two parts that the maximum power tracking technology emphasizes tracking fast and high steady-state tracking accuracy. Since the traditional fixed step disturbance observation method has the trade-off between transient and steady-state response, many scholars have proposed Various variable step control laws are expected to overcome the problem of the fixed step disturbance observation method, thereby improving the overall system efficiency. In the literature, the slope of the power-voltage characteristic curve of the solar cell is used as the basis for the step change, and the traditional incremental conductance method is improved into the variable step control, thereby improving the steady state response of the system. However, the slope of the solar cell power-voltage curve is not a symmetrical curve, so this approach will result in a slower tracking of the left half plane. In addition, some literatures propose the maximum power tracking method for automatically adjusting the step, which uses the incremental conductance relationship to obtain the step change curve to improve the slope of the incremental step incremental conductance method and cause the transient response to be too slow. . Some scholars have considered that the illuminance change may cause the algorithm to chase the problem. When the illuminance changes, the short-circuit current is used to directly place the operating point near the maximum power point to reduce the tracking power loss when the illuminance changes, thereby improving the transient response performance. . In addition, there are also literatures suggesting that a secondary approach is used to improve the steady state response when the solar power system reaches steady state. There are also literatures that use only one sensing element to sense current, and use relational calculations to obtain the relationship between duty cycle and current for algorithmic judgment, thereby reducing circuit cost. In addition to changing the steps, the literature also adds variable frequencies to speed up the tracking and improve the accuracy of steady-state tracking. However, more judgments must be added to achieve results, so the algorithm is more complicated and less feasible. There is also a literature using the binary approach method to avoid the need to perform tracking reset in each interval, and propose adaptive binary and step-down methods to combine the advantages of both to maximize power tracking to reduce tracking power loss and Improve the efficiency of the overall system. There are also literatures based on the incremental conductivity method applied to the solar power system to reduce the computation time and complexity of the program, thereby improving the tracking speed.

Although there are various tracking methods as described above, there is still room for improvement in their performance.

SUMMARY OF THE INVENTION A primary object of the present invention is to provide a maximum power tracking device that allows a solar cell to operate at a maximum power output state using a deterministic cuckoo search method. Compared with the traditional cuckoo search method, the decisive cuckoo bird search method adopted by the present invention can eliminate the complicated Levy Flight mode operation involved in the traditional cuckoo search method, thereby reducing the calculation amount of the program and the complexity.

To achieve the above object, a maximum power tracking device for a solar power generation system is proposed which has:

a boost converter having an input end, a control end and an output end, the input end being coupled to a solar cell, the control end being configured to receive a pulse width modulation signal, and the output end Used to couple with a load;

a digital controller for performing a deterministic cuckoo search method according to a firmware program to adjust a duty cycle of the pulse width modulation signal to gradually converge one output voltage of the solar cell to a maximum power voltage , wherein the deterministic cuckoo bird search method includes:

a first step: sequentially stopping the output voltage at three different voltage values and correspondingly measuring three power output values of the solar cell, and comparing the three different voltage values with the three power output values a voltage value corresponding to the largest one of the three stored in a first memory unit, storing a voltage value corresponding to a second largest of the three power output values among the three different voltage values a second memory unit, storing a voltage value corresponding to a minimum of the three power output values among the three different voltage values in a third memory unit;

a second step: performing a first voltage variation calculation program according to the stored value of the second memory unit and the stored value of the first memory unit to generate a first voltage variation command, and according to the first voltage variation The quantity command adjusts the duty cycle to cause the solar cell to output a tentative second high power voltage, and measure a power output value of the solar cell when outputting the tentative second high power voltage; and according to the third Performing a second voltage fluctuation amount calculation program to generate a second voltage variation amount command according to the stored value of the memory unit, the stored value of the second memory unit, and the stored value of the first memory unit, and according to the second voltage The variable amount command adjusts the duty cycle to cause the solar cell to output a tentative minimum power voltage, and measures a power output value of the solar cell when the tentative minimum power voltage is output, wherein the first voltage variation is calculated The program and the second voltage variation calculation program each include a multiplication by a variation ratio factor α, 0<α<1;

a third step: comparing, for the power output value corresponding to the first memory unit, a power output value corresponding to the tentative second high power voltage, and a power output value corresponding to the tentative minimum power voltage, Finding a new maximum power voltage that is one of the maximum power output values of the stored value of the first memory unit, the tentative second power voltage, and the tentative minimum power voltage, generating a second new second power output value a high power voltage, and a new minimum power voltage that produces one of the minimum power output values, and stores the new maximum power voltage in the first memory unit, and stores the new second high power voltage into the And storing the new minimum power voltage in the second memory unit;

Fourth step: return to the second step.

In an embodiment, the second voltage variation calculation program of the second step includes a changeover calculation program.

In an embodiment, the second voltage variation calculation program of the second step further includes a value limiting program to limit the upper and lower limits of the tentative minimum power voltage.

In one embodiment, the deterministic cuckoo search method further includes an illumination change determination step to determine whether to return to the first step.

The detailed description of the drawings and the preferred embodiments are set forth in the accompanying drawings.

Please refer to FIG. 1, which is a block diagram showing an embodiment of a maximum power tracking device for a solar power generation system of the present invention. As shown in FIG. 1, the maximum power tracking device of the solar power generation system includes a boost converter 100 and a digital controller 110.

The boost converter 100 has an input end, a control end and an output end. The input end is coupled to a solar cell 200, and the control end is configured to receive a pulse width modulation signal V _PWM . The output is coupled to a load 300.

The digital controller 110 can be implemented by a DSP (digital signal processing) chip for performing a deterministic cuckoo search method according to a firmware program to generate the pulse width modulation signal V _PWM to make the solar energy One of the battery output voltages V _PV gradually converges to a power maximization voltage, wherein the deterministic cuckoo search method includes:

The first step: sequentially stopping the output voltage V _PV at three different voltage values and correspondingly measuring three power output values of the solar cell 200, and comparing the three different voltage values with the three a voltage value corresponding to a largest one of the power output values is stored in a first memory unit, and a voltage corresponding to a second largest of the three power output values among the three different voltage values The value is stored in a second memory unit, and a voltage value corresponding to the smallest one of the three power output values among the three different voltage values is stored in a third memory unit;

a second step: performing a first voltage variation calculation program according to the stored value of the second memory unit and the stored value of the first memory unit to generate a first voltage variation command, and according to the first voltage variation The quantity command adjusts the pulse width modulation signal V _PWM to cause the solar cell 200 to output a tentative second high power voltage, and measures a power output value of the solar battery 200 when outputting the tentative second high power voltage (V). _PV *I _PV ); and performing a second voltage fluctuation amount calculation program according to the stored value of the third memory unit, the stored value of the second memory unit, and the stored value of the first memory unit to generate a first And a second voltage fluctuation amount command, and adjusting the pulse width modulation signal V _PWM according to the second voltage fluctuation amount command to cause the solar cell 200 to output a tentative minimum power voltage, and measuring that the solar cell 200 is outputting the tentative minimum power One of the power output values at voltage (V _PV *I _PV );

a third step: comparing, for the power output value corresponding to the first memory unit, a power output value corresponding to the tentative second high power voltage, and a power output value corresponding to the tentative minimum power voltage, Finding a new maximum power voltage that is one of the maximum power output values of the stored value of the first memory unit, the tentative second power voltage, and the tentative minimum power voltage, generating a second new second power output value a high power voltage, and a new minimum power voltage that produces one of the minimum power output values, and stores the new maximum power voltage in the first memory unit, and stores the new second high power voltage into the And storing the new minimum power voltage in the second memory unit;

Fourth step: return to the second step.

