CN113359877B - Intelligent sunlight tracking control system and method for photovoltaic power station - Google Patents
Intelligent sunlight tracking control system and method for photovoltaic power station Download PDFInfo
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- G—PHYSICS
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- G05D3/12—Control of position or direction using feedback
- G05D3/20—Control of position or direction using feedback using a digital comparing device
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
- H02S20/00—Supporting structures for PV modules
- H02S20/30—Supporting structures being movable or adjustable, e.g. for angle adjustment
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
Abstract
The invention discloses an intelligent sunlight tracking control system and method for a photovoltaic power station, wherein a photovoltaic string with a flat single-axis tracking system is controlled as a whole, the angle of the string is coded, the angle fitness of the string is calculated, the selection probability and the accumulation probability of the angle of the string are determined, and then a new string angle matrix is selected; secondly, carrying out string angle crossing and variation calculation to obtain a new string angle; then calculating the real transmitting power of the new string angle again, and determining the termination condition of the iterative calculation of the system; finally, determining a system optimization model; by the intelligent sunlight tracking control method for the photovoltaic power station, the optimal angle of the cluster, which ensures larger generating capacity under a certain environmental temperature and irradiance, can be determined, and the generation power of the photovoltaic power station can be increased under the current condition.
Description
Technical Field
The invention belongs to the technical field of automatic control, and relates to an intelligent sunlight tracking control system and method for a photovoltaic power station.
Background
In recent years, the photovoltaic power station with the flat single-axis tracking system has higher generating capacity and higher investment yield, and is more and more favored by investors. The control modes of the traditional flat single-axis tracking system are generally divided into two modes. One is real-time adjustment according to the incident angle of the sun. The movement direction of the sun is monitored by an optical detection sensor to control the angle of the bracket, so that the function of tracking the sun is realized. The second is a day-by-day system based on experience. The angle of the bracket is controlled by calculating the running track of the sun. In the control process, when the photovoltaic string is shielded, a reverse tracking mode is generally adopted to solve the problem that: the angle of the bracket is adjusted, so that the bracket behind the former bracket is not shielded. This practice, while reducing the shadowing of the rear cluster, results in the previous rack not operating at the optimum angle of incidence of the sun. The problems that arise from this are: when the shielding occurs, the maximization of the power generation capacity of the photovoltaic system can be ensured only by adjusting the tracking system. The shading of a cluster relates to the position of the best solar angle of incidence of the previous cluster, and the impact on the power generation of the next cluster. However, in general, a large photovoltaic power station has thousands of tracking supports, and the optimal position of each support is very difficult to adjust, so that the problem of blocking of a photovoltaic string with a flat single-axis tracking system is complex.
The patent provides an intelligent sunlight tracking control method for a photovoltaic power station, which controls a photovoltaic string with a flat single-axis tracking system as a whole, adopts an intelligent optimization algorithm, and determines the optimal angle of the string for ensuring the increase of generated energy under a certain environment temperature and irradiance through multiple iterations, so as to increase the power generation power of the photovoltaic power station under the current condition.
Disclosure of Invention
The invention aims to provide an intelligent sunlight tracking control system and method for a photovoltaic power station, which solve the problem that the photovoltaic module string is shielded in the conventional flat single-axis tracking system, so that the generated energy of the photovoltaic system cannot be maximized.
In order to achieve the purpose, the invention adopts the technical scheme that:
the invention provides an intelligent sunlight tracking control method for a photovoltaic power station, which comprises the following steps:
step 1, acquiring S angle matrixes at set time intervals, and respectively calculating the fitness of each angle matrix;
step 2, selecting the angle matrix corresponding to the highest fitness value in the step 1 for copying to obtain a plurality of next generation angle matrices;
step 3, sequentially crossing and mutating each next-generation angle matrix obtained in the step 2 to obtain a plurality of new angle matrices;
step 4, calculating the real transmitting power of each new angle matrix obtained in the step 3 to obtain a plurality of real transmitting powers, and selecting a maximum value from the plurality of real transmitting powers;
step 5, repeating the steps 1 to 4 until the maximum actual power is greater than a preset threshold value, and otherwise, stopping the operation after Z times;
and 6, adjusting the angle of each group of strings of the inverter in the photovoltaic power station according to the new angle matrix corresponding to the maximum actual power obtained in the step 5.
