Energy storage resource regulation and control method and device and computer equipment

Abstract

The invention relates to an energy storage resource regulation and control method and device and computer equipment, and belongs to the technical field of resource regulation and control, and the method comprises the steps: obtaining a first related parameter set, and inputting the first related parameter set into a pre-constructed target electricity consumption evaluation model to determine the electricity consumption required in a future time period; acquiring a first environment parameter, and determining a first generating capacity fluctuation probability according to the first environment parameter; based on the first generating capacity fluctuation probability, generating capacity in a future time period is determined; and determining the electricity price in the future time period, and performing charging or discharging regulation and control on the energy storage equipment according to the electricity price in the future time period, the generating capacity in the future time period and the required electricity consumption in the future time period, thereby improving the resource utilization efficiency while improving the dynamic response capability of the power grid.

Description

Technical Field

[0001] The present application relates to the technical field of resource regulation, and in particular to a method, apparatus, and computer equipment for regulating energy storage resources. Background Art

[0002] With the transformation of energy structure and the intelligent development of power systems, the scale of power grids continues to expand, and new power resources such as distributed energy (such as photovoltaics and wind power) and energy storage systems are connected in large quantities, making the operating environment of power grids increasingly complex. Traditional energy storage resource control methods are mainly based on centralized scheduling and static models, which are difficult to adapt to the volatility and uncertainty under the access of a high proportion of renewable energy, resulting in low control efficiency, delayed response, and even causing stability problems of energy storage equipment.

[0003] In existing technologies, energy storage resource regulation typically relies on manual experience or offline optimization algorithms, such as load distribution based on fixed thresholds or simple priority scheduling strategies. These methods lack the ability to dynamically perceive real-time operating data and cannot effectively respond to sudden load changes or the random output of distributed resources. In addition, traditional regulation systems often use isolated control modules, and lack coordination between subsystems, resulting in low resource utilization and increased redundant configurations. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, device and computer equipment for regulating energy storage resources that can improve the dynamic response capability and resource utilization efficiency of the power grid in order to address the above technical problems.

[0005] In a first aspect, a method for regulating energy storage resources is provided, the method comprising: Obtaining a first set of relevant parameters, and inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the required power consumption in a future time period; Acquiring a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining power generation in a future time period based on the first power generation fluctuation probability; The electricity price in a future time period is determined, and the charging or discharging of the energy storage device is regulated based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0006] Optionally, before obtaining the first related parameter set, the method further includes: Constructing the target electricity consumption evaluation model.

[0007] Optionally, constructing the target power consumption evaluation model includes: Obtaining a second set of relevant parameters; preprocessing the second relevant parameter set to obtain a third relevant parameter set; Based on the third relevant parameter set, the constructed initial electricity consumption evaluation model is trained and tested to obtain the target electricity consumption evaluation model, and the model parameters of the target electricity consumption evaluation model are obtained by training the model parameters of the initial electricity consumption evaluation model based on the third relevant parameter set.

[0008] Optionally, preprocessing the second relevant parameter set to obtain a third relevant parameter set includes: performing data cleaning on the second relevant parameter set to obtain cleaned parameters; Normalizing the cleaned parameters to obtain normalized parameters; The normalization parameters are defined as the third correlation parameter set.

[0009] Optionally, after obtaining the third related parameter set, the method further includes: Classifying and saving the parameters in the third related parameter set; According to the preset ratio, the classified parameters are divided into training set and test set.

[0010] Optionally, the third relevant parameter set includes at least electrical parameters, second environmental parameters, and electricity prices. Based on the third relevant parameter set, a pre-built initial electricity consumption evaluation model is trained and tested to obtain a target electricity consumption evaluation model, including: determining power consumption within a target time period based on the electrical parameters; Acquire a plurality of second environmental parameters that affect power consumption fluctuations, and determine a second power consumption fluctuation probability based on the second environmental parameters; determining a third power consumption fluctuation probability based on the electricity price; Determining the initial power consumption evaluation model based on the power consumption within the target time period, the third power consumption fluctuation probability, and the second power consumption fluctuation probability; Training the initial power consumption evaluation model based on the training set, and testing the trained initial power consumption evaluation model using the test set; In response to the test result meeting the preset standard, the target power consumption evaluation model is output.