In the second step, the second voltage variation calculation program may include a face change calculation program (the content of which will be described in the following paragraph), and the edge calculation program may include a numerical limit program to limit the tentative The upper and lower limits of the minimum power voltage.

The principle of the invention will be explained below:

Solar cell electrical characteristics:

The electrical characteristics of a solar cell are a non-linear power source, and the voltage and current are in an exponential curve relationship. Therefore, when the output voltage of the solar cell changes, the output current also changes. 2 is a solar cell single diode equivalent circuit. It can be seen from FIG. 2 that the relationship between the output voltage and current of the solar cell can be expressed as

(1)

among them         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="37" he="23" file="02_image003.jpg" img- Format="jpg"></img></td><td> Solar cell output current</td><td><img wi="20" he="27" file="02_image005.jpg" img-format ="jpg"></img></td><td> Photoelectric conversion current</td></tr><tr><td><img wi="22" he="23" file="02_image007. Jpg" img-format="jpg"></img></td><td> Diode equivalent current</td><td><img wi="39" he="23" file="02_image009 .jpg" img-format="jpg"></img></td><td> Solar cell output voltage</td></tr><tr><td><img wi="24" he=" 23" file="02_image011.jpg" img-format="jpg"></img></td><td> Parallel equivalent resistance</td><td><img wi="23" he="23 " file="02_image013.jpg" img-format="jpg"></img></td><td> Series equivalent resistance</td></tr><tr><td><img wi=" 13" he="20" file="02_image015.jpg" img-format="jpg"></img></td><td> Charge of the carrier (<img wi="93" he="22" File="02_image017.jpg" img-format="jpg"></img>) </td><td><img wi="13" he="15" file="02_image019.jpg" img-format= "jpg"></img></td><td> Ideal Sub (between 1 and 2) </td></tr><tr><td><img wi="20" he="17" file="02_image021.jpg" img-format="jpg">< /img></td><td> Bozeman constant (<img wi="130" he="22" file="02_image023.jpg" img-format="jpg"></img>) </td ><td><img wi="15" he="17" file="02_image025.jpg" img-format="jpg"></img></td><td> Absolute Temperature</td></ Tr></TBODY></TABLE>

Since the resistance of the parallel resistance of the solar cell is much larger than the resistance of the series resistor, the equation (1) can be simplified.

(2)

In order to facilitate the observation of the influence of the ambient temperature and illuminance on the solar cell output characteristic curve, the formula (2) can be organized into

(3)

When the illuminance of the sun rises, the semiconductor increases the amount of electric energy that is transferred due to the increase in the energy of the illuminating light, so the photoelectric conversion current of the solar cell increases. It is known from equation (2) that the output current of the solar cell is proportional to the photoelectric conversion current. Therefore, when the illuminance is increased, the output current of the solar cell is also significantly increased, and it is known from the equation (3) that due to the existence of the natural logarithm, The output voltage of the solar cell changes only slightly when the illuminance rises, so the solar cell characteristic curve under different illumination can be drawn, as shown in Fig. 3a-3b, wherein Fig. 3a shows a current-voltage curve of the solar cell; Fig. 3b A power-voltage curve of one of the solar cells is shown.

Solar Maximum Power Tracking System Hardware Architecture:

The system architecture implemented by the invention comprises three parts: a solar cell simulator, a boost converter and a digital signal processor control core. Generally, the output voltage of the solar cell is generally too low, so the converter needs to be used to increase the output voltage. Therefore, the hardware circuit architecture of the present invention uses a boost converter. The controller part is implemented using a digital signal processor. By inputting the sampled solar cell output voltage and current signal to the digital signal processor for maximum power tracking operation, an appropriate duty cycle signal can be calculated to control the boost converter switching action for maximum power tracking.

The boost converter is a kind of DC-DC converter, which is composed of an inductor (L), a capacitor (C), a diode (D1) and a power switch (Q). The structure diagram is shown in FIG. 4 . The power switching MOSFET operates in the cut-off region and the saturation region, and the output voltage and current of the boost converter are adjusted by the duty cycle control. Assume that each component is in an ideal state, when the switch is turned on, the input voltage It is connected across the inductor L, so the inductor L is stored, the inductor current rises linearly, and the diode D1 is turned off due to the reverse bias. At this time, the capacitor C supplies power to the load; when the switch is turned off, the inductor current cannot be used. The flow direction is changed instantaneously, so the diode D1 is turned on, and the inductor discharges the output load. If D is the duty ratio, the output-to-voltage conversion ratio of the boost converter operated by the Continuous Conduction Mode (CCM) shown in FIG. 4 can be derived as

(4)

Solar Maximum Power Tracking System Firmware Architecture:

The output characteristic curve of a solar cell is a non-linear curve, and the apex of the curve is called a "maximum power point." In order to successfully find the maximum power point of the solar cell, a good control law and a highly accurate controller are needed. Therefore, the present invention selects the dsPIC33FJ16GS502 digital signal processor as the digital control core of the maximum power tracking control, and its control system architecture is as shown in the figure. 5 is shown. First, the sampling circuit draws the solar cell output voltage and current and sends it to the digital signal processor. After analog/digital (A/D) conversion, it enters the digital filter and then is tracked by the maximum power in the digital signal processor. The program operation obtains the voltage command, and finally uses the PID compensator to calculate the duty cycle to control the switching of the boost converter to achieve the maximum power tracking effect.

Digital filter:

Since the present invention uses digital control to implement the solar maximum power tracking technology, a digital filter is selected to assist in processing the voltage and current signals input to the microprocessor. The digital filter transfer function can be expressed as Z after being converted.

(5)

In equation (5), if the denominator coefficients u ₁ , u ₂ , u ₃ ... u _{M are} all zero, it means that the transfer function is a transfer function of the finite impulse response filter. Although the finite impulse response filter has to utilize more filtering orders, it has the advantages of absolute stability and simple design. Therefore, the present invention selects the finite impulse response filter as the sampling system filter of the maximum power tracking system. Converting the transfer function of the finite impulse response filter into a difference equation, as shown in equation (6), where m is the order of the filter and y _i is the operation coefficient.

