WO2023207062A1

WO2023207062A1 - Maximum power tracking control method, and photovoltaic system and energy storage device

Info

Publication number: WO2023207062A1
Application number: PCT/CN2022/134433
Authority: WO
Inventors: 张宸珲; 张宏韬; 陈熙
Original assignee: 深圳市正浩创新科技股份有限公司
Priority date: 2022-04-27
Filing date: 2022-11-25
Publication date: 2023-11-02
Also published as: CN114911301B; CN114911301A

Abstract

A maximum power tracking control method, comprising: acquiring a first maximum output power and a corresponding first output voltage, at the current sampling moment, of a first photovoltaic panel in a photovoltaic array, and a second maximum output power and a corresponding second output voltage, at a previous sampling moment, of the first photovoltaic panel, and acquiring a third output voltage, at the previous sampling moment, of a second photovoltaic panel (S201); when there is no power hop in the first maximum output power, updating a voltage scanning range of the second photovoltaic panel according to the first output voltage, the second output voltage and the third output voltage (S202); and acquiring a third maximum output power, within the voltage scanning range, of the second photovoltaic panel, and outputting the first maximum output power and the third maximum output power (S203).

Description

Maximum power tracking control method, photovoltaic system and energy storage equipment

Cross-references to related applications

This application claims priority to the Chinese patent application submitted to the China Patent Office on April 27, 2022, with the application number 202210450107.0 and the invention title "Maximum power tracking control method, photovoltaic system and energy storage equipment", the entire content of which is incorporated by reference incorporated in this application.

Technical field

This application belongs to the field of photovoltaic power generation technology, and in particular relates to a maximum power tracking control method, photovoltaic systems and energy storage equipment.

Background technique

The statements herein merely provide background information relevant to the present application and do not necessarily constitute exemplary techniques.

At present, solar photovoltaic technology continues to develop and accounts for a large portion of revenue in the world's new energy field. According to different usage scenarios, power and specifications, solar photovoltaic architecture usually includes four common structures: centralized, string, string + Direct Current (DC) optimizer and micro-inverter.

Among them, the photovoltaic architecture of string + DC optimizer is widely used in home energy storage, and the maximum power point of its photovoltaic architecture can be tracked through the global scanning algorithm. During the scanning process, due to different factors such as the laying position of the photovoltaic panels, the laying area, and weather changes, the power-voltage curve of the photovoltaic panels has more than one peak value. The scanning time using the existing global scanning process is long, which affects the Maximum power point tracking efficiency of photovoltaic architectures.

Contents of the invention

According to various embodiments of the present application, a maximum power tracking control method, a photovoltaic system and an energy storage device are provided.

In the first aspect, this application provides a maximum power tracking control method, which is applied to a photovoltaic system. The photovoltaic system includes a photovoltaic array. The method may include:

Obtaining the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling moment and the first output voltage corresponding to the first maximum output power;

Obtain the second maximum output power and the corresponding second output voltage of the first photovoltaic panel at the last sampling moment;

Obtain the third output voltage of the second photovoltaic panel at the last sampling moment;

Comparing the first maximum output power and the second maximum output power, when it is determined that no power jump occurs in the first maximum output power, according to the first output voltage, the second output voltage and the The third output voltage updates the voltage scanning range of the second photovoltaic panel;

Obtain the third maximum output power of the second photovoltaic panel within the voltage scanning range, and output the first maximum output power and the third maximum output power;

Wherein, the second photovoltaic panel is a photovoltaic panel other than the first photovoltaic panel in the photovoltaic array.

In a second aspect, embodiments of the present application provide a photovoltaic system, including:

The photovoltaic system includes: an MPPT controller, a photovoltaic array and a voltage converter, and the MPPT controller connects the photovoltaic array and the voltage converter;

The MPPT controller is used to obtain the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling moment and the first output voltage corresponding to the first maximum output power; obtain the first maximum output power of the first photovoltaic panel at the current sampling moment. The second maximum output power and the second output voltage at the last sampling moment; obtain the third output voltage of the second photovoltaic panel at the last sampling moment; compare the first maximum output power and the second maximum output power, at When it is determined that no power jump occurs in the first maximum output power, update the voltage scanning range of the second photovoltaic panel according to the first output voltage, the second output voltage and the third output voltage;

The MPPT controller is also used to obtain the third maximum output power of the second photovoltaic panel within the voltage scanning range, and output the first maximum output power and the third maximum output power to the voltage converter;

In a third aspect, the application provides an energy storage device, the energy storage device is used to connect to a photovoltaic system, and the photovoltaic system includes a photovoltaic array;

The energy storage device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the maximum power tracking control described in the first aspect. Method steps.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium that stores a computer program. When the computer program is executed by a processor, the method described in the first aspect is implemented.

In a fifth aspect, embodiments of the present application provide a computer program product, which when the computer program product is run on a terminal device, causes the terminal device to execute the method described in the first aspect.

It can be understood that the beneficial effects of the above second to fifth aspects can be referred to the relevant descriptions in the first aspect, and will not be described again here.

The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below. Other features, objects and advantages of the application will become apparent from the description, drawings and claims.

Description of the drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the purpose of the present application. For some embodiments, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting creative efforts.

Figure 1 is a schematic diagram of the application of the photovoltaic system provided by the embodiment of the present application.

Figure 2 is a schematic flowchart of the maximum power point tracking control method provided by an embodiment of the present application.

Figure 3 is a schematic flowchart of the MPPT controller operating algorithm provided by the embodiment of the present application.

Figure 4 is a schematic diagram of a particle tracking algorithm on a power-voltage curve provided by an embodiment of the present application.

FIG. 5 is an overall flow diagram of the maximum power point tracking control method provided by the embodiment of the present application.

Figure 6 is a schematic structural diagram of a maximum power tracking control device provided by an embodiment of the present application.