Preferably, in step 1, at time t, the angle of each group string in the inverter is encoded to obtain an angle matrix of all the group strings;
the change rate of the environmental temperature in 10 minutes is not more than +/-2 percent; and selecting an angle matrix every 5 minutes under the condition that the variation rate of irradiance is not more than +/-2% within 10 minutes to obtain an S angle matrix.
Preferably, in step 1, at time t, the angle of each group string in the inverter is encoded to obtain an angle matrix of all the group strings, and the specific method is as follows:
calculating the percentage of the angle of each group string to obtain the percentage angle of each group string;
then converting the percentage angle of each group string into a 7-bit binary angle;
and sequentially arranging the 7-bit binary system angles of all the group strings to obtain the angle matrix of all the group strings.
Preferably, in step 1, the fitness of each angle matrix is calculated respectively, and the specific method is as follows:
respectively calculating the fitness of the S angle matrix through the following formula;
wherein j is the jth angle matrix; j =1,2.
Preferably, in step 2, the angle matrix corresponding to the highest fitness value in step 1 is selected to be copied to obtain a plurality of next-generation angle matrices, and the specific method is as follows:
firstly, respectively calculating the selection probability of each angle matrix;
secondly, calculating the cumulative probability of the jth angle matrix;
then, setting any one random two-bit decimal u which is uniformly distributed in the interval of [0,1 ];
if the jth angle matrix Y j Satisfies the accumulation probability of Q (Y) j-1 )<u≤Q(Y j+1 ) Then, the j-th angle matrix Y is selected j Carrying out copying;
finally, repeating the step S to obtain a plurality of next generation angle matrixes;
wherein, Q (Y) j-1 ) Is the j-1 th angle matrix Y j The cumulative probability of (d); q (Y) is not more than j+1 ) Is the j +1 th angle matrix Y j The cumulative probability of (c).
Preferably, in step 3, each next-generation angle matrix obtained in step 2 is sequentially crossed and mutated to obtain a plurality of new angle matrices, and the specific method is as follows:
firstly, randomly pairing angle matrixes of the next generation; obtaining a matched angle matrix group;
secondly, mutually exchanging two next generation angle matrixes in the obtained angle matrix group in a cross probability exchange mode to obtain an exchange angle matrix;
and finally, carrying out mutation processing on a certain bit value of the obtained exchange angle matrix according to the mutation probability to obtain a new angle matrix.
Preferably, in step 4, the real power of each new angle matrix obtained in step 3 is calculated to obtain a plurality of real powers, and the specific method is as follows:
and respectively converting the obtained new angle matrixes into a 10-system, and then bringing the 10-system into a photovoltaic power station to obtain actual power corresponding to each new angle matrix.
Preferably, in step 6, the angle of each string of the inverter in the photovoltaic power station is adjusted according to the new angle matrix corresponding to the maximum actual power obtained in step 5, and the specific method is as follows:
and performing 10-system conversion on the new angle matrix corresponding to the maximum actual transmitting power, and then adjusting each group of string angles corresponding to the converted values.
An intelligent solar tracking control system for a photovoltaic power plant, comprising a controller, and a memory storing a computer program operable on a processor, the processor implementing the method when executing the computer program.
Preferably, the controller is connected with a motion control board card for transmitting the obtained control signal to the flat single-axis tracking support through the control board card.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an intelligent sunlight tracking control method for a photovoltaic power station, which comprises the steps of firstly coding a string angle, then calculating the adaptability of the string angle, determining the selection probability and the accumulation probability of the string angle, and then selecting a new string angle matrix; secondly, carrying out string angle crossing and variation calculation to obtain a new string angle again; then calculating the actual power of the new string angle, determining the termination condition of the iterative computation of the system, and finally determining an optimization model of the system; the invention simulates the principle of survival of candidates with high or low success rates in the biological world, adopts the concept of natural evolution, reserves individuals with high fitness (group string angle with high electric power under the same condition) in a selected group string with a certain probability, and inherits genes of the group string with high fitness to the next generation; meanwhile, by referring to the probability of occurrence of random variation in nature, on the basis of reserving cluster genes with high fitness to a large extent, the diversity of cluster angles is increased by variation, so that the probability of finding a better cluster angle is improved; through repeated iterative computation, when the termination condition of the iterative computation is met or the optimization target is reached, the angle corresponding to the string is used as the approximate optimal angle of the string which guarantees larger generating capacity under the current certain environmental temperature and irradiance, and the aim of increasing the generating power of the photovoltaic power station under the current condition is achieved.