(6)

The working principle of the finite impulse response filter is shown in Figure 6, where For the current sampling signal, For the previous sampling signal, For the first two sampling signals, and so on to the first m times, y ₀ to y _m-1 are the filter coefficients. First, the current signal and the previous signals are multiplied by the corresponding coefficients, and then the output is summed to complete the filtering, and then wait for the next sampling signal and perform the same action as described above, and repeat the action to achieve the filtering effect. .

Digital PID controller:

Figure 7 shows the block diagram of the PID control structure. The principle of the PID controller is to control the error between the output and the command, and use the results obtained by proportional, integral and differential operations to control the controlled body. In order to make the system output the same as the command value, the command value x (t) is subtracted from the output feedback amount y (t) to generate an error amount e (t), and then an output is obtained after the PID controller operation. The control quantity u (t) is as shown in equation (7). Where K _p represents the proportional gain, K _I represents the integral gain, and K _D represents the differential gain.

(7)

Equation (7) is a continuous PID controller. Because the input and output signals of the digital control system exist in discrete form, it cannot be directly applied to the digital control system. It is necessary to use a discretization method to calculate the digital sampling. Using Euler's approximate integral and differential methods, as shown in equations (8), (9), and (10)

(8)

(9)

(10)

According to equations (8), (9), (10), a discrete PID controller expression can be obtained, as shown in equation (11), where e (n) is the current systematic error amount, and e (n-1) is the system. The previous error amount and T are the sampling period.

(11)

The built-in register of the digital signal processor has a fixed bit width. If the digital PID processor implements the digital PID control, the integral saturation may occur due to the existence of the integral term of the equation (11), resulting in the digital signal processor. The built-in scratchpad overflows due to continuous accumulation, which indirectly affects the control amount of the digital PID controller. In order to prevent the problem of integral saturation from occurring, the present invention employs an incremental PID controller whose expression is as shown in equation (12), wherein For the output variation, e (n) is the current system error, e (n-1) is the system's previous error, e (n-2) is the system's first two errors and T is the sampling period, and the increment The type PID control is only related to the current error amount, the previous error amount, and the first two error amounts, so the problem of integral saturation can be avoided.

(12)

The implementation process of the incremental PID program proposed by the present invention is as shown in FIG. 8. First, the output command value is subtracted from the current output sample value to obtain an error value e ( n ), and then the previous error amount e ( n -1 ) ) and the first two error quantities e ( n -2) are respectively calculated to obtain A, B and C values, and then the values are substituted into equation (12) to obtain an output variation Δ u , and the output result (PID) _Out ) is equal to Δ u and is added to the previous duty cycle (Duty), and then compared with the set upper and lower limits of the duty cycle. If the output is less than Duty _min or greater than Duty _max , the output is equal to Duty _min or Duty respectively. _Max , finally based on PID _out to generate the required duty cycle to achieve the purpose of stabilizing the output voltage or current.

The maximum power tracking algorithm proposed by the present invention:

Rhododendron search rule:

The cuckoo bird search method is inspired by the parasitic and breeding strategies of the cuckoo bird. Its parasitic and breeding strategies can be divided into the following three types:

1. Competing with the same species of organisms for survival: the behavior is as competitive as the performance of each particle in the algorithm.

2. Cooperate with the original nest master: its behavior is like the particle individual and the compared particle individual balance each other, so it does not replace its particle individual.

3. Directly occupy the nest of the original nest: its behavior is more powerful than that of the individual particles, so it can be replaced by the meaning of the nest.

The Levy flight pattern mentioned in the literature is a model discovered by the German physicist Dirk Brockmann in 2004. Dirk Brockmann found in the study of banknote circulation rules that most of the time, banknotes will only be circulated in a small area, and only a small amount of time will flow to distant places. The Levi flight mode is like an animal foraging mode. In most cases, it will only look for food for food nearby. In a few days, it will go far to find food for food. The schematic diagram is shown in Figure 9, and the literature will The theory sets the strategy for the cuckoo to search the nest, and its velocity vector can be expressed as

(13)

among them For the next speed vector, The current velocity vector of the system, a is the limit variation factor, Multiply the individual bullets on the right side for the left item and For the Levi flight function, and Relationship can be expressed as

(14)

Where l is the system random number, For the flight length, and through the parameter design conditions, it can be observed that the range of the Levi flight parameters can be from zero to infinity to facilitate searching for the global maximum power point position.

The program flow using the cuckoo search method for maximum power tracking is shown in Figure 10. First, the parameters are initialized, the output voltage and current of the solar cell are sampled, the power of the solar cell is calculated, and the distance between the voltage particles is determined. If the distance is less than 0.1, it means that it has been chased to the vicinity of the maximum power point. , indicating that its power has a tendency to rise or fall, it means that the illuminance change occurs, the program is re-initialized; if it is judged that no illuminance change occurs, it continues to judge whether its power is greater than zero, and if its power is less than zero, it directly enters the end of the program. If the power is greater than zero, it is judged whether the time has reached the set time. If the time has not reached the specified time, and the output power of this time is greater than the previous adaptation value, then The output voltage and power are recorded; if the output power is not greater than the previous adaptation value, the output voltage and power are not recorded; on the other hand, if the time is counted to the specified time and Lévy = 0, the usage formula (13) Calculate the next voltage command; if Lévy=1, discard the worst-case stored value, create a new voltage command, achieve the effect of Levi flight, and finally continue to repeat according to the above process.

Deterministic cuckoo bird search method:

Because the cuckoo search program is too complicated, it is necessary to calculate the random random number and the power function. The calculation is quite complicated. It is difficult to implement on the actual low-cost digital signal processor, and the intricate judgment and calculation may increase the digital signal processor. By misjudge the probability and increase the tracking time, the tracking performance is degraded. Therefore, the present invention proposes a deterministic cuckoo search method, which improves the complicated program flow and maintains the simple process before maintaining the concept of the algorithm and its tracking performance. And the operation achieves superior tracking performance. The basic operation principle of the deterministic cuckoo bird search method proposed by the present invention is as shown in Fig. 11. The system first starts with a fixed position three-point voltage command ( , , Sampling, if the voltage point with the maximum power between the three is called The voltage point between the maximum and minimum power is called The minimum power voltage point is called If it can versus Voltage points are each oriented The voltage point moves, continuing the aforementioned action versus Voltage point is close The voltage point can achieve the maximum power tracking effect, and the voltage command variation relationship is as shown in equations (15) and (16), where D V _{cmd , b} is the voltage command variation of V _b , D V _{cmd , c} is the voltage command variation of V _c and a is the variation scale factor.

(15)

(16)

However, the decisive type of cuckoo bird search method has a disadvantage in its operation when the initial particle point If the voltage point is not set properly, the system will not be able to track the maximum power point of the system smoothly. Therefore, the present invention proposes a mechanism for preventing mis-chasing to avoid this situation, and the action principle of the edge-changing mechanism for preventing mis-chasing is as shown in the figure. 12 is shown. When the program judges that V _{a , 1} voltage point is at the leftmost or rightmost side of the three points, the program will start the changing mechanism, V _{a , 1} voltage point will remain unchanged, so V _{a , 1} voltage point is equal to V _{a , 2} voltage point , V _{c , 1} voltage point shift to the other side of V _{a , 1} voltage point, at this time the minimum V _{c , 2} voltage point command can be calculated by (17), because the three points become a diagonal line, so V _{b , 1} voltage The distance between the point and the voltage point of V _{a , 1} is short, and the distance is used as the variation of the changing mechanism to prevent the tracking distance from being too large and the tracking speed to be lowered.

