CN119906089B - Marine Photovoltaic MPPT Control Method and System Based on Improved Variable Step Size Conductivity Increment Method - Google Patents
Marine Photovoltaic MPPT Control Method and System Based on Improved Variable Step Size Conductivity Increment MethodInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05F—SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
- G05F1/00—Automatic systems in which deviations of an electric quantity from one or more predetermined values are detected at the output of the system and fed back to a device within the system to restore the detected quantity to its predetermined value or values, i.e. retroactive systems
- G05F1/66—Regulating electric power
- G05F1/67—Regulating electric power to the maximum power available from a generator, e.g. from solar cell
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
- H02J2300/26—The renewable source being solar energy of photovoltaic origin involving maximum power point tracking control for photovoltaic sources
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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Abstract
本发明属于船用光伏发电技术领域，具体涉及一种基于改进变步长电导增量法的船用光伏MPPT控制方法及系统，方法先利用长鼻浣熊优化算法对光伏系统中DC‑DC变换器的占空比进行寻优，获得输出功率满足切换条件的全局最优个体，然后将该全局最优个体所对应的占空比和输出功率作为变步长电导增量法的初始条件，设置初始变化步长并通过逐渐减小步长变化量，继续对占空比进行搜索，利用得到的最终占空比和输出功率进行光伏MPPT控制。本发明将长鼻浣熊优化算法与变步长电导增量法相结合形成混合算法，不仅可以缩短算法搜索全局最优点的时间，还可以有效降低算法收敛过程中的功率波动。
This invention belongs to the field of marine photovoltaic power generation technology, specifically relating to a marine photovoltaic MPPT control method and system based on an improved variable step-size conductance incremental method. The method first uses the Long-Nosed Raccoon optimization algorithm to optimize the duty cycle of the DC-DC converter in the photovoltaic system, obtaining a globally optimal individual whose output power satisfies the switching conditions. Then, the duty cycle and output power corresponding to this globally optimal individual are used as the initial conditions for the variable step-size conductance incremental method. An initial variable step size is set, and the duty cycle is searched again by gradually decreasing the step size change. The final duty cycle and output power obtained are used for photovoltaic MPPT control. This invention combines the Long-Nosed Raccoon optimization algorithm with the variable step-size conductance incremental method to form a hybrid algorithm, which not only shortens the time for the algorithm to search for the global optimum but also effectively reduces power fluctuations during the algorithm's convergence process.
Description
Technical Field
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 conductivity increment method.
Background
In recent years, with the increasing demand for energy and the increasing supply of conventional fuels, research and development of renewable energy have become hot spots. Among them, solar energy is favored for its unique advantages of abundant resources, no regional boundary, cleanliness, etc. However, the solar power generation cost is high, so research aiming at improving the conversion efficiency of a photovoltaic system and reducing the photovoltaic power generation cost is particularly necessary.
In order to improve the photovoltaic technology for the ship, reduce the fuel consumption and the exhaust emission, and propel the green ship, the photovoltaic cell needs to be operated on the maximum power point as much as possible to realize the tracking of the maximum power point, and the method for converting the light energy into the electric energy to the maximum extent is the maximum power tracking technology (Maximum Power Point Track, MPPT). The maximum power tracking technology adopts mature methods such as a constant voltage method, a disturbance observation method, a variable step-length conductivity increment method and the like. The traditional variable step-length conductivity increment method has slow response speed in the starting stage and large power fluctuation in the tracking convergence process.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a marine photovoltaic MPPT control method and system based on an improved variable step conductivity increment method, wherein the response speed is high, and the power fluctuation is small.