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Fig. 1 is a flow chart relating to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention provides an intelligent sunlight tracking control method for a photovoltaic power station, which takes a centralized photovoltaic power generation system with a flat single-axis tracking support as a research object, takes a centralized inverter (corresponding to a square matrix) in the power station as an example, the inverter comprises N group strings, and each group string corresponds to an MPPT module.
Each group string corresponds to one flat single-axis tracking support, and real-time adjustment along with the incident angle of the sun can be realized; the adjustment angle of the flat single-axis tracking support is-40 degrees to +60 degrees.
According to the intelligent sunlight tracking control method for the photovoltaic power station, the generated power of the photovoltaic power station is improved by adjusting the angles of the N groups of the serial-parallel single-axis tracking supports.
Grouping actual transmitting power P (unit is KW); the cluster angle is R (in degrees); ambient temperature is Te (in ℃); irradiance is F (unit is W/m) 2 )；
As shown in fig. 1, an intelligent sunlight tracking control method for a photovoltaic power station includes the following steps:
firstly, coding the angle of each group string to obtain an angle matrix Y of all the group strings;
firstly, respectively calculating the percentage of the angle R of each group string at the time t to obtain the percentage angle R of each group string a (ii) a The percentile angle of each group string is then converted to a 7-bit binary angle
Wherein, minR i Is the minimum value of the string angle R; maxR i Is the maximum value of the cluster angle R; r i Is the angle of the ith cluster; r ai Is the angle of the ith cluster in percent.
Next, let Y be the 7-bit binary angle of all strings at time t
Sequentially arranging the matrixes, and obtaining an angle matrix Y of all the groups of strings through the following formula;
secondly, selecting and copying an angle matrix;
the environmental temperature and irradiance stability judgment basis is as follows: the change rate of the environmental temperature Te in 10 minutes is not more than +/-2 percent; the variation rate of irradiance F in 10 minutes is not more than +/-2 percent;
selecting S angle matrixes Y with the time interval of 5 minutes, wherein each angle matrix Y corresponds to one actual transmitting power P Y And N string angles R.
And evaluating the quality of each angle matrix Y by using a fitness function, wherein the higher the calculated value of the fitness function is, the better the fitness of the representative angle matrix Y is.
The fitness of the S angle matrix Y is calculated by the following formula:
wherein j is the jth angle matrix; j =1,2.
The selection is an operation of a natural selection rule for simulating the victory or victory in the biological world, and an angle matrix Y with high fitness in the S angle matrices Y is selected for copying to generate the next generation of angle matrices
The method comprises the following specific steps:
first, the selection probability G (Y) of each angle matrix Y is calculated according to the following formula:
next, the jth angle matrix Y is calculated j The cumulative probability of (2):
Q(Y j )＝G(Y 1 )+G(Y 2 )+…+G(Y j )
finally, selecting and copying an angle matrix Y, specifically:
setting a random two-bit decimal u which is uniformly distributed in a [0,1] interval;
if the jth angle matrix Y j Satisfies the accumulation probability of Q (Y) j-1 )<u≤Q(Y j+1 ) Then, the j-th angle matrix Y is selected j Carrying out copying; repeating the steps S times to obtain a plurality of next generation angle matrixes
Thirdly, obtaining a plurality of next generation angle matrixes
Respectively and sequentially carrying out cross and variation processing to obtain a plurality of new angle matrixes
Specifically, the method comprises the following steps:
first, for the next generation of angle matrix
Pairing randomly; obtaining a matched angle matrix group;
secondly, two next generation angle matrixes in the obtained angle matrix group are obtained
With a cross probability P x The exchange modes are exchanged mutually to obtain an exchange angle matrix
Wherein, exchangeThe alternative means to combine two next generation angle matrices
The last four bit codes of (a) are interchanged.
