CN116613872B - Charging control method and system of photovoltaic energy storage system - Google Patents
Charging control method and system of photovoltaic energy storage system Download PDFInfo
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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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
- H02J7/35—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
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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
- H02J15/00—Systems for storing electric energy
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- 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
The application relates to the technical field of photovoltaic power generation and energy storage, in particular to a charging control method and system of a photovoltaic energy storage system. The photovoltaic energy storage system comprises a storage battery, and the method comprises the following steps: storing a plurality of pieces of sample data to obtain a data set, wherein the sample data are values of control factors during abnormal charging; calculating initial weights of all control factors in the data set according to a weight distribution algorithm; collecting real-time information of each control factor at the current moment; adjusting the initial weight of the control factors based on the real-time information to obtain the real-time weight of each control factor at the current moment; and adjusting a control factor corresponding to the maximum value of the real-time weight in response to the fact that the internal air pressure of the storage battery at the current moment is not smaller than the standard air pressure, so that the internal air pressure of the storage battery is reduced. Through the technical scheme of the application, the internal air pressure of the storage battery can be effectively and rapidly reduced, and the charging safety is ensured.
Description
Technical Field
The application relates to the technical field of photovoltaic power generation and energy storage, in particular to a charging control method and a charging control system of a photovoltaic energy storage system.
Background
With advances in photovoltaic power generation technology and cost reduction, many households are beginning to install solar panels to obtain clean, renewable energy sources; however, because the electric energy output by the solar panel has the characteristics of intermittence and uncertainty, it is difficult to provide a continuous and stable electric power supply for the load, so that the household energy storage system is generated, and the electric energy is stored or released through the household energy storage system, so that the continuous and stable electric power supply is realized; in this process, the household energy storage system needs to be constantly charged to store electric energy.
Currently, patent document with publication number CN109149746a discloses a control method of an energy storage converter, when a battery is in a charging process, the current capacity of the battery is obtained, and the charging mode of the battery is obtained according to the current capacity of the battery, so that the charging mode of the battery is controlled by the energy storage converter.
However, the method can control the charging current or voltage of the battery according to different periods of the battery to ensure the safe operation of the battery during charging, but in the photovoltaic power generation and energy storage, the factors influencing the charging safety of the battery in different periods are numerous and the influence degree is continuously changed, and at the moment, the charging safety of the photovoltaic energy storage system cannot be ensured by only controlling the charging current or voltage of the battery.
Disclosure of Invention
In order to solve the technical problems, the application provides a charging control method and a charging control system for a photovoltaic energy storage system, so that safety in a charging process of the photovoltaic energy storage system is improved.
According to a first aspect of the present application, there is provided a charge control method of a photovoltaic energy storage system, comprising: storing a plurality of pieces of sample data to obtain a data set, wherein the sample data is the value of a control factor during abnormal charging, the control factor comprises a long-time factor and a short-time factor, the long-time factor comprises temperature and light intensity, the short-time factor comprises charging voltage and charging current, and the abnormal charging is the moment when the internal air pressure of a storage battery is larger than standard air pressure; in the data set, calculating initial weights of all control factors according to a weight distribution algorithm, wherein the initial weights are used for reflecting the influence degree of the corresponding control factors on the internal air pressure of the storage battery; collecting real-time information of each control factor at the current moment, wherein the real-time information of the long-time factors comprises an instantaneous change rate and a long-time value, and the real-time information of the short-time factors comprises the instantaneous change rate and the short-time value; adjusting the initial weight of the control factors based on the real-time information to obtain the real-time weight of each control factor at the current moment; and adjusting a control factor corresponding to the maximum value of the real-time weight in response to the fact that the internal air pressure of the storage battery at the current moment is not smaller than the standard air pressure, so that the internal air pressure of the storage battery is reduced.
In one embodiment, the storing the plurality of pieces of sample data to obtain the data set includes: collecting the internal air pressure of the storage battery at any moment in the historical charging process of the photovoltaic energy storage system; in response to the internal air pressure being greater than the standard air pressure, collecting values of all control parameters at corresponding moments, wherein the values of all the control parameters correspond to sample data during abnormal charging; and storing all sample data during abnormal charging to obtain a data set.