In order to achieve the above object, the technical scheme of the present invention is as follows:
In a first aspect, the invention provides a marine photovoltaic MPPT control method based on an improved variable step-size conductivity increment method, which comprises the following steps:
S1, optimizing the duty ratio of a DC-DC converter in a photovoltaic system by utilizing a long-nose raccoon optimization algorithm, judging whether output power corresponding to a globally optimal individual under the current iteration meets a switching condition, if so, entering S2, otherwise, continuing iteration;
s2, taking the duty ratio and the output power corresponding to the global optimum obtained in the S1 as initial conditions of a variable step length conductivity increment method, setting initial change step length, and continuously searching the duty ratio by gradually reducing the step length change quantity;
And S3, performing photovoltaic MPPT control by utilizing the final duty ratio and output power output by the S2.
The S1 comprises the following steps:
S11, initializing the population number of the long-nose raccoon and the positions of the long-nose raccoon individuals, wherein the positions of the long-nose raccoon individuals correspond to the duty ratio of a DC-DC converter in a photovoltaic system;
S12, calculating the fitness value of the long-nose raccoon individual, obtaining a global optimal individual, and updating the position of the long-nose raccoon individual in the long-nose raccoon population, wherein the fitness value of the long-nose raccoon individual corresponds to the output power obtained by multiplying the load current and the voltage of the photovoltaic system, the global optimal individual is the long-nose raccoon individual with the highest fitness value, and the updating the position of the long-nose raccoon individual in the long-nose raccoon population is the fitness value of the long-nose raccoon individual i under the current iteration Fitness value corresponding to a location updated according to a location update policyFor comparison, ifThe position of the long-nasal raccoon individual i is determined byUpdated toConversely, the position of raccoon individual i remains unchanged;
S13, judging whether the output power corresponding to the global optimal individual under the current iteration meets the switching condition, if so, entering S2, otherwise, returning to S12, and continuing iteration.
The position updating strategy of the long-nose raccoon individuals comprises the steps of sequentially carrying out position updating in hunting and attacking stages and escaping predators, wherein the long-nose raccoon individuals in the long-nose raccoon population are ordered in descending order of fitness value in the hunting and attacking stages, and the long-nose raccoon population is subjected to anterior-anterior treatmentA long-nose raccoon individual whose location update formula is:
In the above-mentioned method, the step of, Respectively representing the positions of individuals i of the long nasal raccoon at the t+1st iteration, wherein alpha is a step control factor; The method is characterized by comprising the steps of performing point-to-point multiplication, wherein Iguana t is a globally optimal individual obtained by the t-th iteration, I represents random numbers in a set {1,2}, levy (lambda) is a Levy flight function, and N is the individual number of the raccoon;
for mid-postnatal raccoon population A long-nose raccoon individual whose location update formula is:
in the above formula, r is a random number in the interval (0, 1); Is a random number within interval [0.2,0.9 ]; Is that A corresponding fitness value; is the fitness value corresponding to the position of the long-nose raccoon individual i under the current iteration.
The switching conditions are as follows:
In the above formula, P 1 is the output power corresponding to the globally optimal individual in the current iteration, and P 2 is the output power corresponding to the globally optimal individual in the last iteration.
In the step S2, the expression for searching the duty ratio by using the variable step conductivity increment method is as follows:
p=e-k·(iter-1)
in the above formula, D old、Dnew is the duty ratio before and after searching respectively, I, U is the current and the voltage corresponding to the duty ratio after searching respectively, dI is the difference value obtained by subtracting the current corresponding to the duty ratio before searching from the current corresponding to the duty ratio after searching, dU is the difference value obtained by subtracting the voltage corresponding to the duty ratio before searching from the voltage corresponding to the duty ratio after searching, and p is the contraction factor; the method is characterized by comprising the steps of obtaining an initial duty ratio variation, wherein e is a natural logarithm, k is a constant for controlling the decreasing rate of a search factor, and item is the current iteration number of a variable step-length conductivity increment method.