[0011] Optionally, determining the power generation in a future time period based on the first power generation fluctuation probability includes: According to the first power generation fluctuation probability, based on , determine the power generation in the future time period; in, Indicates power generation equipment i In the time periodt of power generation, i Indicates the identification of power generation equipment. t Indicates the time period identifier, represents the second adjustable parameter, Indicates that the power generation can be controlled. represents the number of time periods, represents the regression coefficient of the power generation variable, express Fluctuating power generation within a time period, Indicates the time period identifier, Indicates the number of the first environment parameters, represents the regression coefficient of the first environmental parameter, Indicates the c The probability that the first environmental parameter affects the fluctuation of power generation, c Indicates the first environmental parameter identifier, Indicates the c Assign a value to the impact degree of the first environmental parameter, represents the second random error term.

[0012] Optionally, regulating the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period includes: Determine whether to perform charge or discharge regulation based on the objective function and constraints, wherein the objective function includes: ; The constraints include: Supply and demand balance constraints: ; Power generation equipment constraints: ; Energy storage device constraints, including charge and discharge power constraints, power dynamics, and capacity constraints, where: Charge and discharge power constraints: ; Power dynamics: ; Capacity constraints: ; Electrical equipment constraints: ; Priority constraints: ; Line transmission constraints: ; in, H represents the calculated value of the objective function, T represents a set of time periods, I Represents a collection of power generation equipment, J Represents a collection of electrical equipment. K Represents a collection of energy storage devices, L Represents a grid node or line, Indicates the time period t The electricity price at that time, t Indicates the time period identifier, Indicates the time period t The power purchased from the grid, Indicates power generation equipment i The unit cost of electricity generation, i Indicates the identification of power generation equipment. Indicates power generation equipment i In the time period t of power generation, Indicates electrical equipment j The priority weight coefficient, j Indicates the identification of electrical equipment. Indicates electrical equipment j In the time period t The required electricity consumption, Indicates the time period t For electrical equipment j The actual power supply, Energy storage equipment k In the time period t The remaining power, k Indicates the energy storage device identification. To prevent simultaneous charging and discharging, Indicates electrical equipment j In the time period t Whether it is powered, Indicates the highest priority electrical device set, Represents energy storage devices k In the time period t The charging power and discharging power, Respectively represent power generation equipment i In the time period t The upper and lower limits of power generation, Represents energy storage devices k The discharge efficiency and charging efficiency, Represents energy storage devices k The lower and upper capacity limits, Represents energy storage devices kThe upper limit of charging power and the upper limit of discharging power, Indicates the upper limit of the transmission capacity of the grid node or line, Respectively indicate connection Power generation equipment and power consumption equipment on the site; In response to the calculated value of the objective function being less than a first preset threshold, charging the energy storage device; In response to the calculated value of the objective function being greater than a second preset threshold, the energy storage device is discharged.

[0013] Determining whether to perform charging or discharging control In a second aspect, a device for regulating energy storage resources is provided, the device comprising: a first determination module, configured to obtain a first set of relevant parameters and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the required power consumption in a future time period; a second determining module, configured to obtain a first environmental parameter and determine a first power generation fluctuation probability according to the first environmental parameter; a third determining module, configured to determine power generation in a future time period based on the first power generation fluctuation probability; The control module is used to determine the electricity price in a future time period and control the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period and the required power consumption in the future time period.

[0014] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are performed: Obtaining a first set of relevant parameters, and inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the required power consumption in a future time period; Acquiring a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining power generation in a future time period based on the first power generation fluctuation probability; The electricity price in a future time period is determined, and the charging or discharging of the energy storage device is regulated based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0015] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Obtaining a first set of relevant parameters, and inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the required power consumption in a future time period; Acquiring a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining power generation in a future time period based on the first power generation fluctuation probability; The electricity price in a future time period is determined, and the charging or discharging of the energy storage device is regulated based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0016] In a fifth aspect, a computer program product is provided, the computer program product comprising a computer program, wherein when the computer program is executed by a processor, the following steps are implemented: Obtaining a first set of relevant parameters, and inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the required power consumption in a future time period; Acquiring a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining power generation in a future time period based on the first power generation fluctuation probability; The electricity price in a future time period is determined, and the charging or discharging of the energy storage device is regulated based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0017] The above-mentioned energy storage resource regulation method, device and computer equipment, the method includes: obtaining a first set of relevant parameters, inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the required power consumption in a future time period; obtaining a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining the power generation in a future time period based on the first power generation fluctuation probability; determining the electricity price in the future time period, and regulating the charging or discharging of the energy storage device based on the electricity price in the future time period, the power generation in the future time period and the required power consumption in the future time period. This application can improve resource utilization efficiency while improving the dynamic response capability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is an application environment diagram of the energy storage resource control method in one embodiment; Figure 2Schematic diagram of a flow chart of a method for regulating energy storage resources in one embodiment; Figure 3 This is a structural block diagram of an energy storage resource control device in one embodiment; Figure 4 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0020] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] It should be understood that in the description of this application, unless the context clearly requires otherwise, words such as "include", "comprises", and the like throughout the specification should be interpreted as inclusive rather than exclusive or exhaustive; that is, as "including but not limited to".