In one embodiment, the weight distribution algorithm is an entropy weight method, a coefficient of variation method, or a CRITIC method.
In one embodiment, the weight distribution algorithm is a principal component analysis method, and the initial weight obtaining method includes: calculating the average value of all sample data in the data set to obtain an average sample; subtracting the average sample from all sample data to obtain a de-centralized data set; acquiring at least one principal component vector of the de-centralized data set and a corresponding characteristic value by using a PCA algorithm; constructing a principal component model of each principal component vector, wherein the principal component model is a linear combination of all control factors, a firstPrincipal component models corresponding to the principal component vectors satisfy the relation:
wherein ,respectively represent the 1 st control factor and the n th control factor, and n is the total number of the control factors,indicate->Group of nth control factors in principal component model corresponding to each principal component vectorCoefficient of integration (I)>Is->A principal component vector; for each principal component model, taking the duty ratio of the eigenvalue of the principal component vector corresponding to the principal component model in all eigenvalues as model weight; carrying out weighted summation on all principal component models according to the model weights to obtain a principal component fusion model, wherein the principal component fusion model comprises fusion coefficients of all control factors; the ratio of the fusion coefficient of one control factor to the sum of all fusion coefficients is taken as the initial weight of the control factor.
In one embodiment, the model weights satisfy the relationship:
wherein ,indicate->The principal component model corresponds to the eigenvalues of the principal component vector, < ->Indicate->The number of principal component models is K, which is the number of all principal component models, < ->Is->Model weights of the individual principal component models.
In one embodiment, the principal component fusion model satisfies the relationship:
wherein ,is->Principal component vector,/->Fusion vector for principal component(s),>is->Model weights of the individual principal component models, +.>The fusion coefficient of the nth control factor is the fusion coefficient of the nth control factor, wherein the fusion coefficient of the nth control factor meets the relation:
wherein ,is->And the combination coefficient of the nth control factor in the principal component model corresponding to each principal component vector.
In one embodiment, the collecting the real-time information of each control factor at the current moment includes: for a short-time factor, subtracting the value of the current moment from the value of the last adjacent moment to obtain an instantaneous change rate, and taking the value of the current moment as a short-time value, wherein the instantaneous change rate and the short-time value correspond to real-time information of the short-time factor at the current moment; for a long-time factor, collecting a time sequence in a set time window, subtracting the value of the current moment from the value of the last adjacent moment in the time sequence to obtain an instantaneous change rate, taking the average value of all values in the time sequence as a long-time value, wherein the instantaneous change rate and the long-time value correspond to real-time information of the long-time factor at the current moment; wherein the set time window includes the current time and a set number of times prior to the current time.
In one embodiment, the adjusting the initial weights of the control factors based on the real-time information to obtain the real-time weights of the control factors at the current time includes: acquiring a reference value of each control factor, wherein the reference value is an average value of each control factor during normal charging, and the normal charging is when the internal air pressure of the storage battery is not more than the standard air pressure; adjusting the initial weights of the control factors based on the reference value and the real-time information to obtain the real-time weights of the control factors at the current moment, wherein the real-time weights meet the relation:
wherein ,for the current time +.>First->Instantaneous rate of change of individual control factors, +.>For the current time +.>First->A long or short value of the individual control factor, < ->Is->Initial weight of individual control factors, +.>Is->Reference value of individual control factor,/->For the current time +.>First->Real-time weights of individual control factors.
In one embodiment, the charging voltage and the charging current are adjustable by PWM control; the temperature can be adjusted by a heat dissipation device; the light intensity can be adjusted by a shading device.
According to a second aspect of the present application, there is provided a charge control system for a photovoltaic energy storage system, comprising a processor and a memory, the memory storing computer program instructions which, when executed by the processor, implement a charge control method for a photovoltaic energy storage system according to the first aspect of the present application.
According to the technical scheme provided by the application, the initial weight is firstly distributed to each control factor according to the sample data in the historical charging process of the photovoltaic energy storage system, and then the initial weight is regulated according to the change state and the numerical state of the control factor at the current moment, so that the real-time weight of each control factor is obtained; when the internal air pressure of the storage battery is not less than the standard air pressure, the control factors corresponding to the maximum value of the real-time weight are preferentially regulated, so that the internal air pressure of the storage battery is effectively and rapidly reduced, and the charging safety is ensured.
