Marine photovoltaic MPPT (Maximum Power Point Tracking) control method and system based on improved variable step size incremental conductance method

Abstract

The invention belongs to the technical field of marine photovoltaic power generation, and particularly relates to a marine photovoltaic MPPT control method and system based on an improved variable-step-size incremental conductance method.The method comprises the steps that firstly, the duty ratio of a DC-DC converter in a photovoltaic system is optimized through a raccoon longnoraccoon optimization algorithm, and a global optimal individual with the output power meeting the switching condition is obtained; and then taking the duty ratio and the output power corresponding to the globally optimal individual as initial conditions of a variable step size incremental conductance method, setting an initial change step size, continuously searching the duty ratio by gradually reducing the variable quantity of the step size, and carrying out photovoltaic MPPT control by utilizing the obtained final duty ratio and the output power. The raccoon optimization algorithm and the variable step size incremental conductance method are combined to form the hybrid algorithm, so that the time for searching the global optimal point by the algorithm can be shortened, and the power fluctuation in the algorithm convergence process can be effectively reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of marine photovoltaic power generation, and in particular relates to a marine photovoltaic MPPT control method and system based on an improved variable step-size conductance increment method. Background Art

[0002] In recent years, with the growing demand for energy and the increasingly tight supply of traditional fuels, the research and development of renewable energy has become a hot topic. Among them, solar energy is favored for its unique advantages such as abundant resources, no geographical boundaries, and cleanliness. However, the cost of solar power generation is relatively high, so it is particularly necessary to focus on improving the conversion efficiency of photovoltaic systems and reducing the cost of photovoltaic power generation.

[0003] In order to improve marine photovoltaic technology, reduce fuel consumption, reduce exhaust emissions, and promote green ships, it is necessary to make photovoltaic cells work at the maximum power point as much as possible to achieve maximum power point tracking, which is a method of converting light energy into electrical energy to the maximum extent, namely maximum power point tracking technology (MPPT). The mature methods of maximum power tracking technology include constant voltage method, perturbation observation method and variable step conductivity increment method. The traditional variable step conductivity increment method has a slow response speed in the startup phase and large power fluctuations during the tracking convergence process. Summary of the invention

[0004] The purpose of the present invention is to provide a marine photovoltaic MPPT control method and system based on an improved variable step conductance increment method with fast response speed and small power fluctuation in view of the above problems existing in the prior art.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] In a first aspect, the present invention proposes a marine photovoltaic MPPT control method based on an improved variable step conductance increment method, the control method comprising:

[0007] S1. Use the coati optimization algorithm to optimize the duty cycle of the DC-DC converter in the photovoltaic system; determine whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition. If so, enter S2, otherwise continue to iterate;

[0008] S2, taking the duty cycle and output power corresponding to the global optimal individual obtained in S1 as the initial conditions of the variable step conductivity increment method, setting the initial change step size and continuing to search for the duty cycle by gradually reducing the step size change;

[0009] S3, using the final duty cycle and output power output by S2 to perform photovoltaic MPPT control.

[0010] The S1 includes:

[0011] S11, initializing the number of coatis population and individual positions of coatis, wherein the individual positions of coatis correspond to the duty cycle of the DC-DC converter in the photovoltaic system;

[0012] S12, calculating the fitness value of the coati individual, obtaining the global optimal individual, and updating the position of the coati individual in the coati population; the fitness value of the coati individual corresponds to the output power obtained by multiplying the load current of the photovoltaic system and the voltage at both ends; the global optimal individual refers to the coati individual with the highest fitness value; the updating of the position of the coati individual in the coati population refers to: changing the fitness value of the coati individual i in the current iteration to The fitness value corresponding to the updated position according to the position update strategy For comparison, if Then the position of coati individual i is changed from Updated to Otherwise, the position of coati individual i remains unchanged;

[0013] S13, judging whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition, if so, entering S2, otherwise returning to S12 to continue iteration.