[0022] It should also be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" is two or more.

[0023] It should be noted that the terms "S1", "S2", etc. are used only for the purpose of describing the steps and do not specifically refer to the order or sequence, nor are they used to limit this application. They are merely for the convenience of describing the method of this application and should not be understood as indicating the order of the steps. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0024] The energy storage resource control method provided in this application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with a data processing platform provided on the server 104 via a network. The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0025] In one embodiment, Figure 2 As shown, a method for regulating energy storage resources is provided, which is applied to Figure 1 The following steps are used as an example to illustrate the terminal in the figure: S1: Obtain a first set of relevant parameters, and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the power consumption required in a future time period.

[0026] In some specific implementations, before obtaining the first related parameter set, the method further includes: Constructing the target electricity consumption evaluation model.

[0027] In some specific implementations, constructing the target power consumption evaluation model includes: Obtaining a second set of relevant parameters that affect energy storage resource regulation in the target region during different historical time periods, the second set of relevant parameters including at least electrical parameters, environmental parameters, and electricity prices; preprocessing the second relevant parameter set to obtain a third relevant parameter set; Based on the third relevant parameter set, the pre-built initial electricity consumption evaluation model is trained and tested to obtain the target electricity consumption evaluation model, and the model parameters of the target electricity consumption evaluation model are obtained by training the model parameters of the initial electricity consumption evaluation model based on the third relevant parameter set.

[0028] In some specific implementations, preprocessing the second set of relevant parameters to obtain a third set of relevant parameters includes: Performing data cleaning on the second related parameter set to obtain cleaned parameters, wherein the data cleaning method is a commonly used method and the specific process is not repeated here; The cleaned parameters are normalized to obtain normalized parameters, which are defined as the third related parameter set. The normalization method is a commonly used method, and the specific process will not be repeated here.

[0029] In some specific implementations, after obtaining the third set of related parameters, the method further includes: The parameters in the third related parameter set are classified and saved, and a classification tag value corresponding to each classification category is determined, wherein the classification tag value can represent the data attributes included in each category. For example, if 1 is represented as an environmental parameter, the classification tag value is 1, and so on. By classifying, saving, and marking the parameters, parameters of different categories can be quickly extracted in the subsequent step, thereby improving operation efficiency; The classified parameters are divided into a training set and a test set according to a preset ratio, wherein the preset ratio can be set according to actual needs, such as 8:2.

[0030] It should be noted that the training set is used to train the pre-built initial electricity consumption evaluation model, and the test set is used to test the pre-built initial electricity consumption evaluation model.