Further, the control factors are divided into short-time factors and long-time factors according to the influence of the control factors on the charging state; for the short-time factor, determining the numerical state of the current moment according to the value of the current moment; for the long-time factor, determining the numerical state of the current moment according to the time sequence in the set time window; the adjusted real-time weight is more in line with the application scene, and the accuracy of charging control is improved.
Drawings
The above, as well as additional purposes, features, and advantages of exemplary embodiments of the present application will become readily apparent from the following detailed description when read in conjunction with the accompanying drawings. In the drawings, embodiments of the application are illustrated by way of example and not by way of limitation, and like reference numerals refer to similar or corresponding parts and in which:
FIG. 1 is a flow chart of a method of charge control of a photovoltaic energy storage system according to an embodiment of the present application;
fig. 2 is a block diagram of a charge control system of a photovoltaic energy storage system according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be understood that when the terms "first," "second," and the like are used in the claims, the specification and the drawings of the present application, they are used merely for distinguishing between different objects and not for describing a particular sequential order. The terms "comprises" and "comprising" when used in the specification and claims of the present application are taken to specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
According to a first aspect of the application, a method for controlling charging of a photovoltaic energy storage system is provided. The testing method can be applied to charge control of any photovoltaic energy storage system, and safety of the storage battery in the photovoltaic energy storage system during charging is guaranteed.
Fig. 1 is a flow chart of a method of controlling charging of a photovoltaic energy storage system according to an embodiment of the present application. As shown in fig. 1, the test method 100 includes steps S101 to S105, which are described in detail below.
S101, storing a plurality of pieces of sample data to obtain a data set, wherein the sample data are values of control factors during abnormal charging, the control factors comprise long-time factors and short-time factors, the long-time factors comprise temperature and light intensity, the short-time factors comprise charging voltage and charging current, and the abnormal charging is at a moment when the internal air pressure of a storage battery is larger than standard air pressure.
In one embodiment, the photovoltaic energy storage system comprises at least one storage battery, and the direct current output by the photovoltaic battery assembly charges the storage battery so as to store electric energy in the photovoltaic energy storage system. In the process of charging the storage battery, the internal air pressure of the storage battery directly determines the charging safety of the storage battery, and when the internal air pressure is greater than or equal to the limit air pressure, the storage battery can explode. The standard air pressure is the maximum air pressure in the safe charging process of the storage battery, namely, when the internal air pressure of the storage battery is not more than the standard air pressure, the state of the storage battery is represented as normal charging; when the internal air pressure of the storage battery is greater than the standard air pressure, the state of the storage battery is indicated to be abnormal charging; and when the internal air pressure of the battery is greater than or equal to the limit air pressure, the battery may explode. It is understood that the limit air pressure is greater than the standard air pressure, and the limit air pressure and the standard air pressure are preset.
Further, as the voltage of the direct current output by the photovoltaic battery pack is interfered by various external factors such as light intensity, temperature and the like, the control factors influencing the safe charging of the photovoltaic energy storage system are numerous. In the application, the temperature, the light intensity, the charging voltage and the charging current are used as control factors for influencing the safe charging of the photovoltaic energy storage system; further, since the charging voltage and the charging current can be changed instantaneously, the values of the charging voltage and the charging current in the historical time period do not affect the charging voltage and the charging current at the current moment, and the charging voltage and the charging current affect the charging state instantaneously, the charging voltage and the charging current are taken as short-time factors; the change rate of the light intensity and the temperature is slower, and the light intensity and the temperature in the historical time period are continuously accumulated, so that the light intensity and the temperature at the current moment are influenced, and the influence of the light intensity and the temperature on the charging state is accumulated along with the time, so that the light intensity and the temperature are taken as long-term factors.