In a second aspect, the invention provides a marine photovoltaic MPPT control system based on an improved variable step-size conductivity increment method, wherein the control method comprises a first optimizing module, a second optimizing module and an MPPT control module;
the first optimizing module is used for optimizing the duty ratio of the DC-DC converter in the photovoltaic system by utilizing a long-nose raccoon optimizing algorithm, and outputting the duty ratio and the 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 optimizing module is used for taking the duty ratio and the output power corresponding to the global optimal individual obtained by the first optimizing module as initial conditions of a variable step length conductivity increment method, setting initial change step length, continuously searching the duty ratio by gradually reducing the step length change amount, and outputting final duty ratio and output power;
And the MPPT control module is used for carrying out photovoltaic MPPT control according to the final duty ratio and the output power output by the second optimizing module.
The first optimizing module optimizes the duty ratio of a DC-DC converter in the photovoltaic system according to the following steps:
S11, initializing the population number of the long-nose raccoon and the positions of the long-nose raccoon individuals, wherein the positions of the long-nose raccoon individuals correspond to the duty ratio of a DC-DC converter in a photovoltaic system;
S12, calculating the fitness value of the long-nose raccoon individual, obtaining a global optimal individual, and updating the position of the long-nose raccoon individual in the long-nose raccoon population, wherein the fitness value of the long-nose raccoon individual corresponds to the output power obtained by multiplying the load current and the voltage of the photovoltaic system, the global optimal individual is the long-nose raccoon individual with the highest fitness value, and the updating the position of the long-nose raccoon individual in the long-nose raccoon population is the fitness value of the long-nose raccoon individual i under the current iteration Fitness value corresponding to a location updated according to a location update policyFor comparison, ifThe position of the long-nasal raccoon individual i is determined byUpdated toConversely, the position of raccoon individual i remains unchanged;
S13, judging whether the output power corresponding to the global optimal individual under the current iteration meets the switching condition, if so, entering S2, otherwise, returning to S12, and continuing iteration.
The position updating strategy of the long-nose raccoon individuals comprises the steps of sequentially carrying out position updating in hunting and attacking stages and escaping predators, wherein the long-nose raccoon individuals in the long-nose raccoon population are ordered in descending order of fitness value in the hunting and attacking stages, and the long-nose raccoon population is subjected to anterior-anterior treatmentA long-nose raccoon individual whose location update formula is:
In the above-mentioned method, the step of, Respectively representing the positions of individuals i of the long nasal raccoon at the t+1st iteration, wherein alpha is a step control factor; The method is characterized by comprising the steps of performing point-to-point multiplication, wherein Iguana t is a globally optimal individual obtained by the t-th iteration, I represents random numbers in a set {1,2}, levy (lambda) is a Levy flight function, and N is the individual number of the raccoon;
for mid-postnatal raccoon population A long-nose raccoon individual whose location update formula is:
in the above formula, r is a random number in the interval (0, 1); Is a random number within interval [0.2,0.9 ]; Is that A corresponding fitness value; is the fitness value corresponding to the position of the long-nose raccoon individual i under the current iteration.
The switching conditions are as follows:
In the above formula, P 1 is the output power corresponding to the globally optimal individual in the current iteration, and P 2 is the output power corresponding to the globally optimal individual in the last iteration.
The expression for searching the duty ratio by using the variable step-size conductivity increment method is as follows:
p=e-k·(iter-1)
in the above formula, D old、Dnew is the duty ratio before and after searching respectively, I, U is the current and the voltage corresponding to the duty ratio after searching respectively, dI is the difference value obtained by subtracting the current corresponding to the duty ratio before searching from the current corresponding to the duty ratio after searching, dU is the difference value obtained by subtracting the voltage corresponding to the duty ratio before searching from the voltage corresponding to the duty ratio after searching, and p is the contraction factor; the method is characterized by comprising the steps of obtaining an initial duty ratio variation, wherein e is a natural logarithm, k is a constant for controlling the decreasing rate of a search factor, and item is the current iteration number of a variable step-length conductivity increment method.