[0031] In some specific implementations, based on the third set of relevant parameters, training and testing the pre-built initial power consumption evaluation model to obtain the target power consumption evaluation model includes: Based on the electrical parameters, determining the power consumption within a target time period, wherein the target time period refers to the next time period corresponding to the current time period, and the power consumption can be determined by comprehensive calculation based on parameters such as current, voltage, and time; Obtain multiple secondary environmental parameters that affect power consumption fluctuations , such as temperature, humidity, etc., according to the second environmental parameter, determine the second power consumption fluctuation probability , where the probability and value are 1, where there is a mapping relationship between the second environmental parameter and the second power consumption fluctuation probability, the mapping relationship is determined through multiple experiments, for example, when the temperature rises from 25 degrees Celsius to 35 degrees Celsius, some users need to turn on cooling equipment such as air conditioners, and the probability of power consumption fluctuation is 50%; when the humidity rises from 80% to 95%, some users need to turn on dehumidification equipment, and the probability of power consumption fluctuation is 10%; when the temperature drops from 25 degrees Celsius to 10 degrees Celsius, some users need to turn on heating equipment such as air conditioners, and the probability of power consumption fluctuation is 35%, and so on, no longer repeated; Based on the electricity price, determine the third power consumption fluctuation probability , that is, based on the fluctuation of the electricity price, determine the probability that the electricity price in the target time period affects the fluctuation of electricity consumption, wherein the probability sum value is 1, wherein there is a mapping relationship between the electricity price and the third electricity consumption fluctuation probability, and the mapping relationship is determined through multiple experiments. For example, when the current time is in the valley, such as 22:00, the valley electricity price is adopted. At this time, users are more willing to start electrical equipment, such as charging electric vehicles and starting air conditioners. At this time, the third electricity consumption fluctuation probability is 60%. When the current time is in the valley, such as 3:00, the valley electricity price is adopted. At this time, more users are in a resting state, and the number of electrical equipment started becomes less. Its fluctuation probability is 20%. And so on, no further details are given. Determining the initial power consumption evaluation model based on the power consumption within the target time period, the third power consumption fluctuation probability, and the second power consumption fluctuation probability; Training the initial power consumption evaluation model based on the training set, and testing the trained initial power consumption evaluation model using the test set; In response to the test result meeting the preset standard, the target power consumption evaluation model is output, wherein the preset standard may be that the evaluation accuracy is greater than a preset value, and the preset value can be set according to actual needs, such as 95%. The expression of the target power consumption evaluation model includes: ; in, Indicates the time period t The electricity consumption inside t Indicates the time period identifier, represents the first adjustable parameter, represents the regression coefficient of the electricity consumption variable, represents the first random error term, express The power consumption during the time period, Indicates the time period identifier, represents the number of time periods, Indicates the number of second environment parameters, represents the regression coefficient of the second environmental parameter, Indicates the b The probability that a second environmental parameter affects the fluctuation of electricity consumption, b Indicates the second environment parameter identifier, Indicates the b Assign a value to the impact degree of the second environmental parameter, s represents the quantity of electricity price, represents the regression coefficient of electricity price, No. r The probability that individual electricity prices will affect electricity consumption fluctuations, Indicates the r Assign a value to the impact degree of electricity price, r Indicates the electricity price identifier.

[0032] It should be noted that the first set of relevant parameters includes at least electrical parameters, environmental parameters and electricity prices. The target area may refer to a town or some areas divided according to actual needs, such as Shanghai. The time period may refer to a peak-valley time-sharing period or a peak period and a valley period of electricity consumption. The time period specifically includes a time step that can be set according to actual needs. Electrical parameters may include parameters such as voltage, current, power, frequency and efficiency. Environmental parameters may include temperature, humidity, etc. The electricity price includes the electricity price of the peak-valley time period. For example, the peak-valley time-sharing electricity price in Shanghai includes: Peak period: from 6:00 to 22:00 every day, the electricity price is 0.641 yuan per kilowatt-hour (including Including renewable energy electricity price surcharge of 0.1 cents per kilowatt-hour), off-peak period: from 22:00 to 6:00 the next day, the electricity price is about 0.331 yuan per kilowatt-hour, etc. Among them, the methods for obtaining the above data are all commonly used methods, and the specific acquisition process will not be repeated here. The preprocessing methods generally include data cleaning and data conversion, among which data cleaning includes removing duplicate values, processing missing values, processing outliers, etc., such as using the mean or median to fill missing values, or estimating through interpolation methods. Data conversion includes converting the data to make it suitable for specific analysis methods, such as normalization / standardization, etc. The data conversion method used in this application is normalization processing. S2: Acquire a first environmental parameter, and determine a first power generation fluctuation probability according to the first environmental parameter.

[0033] S3: Determine the power generation in a future time period based on the first power generation fluctuation probability.