In one embodiment, in order to obtain the initial weight of the control factor, the value of each control factor during normal charging and abnormal charging of the storage battery needs to be collected, which is described in detail below. The storing the plurality of pieces of sample data to obtain the data set includes: collecting the internal air pressure of the storage battery at any moment in the historical charging process of the photovoltaic energy storage system; in response to the internal air pressure being greater than the standard air pressure, collecting values of all control parameters at corresponding moments, wherein the values of all the control parameters correspond to sample data during abnormal charging; and storing all sample data during abnormal charging to obtain a data set.
Thus, a data set is obtained, wherein the data set comprises a plurality of pieces of sample data during abnormal charging, and one piece of sample data comprises values of all control factors.
S102, in the data set, calculating initial weights of all control factors according to a weight distribution algorithm, wherein the initial weights are used for reflecting the influence degree of the corresponding control factors on the internal air pressure of the storage battery.
In one embodiment, the weight distribution algorithm is an entropy weight method, a principal component analysis method, a coefficient of variation method, or a CRITIC method.
As an example, the weight distribution algorithm is a principal component analysis method, and the initial weight obtaining method includes: calculating the average value of all sample data in the data set to obtain an average sample; subtracting the average sample from all sample data to obtain a de-centralized data set; acquiring at least one principal component vector of the de-centralized data set and a corresponding characteristic value by using a PCA algorithm; constructing a principal component model of each principal component vector, wherein the principal component model is a linear combination of all control factors; for each principal component model, taking the duty ratio of the eigenvalue of the principal component vector corresponding to the principal component model in all eigenvalues as model weight; carrying out weighted summation on all principal component models according to the model weights to obtain a principal component fusion model, wherein the principal component fusion model comprises fusion coefficients of all control factors; the ratio of the fusion coefficient of one control factor to the sum of all fusion coefficients is taken as the initial weight of the control factor.
The PCA algorithm (Principal Component Analysis) is a principal component analysis method, and can acquire a plurality of principal component vectors of a data set, wherein the principal component vectors are orthogonal in pairs; each principal component vector corresponds to a characteristic value that reflects the amount of information in the dataset contained on the principal component vector, the larger the amount of information, the larger the characteristic value.
Wherein, the firstPrincipal component models corresponding to the principal component vectors satisfy the relation:
wherein ,respectively represent the 1 st control factor and the n th control factor, and n is the total number of the control factors,indicate->The combination coefficient of the nth control factor in the principal component model corresponding to each principal component vector,>is->And a principal component vector. The model weights satisfy the relationship:
wherein ,indicate->The principal component model corresponds to the eigenvalues of the principal component vector, < ->Indicate->The number of principal component models is K, which is the number of all principal component models, < ->Is->Model weights of the individual principal component models. The principal component fusion model satisfies the relationship:
wherein ,is->Principal component vector,/->Fusion vector for principal component(s),>is->Model weights of the individual principal component models, +.>The fusion coefficient of the nth control factor is the fusion coefficient of the nth control factor, wherein the fusion coefficient of the nth control factor meets the relation:
wherein ,is->And the combination coefficient of the nth control factor in the principal component model corresponding to each principal component vector.
Specifically, the initial weight of the x-th control factor satisfies the relationship:
wherein ,fusion coefficient for the b-th control factor, < ->Is the sum of all fusion coefficients->Fusion coefficient for the xth control factor, +.>Is the initial weight of the xth control factor.
Thus, the initial weight of each control factor is obtained according to the plurality of pieces of sample data acquired in the historical time, and the initial weight reflects the influence degree of the control factors on the internal air pressure of the storage battery in the charging process of the photovoltaic energy storage system.
S103, collecting real-time information of each control factor at the current moment, wherein the real-time information of the long-time factors comprises an instantaneous change rate and a long-time value, and the real-time information of the short-time factors comprises the instantaneous change rate and a short-time value.