FIG. 7 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

In the following description, for the purpose of explanation rather than limitation, specific details such as specific system structures and technologies are provided to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It will be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and/or components but does not exclude one or more other The presence or addition of features, integers, steps, operations, elements, components and/or collections thereof.

It will also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "once" or "in response to determining" or "in response to detecting" depending on the context. ". Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, to mean "once determined" or "in response to a determination" or "once the [described condition or event] is detected ]" or "in response to detection of [the described condition or event]".

In addition, in the description of this application and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

Reference in this specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Therefore, the phrases "in one embodiment", "in some embodiments", "in other embodiments", "in other embodiments", etc. appearing in different places in this specification are not necessarily Reference is made to the same embodiment, but rather to "one or more but not all embodiments" unless specifically stated otherwise. The terms “including,” “includes,” “having,” and variations thereof all mean “including but not limited to,” unless otherwise specifically emphasized.

Currently, string and DC optimizer photovoltaic architectures are widely used in home energy storage. For home energy storage, due to the different laying locations of photovoltaic panels, the sunshine conditions in the laying areas cannot be uniformly coordinated, and there is no fixed photovoltaic panel maintenance. Therefore, factors such as shadowing, aging or unclean photovoltaic panels will cause the power-voltage curve of the photovoltaic panels. There is often more than one peak. Therefore, algorithms based on global scan are widely used, such as global scan conductance increment method or particle swarm maximum power point tracking (MPPT) algorithm.

However, although traditional global scanning can determine the maximum power point of the photovoltaic panel, the scanning time is long. During the scanning process, if the scanning time is too long, it will affect the average power for a period of time (for example, if the scanning time is 5 minutes, it may affect the average power for one hour). Secondly, in changing weather conditions and different solar irradiances, the scanning process must be run at regular intervals. Therefore, it is very important to reduce unnecessary scanning time during the tracking of the maximum power point. function and significance.

Please refer to Figure 1, which is a schematic diagram of the application of the photovoltaic system provided by the embodiment of the present application. As shown in Figure 1, the photovoltaic system is connected to the power grid system. The photovoltaic system includes a photovoltaic array and a DC optimizer. The photovoltaic system is connected to the power grid system through an inverter. Among them, the photovoltaic array includes several photovoltaic panels. The photovoltaic panels operate independently of each other and are connected in series through a DC optimizer. The DC optimizer is connected to each photovoltaic panel correspondingly. The DC optimizer is used to track the maximum power point and stable output current of the solar photovoltaic panel to maximize the output power of the solar photovoltaic panel. The outputs of all DC optimizers are connected in series to input the current into the inverter. The output of the inverter It is connected in parallel to the power grid system and converts the input DC power into fixed-frequency and constant-voltage or frequency-regulated and voltage-regulated AC power to provide to the power grid system.

For example, the DC optimizer in the photovoltaic architecture may include an MPPT controller and a voltage converter configured for each photovoltaic panel. The MPPT controller tracks the maximum output power of the maximum power point of each photovoltaic panel in the photovoltaic array. , the voltage converter converts the DC power at the maximum power point output by the photovoltaic panel into stable DC power output of different voltages. Among them, the voltage converter adopts the pulse width modulation (PWM) working mode, uses the switching tube to process the DC power into a square wave (pulse wave), and changes the voltage by adjusting the duty cycle of the square wave (the ratio of pulse width to pulse period).

In the maximum power tracking control method provided by the above-mentioned photovoltaic system in the embodiment of the present application, MPPT controllers on the same string can communicate with each other. By communicating information, the average scanning time of the MPPT algorithm used in the entire string can be greatly reduced. Small. Moreover, the MPPT algorithm adopted has added anti-misjudgment logic. When abnormal output power is detected, the original sampling scanning range can be jumped out and a new sampling benchmark and algorithm model can be regenerated. The maximum power tracking control method provided by this application will be described below through specific embodiments.

Based on the above architecture of the overall photovoltaic system, embodiments of the present application provide a maximum power point tracking control method. The specific process of implementing this method is introduced below through the embodiments of this application.

Please refer to Figure 2. Figure 2 is a schematic flowchart of a maximum power point tracking control method provided by an embodiment of the present application. As shown in Figure 2, the method includes the following steps:

S201. Obtain the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling time and the first output voltage corresponding to the first maximum output power, and the sum of the second maximum output power of the first photovoltaic panel at the previous sampling time. The corresponding second output voltage and the third output voltage of the second photovoltaic panel at the last sampling moment.

In some embodiments, after the photovoltaic system is turned on, the DC optimizer attached to all photovoltaic panels executes the particle swarm MPPT algorithm, and determines the maximum power point of each photovoltaic panel at the first sampling time based on the standard voltage scan range at the initial time. , and record the maximum output power corresponding to the maximum power point and the output voltage corresponding to the maximum output power. The standard voltage scanning range can be 0V ~ 200V.

For example, after a sampling of the photovoltaic system is completed, the maximum output power of each photovoltaic panel obtained by the sampling is continued to operate. After reaching the preset operating time period, the calculation of the next sampling time is performed to determine the time at which The maximum output power and output voltage corresponding to each photovoltaic panel at the next sampling time. Among them, the running time period can be set according to the time for a complete calculation of the MPPT algorithm, and can also be set or dynamically adjusted according to the weather change characteristics of the local environment. For example, the running time period can be set to five minutes.

For example, at the next sampling moment after the first sampling is completed, the MPPT algorithm can be used to first calculate the maximum output power of the first photovoltaic panel and its corresponding output voltage. The first photovoltaic panel may be any photovoltaic panel in the photovoltaic array, such as photovoltaic panel No. 1 in the photovoltaic array arranged in sequence. Based on the first maximum output power and first output voltage of the first photovoltaic panel collected at the current sampling time, combined with the third output of the second photovoltaic panel other than the first photovoltaic panel recorded by the photovoltaic system at the first sampling time voltage, the new voltage scanning range corresponding to other second photovoltaic panels in the photovoltaic array can be further calculated, so that other photovoltaic panels no longer need to perform algorithm calculations based on the original standard voltage scanning range.