[0034] It should be noted that the above steps specifically include: Obtain multiple first environmental parameters that affect power generation fluctuations in the future time period , such as temperature, typhoon, rainstorm and solar radiation intensity, etc. This data can be obtained through weather forecast and other means, and the probability of each first environmental parameter affecting the power generation fluctuation is determined as , that is, the first power generation fluctuation probability, wherein there is a mapping relationship between the first environmental parameter and the first power generation fluctuation probability, and the mapping relationship is determined through multiple experiments. For example, when the temperature rises from 25 degrees Celsius to 35 degrees Celsius, the efficiency of the photovoltaic module will decrease by about -0.35% / ℃, and its power generation fluctuation probability is 3.5%. When heavy rain occurs, the transmission facilities are damaged or the power generation of new energy such as photovoltaics is small, and its power generation fluctuation probability is 40%. And so on, no further details are given. Combining the first power generation fluctuation probability and , determine the power generation in the future time period; in, Indicates power generation equipment i In the time period t of power generation, iIndicates the identification of power generation equipment. t Indicates the time period identifier, represents the second adjustable parameter, Indicates that the power generation can be controlled. represents the number of time periods, represents the regression coefficient of the power generation variable, express Fluctuating power generation within a time period, Indicates the time period identifier, Indicates the number of the first environment parameters, represents the regression coefficient of the first environmental parameter, Indicates the c The probability that the first environmental parameter affects the fluctuation of power generation, c Indicates the first environmental parameter identifier, Indicates the c Assign a value to the impact degree of the first environmental parameter, Represents the second random error term, wherein the above-mentioned environmental parameter influence degree assignments can be determined through multiple experiments. For example, if the temperature among the second environmental parameters has a higher influence on electricity consumption, then a higher value is assigned. If the levels are low, medium, and high, the assigned values ​​are 1, 3, and 5 respectively, then the temperature influence degree is assigned a value of 5. For example, if the impact of new energy power generation on power generation is medium, if the levels are low, medium, and high, the assigned values ​​are 2, 4, and 6 respectively, then the impact degree of new energy power generation is assigned a value of 4. The controllable power generation is the power generation obtained by traditional means, such as power generation by burning coal, oil, etc. Fluctuating power generation refers to the power generation determined by renewable energy methods, such as solar power and wind power generation.

[0035] S4: Determine the electricity price in a future time period, and regulate the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0036] It should be noted that the future time period is the time period next to the current time period.

[0037] In some specific embodiments, an electricity price in a future time period is determined, and charging or discharging of the energy storage device is regulated based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period: Determine whether to perform charge or discharge regulation based on the objective function and constraints, wherein the objective function includes: ; The constraints include: Supply and demand balance constraints: ; Power generation equipment constraints: ; Energy storage device constraints, including charge and discharge power constraints, power dynamics, and capacity constraints, where: Charge and discharge power constraints: ; Power dynamics: ; Capacity constraints: ; Electrical equipment constraints: ; Priority constraints: ; Line transmission constraints: ; in, H represents the calculated value of the objective function, T represents a set of time periods, I Represents a collection of power generation equipment, J Represents a collection of electrical equipment. K Represents a collection of energy storage devices, L Represents a grid node or line, Indicates the time period t The electricity price at that time, t Indicates the time period identifier, Indicates the time period t The power purchased from the grid, Indicates power generation equipment i The unit cost of electricity generation, i Indicates the identification of power generation equipment. Indicates power generation equipment i In the time period t of power generation, Indicates electrical equipment j The priority weight coefficient, j Indicates the identification of electrical equipment. Indicates electrical equipment j In the time period t The required electricity consumption, Indicates the time period t For electrical equipment j The actual power supply, Energy storage equipment k In the time period t The remaining power, k Indicates the energy storage device identification. To prevent simultaneous charging and discharging, Indicates electrical equipment j In the time period t Whether it is powered, Indicates the highest priority electrical device set, Represents energy storage devices k In the time period t The charging power and discharging power, Respectively represent power generation equipment i In the time period t The upper and lower limits of power generation, Represents energy storage devices k The discharge efficiency and charging efficiency, Represents energy storage devices k The lower and upper capacity limits, Represents energy storage devices k The upper limit of charging power and the upper limit of discharging power, Indicates the upper limit of the transmission capacity of the grid node or line, Respectively indicate connection Power generation equipment and power consumption equipment on the site; In response to the calculated value of the objective function being less than a first preset threshold, charging the energy storage device; In response to the calculated value of the objective function being greater than a second preset threshold, the energy storage device is discharged.

[0038] The first preset threshold and the second preset threshold mentioned above can be set according to actual needs.