The crossover probability P is calculated by x ：
Wherein, the first and the second end of the pipe are connected with each other,
to select a probability
A maximum value;
to select a probability
An average value; beta is a 1 、β 2 Is constant, and β 1 <β 2 。
Finally, the obtained exchange angle matrix is subjected to
Performing variation processing to obtain a new angle matrix
Specifically, the method comprises the following steps:
first, for each switching angle matrix
According to the mutation probability P b A change is made wherein: at each switching angle matrix
Random selection of a Gene mutationSetting as a variation point; then according to the mutation probability P b The original value of the variation point is inverted to obtain the angle matrix after variation
The inverse calculation method comprises the following steps: the original value is 0, and the value is 1 after negation; the original value is 1, and the value is 0 after inversion.
The mutation probability P is calculated by the following formula b ：
Wherein the content of the first and second substances,
is a matrix of angles
The selection probability of (2);
to select a probability
Average value; beta is a 3 、β 4 Is constant, and β 3 <β 4 。
Fourthly, calculating a new angle matrix
The actual power of (c);
a plurality of new angle matrixes obtained
Respectively converted into 10 systems, and then brought into a photovoltaic power station to obtain each new angle matrix
Corresponding actual transmitting power P'; from the obtained plurality of real hairsSelecting a maximum value maxP 'from the power P';
fifthly, iterating the process;
repeating the second step to the fourth step until the calculation process is terminated when maxP' is not less than KmaxP; otherwise, after Z times of operation, the operation is terminated.
1.05≤K≤1.1
Wherein Z is a constant less than 20.
Sixthly, determining an optimization model;
new angle matrix corresponding to maxP
Performing 10-system conversion on the matrix, and taking the converted value as the optimal solution of the system under the current ambient temperature T and the irradiance F; then the photovoltaic power station is according to the new angle matrix
The converted value is adjusted for each string angle R, and a large power generation power can be obtained.
And (4) building an algorithm programming environment by using a computer, selecting appropriate system parameters and control parameters according to the photovoltaic power station in practical application, and obtaining the angle of each corresponding group string according to the fifth step, so that the real-time control on the photovoltaic power station is realized, and further, larger generating power is obtained.
Example (b):
the installation capacity of a certain photovoltaic power station component in China is 21.632MWp, and the inverter capacity is 20MWp. The photovoltaic power station is connected to the grid at 2016, 6 and 24 days, the peak power of a photovoltaic module is 260Wp, 83200 photovoltaic panels are adopted, and the floor area is about 53.659 ten thousand square meters. Each group of supports of the photovoltaic power station adopts a longitudinal 2 arrangement scheme and comprises 20/22 photovoltaic modules; the electrical design is that every 20/22 blocks of the polysilicon photovoltaic modules with the peak power of 280Wp are in a string, a 1MWp photovoltaic array is configured under each inverter, and 20 inverters are arranged in the whole field. The photovoltaic module adopts a fixed adjustable support mode, each group string corresponds to one flat single-axis tracking support, and real-time adjustment along with the incident angle of the sun can be realized; the adjustment angle of the flat single-axis tracking support is-40 degrees to +60 degrees.
At ambient temperature T =25 ℃, irradiance F =950W/m 2 .5 groups of strings of the photovoltaic power station are selected for research and test in the experiment. The S value is 6, and 6 groups of data are selected every five minutes and marked as Y t1 、Y t2 、Y t3 、Y t4 、Y t5 、Y t6 。
Original data table:
PY t1 ＝4.5KW、PY t2 ＝5.0KW、PY t3 ＝4.7KW、PY t4 ＝5.9KW、PY t5 ＝4.0KW、PY t6 ＝5.5KW；
firstly, encoding the angle of each group string to obtain the angle matrix of all the group strings.