Compared with the prior art, the invention has the beneficial effects that:
According to the marine photovoltaic MPPT control method based on the improved variable-step-size conductivity increment method, the long-nose raccoon optimization algorithm is utilized to optimize the duty ratio of a DC-DC converter in a photovoltaic system, a global optimal individual with output power meeting switching conditions is obtained, the duty ratio and the output power corresponding to the global optimal individual are used as initial conditions of the variable-step-size conductivity increment method, initial change step sizes are set, the step-size change quantity is gradually reduced, the searching of the duty ratio is continued, the obtained final duty ratio and the obtained output power are utilized to conduct photovoltaic MPPT control, and the long-nose raccoon optimization algorithm and the variable-step-size conductivity increment method are combined to form a mixed 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.
Drawings
Fig. 1 is a flowchart of a control method according to embodiment 1 of the present invention.
Fig. 2 is a graph showing the P-U characteristics of the photovoltaic system in different illumination modes set forth in example 1.
Fig. 3 is a graph of the output power of the photovoltaic array obtained by applying the control method described in example 1 in illumination mode P1.
Fig. 4 is a graph showing the output power of the photovoltaic array obtained by applying the control method described in example 1 under the condition that the illumination mode is changed from P2 to P3.
Fig. 5 is a block diagram of a control system according to embodiment 2 of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and the accompanying drawings.
Example 1:
Referring to fig. 1, a marine photovoltaic MPPT control method based on an improved variable step conductivity increment method sequentially comprises the following steps:
s1, optimizing the duty ratio of a DC-DC converter in a photovoltaic system by using a long-nose raccoon optimization algorithm:
S11, initializing the population number of the long-nose raccoon and the positions of the long-nose raccoon individuals, wherein the positions of the long-nose raccoon individuals correspond to the duty ratio of a DC-DC converter in a photovoltaic system, and the positions of the long-nose raccoon are set to be random values in a section [0.2,0.9 ];
s12, calculating the fitness value of the long-nose raccoon individual, wherein the fitness value of the long-nose raccoon individual corresponds to the output power obtained by multiplying the load current and the voltage at two ends after the output voltage and the current of the photovoltaic system are stable, then obtaining the global optimal individual, the global optimal individual is the long-nose raccoon individual with the highest fitness value, updating the position of the long-nose raccoon individual in the long-nose raccoon population, and the updating the position of the long-nose raccoon individual in the long-nose raccoon population is the fitness value of the long-nose raccoon individual i under the current iteration Fitness value corresponding to a location updated according to a location update policyFor comparison, ifThe position of the long-nasal raccoon individual i is determined byUpdated toOn the contrary, the position of the long-nose raccoon individual i remains unchanged, and the position updating strategy of the long-nose raccoon individual i is divided into hunting and attack phases and escape predator phases, and the position updating formula of the hunting and attack phases is improved by utilizing the Lewy flight function to obtain an improved long-nose raccoon optimization algorithm (ICOA algorithm) in order to better explore the search space and accelerate the search speed:
the individuals of the long-nose raccoon population are sorted in descending order of fitness value, and the individuals of the long-nose raccoon population are sorted before A long-nose raccoon individual whose location update formula is:
In the above-mentioned method, the step of, Respectively representing the positions of individuals i of the long nasal raccoon at the t+1st iteration, wherein alpha is a step control factor; The method is characterized by comprising the steps of performing point-to-point multiplication, carrying out Iguana t on globally optimal individuals obtained by the t-th iteration, wherein I represents random numbers in a set {1,2}, N is the number of individuals in a long-nose raccoon population, N is an even number, and Levy (lambda) is a Levy flight function;