(17)

The operation process of the decisive cuckoo bird search method is shown in Figure 13. First, set the particle initial placement position 0 < par 1, par 2, par 3 <100% and the variation scale factor 0 < a < 1, and then sample the solar cell. The open circuit voltage, the initial particle placement operation and sampling the output voltage and current of each particle point to calculate each output power value, and then determine whether there is a change in illumination, and if the illumination changes, the system restarts; otherwise, Find the maximum, median and minimum power points of each particle point, and judge the demand of the changing edge mechanism. If it is judged that the edge changing mechanism is not needed, the next V _{a , new} voltage point is maintained at the V _a voltage point, the next time V _{b , new} voltage point is moved from the previous V _b voltage point by a times of ( V _a - V _b ) toward the previous V _a voltage point, the next V _{c , new} voltage point is from V _c voltage point ( V _a - V _c) of times toward a point is moved the previous V _a voltage; contrary, if the maximum power point voltage of the maximum point or the minimum voltage point, it indicates the need for mode change mechanism side, this time under a V _{a, new new} voltage point Then continue to maintain the V _a voltage point, and the next time V _{b , new} voltage point is shifted from the previous V _b voltage point by a times of ( V _a - V _b ) toward the previous V _a voltage point, and the next V _{c , new} voltage point needs to be changed to another point of the side of the voltage V _a, V _a voltage using point to the anchor point (V _a - V _b) of a fold in the opposite direction toward the moving point voltage V _b, and then determines the last edge change point V _{c, new} exceeds The boundary set by the program, if it exceeds the boundary value, is fixed within the set boundary to prevent the system from generating an erroneous voltage command, and the above process can be traced to the maximum power point. The illuminance change judgment in the flow chart is based on the voltage difference and power difference of each particle point. If the voltage difference between the particle points is less than 0.1, it means that it has been chased to the vicinity of the maximum power point. In theory, the power will not be too large. Difference, but if the power difference is greater than 10 watts at this time, it means that the illuminance changes.

Firmware implementation:

The invention selects a digital signal processor to implement the control core, and FIG. 14 shows the firmware main program implementation architecture, including digital signal processor internal working environment setting and initialization, input/output pin selection, interrupt demand design, analogy/ Digital converter (ADC), pulse width modulation (PWM) and timer related settings. First, the digital signal processor initializes the variables used in the program, initializes the internal oscillator, plans the input/output pin, design timer (TIMER), analog/digital converter (ADC), and pulse width modulation. The (PWM) module enables the Analog/Digital Converter (ADC) and Pulse Width Modulation (PWM) module interrupt vectors, and the main program will enter an infinite loop to wait for the interrupt to occur. The interrupt of the present invention uses only ADC interrupts, which can be subdivided into three parts: sampling, filtering, and maximum power tracking subroutine. The sampling portion converts the analog quantity into a digital quantity input to the digital signal processor by using an analog/digital converter. In order to prevent the high frequency noise from affecting the program misjudgment, the present invention uses a 16th order finite impulse response filter to eliminate high frequency noise and restore the real signal. In addition, the actual solar radiation of the solar cell power generation system changes slowly. Therefore, the present invention designs a voltage command for 0.2 seconds. Since the programmed ADC interrupt interval is 1 ms, the time count is designed to be 200, and when the count is not counted to 200 times, only The solar cell input voltage and current sampling values are FIR filtered, and the PID operation is used to follow the voltage command given by the solar maximum power tracking subroutine to achieve accurate voltage tracking; conversely, if the count is 200, it means that 0.2 seconds have passed. Then, it is judged whether there is power supply at the input of the boost converter. If there is power supply, the maximum power tracking subroutine is executed, and the timecount is reset to zero for the next recount; otherwise, if there is no power supply, the timecount is reset to zero for the next recount. And enter the rest mode. The maximum power tracking can be completed by sequentially operating the above actions in sequence.

Comparative analysis of experimental verification and results:

Experimental environment and equipment:

In order to test the correctness of the deterministic cuckoo bird's maximum power tracking search method of the present invention, the TESTS company's TerraSAS ETS 600X8 D-PVE solar cell simulator was used in the actual test, and the model HESPV was introduced as HES- 50 solar cells (a total of 5 chips) as the system input source, solar cell electrical specifications as shown in Table 1, the electrical specifications of the corresponding solar cell simulation curve after series connection, as shown in Table 2, the resulting solar cell simulation The curve is shown in Figure 15. The power stage circuit is a boost converter circuit, and its specifications are shown in Table 3. The control stage circuit uses the dsPIC33FJ16GS502 digital signal processor introduced by Microchip as the control core to control the power switch of the power stage circuit to achieve the maximum power tracking of the system. .

Table 1. Electrical Specifications for HES-50 Solar Modules         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Model</td><td> HES-50 </td></tr><tr ><td> Maximum power <img wi="33" he="27" file="02_image087.jpg" img-format="jpg"></img></td><td> 50 W </td> </tr><tr><td> Open circuit voltage <img wi="24" he="23" file="02_image089.jpg" img-format="jpg"></img></td><td> 22.1 V </td></tr><tr><td> Short circuit current <img wi="23" he="23" file="02_image091.jpg" img-format="jpg"></img>< /td><td> 3.14 A </td></tr><tr><td> Maximum power point voltage <img wi="33" he="27" file="02_image093.jpg" img-format=" Jpg"></img></td><td> 17.2 V </td></tr><tr><td> Maximum power point current <img wi="31" he="27" file="02_image095 .jpg" img-format="jpg"></img></td><td> 2.91 A </td></tr></TBODY></TABLE>

Table 2. Electrical specifications for five-piece solar modules         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Maximum power <img wi="33" he="27" file="02_image087.jpg" Img-format="jpg"></img></td><td> 250W </td></tr><tr><td> Open circuit voltage <img wi="24" he="23" file= "02_image089.jpg" img-format="jpg"></img></td><td> 110.5V </td></tr><tr><td> Short circuit current <img wi="23" he ="23" file="02_image091.jpg" img-format="jpg"></img></td><td> 3.14 A </td></tr><tr><td> Maximum Power Point Voltage <img wi="33" he="27" file="02_image093.jpg" img-format="jpg"></img></td><td> 88.52 V </td></tr><tr ><td> Maximum power point current <img wi="31" he="27" file="02_image095.jpg" img-format="jpg"></img></td><td> 2.84 A </ Td></tr></TBODY></TABLE>