After binary conversion of the original data table, the numerical values are as follows
| Y t1 | Y t2 | Y t3 | Y t4 | Y t5 | Y t6 | |
| First string | 0001010 | 0101000 | 0111100 | 0110010 | 1011010 | 0011110 |
| The second string | 0010100 | 0011110 | 0001010 | 0110010 | 0010100 | 0111100 |
| Third string | 0011110 | 0010100 | 1010000 | 0110010 | 0101000 | 0010100 |
| The fourth string | 0101000 | 001010 | 0011110 | 0110010 | 0011110 | 0101000 |
| The fifth string | 0110010 | 0010001 | 1010000 | 0110010 | 0011110 | 1000110 |
Second, selection and replication of the angle matrix:
will Y t1 、Y t2 、Y t3 、Y t4 、Y t5 、Y t6 The corresponding real power P is substituted into the fitness function of Y:
calculating to obtain: f (Y) t1 )＝0.3；f(Y t2 )＝0.6；f(Y t3 )＝0.5；f(Y t4 )＝0.8；f(Y t5 )＝0.1；f(Y t6 )＝0.7；
According to the selection probability formula:
the selection probability G (Y) of the angle matrix Y is calculated as:
G(Y t1 )＝0.10；G(Y t2 )＝0.20；G(Y t3 )＝0.17；G(Y t4 )＝0.26；G(Y t5 )＝0.03；G(Y t6 )＝0.23；
cumulative probability of angle matrix Y: 0<Q(Y t1 )≤0.1；0.1<Q(Y t2 )≤0.3；0.3<Q(Y t3 )≤0.47；0.47<Q(Y t4 )≤0.73；0.73<Q(Y t5 )≤0.76；0.76<Q(Y t6 )≤0.99；
Selection and replication of the angle matrix:
setting to generate a uniformly distributed random two-bit fraction u within the [0,1] interval:
u 1 =0.51, take Y t4 ；
u 1 =0.80, take Y t6 ；
u 1 =0.33, take Y t3 ；
u 1 =0.15, take Y t2 ；
u 1 =0.61, take Y t4 ；
u 1 =0.94, take Y t6 ；
Obtaining a new group of angle components: y is t4 、Y t6 、Y t3 、Y t2 、Y t4 、Y t6 。
| Y t4 | Y t6 | Y t3 | Y t2 | Y t4 | Y t6 | |
| First string | 0110010 | 0011110 | 0111100 | 0101000 | 0110010 | 0011110 |
| Second string | 0110010 | 0111100 | 0001010 | 0011110 | 0110010 | 0111100 |
| Third string | 0110010 | 0010100 | 1010000 | 0010100 | 0110010 | 0010100 |
| The fourth string | 0110010 | 0101000 | 0011110 | 0001010 | 0110010 | 0101000 |
| The fifth string | 0110010 | 1000110 | 1010000 | 0010001 | 0110010 | 1000110 |
Third, the angle of the cluster is crossed and varied
Form Y for new group string angle t4 、Y t6 、Y t3 、Y t2 、Y t4 、Y t6 And (3) pairing: y is t4 And Y t6 Is a pair; y is t3 And Y t2 Is a pair; y is t4 And Y t6 Is a pair; then with a cross probability P x And exchanging 1,2, 3 and 5 strings of codes among the angle components of the new string group with each other. The exchange mode is as follows: the two individual last four bit codes are interchanged.
After crossing, a new cluster angle is obtained: y is tj4 、Y tj6 、Y tj3 、Y tj2 、Y tj4 、Y tj6 。
For Y tj4 、Y tj6 、Y tj3 、Y tj2 、Y tj4 、Y tj6 Is changed according to the mutation probability Pb. Firstly, randomly selecting a new cluster angle Y after variation tj4 、Y tj6 、Y tj3 、Y tj2 、Y tj4 、Y tj6 And (3) negating the original value of the variation point according to the variation probability Pb (negation calculation method: the original value is 0, and is 1 after negation, and the original value is 1 and is 0 after negation).