Levy (λ) can be expressed as Wherein beta is an exponential coefficient of the Lewy flight function, u and v obey normal distribution, and the calculation formula is as follows:
in the above formula, Γ is a standard gamma function; Representing the variance of u and v;
for mid-postnatal raccoon population A long-nose raccoon individual whose location update formula is:
in the above formula, r is a random number in the interval (0, 1); Is a random number within interval [0.2,0.9 ]; Is that A corresponding fitness value; The fitness value corresponding to the position of the long-nose raccoon individual i under the current iteration;
S13, judging whether output power corresponding to a global optimal individual under the current iteration meets a switching condition, if so, indicating that the situation that the final vicinity of the duty ratio is searched by ICOA at the moment, entering S2 for accurate approach is needed, otherwise, returning to S12 for iteration, wherein the switching condition is as follows:
In the above formula, P 1 is the output power corresponding to the globally optimal individual in the current iteration, and P 2 is the output power corresponding to the globally optimal individual in the last iteration;
S2, taking the duty ratio, output power and voltage corresponding to the global optimum individual obtained in the S1 as the initial duty ratio, output power and voltage of a variable step length conductivity increment method (VSCI algorithm), setting an initial change step length, and continuously searching the duty ratio more accurately by gradually reducing the step length change amount until the algorithm converges, wherein the expression for searching the duty ratio by using the variable step length conductivity increment method is as follows:
p=e-k·(iter-1)
in the above formula, D old、Dnew is the duty ratio before and after searching respectively, I, U is the current and the voltage corresponding to the duty ratio after searching respectively, dI is the difference value obtained by subtracting the current corresponding to the duty ratio before searching from the current corresponding to the duty ratio after searching, dU is the difference value obtained by subtracting the voltage corresponding to the duty ratio before searching from the voltage corresponding to the duty ratio after searching, and p is the contraction factor; E is natural logarithm, k is a constant for controlling the decreasing rate of the search factor, and iter is the current iteration times of the variable step-length conductivity increment method;
using the duty ratio obtained in S1 as D old, if the current and voltage of the duty ratio after searching meet Then D new is reduced toIf it meetsThen D new increases toIn the above process, the iteration number is increased by one when the D new value is updated once, and the duty ratio variation is increasedDecreasing with the increase of the iteration times, and so on until D new is not changed when D new is equal to D old, wherein D new is the duty ratio of the maximum power point;
In the process, in order to cope with the change of the final duty ratio caused by the change of the external environment, the photovoltaic output power needs to be continuously monitored at regular time, if the front and rear output powers of the photovoltaic system are monitored to meet the restarting condition, the step S1 is returned to perform restarting calculation, wherein the restarting condition is as follows:
In the above formula, P 3、P4 is the output power of the monitoring front and rear photovoltaic systems, respectively.
The effectiveness of the control method is verified by taking a photovoltaic system on a ship deck as a research object, building a photovoltaic system simulation model in a MATLAB/Simulink environment, setting P (power) -U (voltage) characteristic curves of the photovoltaic system under different illumination modes as shown in figure 2, changing the illumination mode from P2 to P3, and obtaining a photovoltaic array output power curve as shown in figure 4. From fig. 3 and fig. 4, it can be seen that the control method of the present invention has fast response speed and small power fluctuation, and can quickly recover the steady state even if the illumination condition is suddenly changed.