In one embodiment, the initial weight reflects the influence degree of the control factor on the internal air pressure of the storage battery in the history time; in order to realize accurate control during charging of the photovoltaic energy storage system, real-time information of each control factor at the current moment also needs to be obtained, and the method is specifically described below. The step of collecting the real-time information of each control factor at the current moment comprises the following steps: for a short-time factor, subtracting the value of the current moment from the value of the last adjacent moment to obtain an instantaneous change rate, and taking the value of the current moment as a short-time value, wherein the instantaneous change rate and the short-time value correspond to real-time information of the short-time factor at the current moment; for a long-time factor, collecting a time sequence in a set time window, subtracting the value of the current moment from the value of the last adjacent moment in the time sequence to obtain an instantaneous change rate, taking the average value of all values in the time sequence as a long-time value, wherein the instantaneous change rate and the long-time value correspond to real-time information of the long-time factor at the current moment; wherein the set time window includes the current time and a set number of times prior to the current time. For example, the current time is recorded asThe set number is set to 4, said set time window comprises + ->、/>、/>、/>、/>And 5 times.
The instantaneous change rate may reflect a change state of the short-time factor and the long-time factor at the current time, the short-time value may reflect a numerical state of the short-time factor at the current time, and the long-time factor may reflect a numerical state of the long-time factor at the current time. It can be understood that the short-time factors (i.e., the charging voltage and the charging current) are instantaneously changeable, and the influence thereof on the charging state is not accumulated with time, and the numerical state at the current moment can be determined only according to the value at the current moment; the long-term factors (i.e. temperature and illumination) cannot be changed instantaneously and their effects on the state of charge are accumulated over time, so that the state of the value at the current moment needs to be determined according to the time sequence within the set time window.
Therefore, the real-time information of each control factor at the current moment is obtained, the change state and the numerical state of each control factor at the current moment can be accurately reflected, a data basis is provided for realizing accurate control during charging of the photovoltaic energy storage system, and charging safety is ensured.
S104, adjusting the initial weight of the control factors based on the real-time information to acquire the real-time weight of each control factor at the current moment.
In one embodiment, the initial weight is obtained according to sample data in historical time, and can comprehensively reflect the influence degree of each control factor on the internal air pressure of the storage battery during charging; in the process of charging control, in order to realize accurate control at the current moment, the initial weight of the control factors is also required to be adjusted based on the real-time information so as to acquire the real-time weight of each control factor at the current moment.
Specifically, the adjusting the initial weights of the control factors based on the real-time information to obtain the real-time weights of the control factors at the current moment includes: acquiring a reference value of each control factor, wherein the reference value is an average value of each control factor during normal charging, and the normal charging is when the internal air pressure of the storage battery is not more than the standard air pressure; adjusting the initial weights of the control factors based on the reference value and the real-time information to obtain the real-time weights of the control factors at the current moment, wherein the real-time weights meet the relation:
wherein ,for the current time +.>First->Instantaneous rate of change of individual control factors, +.>For the current time +.>First->A long or short value of the individual control factor, < ->Is->Initial weight of individual control factors, +.>Is->Reference value of individual control factor,/->For the current time +.>First->Real-time weights of individual control factors.
It will be appreciated that when the firstWhen the individual control factors are short-term factors, the individual control factors are +.>For the current time +.>First->Short duration values of individual control factors; when->When the control factor is a long-term factor, the control factor is +.>For the current time +.>First->A long time value of each control factor.
Thus, the initial weight is adjusted according to the real-time information of each control factor, the real-time weight of each control factor at the current moment is obtained, the accuracy and the instantaneity of charging control are ensured, and the charging safety is ensured.
And S105, adjusting a control factor corresponding to the maximum value of the real-time weight in response to the fact that the internal air pressure of the storage battery at the current moment is not smaller than the standard air pressure, so that the internal air pressure of the storage battery is reduced.
In one embodiment, in response to the internal air pressure of the storage battery at the current moment not being less than the standard air pressure, the current moment is in an abnormal charging state, and in order to ensure charging safety, a control factor needs to be adjusted so that the internal air pressure of the storage battery at the current moment is less than or equal to the standard air pressure.
The real-time weight of each control factor at the current moment can reflect the influence degree of each control factor on the internal air pressure of the storage battery, and the control factor corresponding to the maximum value of the real-time weight is preferably regulated in order to effectively and rapidly reduce the internal air pressure of the storage battery.
Wherein, the adjustment of the charging voltage and the charging current can be realized through PWM control; the temperature can be adjusted through the heat abstractor, and the light intensity can be adjusted through the shade. For example, the heat dissipating device may be a fan, and the light shielding device may be a light shielding plate.