It should be noted that at each sampling moment after the first sampling moment, the maximum output power and output voltage of a photovoltaic panel in the photovoltaic array at the current sampling moment can be calculated based on the standard voltage scanning range, and then combined with the previous The maximum output power and output voltage of all photovoltaic panels at the sampling time are calculated. The corresponding voltage scanning ranges of other photovoltaic panels at the current sampling time are further calculated. Based on the voltage scanning range at the current sampling time, the maximum output power and output voltage of other photovoltaic panels are calculated. The maximum output power and output voltage of the first photovoltaic panel and other second photovoltaic panels at the current sampling time can be used as a reference value for the next sampling time. Record and store the maximum output power and output voltage of each photovoltaic panel obtained at each sampling time.

S202: Compare the first maximum output power and the second maximum output power. When it is determined that no power jump occurs in the first maximum output power, according to the first output voltage, the second output voltage and The third output voltage updates the voltage scanning range of the second photovoltaic panel.

In some embodiments, in order to prevent abnormal output power, after obtaining the second maximum output power and second output voltage of the first photovoltaic panel at the last sampling time, and the first maximum output power and first output voltage of the current sampling time, After the voltage is measured, it is necessary to judge the maximum output power of the first photovoltaic panel before and after the first photovoltaic panel. By calculating the change amplitude of the two maximum output powers, it is determined whether the maximum output power of the first photovoltaic panel obtained at the current sampling time is abnormal.

For example, the formula

Determine whether the maximum output power at the current sampling time has jumped. Among them, A is the change amplitude, p ₁ is the first maximum output power of the first photovoltaic panel at the current sampling time, and p ₂ is the second maximum output power of the first photovoltaic panel at the previous sampling time. When the change amplitude exceeds 10%, it is determined that the maximum output power of the first photovoltaic panel has jumped, and the maximum output power has become abnormal. The cause of the power jump may be caused by major changes in weather conditions in a short period of time. At this time, the entire algorithm needs to be reset, that is, returned to the state at the initial sampling moment after power-on. When A is less than or equal to 10%, it is determined that there is no power jump in the first maximum output power. The lack of power jump may be caused by the fine adjustment of the sun's irradiation angle due to time. When the maximum output power of the first photovoltaic panel does not jump, the voltage scanning range of the second photovoltaic panel is updated according to the first output voltage, the second output voltage and the third output voltage, and the voltage scanning range of the other second photovoltaic panels is updated. The voltage scanning range is updated to the reduced scanning range, thereby reducing the average time for the photovoltaic array to track the maximum power point, improving tracking efficiency, and reducing the impact of the photovoltaic system's time occupied by the scanning process on the average output power.

In some embodiments, before updating the voltage scanning range of the second photovoltaic panel according to the first output voltage, the second output voltage and the third output voltage, the method further includes: obtaining the learning of the first photovoltaic panel at the current sampling moment. coefficient.

For example, the algorithm used in this application is based on the logical structure of the self-learning adaptation algorithm. By defining learning coefficients and controlling the information interaction function between the MPPT controllers of each photovoltaic panel, the MPPT learning algorithm of the entire system is implemented. This learning coefficient is updated with the number of iterations when the PV system runs the MPPT algorithm at the sampling moment.

Correspondingly, the voltage scanning range of the second photovoltaic panel is updated according to the first output voltage, the second output voltage and the third output voltage, including:

Calculate the lower limit of the voltage scanning range according to the first formula, which is expressed as:

Calculate the upper limit of the voltage scanning range according to the second formula, which is expressed as:

Among them, x is the serial number of the photovoltaic panel in the photovoltaic array. n is the iteration coefficient at the sampling time, n≥1. U _min is the lower limit of the voltage scanning range. U _max is the upper limit of the voltage scanning range. V _max is the rated voltage of the photovoltaic panel. C _n is the learning coefficient corresponding to the nth sampling time. V _x-(n-1) is the third output voltage corresponding to the maximum output power of the x-th photovoltaic panel except the first photovoltaic panel in the photovoltaic array at the n-1th sampling time. V _1-n is the first output voltage corresponding to the maximum output power of the first photovoltaic panel at the n-th sampling moment. V _1-(n-1) is the second output voltage corresponding to the maximum output power of the first photovoltaic panel at the n-1th sampling time.

In some embodiments, after comparing the first maximum output power and the second maximum output power, the method further includes:

When the difference between the first maximum output power and the second maximum output power exceeds the preset threshold range, it is determined that a power jump occurs in the first maximum output power, and the standard voltage scanning range of the photovoltaic array is obtained; each block in the photovoltaic array is obtained The maximum power point of the photovoltaic panel within the standard voltage scanning range; use the standard voltage scanning range as the voltage scanning range of each photovoltaic panel in the photovoltaic array at the current sampling moment; update the learning coefficient of the first photovoltaic panel to the initial value; The maximum power point of each photovoltaic panel in the photovoltaic array within the standard voltage scanning range is used as the maximum output power of each photovoltaic panel at the current sampling moment.

For example, the standard voltage scanning range is the standard voltage scanning range of the photovoltaic panel, such as the set 0V to 200V. When the maximum output power of the first photovoltaic panel jumps, the learning algorithm of the photovoltaic system is restored to the state at the first sampling time, that is, the learning coefficient is restored to the initial value. Based on the standard voltage scanning range of the photovoltaic system, the MPPT algorithm is used to calculate The maximum output power and output voltage of each photovoltaic panel; and the maximum power point obtained by each photovoltaic panel based on the standard voltage scanning range is regarded as the maximum output power of each photovoltaic panel at the current sampling moment.