[0039] In the above-mentioned energy storage resource control method, the method includes: obtaining a first set of relevant parameters, inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the power consumption required in a future time period; obtaining a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining the power generation in a future time period based on the first power generation fluctuation probability; determining the electricity price in a future time period, and regulating the charging or discharging of the energy storage device based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period. This application can improve resource utilization efficiency while improving the dynamic response capability of the power grid.

[0040] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0041] In one embodiment, Figure 3 As shown, an energy storage resource control device is provided, including: a first determination module, a second determination module, a third determination module and a control module, wherein: a first determination module, configured to obtain a first set of relevant parameters and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the required power consumption in a future time period; a second determining module, configured to obtain a first environmental parameter and determine a first power generation fluctuation probability according to the first environmental parameter; a third determining module, configured to determine power generation in a future time period based on the first power generation fluctuation probability; The control module is used to determine the electricity price in a future time period and control the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period and the required power consumption in the future time period.

[0042] Determine whether to perform charging or discharging control. For the specific definition of the energy storage resource control device, please refer to the definition of the energy storage resource control method above, and will not be repeated here. The various modules in the above-mentioned energy storage resource control device can be implemented in whole or in part by software, hardware, and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0043] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for regulating energy storage resources is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0044] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0045] In one embodiment, a computer device is provided, including 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 following steps are performed: S1: Obtain a first set of relevant parameters, and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the power consumption required in a future time period; S2: Acquire a first environmental parameter, and determine a first power generation fluctuation probability according to the first environmental parameter; S3: determining power generation in a future time period based on the first power generation fluctuation probability; S4: Determine the electricity price in a future time period, and regulate the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0046] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: S1: Obtain a first set of relevant parameters, and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the power consumption required in a future time period; S2: Acquire a first environmental parameter, and determine a first power generation fluctuation probability according to the first environmental parameter; S3: determining power generation in a future time period based on the first power generation fluctuation probability; S4: Determine the electricity price in a future time period, and regulate the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0047] In one embodiment, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the following steps: S1: Obtain a first set of relevant parameters, and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the power consumption required in a future time period; S2: Acquire a first environmental parameter, and determine a first power generation fluctuation probability according to the first environmental parameter; S3: determining power generation in a future time period based on the first power generation fluctuation probability; S4: Determine the electricity price in a future time period, and regulate the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

[0048] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0049] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0050] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the scope of the present application, and such modifications and improvements are all within the scope of protection of the present application.

Claims

1. A method for regulating energy storage resources, characterized in that: The method comprises: Obtaining a first set of relevant parameters, and inputting the first set of relevant parameters into a pre-built target power consumption assessment model to determine the required power consumption in a future time period; Acquiring a first environmental parameter, and determining a first power generation fluctuation probability based on the first environmental parameter; determining power generation in a future time period based on the first power generation fluctuation probability; The electricity price in a future time period is determined, and the charging or discharging of the energy storage device is regulated based on the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period.

2. The energy storage resource control method according to claim 1, characterized in that: Before obtaining the first relevant parameter set, the method further includes: Constructing the target electricity consumption evaluation model.

3. The energy storage resource control method according to claim 2, characterized in that: The constructing of the target power consumption evaluation model includes: Obtaining a second set of relevant parameters; preprocessing the second relevant parameter set to obtain a third relevant parameter set; Based on the third relevant parameter set, the constructed initial electricity consumption evaluation model is trained and tested to obtain the target electricity consumption evaluation model, and the model parameters of the target electricity consumption evaluation model are obtained by training the model parameters of the initial electricity consumption evaluation model based on the third relevant parameter set.

4. The energy storage resource control method according to claim 3, characterized in that: Preprocessing the second relevant parameter set to obtain a third relevant parameter set includes: performing data cleaning on the second relevant parameter set to obtain cleaned parameters; Normalizing the cleaned parameters to obtain normalized parameters; The normalization parameters are defined as the third correlation parameter set.

5. The energy storage resource control method according to claim 4, characterized in that: After obtaining the third set of relevant parameters, the method further includes: Classifying and saving the parameters in the third related parameter set; According to the preset ratio, the classified parameters are divided into training set and test set.