Table 3. Boost Converter Specifications         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Input voltage (<img wi="23" he="23" file="02_image097.jpg " img-format="jpg"></img>) </td><td> 70~120V </td></tr><tr><td> Output voltage (<img wi="20" he= "23" file="02_image098.jpg" img-format="jpg"></img>) </td><td> 180V </td></tr><tr><td> Output Power (<img Wi="20" he="23" file="02_image100.jpg" img-format="jpg"></img>) </td><td> 250W </td></tr><tr>< Td> Switching frequency (<img wi="20" he="23" file="02_image102.jpg" img-format="jpg"></img>) </td><td> 50kHz </td> </tr><tr><td> output voltage chopping (D<i>V_o</i>/<i>V_o</i>) </td><td> 1% </td></tr><tr><td> Output current chopping (D<i>I_o</i>/<i>I _o</i>) </td><td> 20% </td></tr></TBODY></TABLE>

Measurement project and performance evaluation definition:

In the comparison of the maximum solar power tracking methods, a set of standard measurement items and performance evaluation criteria must be established to achieve comparative fairness. The present invention defines the following measurement project criteria for comparison, a schematic of which is shown in FIG.

Rise time : The time required to increase the power initial value to 95% of the maximum power line.

2. Stabilization time : Time from the initial value of the power to the amplitude within the range of less than ±1% of the maximum power line (99% of the maximum power line).

3. Steady-state average power: The sum of the power of 1 second after the steady state is recorded, and divided by the amount of recorded data.

4. Steady-state tracking accuracy: The data obtained by dividing the above-mentioned steady-state average power by the maximum power value.

5. Tracking power loss: record the tracking power value to 10 seconds, and then use the maximum power value minus the value of each power tracking point. The setting of 10 seconds is mainly based on the simulation result. The maximum stabilization time of each method is 5 seconds. Therefore, multiply it by 2 to balance the tracking power loss during transient and steady state evaluation.

6. Average tracking power loss: The tracking energy loss described above is divided by 10 seconds.

The energy of the solar power system comes from the sun, and in normal day, the illuminance of the solar energy changes with the rotation of the earth, but the change is small and the time interval is long, indicating that the solar power system will be in a stable state for a long time. Only a small part of the time needs to re-execute the maximum power tracking, so the present invention sets the steady-state tracking accuracy as the first priority consideration item, the secondary is the average tracking power loss, and finally the rise time and steady-state time considerations. Therefore, the tracking performance evaluation criteria of the present invention are defined as

(18)

From (18), the steady-state tracking accuracy, rise time performance and settling time performance can be known by the above measurement method, while the average tracking power loss is different from the previous factors. The worse, the present invention finds the maximum average tracking power loss for each method, and uses the difference between the maximum average power loss and the average power loss to calculate its average tracking power loss performance.

Simulation results:

In order to verify the correctness and performance improvement of the proposed maximum power tracking method, the simulation results will be compared with the prior art, including fixed step disturbance observation method and variable step disturbance observation method (including scale factor M method, digital PI control disturbance). Observation method, adaptive variable step incremental conductivity method) for comparison. When performing the simulation of each maximum power tracking algorithm, the maximum power tracking command variation value is represented by a step. The present invention defines a step by step of 0.2 seconds to record each maximum power tracking algorithm. Table 4 shows the simulation results of the fixed step disturbance observation method, which has a fixed step ( Using 1 V, 3 V and 5 V for simulation and analysis and comparison, the trade-offs of the fixed step disturbance observation method can be clearly seen from Table 4. When the fixed step value is 5 V, there is a faster tracking. The speed makes the tracking energy loss less in 10 seconds, but because it can not reach the stable state defined by the present invention, the stabilization time is infinitely long, and the steady-state tracking accuracy is low. If the tracking power loss calculation time is lengthened, This value is increased indefinitely; when the fixed step value is 1 V, the steady-state tracking accuracy is high, but because of its slow tracking speed, the rise time and the settling time are long, which also affects the tracking power loss and greatly reduces The performance score is; and when the fixed step value is 3 V, the measured values are averaged, so that the performance score is the highest, so the present invention will select the design parameter value and compare the proposed algorithm. analysis.

Table 4. Simulation results for fixed step disturbance observations         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Step value measurement project</td><td><img wi="91" he ="23" file="02_image112.jpg" img-format="jpg"></img></td><td><img wi="93" he="23" file="02_image114.jpg" img -format="jpg"></img></td><td><img wi="93" he="23" file="02_image116.jpg" img-format="jpg"></img>< /td></tr><tr><td> Rise time</td><td> - seconds</td><td> 5 seconds</td><td> 3.2 seconds</td></tr> <tr><td> Stabilization time</td><td> - Seconds</td><td> 5.8 seconds</td><td> - Seconds</td></tr><tr><td> Steady State average power </td><td> 180.68 W </td><td> 257.65 W </td><td> 252.78 W </td></tr><tr><td> steady state tracking accuracy < /td><td> 69.7 % </td><td> 99.4 % </td><td> 97.52 % </td></tr><tr><td> Tracking Power Loss</td><td> 7523.9 J </td><td> 2933.3 J </td><td> 1956.9 J </td></tr><tr><td> Average tracking power loss</td><td> 150.48 W </td ><td> 58.67 W </td><td> 39.14 W </td></tr><tr><td> Performance</td><td> 46.77 points</td><td><b> 82.973</b> points</td><td> 81.398 points </td></tr></TBODY></TABLE>

Then, the three variable step-step maximum power tracking algorithms are simulated. Since each algorithm needs to adjust the parameters to get the better value of the system, the trial and error method is used to find the algorithms according to the defined evaluation rules. Better performance score. The optimal performance parameters of each algorithm are listed in Table 5. It can be observed that the steady-state tracking accuracy of each algorithm can reach 100%. This phenomenon can be seen that the variable step control and the traditional fixed step control Differences, in addition, it can be found that the rise and settling time of each algorithm are the same, indicating that it is limited by the maximum value of the voltage fluctuation command, so the variable step control solves the trade-off problem of the fixed step size design, but derives The trade-off problem of the maximum step size. It can be seen from the performance scores that the three-step variation of the step-by-step perturbation observation method is the highest, so the variable step disturbance observation method is selected to compare and analyze with the proposed algorithm.