Therefore, when the storage battery in the photovoltaic energy storage system is in an abnormal charging state, the control factor corresponding to the maximum value of the real-time weight is preferably regulated, so that the internal air pressure of the storage battery is effectively and rapidly reduced, and the charging safety is ensured.
Technical principles and implementation details of the charge control method of the photovoltaic energy storage system of the present application are described above by specific embodiments. According to the technical scheme provided by the application, the initial weight is firstly distributed to each control factor according to the sample data in the historical charging process of the photovoltaic energy storage system, and then the initial weight is regulated according to the change state and the numerical state of the control factor at the current moment, so that the real-time weight of each control factor is obtained; when the internal air pressure of the storage battery is not less than the standard air pressure, the control factors corresponding to the maximum value of the real-time weight are preferentially regulated, so that the internal air pressure of the storage battery is effectively and rapidly reduced, and the charging safety is ensured.
Further, the control factors are divided into short-time factors and long-time factors according to the influence of the control factors on the charging state; for the short-time factor, determining the numerical state of the current moment according to the value of the current moment; for the long-time factor, determining the numerical state of the current moment according to the time sequence in the set time window; the adjusted real-time weight is more in line with the application scene, and the accuracy of charging control is improved.
According to a second aspect of the present application, the present application further provides a charging control system of a photovoltaic energy storage system. Fig. 2 is a block diagram of a charge control system of a photovoltaic energy storage system according to an embodiment of the present application. As shown in fig. 2, the apparatus 50 comprises a processor and a memory storing computer program instructions which, when executed by the processor, implement a method of controlling charging of a photovoltaic energy storage system according to the first aspect of the present application. The device also includes other components, such as a communication bus and a communication interface, which are well known to those skilled in the art, and the arrangement and function of which are known in the art and therefore not described in detail herein.
In the context of this patent, the foregoing memory may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, the computer readable storage medium may be any suitable magnetic or magneto-optical storage medium, such as, for example, resistance change Memory RRAM (Resistive Random Access Memory), dynamic Random Access Memory DRAM (Dynamic Random Access Memory), static Random Access Memory SRAM (Static Random-Access Memory), enhanced dynamic Random Access Memory EDRAM (Enhanced Dynamic Random Access Memory), high-Bandwidth Memory HBM (High-Bandwidth Memory), hybrid storage cube HMC (Hybrid Memory Cube), etc., or any other medium that may be used to store the desired information and that may be accessed by an application, a module, or both. Any such computer storage media may be part of, or accessible by, or connectable to, the device. Any of the applications or modules described herein may be implemented using computer-readable/executable instructions that may be stored or otherwise maintained by such computer-readable media.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the claims. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (9)
1. A method of charge control of a photovoltaic energy storage system comprising at least one battery, the method comprising:
storing a plurality of pieces of sample data to obtain a data set, wherein the sample data is the value of a control factor during abnormal charging, the control factor comprises a long-time factor and a short-time factor, the long-time factor comprises temperature and light intensity, the short-time factor comprises charging voltage and charging current, and the abnormal charging is the moment when the internal air pressure of a storage battery is larger than standard air pressure;
in the data set, calculating initial weights of all control factors according to a weight distribution algorithm, wherein the initial weights are used for reflecting the influence degree of the corresponding control factors on the internal air pressure of the storage battery;
collecting real-time information of each control factor at the current moment, wherein the real-time information of the long-time factors comprises an instantaneous change rate and a long-time value, and the real-time information of the short-time factors comprises the instantaneous change rate and the short-time value;
adjusting the initial weight of the control factors based on the real-time information to obtain the real-time weight of each control factor at the current moment;
responding to the condition that the internal air pressure of the storage battery at the current moment is not less than the standard air pressure, and adjusting a control factor corresponding to the maximum value of the real-time weight to reduce the internal air pressure of the storage battery;
the step of collecting the real-time information of each control factor at the current moment comprises the following steps:
for a short-time factor, subtracting the value of the current moment from the value of the last adjacent moment to obtain an instantaneous change rate, and taking the value of the current moment as a short-time value, wherein the instantaneous change rate and the short-time value correspond to real-time information of the short-time factor at the current moment;
for a long-time factor, collecting a time sequence in a set time window, subtracting the value of the current moment from the value of the last adjacent moment in the time sequence to obtain an instantaneous change rate, taking the average value of all values in the time sequence as a long-time value, wherein the instantaneous change rate and the long-time value correspond to real-time information of the long-time factor at the current moment;
wherein the set time window includes the current time and a set number of times prior to the current time.