In some embodiments, after obtaining the third maximum output power of the second photovoltaic panel within the voltage sweep range, the method further includes:

When the difference between the third maximum output power of any second photovoltaic panel in the photovoltaic array and the maximum output power of the second photovoltaic panel at the previous sampling moment exceeds the preset threshold range, it is determined that the second photovoltaic panel has jumped, then Obtain the maximum power point of each photovoltaic panel in the photovoltaic array within the standard voltage scanning range, and use the maximum power point of each photovoltaic panel in the photovoltaic array within the standard voltage scanning range as the maximum output power of the photovoltaic panel at the current sampling moment. .

For example, if the maximum output power of the first photovoltaic panel at the current sampling time does not jump relative to the maximum output power at the previous sampling time, then the output voltage of the maximum output power at the current sampling time and the output voltage at the previous sampling time are obtained. Output the voltage and put it into the above formula to calculate the voltage scanning range corresponding to the other photovoltaic panels except the first photovoltaic panel. The voltage scanning range is smaller than the standard voltage scanning range. Then, corresponding to the current sampling moment and based on the reduced voltage scanning range, the maximum power points of other photovoltaic panels except the first photovoltaic panel are rescanned, and the maximum output power and output voltage corresponding to the maximum power point are determined, thereby based on the reduced voltage scanning range. The voltage scanning range saves the scanning time of other photovoltaic panels and reduces the energy loss during the scanning process.

Among them, the rated voltage of the photovoltaic panel is related to the characteristics of the photovoltaic panel itself, and the rated voltage of the same string is the same.

It should be noted that after the scanning of all photovoltaic panels corresponding to the current sampling time is completed, in order to avoid power misjudgments in similar situations, after scanning the maximum output power and output voltage of all other second photovoltaic panels, each The maximum output power of the second photovoltaic panel at the current sampling time is compared with the maximum output power of the previous sampling time to determine whether the maximum output power of the second photovoltaic panel has jumped. If the maximum output power of any second photovoltaic panel at the current sampling moment jumps, the MPPT learning algorithm is reset, that is, all set parameters (including learning coefficients, iteration coefficients, etc.) are restored to their initial values. For example, restore the learning coefficient to the initial value of 0.5 and restore the iteration coefficient to 1. When no transition occurs in any of the second photovoltaic panels at the corresponding current sampling moment, the learning coefficients are adaptively updated, and the iteration coefficients are also incrementally updated.

For example, the learning coefficient of the first photovoltaic panel is updated according to a preset gradient. After the update, the learning coefficient will be used as the learning coefficient at the next sampling moment.

In some embodiments, updating the learning coefficient of the first photovoltaic panel according to a preset gradient includes:

Get the learning coefficient of the first photovoltaic panel. When the learning coefficient of the first photovoltaic panel is greater than the minimum learning coefficient, the learning coefficient of the first photovoltaic panel is updated according to the preset gradient.

For example, the minimum value of the learning coefficient is set, for example, the minimum value can be set to 0.2, and the preset gradient is set to the gradient of proportional reduction, for example, the gradient of proportional reduction is 0.9, then C _n+1 =C _n *0.9, Where n is the number of iterations at the corresponding sampling time. For example, the learning coefficient corresponding to the first sampling time is C ₁ =0.5. The maximum output power corresponding to all photovoltaic panels at the current sampling time is relative to the maximum output power corresponding to the previous sampling time. When no jump occurs, the number of iterations at the sampling time is incrementally updated. The incremental update method is to increase one by one with the number of iterations at the sampling time; when the maximum output power of any photovoltaic panel jumps, it returns to the value at the first sampling time. state, that is, n=1, C ₁ =0.5. When the learning coefficient is updated to the minimum value of the learning coefficient with the number of iterations at the sampling time, the learning coefficient is no longer updated, and the minimum value is used as the learning coefficient corresponding to the sampling time of each subsequent iteration.

It should be noted that the initial value and minimum value of the learning coefficient can be set according to the architecture of the photovoltaic system and the application environment, and are not limited here.

S203: Obtain the third maximum output power of the second photovoltaic panel within the voltage scanning range, and output the first maximum output power and the third maximum output power.

In some embodiments, after the photovoltaic system obtains the maximum output power of other second photovoltaic panels, it is based on the maximum output power of the first photovoltaic panel obtained at the current sampling time and the maximum output power of each other second photovoltaic panel. , the maximum output power of the entire photovoltaic system can be obtained. Due to the string connection method, controlling the first photovoltaic panel to operate according to the first maximum output power, and the other second photovoltaic panels to operate according to the third maximum output power, will obtain the maximum power of the entire system currently sampled, and use this maximum power Run for a preset time period.

In the embodiment of the present application, during the process of scanning and tracking the maximum power of the photovoltaic system, when the maximum output power of the first photovoltaic panel does not undergo a power jump, the maximum output of the first photovoltaic panel in the photovoltaic array can be obtained based on the current sampling time. power, as well as the maximum output power of the first photovoltaic panel at the last sampling time, the maximum output power of other photovoltaic panels in the photovoltaic array at the previous sampling time, and their respective corresponding voltages, and calculate the current use of other photovoltaic panels in the photovoltaic array. Each moment corresponds to the reduced voltage scanning range, thereby tracking and determining the maximum output power of other photovoltaic panels in the photovoltaic array based on the reduced voltage scanning range and determining the maximum power of the photovoltaic array. This saves the scanning time of the photovoltaic array and improves the efficiency of the photovoltaic system. Efficiency of maximum power tracking control.