Table 5. Simulation results for each step of the variable step         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Method measurement items</td><td> Change step disturbance observation method (M =0.17) </td><td> Digital PI Control Disturbance Observation Method (K_p=0.45, K_i=20) </td><td> Adaptive Variable step incremental conductivity method <img wi="102" he="26" file="02_image118.jpg" img-format="jpg"></img></td></tr><tr> <td> Rise time</td><td> 3.2 seconds</td><td> 3.2 seconds</td><td> 3.2 seconds</td></tr><tr><td> settling time</ Td><td> 3.8 seconds</td><td> 3.8 seconds</td><td> 3.8 seconds</td></tr><tr><td> steady state average power</td><td> 259.21 W </td><td> 259.19 W </td><td> 259.21 W </td></tr><tr><td> Steady-state tracking accuracy</td><td> 100 % </ Td><td> 100 % </td><td> 100 % </td></tr><tr><td> Tracking Power Loss</td><td> 1787.7 J </td><td> 1789.6 J </td><td> 1811.7 J </td></tr><tr><td> Average tracking power loss</td><td> 35.76 W </td><td> 35.79 W </td> <td> 36.23 W </td></tr><tr><td> Performance</td><td><b>89.424</b><b>分</b></td><td > 89.415 points </td ><td> 89.377 points </td></tr></TBODY></TABLE>

In addition, the present invention will vary the factor Divided into 16 equal parts, the reason is that in the digital implementation, the numerical division increases the time and difficulty required for the operation. Therefore, using the multiple of 2 as the denominator, using the characteristics of the binary, the data is shifted to the left or right in the program. Move to perform division to simplify the operation, and the 16/16 value is 1, this value will cause the system to misjudge the maximum power point, so it is not included in the simulation and implementation comparison and analysis. Table 6 lists the simulation results for various variation factors a under uniform illumination, which can be seen with the variation factor. The larger the system, the faster the system is stable and the higher the performance score.

Table 6. Simulation results for the deterministic cuckoo search method under different a         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> variation factor a </td><td> performance</td><td> variation factor a </td><td> Performance </td><td> Change factor a </td><td> Performance </td></tr><tr><td> 1/16 </td> <td> 79.79 points</td><td> 6/16 </td><td> 94.02 points</td><td> 11/16 </td><td> 96.50 points</td></tr ><tr><td> 2/16 </td><td> 85.85 points</td><td> 7/16 </td><td> 94.02 points</td><td> 12/16 </ Td><td> 96.50 points</td></tr><tr><td> 3/16 </td><td> 89.85 points</td><td> 8/16 </td><td> 94.02 points</td><td> 13/16 </td><td> 96.50 points</td></tr><tr><td> 4/16 </td><td> 91.92 points</td ><td> 9/16 </td><td> 94.02 points</td><td> 14/16 </td><td> 96.50 points</td></tr><tr><td> 5 /16 </td><td> 93.12 points</td><td> 10/16 </td><td> 94.02 points</td><td><b>15/16</b></td ><td><b>96.50</b><b>分</b></td></tr></TBODY></TABLE>

In addition, the proposed determinant cuckoo bird search method can also be used in partial shading. Because it has the spirit of particle swarm algorithm, it can increase the hit area by using the scattered particle points to gradually search for the characteristics of the maximum power point. The probability of the maximum power point, so in the simulation, the partial shielding is also considered in the comparison. Since five solar cells are used for series connection, each illumination has a minimum difference of 100 W/m ² and a total of 252 can be calculated considering that the illumination is not repeated. ) Different kinds of shielding situations. Simulations were performed for 252 different occlusion scenarios, and 252 masking simulation results were compiled, as shown in Figure 17. From the hit rate of successful maximum power, it can be known that the variation factor a of the best performance under uniform illumination is 15/16, but the simulation results in 252 kinds of shielding cases are not satisfactory; the variation factor a is 9/. At 16:00, the hit rate was as high as 249 times, and only 3 kinds of masking conditions could not successfully hit the maximum power point of the whole region. Since the actual application environment cannot meet the uniform illumination at all times, the present invention adds part of the masking situation to the evaluation consideration, and finally selects the variation factor a to be 9/16 to be compared and analyzed with other methods.

The performance of the simulation results in the various algorithms is shown in Table 7. It can be seen from the table that the disturbance observation method is easy to implement and simple in structure, but the step design must consider the trade-off problem. The three variable step control algorithms proposed in the literature all solve the trade-off problem of the fixed step disturbance observation method. Therefore, a good steady-state response is obtained, but the complexity of the program operation is increased, and at the same time, the problem that the disturbance observation method is limited to the maximum power point of the region in the partial masking condition and the mis-chasing phenomenon occurs is not solved; The proposed decision-making cuckoo bird search method not only solves the design trade-off problem of the fixed step disturbance observation method, but also successfully achieves the maximum power high hit rate of the partial coverage. The only shortcoming is the shortcoming of all algorithms. Can not be applied to a variety of solar cell curves, that is, the variation factor a needs to be simulated according to system characteristics to find the optimum value for the system.

Table 7. Comparison of simulation results for various algorithms         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Tracking algorithm measurement project</td><td><img wi="93" he ="23" file="02_image114.jpg" img-format="jpg"></img></td><td> Change step disturbance observation (M=0.17) </td><td> Rhododendron search method a=15/16 </td></tr><tr><td> rise time</td><td> 5 seconds</td><td> 3.2 seconds</td><td > 0.6 seconds</td></tr><tr><td> Stabilization time</td><td> 5.8 seconds</td><td> 3.8 seconds</td><td> 1.8 seconds</td> </tr><tr><td> steady state average power</td><td> 257.65 W </td><td> 259.21 W </td><td> 259.21 W </td></tr>< Tr><td> Steady-state tracking accuracy</td><td> 99.4 % </td><td> 100 % </td><td> 100 % </td></tr><tr><td > Tracking Power Loss</td><td> 2933.3 J </td><td> 1787.7 J </td><td> 412.69 J </td></tr><tr><td> Average Tracking Power Loss < /td><td> 58.67 W </td><td> 35.76 W </td><td> 8.25 W </td></tr><tr><td> Performance </td><td>< b>82.973</b> points</td><td><b>89.424</b> points</td><td><b>96.77</b> points</td></tr></ TBODY></TABLE>

results of testing:

The measured condition of the invention is the same as the simulated environment condition, and each algorithm updates the maximum power tracking command by 0.2 seconds, wherein the fixed step disturbance observation method and the variable step disturbance observation method only test the general uniform illumination (Standard Test Condition). , STC) situation, and the deterministic cuckoo search method proposed by the present invention will increase the partial obscuration test. It is known from the simulation results that the fixed step-order disturbance observation method performs best when the voltage variation command D V _cmd = 3V is selected, so the voltage variation command is used. Set to 3 V to perform the actual measurement, the measured waveform is shown in Figure 18 and record the relevant measurement project data; using the best performance of the step-by-step disturbance observation method, the scale factor M design value is 0.17 for the actual test. In fact, the measured tracking waveform is shown in Figure 19. The deterministic type of cuckoo bird search method of the present invention is divided into general uniform illuminance measurement and partial occlusion measurement. Using the best variation factor a design value of 9/16 for general uniform illumination measurement, the actual measurement tracking waveform is shown in Figure 20.