[0014] The position update strategy of the coati individual is as follows: the position is updated in the hunting and attacking stage and the predator escape stage in sequence; in the hunting and attacking stage, the coati individuals in the coati population are sorted in descending order according to the fitness value, and the coati individuals in the front of the coati population are updated in descending order. The position update formula for each coati individual is:

[0015]

[0016] In the above formula, denote the position of coati individual i in the t+1th and tth iterations respectively; α is the step length control factor; is a point-to-point multiplication operation; Iguana t is the global optimal individual obtained in the tth iteration; I represents a random number in the set {1, 2}; Levy(λ) is the Levy flight function; N is the number of coatis individuals;

[0017] For coatis populations The position update formula for each coati individual is:

[0018]

[0019] In the above formula, r is a random number in the interval (0, 1); is a random number in the interval [0.2, 0.9]; for The corresponding fitness value; is the fitness value corresponding to the position of coati individual i in the current iteration.

[0020] The switching conditions are:

[0021]

[0022] In the above formula, P1 is the output power corresponding to the global optimal individual in the current iteration, and P2 is the output power corresponding to the global optimal individual in the previous iteration.

[0023] In S2, the expression for searching the duty cycle using the variable step size conductance increment method is:

[0024]

[0025] p=e -k·(iter-1)

[0026] In the above formula, D old , D new are the duty cycles before and after the search respectively; I and U are the current and voltage corresponding to the duty cycle after the search respectively; dI is the difference between the current corresponding to the duty cycle after the search and the current corresponding to the duty cycle before the search; dU is the difference between the voltage corresponding to the duty cycle after the search and the voltage corresponding to the duty cycle before the search; p is the contraction factor; is the initial duty cycle change; e is the natural logarithm; k is the constant that controls the rate at which the search factor decreases; iter is the current iteration number of the variable step conductivity increment method.

[0027] In a second aspect, the present invention proposes a marine photovoltaic MPPT control system based on an improved variable step conductance increment method, wherein the control method comprises a first optimization module, a second optimization module, and an MPPT control module;

[0028] The first optimization module is used to optimize the duty cycle of the DC-DC converter in the photovoltaic system using the coati optimization algorithm, and output the duty cycle and output power corresponding to the global optimal individual in the current iteration when the output power corresponding to the global optimal individual in the current iteration meets the switching condition;

[0029] The second optimization module is used to use the duty cycle and output power corresponding to the global optimal individual obtained by the first optimization module as the initial conditions of the variable step conductance increment method, set the initial change step size, and continue to search for the duty cycle by gradually reducing the step size change, and output the final duty cycle and output power;

[0030] The MPPT control module is used to perform photovoltaic MPPT control according to the final duty cycle and output power output by the second optimization module.

[0031] The first optimization module optimizes the duty cycle of the DC-DC converter in the photovoltaic system according to the following steps:

[0032] S11, initializing the number of coatis population and individual positions of coatis, wherein the individual positions of coatis correspond to the duty cycle of the DC-DC converter in the photovoltaic system;

[0033] S12, calculating the fitness value of the coati individual, obtaining the global optimal individual, and updating the position of the coati individual in the coati population; the fitness value of the coati individual corresponds to the output power obtained by multiplying the load current of the photovoltaic system and the voltage at both ends; the global optimal individual refers to the coati individual with the highest fitness value; the updating of the position of the coati individual in the coati population refers to: changing the fitness value of the coati individual i in the current iteration to The fitness value corresponding to the updated position according to the position update strategy For comparison, if Then the position of coati individual i is changed from Updated to Otherwise, the position of coati individual i remains unchanged;

[0034] S13, judging whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition, if so, entering S2, otherwise returning to S12 to continue iteration.