6. The energy storage resource control method according to claim 5, characterized in that: The third set of relevant parameters includes at least electrical parameters, second environmental parameters, and electricity prices. Based on the third set of relevant parameters, a pre-built initial electricity consumption evaluation model is trained and tested to obtain a target electricity consumption evaluation model, including: determining power consumption within a target time period based on the electrical parameters; Acquire a plurality of second environmental parameters that affect power consumption fluctuations, and determine a second power consumption fluctuation probability based on the second environmental parameters; determining a third power consumption fluctuation probability based on the electricity price; determining the initial power consumption evaluation model based on the power consumption within the target time period, the second power consumption fluctuation probability, and the third power consumption fluctuation probability; Training the initial power consumption evaluation model based on the training set, and testing the trained initial power consumption evaluation model using the test set; In response to the test result meeting the preset standard, the target power consumption evaluation model is output.

7. The energy storage resource control method according to claim 1, characterized in that: The determining of the power generation in a future time period based on the first power generation fluctuation probability includes: According to the first power generation fluctuation probability, based on , determine the power generation in the future time period; in, Indicates power generation equipment i In the time period t of power generation, i Indicates the identification of power generation equipment. t Indicates the time period identifier, represents the second adjustable parameter, Indicates that the power generation can be controlled. represents the number of time periods, represents the regression coefficient of the power generation variable, express Fluctuating power generation within a time period, Indicates the time period identifier, Indicates the number of the first environment parameters, represents the regression coefficient of the first environmental parameter, Indicates the c The probability that the first environmental parameter affects the fluctuation of power generation, c Indicates the first environmental parameter identifier, Indicates the c Assign a value to the impact degree of the first environmental parameter, represents the second random error term.

8. The energy storage resource control method according to claim 1, characterized in that: The regulating and controlling the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period, and the required power consumption in the future time period includes: Determine whether to perform charge or discharge regulation based on the objective function and constraints, wherein the objective function includes: ； The constraints include: Supply and demand balance constraints: ； Power generation equipment constraints: ； Energy storage device constraints, including charge and discharge power constraints, power dynamics, and capacity constraints, where: Charge and discharge power constraints: ； Power dynamics: ； Capacity constraints: ； Electrical equipment constraints: ； Priority constraints: ； Line transmission constraints: ； in, H represents the calculated value of the objective function, T represents a set of time periods, I Represents a collection of power generation equipment, J Represents a collection of electrical equipment. K Represents a collection of energy storage devices, L Represents a grid node or line, Indicates the time period t The electricity price at that time, t Indicates the time period identifier, Indicates the time period t The power purchased from the grid, Indicates power generation equipment i The unit cost of electricity generation, i Indicates the identification of power generation equipment. Indicates power generation equipment i In the time period t of power generation, Indicates electrical equipment j The priority weight coefficient, j Indicates the identification of electrical equipment. Indicates electrical equipment j In the time period t The required electricity consumption, Indicates the time period t For electrical equipment j The actual power supply, Energy storage equipment k In the time period t The remaining power, k Indicates the energy storage device identification. To prevent simultaneous charging and discharging, Indicates electrical equipment j In the time period t Whether it is powered, Indicates the highest priority electrical device set, Represents energy storage devices k In the time period t The charging power and discharging power, Respectively represent power generation equipment i In the time period t The upper and lower limits of power generation, Represents energy storage devices k The discharge efficiency and charging efficiency, Represents energy storage devices k The lower and upper capacity limits, Represents energy storage devices k The upper limit of charging power and the upper limit of discharging power, Indicates the upper limit of the transmission capacity of the grid node or line, Respectively indicate connection Power generation equipment and power consumption equipment on the site; In response to the calculated value of the objective function being less than a first preset threshold, charging the energy storage device; In response to the calculated value of the objective function being greater than a second preset threshold, the energy storage device is discharged.

9. An energy storage resource control device, characterized in that: The device comprises: a first determination module, configured to obtain a first set of relevant parameters and input the first set of relevant parameters into a pre-built target power consumption evaluation model to determine the required power consumption in a future time period; a second determining module, configured to obtain a first environmental parameter and determine a first power generation fluctuation probability according to the first environmental parameter; a third determining module, configured to determine power generation in a future time period based on the first power generation fluctuation probability; The control module is used to determine the electricity price in a future time period and control the charging or discharging of the energy storage device according to the electricity price in the future time period, the power generation in the future time period and the required power consumption in the future time period.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

Images