Figure 21 is an enlarged view of the waveform of Figure 20, wherein the step number indication of the voltage-time tracking waveform diagram can be linked to the digital point of Figure 22, and the method of the present invention can be judged as to whether it is correct. It can be seen from Fig. 21 that the initial points 1, 2, and 3 are initial particle point settings, which are open circuit voltage values set at 0.85, 0.5, and 0.15 times. As shown in Fig. 22, an oblique line is formed at the beginning, according to prevention. The principle of mismatching the edge-changing mechanism, when this happens, the edge-changing operation needs to be performed. Therefore, it can be seen from the changes of the 4th and 5th points in Fig. 21 that the system will retain the first point position and continue to operate the points. At the 6th position, when searching to the 6th, 7th, and 1st points, it can be seen in Figure 22 that each power point presents a diagonal line, and the replacement operation is required, so it can be 8th and 9th in Figure 21. As seen from the point change, the system will change the current maximum power point from the 1st position to the 6th position, and continue to move each operation point to the 6th position. Maximum power tracking can be accomplished by continuing as described above.

Partial shading will cause multiple peaks in the solar cell characteristic curve, and the number of peaks depends on how many different illumination levels are present. The invention adopts five sets of solar cells in series for actual measurement, so in the most extreme case, five different illumination levels will appear, resulting in five peak points of the characteristic curve. When the five solar cell illuminances are 100W/m ² , 200W/m ² , 300W/m ² , 500W/m ² and 900W/m ² respectively, the global maximum power point will appear at the second peak position, and the global maximum power point The measured solar cell characteristic curve at the second peak position is shown in Fig. 23. The maximum power P _mpp is 56.18 W, the maximum power voltage point V _mpp is 36.54 V, and the maximum power current point I _mpp is 1.537 A. The measured tracking waveform is shown in Figure 24. The waveform is enlarged as shown in Figure 25. The step number of the voltage-time tracking waveform can be linked with the digital point of Figure 25. It can be seen that the initial 1, 2, and 3 points are initial particles. Point setting, which is an open circuit voltage value set at 0.85, 0.5, and 0.15 times, wherein the second point is the maximum of the three, so the first and third points move toward the second point to form the fourth and fifth points. Then, the second, fourth, and fifth points are analyzed, and the fifth point is the maximum point and the leftmost point of the three points. Therefore, the edge changing operation is required, and the fifth point is set as the maximum point position, and the three points are The fourth point of the minimum point is changed to the other side of the maximum point position to achieve the edge changing action, while the second point continues to move toward the fifth point of the maximum point, and then the above action can be continued to track the maximum power point of the whole field. Position, to achieve the goal of global maximum power tracking, as shown in Figure 26, the tracking accuracy after convergence is 99.83%.

Comparison and analysis of experimental results:

The simulation results of each algorithm are compared with the measured results and are listed in Table 8. It can be seen from Table 8 that the actual test and simulation results of the present invention are very small, so that the correctness of the simulated data of the present invention can be verified. In the actual test results, it can be observed that the fixed step-level disturbance observation method cannot meet the requirement of short rise time and high steady-state tracking accuracy because the step size cannot be adjusted with time, so the fixed step-order disturbance observation method The rise time, settling time and steady-state tracking accuracy are inferior to the other two; while the variable step disturbance observation method successfully overcomes the trade-off problem of the fixed step disturbance observation method, but also derives the step maximum The design problem, the maximum step size will lead to system instability, on the contrary, the maximum step size of too small will also cause the transient response speed is too slow, so the variable step disturbance observation method must be a different pair The electrical specifications of the solar cells are designed to increase the design difficulty; and the deterministic cuckoo search method proposed by the present invention can solve the problems of the above two algorithms, thereby improving the performance of each measurement project.

Table 8. Comparison of simulation and actual measurement of each algorithm         <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Algorithm Performance Project</td><td> Fixed Step Disturbance Observation Method</td> <td> Fixed Step Disturbance Observation Method</td><td> Deterministic Rhododendron Search Method</td></tr><tr><td> Simulation Results</td><td> Measured Results</td ><td> Simulation Results</td><td> Measured Results</td><td> Simulation Results</td><td> Measured Results</td></tr><tr><td> Rise Time< /td><td> 5 seconds</td><td> 4.6 seconds</td><td> 3.2 seconds</td><td> 2.8 seconds</td><td> 0.6 seconds</td><td > 1.8 seconds</td></tr><tr><td> Stabilization time</td><td> 5.8 seconds</td><td> 5.6 seconds</td><td> 3.8 seconds</td> <td> 3.4 seconds</td><td> 2.8 seconds</td><td> 3 seconds</td></tr><tr><td> steady state average power</td><td> 257.65 W </td><td> 248.61 W </td><td> 259.21 W </td><td> 249.8 W </td><td> 259.21 W </td><td> 251.16 W </td>< /tr><tr><td> Steady-state tracking accuracy</td><td> 99.4 % </td><td> 98.92 % </td><td> 100 % </td><td> 99.40 % </td><td> 100 % </td><td> 99.94 % </td></tr><tr><td> Tracking Power Loss</td><td> 2933.3 J </td><td > 208 2.49 J </td><td> 1787.7 J </td><td> 1092.89 J </td><td> 490.61 J </td><td> 502.62 J </td></tr><tr>< Td> Average tracking power loss</td><td> 58.67 W </td><td> 41.65 W </td><td> 35.76 W </td><td> 21.86 W </td><td> 9.81 W </td><td> 10.05 W </td></tr></TBODY></TABLE>

In terms of transient performance, the rise time of the present invention is reduced by 2.8 seconds compared to the fixed step disturbance observation method, and is reduced by 0.8 seconds compared with the variable step disturbance observation method; the stabilization time is compared to the fixed step disturbance The observation method was reduced by 2.6 seconds, which was reduced by 0.4 seconds compared with the variable step disturbance observation method, so that the method proposed by the present invention has the advantage of fast tracking. In the steady-state part, the fixed-step disturbance observation method will oscillate near the maximum power point and will cause the steady-state average power to decrease. The steady-state average power is only 248.61 W, and the steady-state tracking accuracy is 98.92%. The variable step disturbance observation method adds a variable step and greatly reduces the oscillation near the maximum power point. Compared with the fixed step disturbance observation method, the steady state tracking accuracy can be effectively improved to 99.40%; The steady-state tracking accuracy of the deterministic cuckoo search method is 99.94%, which is 1.02% and 0.54% higher than the first two methods. Therefore, the deterministic cuckoo search method of the present invention has a better steady state response. In the tracking of power loss, due to the fixed-step disturbance observation method, the step design must consider the trade-off between transient and steady-state response performance, and can not take into account the performance of both, the average tracking energy loss is more, and the variable step disturbance The observation method is faster than the fixed step disturbance analysis method, so the average tracking energy loss is reduced by 47.5 % compared with the fixed step disturbance observation method; and the deterministic cuckoo bird search method proposed by the present invention regardless of the transient state The steady-state response has a good performance, so the average tracking energy loss is the lowest of the three methods, which is 75.87 % lower than the fixed step disturbance observation method, and 54.02% compared with the variable step disturbance observation method. The results are the best.

in conclusion:

The invention proposes a deterministic cuckoo bird searching method, and the invention adopts the spirit and concept of the traditional cuckoo bird searching method, but simplifies the program judgment and calculation process and implements it in the digital signal processor, and finally is more common with the current industry. The performance of the disturbance observation method is used for performance comparison and evaluation analysis. According to the measured results, it can be seen that although the disturbance observation method can use the variable step to improve the tradeoff between the transient and steady state response, the tracking method of the present invention can be applied to the tracking method of the present invention. Partially obscured and with good performance regardless of transient or steady-state response, so the performance in terms of rise time, steady-state time, tracking energy loss and average tracking energy loss are the best of the three, and stable State tracking accuracy is as high as 99.94%, which is an increase of 0.5% compared to the variable step. It can be seen from the above that the deterministic cuckoo bird search method proposed by the present invention has both a fast transient response and a high-performance steady-state response, and also improves the problem that the variable step cannot be applied to partial shading, so the method can be applied to any environment. Successfully achieved the goal of maximum power tracking of solar cells.

