CN114115431B - Photovoltaic power generation maximum power tracking method and system - Google Patents

Photovoltaic power generation maximum power tracking method and system Download PDF

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CN114115431B
CN114115431B CN202111442622.6A CN202111442622A CN114115431B CN 114115431 B CN114115431 B CN 114115431B CN 202111442622 A CN202111442622 A CN 202111442622A CN 114115431 B CN114115431 B CN 114115431B
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CN114115431A (en
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顾月刚
赵晋斌
毛玲
潘超
富勤飞
张鹏宇
王宇斌
孙鹏
孙学兵
沈明珠
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Zhejiang Jarol Scientific Instrument Co ltd
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Abstract

The invention discloses a photovoltaic power generation maximum power tracking method and a system, wherein the method comprises the following steps: acquiring photovoltaic voltage and current, and tracking and calculating photovoltaic power generation power according to the photovoltaic voltage and current; determining the power of each duty ratio, and calculating the global optimal power of all duty ratios of photovoltaic power generation by adopting a butterfly algorithm; establishing a butterfly algorithm search mode switching condition, and taking the absolute value of a power-voltage curve before and after disturbance as a variable step length when the search mode switching condition is met; and the global maximum power point is further found according to the power of the changed duty ratio by judging the change direction of the power and the voltage and changing the duty ratio. The method and the system represent the slope of the curve by calculating the ratio of the power difference value and the voltage difference value before and after the disturbance of the photovoltaic curve, calculate the disturbance step length according to the slope of the curve, change the power duty ratio by judging the change direction of the power difference value and the voltage difference value before and after the disturbance, and accurately search the GMPP.