[0035] The position update strategy of the coati individual is as follows: the position is updated in the hunting and attacking stage and the predator escape stage in sequence; in the hunting and attacking stage, the coati individuals in the coati population are sorted in descending order according to the fitness value, and the coati individuals in the front of the coati population are updated in descending order. The position update formula for each coati individual is:

[0036]

[0037] In the above formula, denote the position of coati individual i in the t+1th and tth iterations respectively; α is the step length control factor; is a point-to-point multiplication operation; Iguana t is the global optimal individual obtained in the tth iteration; I represents a random number in the set {1, 2}; Levy(λ) is the Levy flight function; N is the number of coatis individuals;

[0038] For coatis populations The position update formula for each coati individual is:

[0039]

[0040] In the above formula, r is a random number in the interval (0, 1); is a random number in the interval [0.2, 0.9]; for The corresponding fitness value; is the fitness value corresponding to the position of coati individual i in the current iteration.

[0041] The switching conditions are:

[0042]

[0043] In the above formula, P1 is the output power corresponding to the global optimal individual in the current iteration, and P2 is the output power corresponding to the global optimal individual in the previous iteration.

[0044] The expression for searching the duty cycle using the variable step size conductance increment method is:

[0045]

[0046] p=ek·(iter-1)

[0047] In the above formula, D old , D new are the duty cycles before and after the search respectively; I and U are the current and voltage corresponding to the duty cycle after the search respectively; dI is the difference between the current corresponding to the duty cycle after the search and the current corresponding to the duty cycle before the search; dU is the difference between the voltage corresponding to the duty cycle after the search and the voltage corresponding to the duty cycle before the search; p is the contraction factor; is the initial duty cycle change; e is the natural logarithm; k is the constant that controls the rate at which the search factor decreases; iter is the current iteration number of the variable step conductivity increment method.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The invention discloses a marine photovoltaic MPPT control method based on an improved variable step conductance increment method. The method firstly optimizes the duty cycle of a DC-DC converter in a photovoltaic system by using a coati optimization algorithm to obtain a global optimal individual whose output power satisfies a switching condition. The duty cycle and output power corresponding to the global optimal individual are used as initial conditions of the variable step conductance increment method. The initial change step is set and the duty cycle is continuously searched by gradually reducing the step change. The photovoltaic MPPT control is performed by using the obtained final duty cycle and output power. The method combines the coati optimization algorithm with the variable step conductance increment method to form a hybrid algorithm, which can not only shorten the time for the algorithm to search for the global optimal point, but also effectively reduce the power fluctuation during the convergence process of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of the control method described in Example 1 of the present invention.

[0051] Figure 2 PU characteristic curve diagram of the photovoltaic system under different illumination modes set in Example 1.

[0052] Figure 3 This is a graph of the photovoltaic array output power obtained by applying the control method described in Example 1 under illumination mode P1.

[0053] Figure 4 This is a graph of the photovoltaic array output power obtained by applying the control method described in Example 1 when the illumination mode changes from P2 to P3.

[0054] Figure 5 This is a structural block diagram of the control system described in Example 2 of the present invention. DETAILED DESCRIPTION

[0055] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0056] Embodiment 1:

[0057] See also Figure 1 , a marine photovoltaic MPPT control method based on an improved variable step size conductance increment method is carried out in the following steps:

[0058] S1. Use the coati optimization algorithm to optimize the duty cycle of the DC-DC converter in the photovoltaic system:

[0059] S11, initializing the number of coatis population and the individual positions of coatis, wherein the individual positions of coatis correspond to the duty cycle of the DC-DC converter in the photovoltaic system, and the coatis positions are set to random values ​​in the interval [0.2, 0.9];

[0060] S12, calculating the fitness value of the individual raccoon, the fitness value of the individual raccoon corresponds to the output power obtained by multiplying the load current and the voltage at both ends after the output voltage and current of the photovoltaic system are stable; then obtaining the global optimal individual, the global optimal individual refers to the raccoon individual with the highest fitness value; and then updating the position of the raccoon individual in the raccoon population; the updating of the position of the raccoon individual in the raccoon population refers to: changing the fitness value of the raccoon individual i in the current iteration to The fitness value corresponding to the updated position according to the position update strategy For comparison, if Then the position of coati individual i is changed from Updated to Otherwise, the position of the coati individual i remains unchanged; the position update strategy of the coati individual is: the position is updated in the hunting and attacking stage and the predator escape stage in sequence; in order to better explore the search space and speed up the search speed, this embodiment uses the Levy flight function to improve the position update formula of the hunting and attacking stages, and obtains the improved coati optimization algorithm (ICOA algorithm):