Regarding the particle swarm MPPT algorithm used in the above-mentioned maximum power tracking control method, the embodiment of the present application further explains the particle swarm MPPT algorithm. The flow of the MPPT controller operation algorithm provided by the embodiment of the present application is shown in Figure 3. Schematic diagram, as well as a schematic diagram of the particle tracking algorithm on the power-voltage curve diagram provided by the embodiment of the present application shown in Figure 4. As shown in Figure 3, the particle swarm MPPT algorithm can include the following processes:

S301. Determine the core variables of the MPPT algorithm. The core variables include: the number of particles, the maximum number of loops, the maximum particle value, and the minimum particle value; for example, the number of particles shown in Figure 4 is 4 (P ₁ , P ₂ , P ₃ and P ₄ ), the maximum value of the particle is the value corresponding to particle P ₃ , and the minimum value is the value corresponding to particle P _1. The number of iterations can be determined according to the scanning range setting and the particle movement speed.

S302. Define the formula parameters of the algorithm: inertia weight w, self-learning parameter c ₁ , and social learning parameter c ₂ .

For example, through the following formulas (3) and (4), during the execution of the MPPT algorithm, the speed and position of the particles are determined respectively:

Among them, V is the speed of each particle; k is the number of iterations of the algorithm. i is the particle number. d is the current dimension of the particle. w is the inertia weight, which adjusts the impact of the last particle movement speed on the current time. The greater the weight, the smaller the current speed change. C ₁ is the self-learning coefficient. The larger the coefficient, the greater the weight of the particle on the optimal point it has experienced in the past. C ₂ is the social learning coefficient, which represents the weight proportion of the optimal points of other particles. R ₁ and R ₂ are random numbers, P _id is the maximum fitness value of the i-th particle in history, P _gd is the maximum fitness value of all particles in history, and X is the position of the particle.

is the current best position,

The best location in history. The velocity and position of the particles correspond to the scan step size and the duty cycle of the boost converter (voltage converter), respectively.

S303, if the system meets the conditions for avoiding oscillation (when the speed change is extremely small and the conditions are met), it is determined that the system is in a stable state.

S304: Initialize the particle position and speed, create a corresponding empty set, and create an empty set of the maximum optimized position of the particles.

S305, determine whether the particle position set is an empty set and the algorithm satisfies the reset condition (reset=1); if so, execute S306; if not, execute S307.

S306, re-initialize the particle position, velocity and optimal solution.

S307: Compare the power of each particle at different positions and find the local MPPT.

S308, determine local MPPT > global memory MPPT; for example, in (d) of Figure 4, when the particle P ₁ reaches the position of the local MPPT, it is necessary to further determine whether the local MPPT is greater than the global memory MPPT. In this figure, the global memory MPPT is the particle The position of P ₃ is therefore not satisfied, and the global memory MPPT is not updated, and S310 is executed. For example, assume that the global memory MPPT is the particle P ₃ in (a) of Figure 4. After calculating the particle motion, in (b) of Figure 4, the particle P ₂ is the local MPPT. At this time, the local MPPT is larger than the particle P. ₃ (the position of the global memory MPPT), so the global memory MPPT needs to be updated to the position of the particle P ₂ , and S309 is executed.

S309, refresh the global memory MPPT point, and move other particles to the particle position of this point according to the refreshed MPPT point.

S310, do not refresh the global memory MPPT points and maintain the original movement direction and speed; for example, in (e) of Figure 4, when all particles maintain the original movement direction and speed, the global memory MPPT will no longer change and update. Until all particle movement values are globally memorized to the position corresponding to MPPT, that is, the position shown in (f) of Figure 4, the maximum power point can be tracked.

S311, adjust the speed and position of the particles according to the MPPT point in the judgment condition; continue to search for the global maximum power point.

It should be noted that Figure 4 only schematically illustrates the process of tracking the maximum power point using the particle swarm MPPT algorithm in this application. As shown in (a) of Figure 4, the initial positions of the four particles are respectively at P (power)- At different positions of the U (voltage) curve, as the number of iterations of the algorithm increases, the position of the particles is constantly updated. Due to factors such as the environment of the photovoltaic panel, the PU curve has multiple peaks. During the search process, the particles are on the curve. The local peak value of is constantly updated, so each particle is in an activated state and is always compared with its position at the previous moment. As shown in (d) of Figure 4, the updated position of P ₁ is at a local peak, but the particles do not stop tracking and continue to maintain the tracking state. As shown in (e) in Figure 4, P ₁ crossed the local peak, maintained the search state, and continued to approach the global peak; as shown in (f) in Figure 4, finally all four particles reached the global peak, The particles stop searching so that the system can maintain maximum power output.

Based on the above implementation process of the particle swarm MPPT algorithm, embodiments of the present application provide an overall process diagram of the maximum power point tracking control method, as shown in Figure 5. The overall process diagram may include the following steps:

S501, after all photovoltaic panels are turned on, the particle swarm MPPT algorithm is used to calculate and determine the maximum output power and corresponding output voltage of each photovoltaic panel at the first sampling time at that sampling time.

S502, record the output voltage of each photovoltaic panel, create corresponding variables, continue to run the photovoltaic system and start timing, t=0.

S503, the corresponding variables include: iteration coefficient n=1, learning coefficient C ₁ =0.5; timing t=t+1.

S504: Whether the timing time reaches the preset running time period; if so, execute S505; if not, execute S503.

Illustratively, the embodiment of the present application records the running time t, the iteration coefficient n corresponding to each sampling moment, and the sign bit x of the photovoltaic panel, the learning coefficient C _xn corresponding to each sampling moment, and the output voltage of each photovoltaic panel. V _xn , etc.; for example, C _2-2 represents the second learning coefficient of photovoltaic panel No. 2, and V _2-2 represents the second output voltage of photovoltaic panel No. 2.