Example 2:
Referring to fig. 5, the marine photovoltaic MPPT control system based on the modified variable step-size conductivity increment method comprises a first optimizing module, a second optimizing module and an MPPT control module, wherein the first optimizing module is used for optimizing the duty ratio of a DC-DC converter in the photovoltaic system by using a long-nose raccoon optimizing algorithm, and specifically comprises the following steps:
S11, initializing the population number of the long-nose raccoon and the positions of the long-nose raccoon individuals, wherein the positions of the long-nose raccoon individuals correspond to the duty ratio of a DC-DC converter in a photovoltaic system;
S12, calculating the fitness value of the long-nose raccoon individual, obtaining a global optimal individual, and updating the position of the long-nose raccoon individual in the long-nose raccoon population, wherein the fitness value of the long-nose raccoon individual corresponds to the output power obtained by multiplying the load current and the voltage of the photovoltaic system, the global optimal individual is the long-nose raccoon individual with the highest fitness value, and the updating the position of the long-nose raccoon individual in the long-nose raccoon population is the fitness value of the long-nose raccoon individual i under the current iteration Fitness value corresponding to a location updated according to a location update policyFor comparison, ifThe position of the long-nasal raccoon individual i is determined byUpdated toOn the contrary, the position of the long-nose raccoon individual i remains unchanged, and the position updating strategy of the long-nose raccoon individual i is divided into hunting and attack phases and a prey escape phase, wherein the long-nose raccoon individuals in the long-nose raccoon population are sorted in descending order of fitness value in the hunting and attack phases, and the long-nose raccoon population is subjected to anterior-anterior treatmentA long-nose raccoon individual whose location update formula is:
In the above-mentioned method, the step of, Respectively representing the positions of individuals i of the long nasal raccoon at the t+1st iteration, wherein alpha is a step control factor; The method is characterized by comprising the steps of performing point-to-point multiplication, wherein Iguana t is a globally optimal individual obtained by the t-th iteration, I represents random numbers in a set {1,2}, levy (lambda) is a Levy flight function, and N is the individual number of the raccoon;
for mid-postnatal raccoon population A long-nose raccoon individual whose location update formula is:
in the above formula, r is a random number in the interval (0, 1); Is a random number within interval [0.2,0.9 ]; Is that A corresponding fitness value; The fitness value corresponding to the position of the long-nose raccoon individual i under the current iteration;
S13, judging whether output power corresponding to the global optimal individual under the current iteration meets a switching condition, if so, entering S2, otherwise, returning to S12 to continue iteration, wherein the switching condition is as follows:
In the above formula, P 1 is the output power corresponding to the globally optimal individual in the current iteration, and P 2 is the output power corresponding to the globally optimal individual in the last iteration;
The second optimizing module is used for taking the duty ratio and the output power corresponding to the global optimum individual obtained by the first optimizing module as initial conditions of a variable step length conductivity increment method, setting initial change step length, continuously searching the duty ratio by gradually reducing step length change amount, and outputting final duty ratio and output power, wherein the expression for searching the duty ratio by using the variable step length conductivity increment method is as follows:
p=e-k·(iter-1)
in the above formula, D old、Dnew is the duty ratio before and after searching respectively, I, U is the current and the voltage corresponding to the duty ratio after searching respectively, dI is the difference value obtained by subtracting the current corresponding to the duty ratio before searching from the current corresponding to the duty ratio after searching, dU is the difference value obtained by subtracting the voltage corresponding to the duty ratio before searching from the voltage corresponding to the duty ratio after searching, and p is the contraction factor; E is natural logarithm, k is a constant for controlling the decreasing rate of the search factor, and iter is the current iteration times of the variable step-length conductivity increment method;
and the MPPT control module is used for carrying out photovoltaic MPPT control according to the final duty ratio and the output power output by the second optimizing module.