The present invention has been disclosed in its preferred embodiments, and it is obvious that those skilled in the art will be able to illuminate the subject matter of the present invention without departing from the scope of the invention.

In summary, the present invention, regardless of its purpose, means and efficacy, is showing its technical characteristics different from the prior art, and its first invention is practical and practical, and is also in compliance with the patent requirements of the invention, and is requested to be examined by the reviewing committee. Pray for the patents at an early date.

100‧‧‧Boost Converter

110‧‧‧Digital Controller

200‧‧‧ solar cells

300‧‧‧load

1 is a block diagram showing an embodiment of a maximum power tracking device of a solar power generation system of the present invention. 2 is an equivalent circuit diagram of a single diode of a solar cell. Figures 3a-3b are a current-voltage curve and a power-voltage curve for a solar cell, respectively. Figure 4 illustrates a boost converter of the present invention. FIG. 5 illustrates a control system architecture of the present invention. FIG. 6 is a schematic diagram showing the working principle of a finite impulse response filter according to the present invention. Figure 7 is a block diagram of a PID control structure taken in the present invention. FIG. 8 is a flow chart of an incremental PID controller according to the present invention. Figure 9 is a schematic diagram of a Lévy flight pattern. Figure 10 is a flow chart showing the program of a cuckoo search method. Figure 11 is a diagram showing the basic operation principle of the deterministic cuckoo searching method of the present invention. FIG. 12 is a schematic diagram of the operation of the edge changing mechanism for preventing mis-tracking according to the present invention. Figure 13 is a flow chart showing the operation of a deterministic cuckoo search method according to the present invention. FIG. 14 is a schematic diagram of a firmware main program implementation architecture. Figure 15 is a graph of I-V, P-V simulation of a solar cell. Figure 16 illustrates the measurement project criteria defined by the present invention. FIG. 17 is a diagram showing the hit rate of the maximum power successfully recovered by the different a values in the case of partial masking. Figure 18. depicts a measured waveform of a fixed step disturbance observation method. FIG. 19 illustrates a measured waveform of a variable step disturbance observation method. Figure 20 is a measured waveform of a determined cuckoo bird search method under uniform illumination according to the present invention. Figure 21 shows the deterministic cuckoo search method for the power and voltage waveform amplification of uniform illumination. Fig. 22 is a diagram showing the operation of preventing the wrong chasing and changing the mechanism of the deterministic cuckoo bird searching method of the present invention. Figure 23 is a diagram showing the tracking waveform of one of the maximum power points of the whole domain in a measured operation of the present invention. Figure 24 is an enlarged view of the tracking waveform of Figure 23. FIG. 25 is a schematic diagram of one of the operations of the edge changing mechanism of the present invention when the second peak is the global maximum power point. Figure 26. The second peak of the present invention is the actual measurement of the global maximum power point.

100‧‧‧Boost Converter

110‧‧‧Digital Controller

200‧‧‧ solar cells

300‧‧‧load

Claims (3)

A maximum power tracking device for a solar power generation system, comprising: a boost converter having an input end, a control end and an output end, wherein the input end is coupled to a solar cell, and the control end is used Receiving a pulse width modulation signal, and the output end is coupled to a load; and a digital controller for performing a decisive cuckoo search method according to a firmware program to adjust the pulse width modulation One of the signals is responsible for the cycle, such that the output voltage of one of the solar cells gradually converges to a power maximizing voltage, wherein the deterministic cuckoo searching method comprises: the first step: sequentially stopping the output voltage at three different voltages And correspondingly measuring three power output values of the solar cell, and storing a voltage value corresponding to the largest of the three power output values among the three different voltage values in a first memory In the unit, storing a voltage value corresponding to a second largest one of the three power output values among the three different voltage values in a second memory unit, and the three not a voltage value corresponding to a minimum of the three power output values is stored in a third memory unit; a second step: storing the value according to the second memory unit and the first memory Performing a first voltage fluctuation amount calculation program by using a difference between the stored values of the cells to generate a first voltage variation amount command, and adjusting the duty cycle according to the first voltage variation amount command to cause the solar cell to output a tentative number a second power voltage, and measuring a power output value of the solar cell when the tentative second high power voltage is output; and storing the value of the second memory unit according to the stored value of the third memory unit Performing a second voltage fluctuation amount calculation program on the stored value of the first memory unit to generate a second voltage variation amount command, and adjusting the duty cycle according to the second voltage fluctuation amount command to make the solar cell output tentatively a minimum power voltage, and measuring a power output value of the solar cell when the tentative minimum power voltage is output, wherein the first voltage variation calculation program and the second voltage variation calculation program both include multiplication by a change a multiplication operation of the scale factor α, 0<α<1, wherein the second voltage variation calculation program includes a changeover mechanism demand determination program, wherein the stored value of the first memory unit is between the second And generating, by the difference between the stored value of the third memory unit and the stored value of the first memory unit, the second voltage change between the stored value of the memory unit and the stored value of the third memory unit a quantity command; and when the stored value of the first memory unit is not between the stored value of the second memory unit and the stored value of the third memory unit, according to the stored value of the second memory unit Generating the second voltage fluctuation amount command with a difference between the stored values of the first memory unit; and third step: for the power output value corresponding to the first memory unit, and the tentative second high power Corresponding power output value and a power output value corresponding to the tentative minimum power voltage are compared to find that a maximum is generated in the stored value of the first memory unit, the tentative second high power voltage, and the tentative minimum power voltage a new maximum power voltage of one of the power output values, a new second high power voltage that produces one of the second highest power output values, and a new minimum power voltage that produces one of the minimum power output values, and the new maximum power Depositing a voltage into the first memory unit, storing the new second high power voltage in the second memory unit, and storing the new minimum power voltage in the third memory unit; Fourth step: return to the second step. The maximum power tracking device of the solar power generation system of claim 1, wherein the second voltage variation calculation program of the second step further comprises a numerical limiting program to limit an upper limit of the tentative minimum power voltage and Lower limit. The maximum power tracking device of the solar power generation system as described in claim 2, It further includes an illumination change determination step to decide whether to return to the first step.