[0061] Sort the coatis individuals in the coatis population in descending order according to their fitness values. The position update formula for each coati individual is:

[0062]

[0063] In the above formula, denote the position of coati individual i in the t+1th and tth iterations respectively; α is the step length control factor; is a point-to-point multiplication operation; Iguana t is the global optimal individual obtained in the tth iteration; I represents a random number in the set {1, 2}; N is the number of individuals in the coati population, and N is an even number; Levy(λ) is the Levy flight function;

[0064] Levy(λ) can be expressed as Where β is the exponential coefficient of the Levy flight function, u and v obey the normal distribution, and the calculation formula is:

[0065]

[0066] In the above formula, Γ is the standard gamma function; represents the variance of u and v;

[0067] For coatis populations The position update formula for each coati individual is:

[0068]

[0069] In the above formula, r is a random number in the interval (0, 1); is a random number in the interval [0.2, 0.9]; for The corresponding fitness value; is the fitness value corresponding to the position of coati individual i in the current iteration;

[0070] S13, judging whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition. If so, it means that the ICOA has been used to search near the final duty cycle, and it is necessary to enter S2 for precise approximation, otherwise return to S12 to continue iteration; the switching condition is:

[0071]

[0072] In the above formula, P1 is the output power corresponding to the global optimal individual in the current iteration, and P2 is the output power corresponding to the global optimal individual in the previous iteration;

[0073] S2, the duty cycle, output power, and voltage corresponding to the global optimal individual obtained in S1 are used as the initial duty cycle, output power, and voltage of the variable step size conductivity increment method (VSCI algorithm), the initial change step size is set, and the duty cycle is searched more accurately by gradually reducing the step size change until the algorithm converges; the expression for searching the duty cycle using the variable step size conductivity increment method is:

[0074]

[0075] p=ek·(iter-1)

[0076] In the above formula, D old , D new are the duty cycles before and after the search respectively; I and U are the current and voltage corresponding to the duty cycle after the search respectively; dI is the difference between the current corresponding to the duty cycle after the search and the current corresponding to the duty cycle before the search; dU is the difference between the voltage corresponding to the duty cycle after the search and the voltage corresponding to the duty cycle before the search; p is the contraction factor; is the initial duty cycle change; e is the natural logarithm; k is the constant that controls the search factor reduction rate; iter is the current iteration number of the variable step conductivity increment method;

[0077] Use the duty cycle obtained in S1 as D old , if the current and voltage of the duty cycle after the search meet Then D new Reduce to If satisfied Then D new Increase to In the above process, D new The value is updated once, the number of iterations increases by one, and the duty cycle changes It will decrease as the number of iterations increases, and so on, until D new With D old When equal D new No longer changes, at this time D new That is the duty cycle of the maximum power point;

[0078] S3, using the final duty cycle and output power output by S2 to perform photovoltaic MPPT control; in this process, in order to cope with the change of the final duty cycle caused by the change of the external environment, it is necessary to regularly monitor the photovoltaic output power. If it is monitored that the output power of the photovoltaic system before and after meets the restart condition, return to step S1 and restart the calculation; the restart condition is:

[0079]

[0080] In the above formula, P3 and P4 are the output power of the photovoltaic system before and after monitoring respectively.