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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. The marine photovoltaic MPPT control method based on the improved variable step length conductivity increment method is characterized by comprising the following steps of:
the control method comprises the following steps:
S1, optimizing the duty ratio of a DC-DC converter in a photovoltaic system by utilizing a long-nose raccoon optimization algorithm, judging whether output power corresponding to a globally optimal individual under the current iteration meets a switching condition, if so, entering S2, otherwise, continuing iteration;
s2, taking the duty ratio and the output power corresponding to the global optimum obtained in the S1 as initial conditions of a variable step length conductivity increment method, setting initial change step length, and continuously searching the duty ratio by gradually reducing the step length change quantity;
S3, performing photovoltaic MPPT control by utilizing the final duty ratio and output power output by the S2;
the S1 comprises the following steps:
S11, initializing the population number of the long-nose raccoon and the positions of the long-nose raccoon individuals, wherein the positions of the long-nose raccoon individuals correspond to the duty ratio of a DC-DC converter in a photovoltaic system;
S12, calculating fitness values of long-nose raccoon individuals, namely obtaining globally optimal individuals, updating the positions of the long-nose raccoon individuals in a long-nose raccoon population, wherein the fitness values of the long-nose raccoon individuals correspond to output power obtained by multiplying load currents of a photovoltaic array and voltages at two ends of the load currents of the photovoltaic array, the globally optimal individuals are long-nose raccoon individuals with the highest fitness values, the positions of the long-nose raccoon individuals in the updated long-nose raccoon population are obtained by comparing fitness values F i t of the long-nose raccoon individuals i under the current iteration with fitness values F i t+1 corresponding to the positions updated according to a position updating strategy, and if F i t+1＞Fi t, updating the positions of the long-nose raccoon individuals i from F i t to F i t+1, otherwise, keeping the positions of the long-nose raccoon individuals i unchanged;
S13, judging whether the output power corresponding to the global optimal individual under the current iteration meets the switching condition, if so, entering S2, otherwise, returning to S12 to continue iteration;
In the step S2, the expression for searching the duty ratio by using the variable step conductivity increment method is as follows:
p=e-k·(iter-1)
in the above formula, D old、Dnew is the duty ratio before and after searching respectively, I, U is the current and the voltage corresponding to the duty ratio after searching respectively, dI is the difference value obtained by subtracting the current corresponding to the duty ratio before searching from the current corresponding to the duty ratio after searching, dU is the difference value obtained by subtracting the voltage corresponding to the duty ratio before searching from the voltage corresponding to the duty ratio after searching, and p is the contraction factor; the method is characterized by comprising the steps of obtaining an initial duty ratio variation, wherein e is a natural logarithm, k is a constant for controlling the decreasing rate of a search factor, and item is the current iteration number of a variable step-length conductivity increment method.
2. The marine photovoltaic MPPT control method based on the modified variable step conductivity delta method of claim 1, wherein:
The position updating strategy of the long-nose raccoon individuals comprises the steps of sequentially carrying out position updating in hunting and attacking stages and escaping predators, wherein the long-nose raccoon individuals in the long-nose raccoon population are ordered in descending order of fitness value in the hunting and attacking stages, and the long-nose raccoon population is subjected to anterior-anterior treatment A long-nose raccoon individual whose location update formula is:
In the above-mentioned method, the step of, Respectively representing the positions of individuals i of the long nasal raccoon at the t+1st iteration, wherein alpha is a step control factor; The method is characterized by comprising the steps of performing point-to-point multiplication, wherein Iguana t is a globally optimal individual obtained by the t-th iteration, I represents random numbers in a set {1,2}, levy (lambda) is a Levy flight function, and N is the individual number of the raccoon;
for mid-postnatal raccoon population A long-nose raccoon individual whose location update formula is:
in the above formula, r is a random number in the interval (0, 1); Is a random number within interval [0.2,0.9 ]; Is that And F i t is the fitness value corresponding to the position of the long-nose raccoon individual i under the current iteration.
3. The marine photovoltaic MPPT control method based on the modified variable step conductivity delta method of claim 1, wherein:
The switching conditions are as follows:
In the above formula, P 1 is the output power corresponding to the globally optimal individual in the current iteration, and P 2 is the output power corresponding to the globally optimal individual in the last iteration.
4. A marine photovoltaic MPPT control system based on an improved variable step conductance delta method as set forth in any one of claims 1-3, wherein:
The control system comprises a first optimizing module, a second optimizing module and an MPPT control module;
the first optimizing module is used for optimizing the duty ratio of the DC-DC converter in the photovoltaic system by utilizing a long-nose raccoon optimizing algorithm, and outputting the duty ratio and the 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 optimizing module is used for taking the duty ratio and the output power corresponding to the global optimal individual obtained by the first optimizing module as initial conditions of a variable step length conductivity increment method, setting initial change step length, continuously searching the duty ratio by gradually reducing the step length change amount, and outputting final duty ratio and output power;
And the MPPT control module is used for carrying out photovoltaic MPPT control according to the final duty ratio and the output power output by the second optimizing module.