Description

Photovoltaic power generation maximum power tracking method and system
Technical Field
The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic power generation maximum power tracking method and system.
Background
The photovoltaic array is a nonlinear element, the output power can be influenced by changes such as illumination, temperature and the like to generate fluctuation, and the maximum power is difficult to continuously output when the external environment changes. In order to realize large-scale application of the photovoltaic power generation industry, the first solution is how to improve the photoelectric conversion efficiency. The output voltage of the photovoltaic array is regulated so that the system maintains around the maximum power point for a long time, and further the power output is maintained at the maximum value, i.e. the maximum power point tracking technique (Maximum Power Point Tracking, MPPT) is an effective measure.
Under the conditions of certain illumination intensity and environmental temperature, the photovoltaic cell works at different voltage values and corresponds to different power values, but the photovoltaic cell works at the MPP only when a specific working voltage value is used, the photovoltaic cell can correspond to the maximum output power value. Photovoltaic cells can only exhibit maximum efficiency when operated at MPP.
Disclosure of Invention
One of the purposes of the invention is to provide a photovoltaic power generation maximum power tracking method and a photovoltaic power generation maximum power tracking system, wherein the method and the system are based on a butterfly optimization algorithm and a variable step disturbance observation method (BOA-VST-P & O) combined algorithm, so that the maximum power of a photovoltaic panel under the conditions of unchanged external environment and local shadow and under the conditions of abrupt change of external environment can be still output under the corresponding environment.
The invention further aims to provide a photovoltaic power generation maximum power tracking method and system, wherein the method and system represent a curve slope by calculating the ratio of a power difference value and a voltage difference value before and after disturbance of a photovoltaic curve, calculate a disturbance step length according to the curve slope, and change the power duty ratio by judging the change direction of the power difference value and the voltage difference value before and after disturbance, thereby realizing accurate searching of GMPP (global maximum power point).
The invention further aims to provide a photovoltaic power generation maximum power tracking method and system, wherein the method and system can continuously update the duty ratio under different optimizing modes by setting optimizing switching probability P, and update the butterfly position and random movable type in the search space under the condition of meeting probability.
In order to achieve at least one of the above objects, the present invention further provides a photovoltaic power generation maximum power tracking method, the method comprising:
acquiring photovoltaic voltage and current, and tracking and calculating photovoltaic power generation power according to the photovoltaic voltage and current;
determining the power of each duty ratio, and calculating the global optimal power of all duty ratios of photovoltaic power generation by adopting a butterfly algorithm;
establishing a butterfly algorithm search mode switching condition, and taking the absolute value of a power-voltage curve before and after disturbance as a variable step length when the search mode switching condition is met;
and the global maximum power point is further found according to the power of the changed duty ratio by judging the change direction of the power and the voltage and changing the duty ratio.
According to one preferred embodiment of the present invention, the individual best position D in the search space is stored according to the following formula in tracking state besti (t) and find the current global optimum power P for all duty cycles Gbest (t)：
Figure BDA0003383193050000021
And the current global optimum power P Gbest (t) the butterfly position corresponding to the current optimal duty ratio D Gbest (t)。
According to another preferred embodiment of the present invention, the search mode switching condition includes:
Figure BDA0003383193050000022
if the previous time P is satisfied Gbest Power difference P between (t-1) and current time Gbest (t) and the duty cycle D difference between each butterfly position is less than 5%, then it means that the peak of the global maximum power is searched.
According to another preferred embodiment of the present invention, the variable step acquisition method includes: collecting power P and corresponding voltage U on a photovoltaic power curve, judging a disturbance position on the photovoltaic power curve, calculating a power difference delta P=P (k) -P (k-1) and a voltage difference delta U=U (k) -U (k-1) before and after disturbance on the disturbance position as a slope delta P/delta U of the disturbance position on the photovoltaic power curve, setting a scaling factor a of a variable step length, and setting the variable step length of disturbance as follows: aX|ΔP/ΔU|.
According to another preferred embodiment of the invention, the value of the variable step of the disturbance satisfies:
Figure BDA0003383193050000023
wherein Δd max The maximum slope of the curve is used for further judging the change directions of delta P and delta U, and the duty ratio is changed according to the following formula:
D(t)＝D(t-1)±a×△P/△U；
d (t) is the duty cycle of the current sampling time, D (t-1) is the duty cycle of the last sampling time, and is used for searching the global maximum power point GMPP.
According to another preferred embodiment of the present invention, a optimizing switching probability p is set, and the optimizing switching probability p is used as a global optimizing and local optimizing mode switching condition of the butterfly algorithm under the condition of multiple peaks, and the fitness f (t) =c· (D) under each duty ratio is further calculated Gbest (t)) a The method comprises the steps of carrying out a first treatment on the surface of the And c is a butterfly position corresponding to the change of the sensing coefficient a to the optimal position according to the size between the duty ratio adaptability f (t) and the optimizing change probability p.
According to another preferred embodiment of the present invention, when the value of the duty cycle fitness f (t) is larger than the optimizing switching probability p, the duty cycle is directed to the optimal duty cycle D Gbest (t) change of direction:
D i (t)＝D i (t-1)+(D Gbest (t)-D i (t))·f(t)。
according to another preferred embodiment of the present invention, when the value of the duty cycle fitness f (t) is smaller than the optimizing switching probability p, the duty cycle is directed to the optimal duty cycle D Gbest (t) change of direction:
Figure BDA0003383193050000031
wherein D is j (t) and D k (t) are the duty cycles of the different butterfly positions in the search space, respectively.
In order to achieve at least one of the above objects, the present invention further provides a photovoltaic power generation maximum power tracking system that performs the photovoltaic power generation maximum power tracking method.
The invention further provides a computer readable storage medium storing a computer program executable by a processor for performing the photovoltaic power generation maximum power tracking method.
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Fig. 1 shows a flow chart of a photovoltaic power generation maximum power tracking method.
FIG. 2 shows a flow chart of the BOA-VST-P & O principle in the present invention.
Fig. 3 shows a schematic diagram of MPPT simulation in the case of multimodal in the present invention.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the invention.
It will be understood that the terms "a" and "an" should be interpreted as referring to "at least one" or "one or more," i.e., in one embodiment, the number of elements may be one, while in another embodiment, the number of elements may be plural, and the term "a" should not be interpreted as limiting the number.
Referring to fig. 1-3, the invention discloses a photovoltaic power generation maximum power tracking method and a system, which are based on the combination of a butterfly optimization algorithm and a variable step disturbance observation method (BOA-VST-P & O) to realize accurate searching of global maximum power in photovoltaic power generation.