[0081] In order to verify the effectiveness of the control method described in the present invention, a photovoltaic system on a ship deck is taken as the research object, and a photovoltaic system simulation model is built in the MATLAB / Simulink environment. Through simulation calculation, the P (power)-U (voltage) characteristic curve of the photovoltaic system under different illumination modes is set as shown in the figure. Figure 2 As shown; the photovoltaic array output power curve obtained by applying the control method of the present invention under the illumination mode P1 is as follows Figure 3 As shown, when the illumination mode changes from P2 to P3, the photovoltaic array output power curve obtained by applying the control method of the present invention is as follows Figure 4 As shown. Figure 3 , Figure 4 It can be seen that the control method of the present invention has a fast response speed and small power fluctuation, and can quickly restore the steady state in response to sudden changes in lighting conditions.

[0082] Embodiment 2:

[0083] See also Figure 5 A marine photovoltaic MPPT control system based on an improved variable step size conductance increment method comprises a first optimization module, a second optimization module and an MPPT control module; the first optimization module is used to optimize the duty cycle of a DC-DC converter in a photovoltaic system using a coati optimization algorithm, and the specific steps are as follows:

[0084] S11, initializing the number of coatis population and individual positions of coatis, wherein the individual positions of coatis correspond to the duty cycle of the DC-DC converter in the photovoltaic system;

[0085] S12, calculating the fitness value of the coati individual, obtaining the global optimal individual, and updating the position of the coati individual in the coati population; the fitness value of the coati individual corresponds to the output power obtained by multiplying the load current of the photovoltaic system and the voltage at both ends; the global optimal individual refers to the coati individual with the highest fitness value; the updating of the position of the coati individual in the coati population refers to: changing the fitness value of the coati individual i in the current iteration to The fitness value corresponding to the updated position according to the position update strategy For comparison, if Then the position of coati individual i is changed from Updated to Otherwise, the position of the coati individual i remains unchanged; the position update strategy of the coati individual is: the position is updated in the hunting and attacking stage and the predator escape stage in sequence; in the hunting and attacking stage, the coati individuals in the coati population are sorted in descending order according to the fitness value, and the coati individuals in the front of the coati population are updated in descending order according to the fitness value. The position update formula for each coati individual is:

[0086]

[0087] In the above formula, denote the position of coati individual i in the t+1th and tth iterations respectively; α is the step length control factor; is a point-to-point multiplication operation; Iguana t is the global optimal individual obtained in the tth iteration; I represents a random number in the set {1, 2}; Levy(λ) is the Levy flight function; N is the number of coatis individuals;

[0088] For coatis populations The position update formula for each coati individual is:

[0089]

[0090] In the above formula, r is a random number in the interval (0, 1); is a random number in the interval [0.2,0.9]; for The corresponding fitness value; is the fitness value corresponding to the position of coati individual i in the current iteration;

[0091] S13, judging whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition, if so, entering S2, otherwise returning to S12 to continue iteration; the switching condition is:

[0092]

[0093] In the above formula, P1 is the output power corresponding to the global optimal individual in the current iteration, and P2 is the output power corresponding to the global optimal individual in the previous iteration;

[0094] The second optimization module is used to use the duty cycle and output power corresponding to the global optimal individual obtained by the first optimization module as the initial conditions of the variable step size conductance increment method, set the initial change step size and continue to search for the duty cycle by gradually reducing the step size change, and output the final duty cycle and output power; the expression for searching the duty cycle using the variable step size conductance increment method is:

[0095]

[0096] p=e -k·(iter-1)

[0097] In the above formula, D old , D new are the duty cycles before and after the search respectively; I and U are the current and voltage corresponding to the duty cycle after the search respectively; dI is the difference between the current corresponding to the duty cycle after the search and the current corresponding to the duty cycle before the search; dU is the difference between the voltage corresponding to the duty cycle after the search and the voltage corresponding to the duty cycle before the search; p is the contraction factor; is the initial duty cycle change; e is the natural logarithm; k is the constant that controls the search factor reduction rate; iter is the current iteration number of the variable step conductivity increment method;

[0098] The MPPT control module is used to perform photovoltaic MPPT control according to the final duty cycle and output power output by the second optimization module.