After mutation, a new cluster angle is obtained: y is tjb4 、Y tjb6 、Y tjb3 、Y tjb2 、Y tjb4 、Y tjb6 。
| Y tjb4 | Y tjb6 | Y tjb3 | Y tjb2 | Y tjb4 | Y tjb6 | |
| First string | 0111100 | 0011110 | 0011110 | 0101000 | 0111100 | 0011110 |
| The second string | 0110010 | 0110010 | 0001010 | 0111100 | 0110110 | 0110010 |
| The third string | 0111010 | 0110010 | 1010100 | 1010000 | 0110010 | 0110010 |
| The fourth string | 0110010 | 0101100 | 0011110 | 0001110 | 0110010 | 0101100 |
| The fifth string | 0010100 | 1000110 | 0010100 | 0010001 | 0010100 | 1000110 |
Fourthly, calculating an angle matrix
Actual power of
Will Y tjb4 、Y tjb6 、Y tjb3 、Y tjb2 、Y tjb4 、Y tjb6 Respectively converting into 10-system:
| Y tjb4 | Y tjb6 | Y tjb3 | Y tjb2 | Y tjb4 | Y tjb6 | |
| first string | 60 | 30 | 30 | 40 | 60 | 30 |
| The second string | 50 | 50 | 10 | 60 | 54 | 50 |
| The third string | 58 | 50 | 84 | 80 | 50 | 50 |
| The fourth string | 50 | 44 | 30 | 14 | 50 | 44 |
| The fifth string | 20 | 70 | 20 | 17 | 20 | 70 |
The measured actual power P' is taken into the photovoltaic power generation system after the angle is achieved. P' Y tjb2 ＝5.3KW、P`Y tjb3 ＝5.0KW、P`Y tjb4 ＝6.0KW、P`Y tjb6 ＝5.8KW；
Fifth, process iteration
And continuing the previous steps of 1,2, 3 and 4, and stopping the calculation process when the maxP' is more than or equal to 1.05 maxP. And finally calculating maxP' =6.25KW.
Matrix corresponding to maxP': a first string: 60, adding a solvent to the mixture; a second string: 50; and a third string: 55; and a fourth string: 52; and a fifth string: 57; as the optimal solution of the system at the current ambient temperature T and irradiance F.
In the intelligent sunlight tracking control of the photovoltaic power station, an algorithm programming environment is built by using a computer, an appropriate angle matrix is selected according to an intelligent sunlight tracking system of the photovoltaic power station in practical application, a corresponding string angle is obtained according to a determined optimization model, the string angle is sent to the flat single-shaft tracking support by using the motion control board card, the real-time control of the flat single-shaft tracking support is realized, and the intelligent sunlight tracking control of the photovoltaic power station is further realized.
In yet another embodiment of the present invention, a terminal device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor being configured to execute the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and is specifically adapted to load and execute one or more instructions to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for executing the intelligent sunlight tracking control method for the photovoltaic power station.
In still another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a terminal device and is used for storing programs and data. It is understood that the computer readable storage medium herein may include a built-in storage medium in the terminal device, and may also include an extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor can load and execute one or more instructions stored in the computer readable storage medium to realize the corresponding steps of the checking method related to the long-term maintenance plan in the power grid in the embodiment; one or more instructions in the computer readable storage medium are loaded by the processor and execute the above-mentioned intelligent sunlight tracking control method for the photovoltaic power station.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Claims (9)
1. An intelligent sunlight tracking control method for a photovoltaic power station is characterized by comprising the following steps:
step 1, acquiring S angle matrixes at set time intervals, and respectively calculating the fitness of each angle matrix;
step 2, selecting the angle matrix corresponding to the highest fitness value in the step 1 for copying to obtain a plurality of next generation angle matrices;
step 3, sequentially crossing and mutating each next-generation angle matrix obtained in the step 2 to obtain a plurality of new angle matrices;
step 4, calculating the real transmitting power of each new angle matrix obtained in the step 3 to obtain a plurality of real transmitting powers, and selecting a maximum value from the plurality of real transmitting powers;
step 5, repeating the steps 1 to 4 until the maximum actual power is larger than a preset threshold value, and otherwise, stopping the operation after Z times;
step 6, adjusting the angle of each group of strings of the inverter in the photovoltaic power station according to the new angle matrix corresponding to the maximum actual power obtained in the step 5;
in step 2, selecting the angle matrix corresponding to the highest fitness value in step 1 to copy to obtain a plurality of next generation angle matrices, wherein the specific method comprises the following steps:
firstly, respectively calculating the selection probability of each angle matrix;
secondly, calculate the
The cumulative probability of the angle matrix;
then, setting any one random two-bit decimal u which is uniformly distributed in the interval of [0,1 ];
if it is first
An angle matrix
Is satisfied with
<u
When it is, then choose to
An angle matrix
Carrying out copying;
finally, repeating the step S times to obtain a plurality of next generation angle matrixes;
wherein, the first and the second end of the pipe are connected with each other,
is a first
An angle matrix
The cumulative probability of (2);
is as follows
An angle matrix
The cumulative probability of (c).