For example, after the system is turned on, the DC optimizer attached to all photovoltaic panels simultaneously performs the particle swarm MPPT algorithm and obtains the maximum power point of each photovoltaic panel, and at the same time determines the corresponding maximum output voltage and duty cycle (the duty cycle is The voltage converter determines the duty cycle required for the maximum output voltage. At this time, the output voltage corresponding to the maximum output power of all photovoltaic panels is simultaneously recorded in the memory of the processor MCU of each MPPT algorithm module).

S505, re-run the first photovoltaic panel individually to obtain the maximum output power of the first photovoltaic panel at the sampling time.

S506: Whether the maximum output power of the first photovoltaic panel jumps compared to the maximum output power of the previous sampling moment. If so, return to the initial state and execute S501. If not, execute S507.

For example, all photovoltaic panels are operated at the maximum output power corresponding to the first sampling moment, and the operation time period of the photovoltaic system working at the maximum output power is started simultaneously. For example, the operation time period can be five minutes, and the operation time period can be According to the time change of the DC optimizer's processor MCU for one complete operation of the MPPT algorithm, it can also be dynamically adjusted according to the local weather change characteristics.

Correspondingly, when the set operating time period is reached, the MPPT module of the No. 1 photovoltaic panel is run separately at this time, and the learning coefficient C ₁ = 0.5 is preset in advance. When the operating time period is 5 minutes, t = 300 at this time, The number of iterations at the time taken is n=1. At the current sampling time when photovoltaic panel No. 1 is running alone, the MPPT module of photovoltaic panel No. 1 will measure a new maximum power point. At this time, the algorithm detects the new maximum power point at the current sampling time and the old maximum power at the previous sampling time. If the difference exceeds ten percent (that is, lower than the old 90% or higher than the old 110%), it means that the weather conditions have changed significantly in a short period of time, and the entire algorithm needs to be reset, that is, all photovoltaic panels will return to normal. to the initialization state after power-on. If the detected difference is less than ten percent, it means that there is no major change. Usually the sun angle is slightly adjusted due to time reasons. At this time, the algorithm enters the second large module to calculate and update the voltage scanning range of other photovoltaic panels.

S507: Calculate the voltage scanning range of other photovoltaic panels in the photovoltaic array except the first photovoltaic panel according to formula (1) and formula (2).

S508: Based on the voltage scanning range of other photovoltaic panels in the photovoltaic array, the particle swarm MPPT algorithm is used to calculate the maximum output power of each other photovoltaic panel at the sampling moment.

S509: Determine whether the maximum output power of any photovoltaic panel has jumped compared to the maximum output power of the previous sampling moment; if so, return to the initial state and execute S501; if not, execute S510.

S510, timing t=t+1, adaptive modification of learning coefficient: Cn+1=Cn*0.9, iteration coefficient: n=n+1.

For example, if it is detected that the maximum output power of photovoltaic panel No. 1 has not jumped, the output voltage corresponding to the maximum output power of photovoltaic panel No. 1 at the current sampling time is obtained, and the output voltage at the current sampling time is compared with the above The output voltage corresponding to the maximum output power of photovoltaic panel No. 1 at a sampling time is put into formulas (1) and (2) to calculate the voltage scanning range of other photovoltaic panels except photovoltaic panel No. 1. Then rescan all photovoltaic panels except No. 1 to determine the maximum power points of other photovoltaic panels. The scanning range of other photovoltaic panels is changed to the updated new range, which is calculated by formulas (1) and (2), thus saving the scanning time of other photovoltaic panels except No. 1 photovoltaic panel and avoiding the scanning process. energy loss in.

Among them, in formulas (1) and (2), U _min and U _max are respectively the minimum and maximum values of the new scanning range in this range iteration, and V _max is the rated voltage of the photovoltaic panel, which is The rated maximum voltage of a photovoltaic panel is only related to the characteristics of the photovoltaic panel itself. The rated maximum voltage corresponding to each photovoltaic panel in the same string is the same.

For example, after the scanning of other photovoltaic panels except the No. 1 photovoltaic panel is completed, in order to avoid misjudgments similar to the No. 1 photovoltaic panel, all other photovoltaic panels except the No. 1 photovoltaic panel are re-scanned. Compare the maximum output power of the previous iteration with the newly searched maximum output power to see if there is a jump in the maximum output power. If a transition is detected, the algorithm is reset and returns to step S501. If the output power does not jump, the learning coefficient will be adaptively updated, that is, the learning coefficient C _n is based on the learning coefficient of the No. 1 photovoltaic panel and is reduced to C _n+1 , for example, C _n+1 =C _n *0.9 , and at the same time, the minimum value of C _n+1 can be set to 0.2. When the learning coefficient C _n reaches 0.2 with the number of iterations at the sampling moment, the learning coefficient no longer changes and stabilizes at 0.2.

It should be noted that when the power of photovoltaic panel No. 1 jumps, the learning coefficient C _n returns to the initial value C ₁ =0.5. Secondly, reset t=0 and enter a new round of iteration and timing. Next, run the No. 1 photovoltaic panel separately and repeat the previous process. That is, if the output power jump of the No. 1 photovoltaic panel is detected, the algorithm will be reset. If there is no jump, you can return to the previous process and continue to calculate and update the No. 1 photovoltaic panel. Voltage scanning range for photovoltaic panels other than photovoltaic panels and subsequent processes.

S511, whether the timing time reaches the preset running time period, if so, execute S512, if not, execute S510.

S512, re-run the first photovoltaic panel individually to obtain the maximum output power of the first photovoltaic panel at the sampling time.

S513: Whether the maximum output power of the first photovoltaic panel jumps compared to the maximum output power of the previous sampling time. If so, return to the initial state and execute S501. If not, execute S507.