[0099] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0100] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0102] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0103] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A marine photovoltaic MPPT control method based on an improved variable step conductance increment method, characterized in that: The control method comprises: S1. Use the coati optimization algorithm to optimize the duty cycle of the DC-DC converter in the photovoltaic system; determine whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition. If so, enter S2, otherwise continue to iterate; S2, taking the duty cycle and output power corresponding to the global optimal individual obtained in S1 as the initial conditions of the variable step conductivity increment method, setting the initial change step size and continuing to search for the duty cycle by gradually reducing the step size change; S3, using the final duty cycle and output power output by S2 to perform photovoltaic MPPT control.

2. The marine photovoltaic MPPT control method based on the improved variable step size conductance increment method according to claim 1 is characterized in that: The S1 includes: S11, initializing the number of coatis population and individual positions of coatis, wherein the individual positions of coatis correspond to the duty cycle of the DC-DC converter in the photovoltaic system; S12, calculating the fitness value of the raccoon individual, obtaining the global optimal individual, and updating the position of the raccoon individual in the raccoon population; the fitness value of the raccoon individual corresponds to the output power obtained by multiplying the load current of the photovoltaic array and the voltage at both ends; the global optimal individual refers to the raccoon individual with the highest fitness value; the updating of the position of the raccoon individual in the raccoon population refers to: changing the fitness value F of the raccoon individual i in the current iteration to i t The fitness value F corresponding to the updated position according to the position update strategy i t+1 For comparison, if F i t+1 >F i t , then the position of coati individual i is changed from F i t Updated to F i t+1 ; Otherwise, the position of coati individual i remains unchanged; S13, judging whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition, if so, entering S2, otherwise returning to S12 to continue iteration.

3. The marine photovoltaic MPPT control method based on the improved variable step size conductance increment method according to claim 2 is characterized in that: The position update strategy of the coati individual is as follows: the position is updated in the hunting and attacking stage and the predator escape stage in sequence; in the hunting and attacking stage, the coati individuals in the coati population are sorted in descending order according to the fitness value, and the coati individuals in the front of the coati population are updated in descending order. The position update formula for each coati individual is: In the above formula, denote the position of coati individual i in the t+1th and tth iterations respectively; α is the step length control factor; is a point-to-point multiplication operation; Iguana t is the global optimal individual obtained in the tth iteration; I represents a random number in the set {1, 2}; Levy(λ) is the Levy flight function; N is the number of coatis individuals; For coatis populations The position update formula for each coati individual is: In the above formula, r is a random number in the interval (0, 1); is a random number in the interval [0.2,0.9]; for The corresponding fitness value; F i t is the fitness value corresponding to the position of coati individual i in the current iteration.

4. The marine photovoltaic MPPT control method based on the improved variable step size conductance increment method according to claim 1 is characterized in that: The switching conditions are: In the above formula, P1 is the output power corresponding to the global optimal individual in the current iteration, and P2 is the output power corresponding to the global optimal individual in the previous iteration.

5. The marine photovoltaic MPPT control method based on the improved variable step size conductance increment method according to claim 1 is characterized in that: In S2, the expression for searching the duty cycle using the variable step size conductance increment method is: p=e -k·(iter-1) In the above formula, D old , D new are the duty cycles before and after the search, respectively; I and U are the current and voltage corresponding to the duty cycle after the search, respectively; dI is the difference between the current corresponding to the duty cycle after the search and the current corresponding to the duty cycle before the search; dU is the difference between the voltage corresponding to the duty cycle after the search and the voltage corresponding to the duty cycle before the search; p is the contraction factor; is the initial duty cycle change; e is the natural logarithm; k is the constant that controls the rate at which the search factor decreases; iter is the current iteration number of the variable step conductivity increment method.