2. The intelligent sunlight tracking control method for the photovoltaic power station as recited in claim 1, wherein in step 1, the S angle matrix is obtained at a set time interval, and the specific method is as follows:
in that
Coding the angle of each group string in the inverter at the moment to obtain an angle matrix of all the group strings;
the change rate of the ambient temperature in 10 minutes is not more than
2 percent; the change rate of irradiance in 10 minutes does not exceed
And under the condition of 2%, selecting an angle matrix at a set time interval to further obtain an S angle matrix.
3. The intelligent sunlight tracking control method for the photovoltaic power station as claimed in claim 2, wherein in step 1, in
At a time, encoding the angle of each group string in the inverter to obtain an angle matrix of all the group strings, wherein the specific method comprises the following steps:
calculating the percentage of the angle of each group string to obtain the percentage angle of each group string;
then converting the percentage angle of each group string into a 7-bit binary angle;
and sequentially arranging the 7-bit binary system angles of all the group strings to obtain the angle matrix of all the group strings.
4. The intelligent sunlight tracking control method for the photovoltaic power station as recited in claim 1, wherein in step 1, the fitness of each angle matrix is calculated respectively, and the specific method is as follows:
respectively calculating the fitness of the S angle matrix through the following formula;
wherein the content of the first and second substances,
is as follows
An angle matrix;
；
。
5. the intelligent sunlight tracking control method for the photovoltaic power station as recited in claim 1, wherein in step 3, each next-generation angle matrix obtained in step 2 is sequentially crossed and mutated to obtain a plurality of new angle matrices, and the specific method is as follows:
firstly, randomly pairing angle matrixes of the next generation; obtaining a matched angle matrix group;
secondly, mutually exchanging two next generation angle matrixes in the obtained angle matrix group in a cross probability exchange mode to obtain an exchange angle matrix;
and finally, carrying out mutation processing on a certain bit value of the obtained exchange angle matrix according to the mutation probability to obtain a new angle matrix.
6. The intelligent sunlight tracking control method for the photovoltaic power station as recited in claim 1, wherein in step 4, the actual power of each new angle matrix obtained in step 3 is calculated to obtain a plurality of actual powers, and the specific method is as follows:
and respectively converting the obtained new angle matrixes into a 10-system, and then bringing the 10-system into a photovoltaic power station to obtain actual power corresponding to each new angle matrix.
7. The intelligent sunlight tracking control method for the photovoltaic power station as claimed in claim 1, wherein in step 6, the angle of each string of inverters in the photovoltaic power station is adjusted according to the new angle matrix corresponding to the maximum actual power obtained in step 5, and the specific method is as follows:
and performing 10-system conversion on the new angle matrix corresponding to the maximum real power, and then adjusting each group of string angles corresponding to the converted value.
8. A photovoltaic power plant intelligent sunlight tracking control system comprising a controller and a memory storing a computer program operable on said controller, said controller when executing said computer program implementing the method of any one of claims 1 to 7.
9. The intelligent sunlight tracking control system of the photovoltaic power plant of claim 8 wherein the controller is connected to a motion control board card for transmitting the obtained control signal to the flat single axis tracking support via the control board card.
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