It should be noted that, the Butterfly Optimization Algorithm (BOA) disclosed by the invention simulates the mating and foraging behaviors of butterflies in the nature, wherein the butterflies are very sensitive to the source of fragrance in the foraging process, can track the source of fragrance and can sense the intensity of fragrance, and the simulation process is called as an optimized search agent executed by the butterfly algorithm. In addition, the butterfly can generate a certain fragrance, the fragrance of the butterfly is related to the adaptability of the butterfly, the fragrance of the butterfly can change when the butterfly moves from one place to another place, and the butterfly can move towards other butterfly when sensing the fragrance of other butterflies, so that the algorithm in the mode is a global searching stage.
Wherein, in the global searching stage, when butterfly takes a step g, the global searching stage can be expressed by the following formula:
Figure BDA0003383193050000041
wherein the method comprises the steps of
Figure BDA0003383193050000042
Representing the solution vector of the ith butterfly individual in t iterations, f i Denotes the fragrance intensity of butterfly individual, r denotes [0,1 ]]Is a random number of the random number group.
When the butterfly individual cannot perceive the fragrance of other butterfly individuals, the butterfly will perform a fast movement, which is called a local search phase of the butterfly optimization algorithm, wherein the local search phase can be expressed by the following formula:
Figure BDA0003383193050000043
wherein the method comprises the steps of
Figure BDA0003383193050000044
Representing the solution vector of the ith butterfly individual in t iterations, f i Denotes the fragrance intensity of butterfly individual, r denotes [0,1 ]]Is a random number, x k Representing different butterflies.
In the invention, the butterfly number of the butterfly optimization algorithm represents the duty ratio number in the MPPT, the butterfly position represents the position of the duty ratio, and the more the butterfly number is, the higher the accuracy of GMPP tracking is, but the convergence speed is reduced because the convergence speed and the MPPT efficiency are more important to the MPPT controller. Therefore, in selecting the number of butterflies, a tradeoff between MPPT efficiency and tracking time is required. The invention thus allows successful tracking of peaks in complex shadow patterns by observing four butterflies fixed at equal distances of 0.2, 0.4, 0.6 and 0.8 from the initial position.
Further, it is necessary to determine the power of each butterfly and store its optimal individual position D in the search space during the MPPT tracking state besti (t)；
Figure BDA0003383193050000051
And find the global optimum power P of each butterfly individual during MPPT tracking state Gbest (t), which is the global optimum among the individual optimum powers of each butterfly, the global optimum P Gbest (t) the butterfly position as the optimal duty cycle D Gbest (t)。
The invention further establishes a switching condition of the search mode, and the method for switching the search mode comprises the following steps: calculate the previous time P Gbest (t-1) sum and current time P Gbest The power difference of (t) and the duty cycle difference between each butterfly position is less than 5%, i.e.:
Figure BDA0003383193050000052
when the global optimal power and the duty ratio of two adjacent sampling moments meet the search mode switching condition, the four butterflies are close to each other, and at the moment, the peak value of the global maximum power can be found.
It is worth mentioning that under the conditions of uniform irradiance and temperature, local shadow and abrupt change of external environment, the existing butterfly algorithm may generate power oscillation and misjudgment at the maximum power peak value, so that the GMPP needs to be accurately searched by combining a variable step disturbance observation method. Due to the characteristics of the photovoltaic characteristic curve, the absolute value of the slope of the curve gradually decreases in the process that the point on the curve is close to the maximum power point, and the slope of the curve is zero when the point reaches the maximum power point. And the period of each sampling is very small, so the invention adopts the absolute value of the slope of the power P-voltage curve as a strategy of variable step length, and the strategy comprises the following steps: and obtaining the power P (k) and the power P (k-1) of the current sampling time k and the last sampling time k-1 according to the power P-voltage curve, obtaining the voltages U (k) and U (k-1) of the current sampling time k and the last sampling time k-1, and taking the ratio of the difference value P=P (k) -P (k-1) of the current sampling power and the last sampling power and the difference value delta U=U (k) -U (k-1) of the current sampling voltage and the last sampling voltage as the curve slope delta P/delta U.
Setting a step size scale factor a, wherein a is a constant, and setting a disturbance step size as a×|Δp/Δu|, wherein the disturbance step size satisfies:
Figure BDA0003383193050000061
wherein the Δd max Is the maximum slope of the curve, and the duty ratio is changed by judging the changing directions of deltaP and deltaU and by the following formula (as shown in figure 2):
D(t)＝D(t-1)±a×△P/△U；
when Δp and Δu are both positive or negative values, the current duty cycle is the difference between the previous duty cycle and the disturbance step, and when Δp and Δu are both positive and negative values, the current duty cycle is the sum of the previous duty cycle and the disturbance step.
D (t) is the duty cycle at the current time, and D (t-1) is the duty cycle at the previous time.
When the above formula of the switching condition of the search mode is not satisfied, it is explained that the peak value of the global maximum power is not found at this time, so that the butterfly optimization algorithm needs to be further started to perform global optimization in this state until the peak value of the global maximum power is found.
The invention further calculates the adaptability of each duty ratio, and sets the optimizing switching probability P as the global optimizing and local optimizing mode switching conditions of the butterfly algorithm under the condition of multiple peaks:
f(t)＝c·(D Gbest (t)) a ；
f (t) is fitness, where c is the perceptual coefficient a is a power exponent.
Wherein when the fitness f is greater than the optimizing switching probability P, the duty ratio is directed toward D according to the following formula Gbest (t) direction movement:
D i (t)＝D i (t-1)+(D Gbest (t)-D i (t))·f(t)；
when the fitness f is greater than the optimizing switching probability P, the duty ratio is toward D according to the following formula Gbest (t) direction movement:
Figure BDA0003383193050000071
wherein D is k And (t) is the duty cycle of another butterfly. The butterfly random motion is guided to the optimal position D Gbest (t) this will result in an improvement of the convergence speed and an improvement of the premature convergence towards the peak point. D (D) j (t) and D k (t) will select between the positions of other butterflies in the search space (j, k+.i).
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such embodiments, the computer program may be downloaded and installed from a network via a communication portion, and/or installed from a removable medium. The above-described functions defined in the method of the present application are performed when the computer program is executed by a Central Processing Unit (CPU). It should be noted that the computer readable medium described in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wire segments, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It will be understood by those skilled in the art that the embodiments of the present invention described above and shown in the drawings are merely illustrative and not restrictive of the current invention, and that this invention has been shown and described with respect to the functional and structural principles thereof, without departing from such principles, and that any modifications or adaptations of the embodiments of the invention may be possible and practical.