Through the embodiments of this application, through communication between the MPPT controllers corresponding to each photovoltaic panel, the effect of reducing scanning time can be achieved. By saving scanning time, the impact of scanning on efficiency can be reduced and power generation can be increased. In addition, the learning coefficient and time coefficient in the algorithm used in this application can be adaptively adjusted according to different working sites and common working conditions. The embodiments of the present application can be applied to home energy storage or solar power plants, and are highly adaptable to dynamic weather change application scenarios.

It should be understood that the sequence number of each step in the above embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

Corresponding to the maximum power tracking control method described in the above embodiment, FIG. 6 shows a structural block diagram of the maximum power tracking control device provided by the embodiment of the present application. For convenience of explanation, only the components related to the embodiment of the present application are shown. part.

Referring to Figure 6, the device includes: an acquisition unit 61 configured to acquire the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling moment and the first output voltage corresponding to the first maximum output power, the first photovoltaic The second maximum output power of the panel at the last sampling time and the corresponding second output voltage, and the third output voltage of the second photovoltaic panel at the last sampling time. The processing unit 62 is configured to compare the first maximum output power and the second maximum output power, and when determining that no power jump occurs in the first maximum output power, according to the first output voltage, the The second output voltage and the third output voltage update the voltage scanning range of the second photovoltaic panel; the output unit 63 is configured to obtain the third maximum output of the second photovoltaic panel within the voltage scanning range. power, and output the first maximum output power and the third maximum output power.

It should be noted that the information interaction, execution process, etc. between the above-mentioned devices/units are based on the same concept as the method embodiments of the present application. For details of their specific functions and technical effects, please refer to the method embodiments section. No further details will be given.

Embodiments of the present application also provide a photovoltaic system. The photovoltaic system includes: an MPPT controller, a photovoltaic array and a voltage converter, and the MPPT controller is connected to the photovoltaic array and the voltage converter;

The MPPT controller is used to obtain the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling moment and the first output voltage corresponding to the first maximum output power. Obtain the second maximum output power and second output voltage of the first photovoltaic panel at the last sampling moment. Obtain the third output voltage of the second photovoltaic panel at the last sampling moment. Comparing the first maximum output power and the second maximum output power, when it is determined that no power jump occurs in the first maximum output power, according to the first output voltage, the second output voltage and the The third output voltage updates the voltage scanning range of the second photovoltaic panel. The MPPT controller is also used to obtain the third maximum output power of the second photovoltaic panel within the voltage scanning range, and output the first maximum output power and the third maximum output power to the voltage converter.

An embodiment of the present application also provides an energy storage device, which is used to connect to a photovoltaic system. The photovoltaic system includes a photovoltaic array. The energy storage device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above maximum power tracking control method are implemented.

For example, the energy storage device can be charged through the photovoltaic system, and the energy storage system can also include an MPPT controller and a voltage converter.

Embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps in each of the above method embodiments can be implemented.

Embodiments of the present application provide a computer program product. When the computer program product is run on a mobile terminal, the steps in each of the above method embodiments can be implemented when the mobile terminal is executed.

Figure 7 is a schematic structural diagram of an energy storage device 7 provided by an embodiment of the present application. As shown in Figure 7, the energy storage device 7 of this embodiment includes: at least one processor 70 (only one is shown in Figure 7), a memory 71, and a device stored in the memory 71 and available in the at least one processor. The computer program 72 runs on the computer 70. When the processor 70 executes the computer program 72, the steps in the above embodiments are implemented.

The energy storage device 7 is a device that can implement the MPPT algorithm. The energy storage device 7 may include, but is not limited to, a processor 70 and a memory 71 . Those skilled in the art can understand that FIG. 7 is only an example of the energy storage device 7 and does not constitute a limitation on the energy storage device 7. It may include more or fewer components than shown in the figure, or some components may be combined or different. The components may also include, for example, input and output devices, network access devices, etc. In Figure 7, the photovoltaic system is directly connected to the energy storage device, and the energy storage device performs power tracking based on the maximum output power of each photovoltaic panel in the photovoltaic array. The energy storage device also includes a battery module. After performing the maximum power tracking control method on the photovoltaic array, the energy storage device uses the power converted by the photovoltaic array to charge the battery module. The energy storage device can also use the electric energy converted by the photovoltaic array to power the load connected to the energy storage device after performing the maximum power tracking control method on the photovoltaic array.

The so-called processor 70 can be a central processing unit (Central Processing Unit, CPU), and the processor 70 can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit) , ASIC), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

The memory 71 may be an internal storage unit of the energy storage device 7 in some embodiments, such as a hard disk or memory of the energy storage device 7 . In other embodiments, the memory 71 may also be an external storage device of the energy storage device 7, such as a plug-in hard disk or a smart memory card (Smart Media Card, SMC) equipped on the energy storage device 7. Secure Digital (SD) card, Flash Card, etc. Further, the memory 71 may also include both an internal storage unit of the energy storage device 7 and an external storage device. The memory 71 is used to store operating systems, application programs, boot loaders, data and other programs, such as program codes of the computer programs. The memory 71 can also be used to temporarily store data that has been output or is to be output.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on this understanding, this application can implement all or part of the processes in the methods of the above embodiments by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. The computer program When executed by a processor, the steps of each of the above method embodiments may be implemented. Wherein, the computer program includes computer program code, which may be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying computer program code to the camera device/terminal device, recording media, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. For example, U disk, mobile hard disk, magnetic disk or CD, etc. In some jurisdictions, subject to legislation and patent practice, computer-readable media may not be electrical carrier signals and telecommunications signals.

In the above embodiments, each embodiment is described with its own emphasis. For parts that are not detailed or documented in a certain embodiment, please refer to the relevant descriptions of other embodiments.

It should be understood that the methods and devices/systems disclosed in this application can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, for example, multiple units or components may be combined or can be integrated into another device, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.