6. Marine photovoltaic MPPT control system based on improved variable step conductance increment method, characterized by: The control method includes a first optimization module, a second optimization module, and an MPPT control module; The first optimization module is used to optimize the duty cycle of the DC-DC converter in the photovoltaic system using the coati optimization algorithm, and output the duty cycle and output power corresponding to the global optimal individual in the current iteration when the output power corresponding to the global optimal individual in the current iteration meets the switching condition; The second optimization module is used to use the duty cycle and output power corresponding to the global optimal individual obtained by the first optimization module as the initial conditions of the variable step conductance increment method, set the initial change step size, and continue to search for the duty cycle by gradually reducing the step size change, and output the final duty cycle and output power; The MPPT control module is used to perform photovoltaic MPPT control according to the final duty cycle and output power output by the second optimization module.

7. The marine photovoltaic MPPT control system based on the improved variable step conductance increment method according to claim 6 is characterized in that: The first optimization module optimizes the duty cycle of the DC-DC converter in the photovoltaic system according to the following steps: S11, initializing the number of coatis population and individual positions of coatis, wherein the individual positions of coatis correspond to the duty cycle of the DC-DC converter in the photovoltaic system; S12, calculating the fitness value of the raccoon individual, obtaining the global optimal individual, and updating the position of the raccoon individual in the raccoon population; the fitness value of the raccoon individual corresponds to the output power obtained by multiplying the load current of the photovoltaic array and the voltage at both ends; the global optimal individual refers to the raccoon individual with the highest fitness value; the updating of the position of the raccoon individual in the raccoon population refers to: changing the fitness value F of the raccoon individual i in the current iteration to i t The fitness value F corresponding to the updated position according to the position update strategy i t+1 For comparison, if F i t+1 >F i t , then the position of coati individual i is changed from F i t Updated to F i t+1 ; Otherwise, the position of coati individual i remains unchanged; S13, judging whether the output power corresponding to the global optimal individual in the current iteration meets the switching condition, if so, entering S2, otherwise returning to S12 to continue iteration.

8. The marine photovoltaic MPPT control system based on the improved variable step conductance increment method according to claim 7 is characterized in that: The position update strategy of the coati individual is: The position update strategy of the coati individual is as follows: the position is updated in the hunting and attacking stage and the predator escape stage in sequence; in the hunting and attacking stage, the coati individuals in the coati population are sorted in descending order according to the fitness value, and the coati individuals in the front of the coati population are updated in descending order. The position update formula for each coati individual is: In the above formula, denote the position of coati individual i in the t+1th and tth iterations respectively; α is the step length control factor; is a point-to-point multiplication operation; Iguana t is the global optimal individual obtained in the tth iteration; I represents a random number in the set {1, 2}; Levy(λ) is the Levy flight function; N is the number of coatis individuals; For coatis populations The position update formula for each coati individual is: In the above formula, r is a random number in the interval (0, 1); is a random number in the interval [0.2, 0.9]; for The corresponding fitness value; F i t is the fitness value corresponding to the position of coati individual i in the current iteration.

9. The marine photovoltaic MPPT control system based on the improved variable step conductance increment method according to claim 6 is characterized in that: The switching conditions are: In the above formula, P1 is the output power corresponding to the global optimal individual in the current iteration, and P2 is the output power corresponding to the global optimal individual in the previous iteration.

10. The marine photovoltaic MPPT control system based on the improved variable step size conductance increment method according to claim 6, characterized in that: The expression for searching the duty cycle using the variable step size conductance increment method is: p=e -k·(iter-1) In the above formula, D old , D new are the duty cycles before and after the search, respectively; I and U are the current and voltage corresponding to the duty cycle after the search, respectively; dI is the difference between the current corresponding to the duty cycle after the search and the current corresponding to the duty cycle before the search; dU is the difference between the voltage corresponding to the duty cycle after the search and the voltage corresponding to the duty cycle before the search; p is the contraction factor; e is the natural logarithm; k is the constant that controls the rate at which the search factor decreases; iter is the current iteration number of the variable step conductivity increment method.

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