Claims (7)

1. A method for tracking maximum power of photovoltaic power generation, the method comprising:
acquiring photovoltaic voltage and current, and tracking and calculating photovoltaic power generation power according to the photovoltaic voltage and current;
determining the power of each duty ratio, and calculating the global optimal power of all duty ratios of photovoltaic power generation by adopting a butterfly algorithm;
establishing a butterfly algorithm search mode switching condition, and taking the absolute value of the slope of a power-voltage curve before and after disturbance as a variable step length when the search mode switching condition is met;
the change direction of the power and the voltage is judged to change the duty ratio, and a global maximum power point is further found according to the changed duty ratio power;
the search mode switching condition includes:
Figure DEST_PATH_IMAGE001
；
if the previous time P is satisfied Gbest Power difference P between (t-1) and current time Gbest (t) and the duty cycle D difference between each butterfly position is less than 5%, then indicating that the peak of the global maximum power is searched;
setting optimizing switching probability p which is used as global optimizing and local optimizing mode switching conditions of butterfly algorithm under the condition of multiple peak values, and further calculating the adaptability of each duty ratio
Figure 859493DEST_PATH_IMAGE002
The method comprises the steps of carrying out a first treatment on the surface of the Wherein c is the perceptual coefficient a is a power exponent and is adapted according to the duty cyclef（t）The butterfly position corresponding to the size switching between the optimizing switching probabilities p is updated to the optimal position;
when the duty cycle is adaptivef（t）The duty cycle is directed towards the optimal duty cycle D if the value of (a) is larger than the optimizing switching probability p Gbest (t) change of direction:
Figure DEST_PATH_IMAGE003
。
2. the method for tracking maximum power of photovoltaic power generation according to claim 1, wherein the individual optimum position D in the search space is stored according to the following formula in the tracking state besti (t) and find the current global optimum power P for all duty cycles Gbest (t)：
Figure 307792DEST_PATH_IMAGE004
；
And compare the saidFront global optimum power P Gbest (t) the butterfly position corresponding to the current optimal duty ratio D Gbest (t)。
3. The method for tracking the maximum power of photovoltaic power generation according to claim 1, wherein the step-variable acquisition method comprises the steps of: collecting power P and corresponding voltage U on a photovoltaic power curve, judging a disturbance position on the photovoltaic power curve, calculating a power difference delta P=P (k) -P (k-1) and a voltage difference delta U=U (k) -U (k-1) before and after disturbance on the disturbance position as a slope delta P/delta U of the disturbance position on the photovoltaic power curve, setting a scaling factor a of a variable step length, and setting the variable step length of disturbance as follows: aX|ΔP/ΔU|.
4. A method of maximum power tracking for photovoltaic power generation according to claim 3, characterized in that the value of the variable step of the disturbance satisfies:
Figure DEST_PATH_IMAGE005
；
wherein delta isd max The maximum slope of the curve is used for further judging the change directions of delta P and delta U, and the duty ratio is changed according to the following formula:
Figure 759633DEST_PATH_IMAGE006
\* MERGEFORMAT ；
d (t) is the duty ratio of the current sampling time, D (t-1) is the duty ratio of the last sampling time, and is used for searching the global maximum power point GMPP;
setting optimizing switching probability p which is used as global optimizing and local optimizing mode switching conditions of butterfly algorithm under the condition of multiple peak values, and further calculating the adaptability of each duty ratio
Figure DEST_PATH_IMAGE007
Mergformat; wherein c is the perceptual coefficient a is a power exponent, and according to theDuty cycle adaptationf（t）And the butterfly position corresponding to the size switching between the optimizing switching probabilities p is enabled to be updated towards the optimal position.
5. The method of claim 1, wherein, when the duty cycle is adaptivef（t）The duty cycle is directed towards the optimal duty cycle D if the value of (a) is smaller than the optimizing switching probability p Gbest (t) change of direction:
Figure 826946DEST_PATH_IMAGE008
\* MERGEFORMAT ;
wherein D is j (t) and D k (t) are the duty cycles of the different butterfly positions in the search space, respectively.
6. A photovoltaic power generation maximum power tracking system, characterized in that the system performs a photovoltaic power generation maximum power tracking method according to any one of claims 1 to 5.
7. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program executable by a processor for performing a photovoltaic power generation maximum power tracking method according to any one of claims 1-5.
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