5. The marine photovoltaic MPPT control system based on the modified step-wise conductance delta method of claim 4, wherein:
The first optimizing module optimizes the duty ratio of a DC-DC converter in the photovoltaic system according to the following steps:
S11, initializing the population number of the long-nose raccoon and the positions of the long-nose raccoon individuals, wherein the positions of the long-nose raccoon individuals correspond to the duty ratio of a DC-DC converter in a photovoltaic system;
S12, calculating fitness values of long-nose raccoon individuals, namely obtaining globally optimal individuals, updating the positions of the long-nose raccoon individuals in a long-nose raccoon population, wherein the fitness values of the long-nose raccoon individuals correspond to output power obtained by multiplying load currents of a photovoltaic array and voltages at two ends of the load currents of the photovoltaic array, the globally optimal individuals are long-nose raccoon individuals with the highest fitness values, the positions of the long-nose raccoon individuals in the updated long-nose raccoon population are obtained by comparing fitness values F i t of the long-nose raccoon individuals i under the current iteration with fitness values F i t+1 corresponding to the positions updated according to a position updating strategy, and if F i t+1＞Fi t, updating the positions of the long-nose raccoon individuals i from F i t to F i t+1, otherwise, keeping the positions of the long-nose raccoon individuals i unchanged;
S13, judging whether the output power corresponding to the global optimal individual under the current iteration meets the switching condition, if so, entering S2, otherwise, returning to S12, and continuing iteration.
6. The improved variable step conductivity delta based marine photovoltaic MPPT control system of claim 5, wherein:
the location update strategy for the long-nasal raccoon individuals is:
The position updating strategy of the long-nose raccoon individuals comprises the steps of sequentially carrying out position updating in hunting and attacking stages and escaping predators, wherein the long-nose raccoon individuals in the long-nose raccoon population are ordered in descending order of fitness value in the hunting and attacking stages, and the long-nose raccoon population is subjected to anterior-anterior treatment A long-nose raccoon individual whose location update formula is:
In the above-mentioned method, the step of, Respectively representing the positions of individuals i of the long nasal raccoon at the t+1st iteration, wherein alpha is a step control factor; The method is characterized by comprising the steps of performing point-to-point multiplication, wherein Iguana t is a globally optimal individual obtained by the t-th iteration, I represents random numbers in a set {1,2}, levy (lambda) is a Levy flight function, and N is the individual number of the raccoon;
for mid-postnatal raccoon population A long-nose raccoon individual whose location update formula is:
in the above formula, r is a random number in the interval (0, 1); Is a random number within interval [0.2,0.9 ]; Is that And F i t is the fitness value corresponding to the position of the long-nose raccoon individual i under the current iteration.
7. The marine photovoltaic MPPT control system based on the modified step-wise conductance delta method of claim 4, wherein:
The switching conditions are as follows:
In the above formula, P 1 is the output power corresponding to the globally optimal individual in the current iteration, and P 2 is the output power corresponding to the globally optimal individual in the last iteration.
8. The marine photovoltaic MPPT control system based on the modified step-wise conductance delta method of claim 4, wherein:
the expression for searching the duty ratio by using the variable step-size conductivity increment method is as follows:
p=e-k·(iter-1)
In the above formula, D old、Dnew is the duty ratio before and after searching respectively, I, U is the current and the voltage corresponding to the duty ratio after searching respectively, dI is the difference value obtained by subtracting the current corresponding to the duty ratio before searching from the current corresponding to the duty ratio after searching, dU is the difference value obtained by subtracting the voltage corresponding to the duty ratio before searching from the voltage corresponding to the duty ratio after searching;
p is a contraction factor, e is a natural logarithm, k is a constant controlling a decreasing rate of a search factor, and iter is a current iteration number of the variable step conductivity incremental method.
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