Units described as separate components may or may not be physically separate, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units.

Integrated units may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as independent products. Based on this understanding, the essence of the technical solution of the present application, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a computer software product, and the computer software product is stored in a storage In the medium, the computer software product includes a number of instructions, which are used to cause a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage media may include but are not limited to: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application. should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

A maximum power tracking control method, applied to a photovoltaic system, the photovoltaic system includes a photovoltaic array, the method includes:

Obtaining the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling moment and the first output voltage corresponding to the first maximum output power;

Obtain the second maximum output power and the corresponding second output voltage of the first photovoltaic panel at the last sampling moment;

Obtain the third output voltage of the second photovoltaic panel at the last sampling moment;

Comparing the first maximum output power and the second maximum output power, when it is determined that no power jump occurs in the first maximum output power, according to the first output voltage, the second output voltage and the The third output voltage updates the voltage scanning range of the second photovoltaic panel;

Obtain the third maximum output power of the second photovoltaic panel within the voltage scanning range, and output the first maximum output power and the third maximum output power;

Wherein, the second photovoltaic panel is a photovoltaic panel other than the first photovoltaic panel in the photovoltaic array.
The method of claim 1, wherein before updating the voltage scanning range of the second photovoltaic panel according to the first output voltage, the second output voltage and the third output voltage, the The above methods also include:

Obtain the learning coefficient of the first photovoltaic panel at the current sampling moment;

The updating of the voltage scanning range of the second photovoltaic panel according to the first output voltage, the second output voltage and the third output voltage includes:

The lower limit of the voltage scanning range is calculated according to the first formula, which is expressed as:

Calculate the upper limit of the voltage scanning range according to the second formula, which is expressed as:

Where, x is the serial number of the photovoltaic panel in the photovoltaic array; n is the iteration coefficient at the sampling time, n≥1; U min is the lower limit of the voltage scanning range; U max is the The upper limit value; V max is the rated voltage of the photovoltaic panel; C n is the learning coefficient corresponding to the n-th sampling moment; V x-(n-1) is the number of the photovoltaic array except the first photovoltaic panel. The third output voltage corresponding to the maximum output power of the x-th photovoltaic panel at the n-1th sampling time; V 1-n is the maximum output power corresponding to the first photovoltaic panel at the n-th sampling time. The first output voltage; V 1-(n-1) is the second output voltage corresponding to the maximum output power of the first photovoltaic panel at the n-1th sampling time.
The method of claim 1, wherein after said comparing said first maximum output power and said second maximum output power, said method further comprises:

When the difference between the first maximum output power and the second maximum output power exceeds the preset threshold range, it is determined that a power jump occurs in the first maximum output power, and the standard voltage scanning range of the photovoltaic array is obtained. ;

Obtain the maximum power point of each photovoltaic panel in the photovoltaic array within the standard voltage scanning range;

The maximum power point of each photovoltaic panel within the standard voltage scanning range is used as the maximum output power of each photovoltaic panel at the current sampling time.
The method of claim 3, wherein after obtaining the maximum power point of each photovoltaic panel in the photovoltaic array within a standard voltage scanning range, the method further includes:

The standard voltage scanning range is used as the voltage scanning range of each photovoltaic panel in the photovoltaic array at the current sampling moment.
The method of claim 3, wherein after obtaining the maximum power point of each photovoltaic panel in the photovoltaic array within a standard voltage scanning range, the method further includes:

Update the learning coefficient of the first photovoltaic panel to an initial value.
The method of claim 1, wherein after obtaining the third maximum output power of the second photovoltaic panel within the voltage scanning range, the method further includes:

When the difference between the third maximum output power of any second photovoltaic panel in the photovoltaic array and the maximum output power of the second photovoltaic panel at the previous sampling moment exceeds a preset threshold range, it is determined that the When the second photovoltaic panel jumps, the maximum power point of each photovoltaic panel in the photovoltaic array within the standard voltage scanning range is obtained;

The maximum power point of each photovoltaic panel within the standard voltage scanning range is used as the maximum output power of each photovoltaic panel at the current sampling time.
The method of claim 1, wherein after outputting the first maximum output power and the third maximum output power, the method further includes:

The learning coefficient of the first photovoltaic panel is updated according to a preset gradient.
The method of claim 7, wherein updating the learning coefficient of the first photovoltaic panel according to a preset gradient includes:

Obtain the learning coefficient of the first photovoltaic panel;

When the learning coefficient of the first photovoltaic panel is greater than the minimum learning coefficient, the learning coefficient of the first photovoltaic panel is updated according to a preset gradient.
A photovoltaic system, including: an MPPT controller, a photovoltaic array and a voltage converter, the MPPT controller is connected to the photovoltaic array and the voltage converter;

The MPPT controller is used to obtain the first maximum output power of the first photovoltaic panel in the photovoltaic array at the current sampling moment and the first output voltage corresponding to the first maximum output power; obtain the first maximum output power of the first photovoltaic panel at the current sampling moment. The second maximum output power and the second output voltage at the last sampling moment; obtain the third output voltage of the second photovoltaic panel at the last sampling moment; compare the first maximum output power and the second maximum output power, at When it is determined that no power jump occurs in the first maximum output power, update the voltage scanning range of the second photovoltaic panel according to the first output voltage, the second output voltage and the third output voltage;

The MPPT controller is also used to obtain the third maximum output power of the second photovoltaic panel within the voltage scanning range, and output the first maximum output power and the third maximum output power to the voltage converter;

Wherein, the second photovoltaic panel is a photovoltaic panel other than the first photovoltaic panel in the photovoltaic array.
An energy storage device, the energy storage device is used to connect with a photovoltaic system, the photovoltaic system includes a photovoltaic array;

The energy storage device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any one of claims 1 to 8 is implemented. The steps of the maximum power tracking control method.