2. The method of claim 1, wherein storing the plurality of sample data to obtain the data set comprises:
collecting the internal air pressure of the storage battery at any moment in the historical charging process of the photovoltaic energy storage system;
in response to the internal air pressure being greater than the standard air pressure, collecting values of all control parameters at corresponding moments, wherein the values of all the control parameters correspond to sample data during abnormal charging;
and storing all sample data during abnormal charging to obtain a data set.
3. The method for controlling charging of a photovoltaic energy storage system according to claim 1, wherein the weight distribution algorithm is an entropy weight method, a coefficient of variation method or a CRITIC method.
4. The method for controlling charging of a photovoltaic energy storage system according to claim 1, wherein the weight distribution algorithm is a principal component analysis method, and the method for obtaining the initial weight comprises:
calculating the average value of all sample data in the data set to obtain an average sample;
subtracting the average sample from all sample data to obtain a de-centralized data set;
acquiring at least one principal component vector of the de-centralized data set and a corresponding characteristic value by using a PCA algorithm;
constructing a principal component model of each principal component vector, wherein the principal component model is a linear combination of all control factors, a firstPrincipal component models corresponding to the principal component vectors satisfy the relation:
wherein ,represents the 1 st control factor and the n th control factor, respectively, and n is the total number of control factors, +.>Indicate->The combination coefficient of the nth control factor in the principal component model corresponding to each principal component vector,>is->A principal component vector;
for each principal component model, taking the duty ratio of the eigenvalue of the principal component vector corresponding to the principal component model in all eigenvalues as model weight;
carrying out weighted summation on all principal component models according to the model weights to obtain a principal component fusion model, wherein the principal component fusion model comprises fusion coefficients of all control factors;
the ratio of the fusion coefficient of one control factor to the sum of all fusion coefficients is taken as the initial weight of the control factor.
5. The method of claim 4, wherein the model weights satisfy the relationship:
wherein ,indicate->The principal component model corresponds to the eigenvalues of the principal component vector, < ->Indicate->The number of principal component models is K, which is the number of all principal component models, < ->Is->Model weights of the individual principal component models.
6. The method for controlling charging of a photovoltaic energy storage system according to claim 5, wherein the principal component fusion model satisfies the relationship:
wherein ,is->Principal component vector,/->Fusion vector for principal component(s),>is->Model weights of the individual principal component models, +.>The fusion coefficient of the nth control factor is the fusion coefficient of the nth control factor, wherein the fusion coefficient of the nth control factor meets the relation:
wherein ,is->And the combination coefficient of the nth control factor in the principal component model corresponding to each principal component vector.
7. The method for controlling charging of a photovoltaic energy storage system according to claim 1, wherein the adjusting the initial weights of the control factors based on the real-time information to obtain the real-time weights of the control factors at the current time comprises:
acquiring a reference value of each control factor, wherein the reference value is an average value of each control factor during normal charging, and the normal charging is when the internal air pressure of the storage battery is not more than the standard air pressure;
adjusting the initial weights of the control factors based on the reference value and the real-time information to obtain the real-time weights of the control factors at the current moment, wherein the real-time weights meet the relation:
wherein ,for the current time +.>First->Instantaneous rate of change of individual control factors, +.>For the current time +.>First->A long or short value of the individual control factor, < ->Is->Initial weight of individual control factors, +.>Is->Reference value of individual control factor,/->For the current time +.>First->Real-time weights of individual control factors.
8. The method of claim 1, wherein the charging voltage and the charging current are adjustable by PWM control; the temperature can be adjusted by a heat dissipation device; the light intensity can be adjusted by a shading device.
9. A charge control system of a photovoltaic energy storage system, comprising a processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement a charge control method of a photovoltaic energy storage system according to any one of claims 1 to 8.
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