Control method and device of power device, electronic equipment and storage medium

Abstract

The invention discloses a control method and device of a power device, electronic equipment and a storage medium. The method comprises the steps that a target power device is determined, and the target power device comprises a target energy storage device and a target distribution transformer connected with the target energy storage device; determining predicted load data of the target distribution transformer in a target prediction time period and predicted energy storage energy of the target energy storage device in the target prediction time period; determining a real-time load rate of the target distribution transformer and a real-time charge state of the target energy storage device; and controlling the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time charge state. Based on the technical scheme, the problem of heavy overload of the distribution transformer can be effectively solved in a power device control mode, and safe and stable operation of a power system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a control method, device, electronic equipment and storage medium for an electric power device. Background Art

[0002] With the growth of electricity demand and the limitation of distribution transformer capacity, the problem of heavy overload of distribution transformers is becoming increasingly serious in the power system.

[0003] In the related art, the problem of distribution transformer overload is usually solved by increasing the transformer capacity to ensure the stability and safety of the power system, but this is too costly. In order to save costs, there is currently a lack of a method to solve the problem of distribution transformer overload through power device control. Summary of the Invention

[0004] The present invention provides a control method, device, electronic equipment and storage medium for an electric power device, so as to solve the current lack of a method for solving the problem of heavy overload of distribution transformers by controlling the electric power device.

[0005] According to one aspect of the present invention, a method for controlling an electric power device is provided, the method comprising:

[0006] determining a target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device;

[0007] Determining predicted load data of the target distribution transformer in a target prediction time period and predicted energy storage capacity of the target energy storage device in the target prediction time period;

[0008] Determining a real-time load rate of the target distribution transformer and a real-time state of charge of the target energy storage device;

[0009] The target power device is controlled according to the predicted load data, the predicted energy storage energy, the real-time load rate, and the real-time state of charge.

[0010] According to another aspect of the present invention, there is provided a control device for an electric power device, the device comprising:

[0011] an electric power device determination module, configured to determine a target electric power device, wherein the target electric power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device;

[0012] A forecast data determination module, configured to determine the forecast load data of the target distribution transformer in a target forecast time period and the forecast energy storage capacity of the target energy storage device in the target forecast time period;

[0013] A real-time data determination module, configured to determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device;

[0014] The power device control module is used to control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge.

[0015] According to another aspect of the present invention, an electronic device is provided, comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the control method of the power device according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the control method of the power device according to any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention is to determine the target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device; determine the predicted load data of the target distribution transformer in the target prediction time period and the predicted energy storage energy of the target energy storage device in the target prediction time period; determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device; and control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge. The present invention monitors the power system from multiple dimensions of predicted load data, predicted energy storage energy, real-time load rate and real-time state of charge and makes adaptive adjustments to the power devices. Controlling the power devices based on the technical solution of the present invention can effectively solve the problem of heavy overload of the distribution transformer and ensure the safe and stable operation of the power system.

[0021] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is a flow chart of a control method for an electric power device provided according to a first embodiment of the present invention;

[0024] Figure 2 This is a flow chart of a control method for an electric power device according to a second embodiment of the present invention;

[0025] Figure 3 This is a schematic structural diagram of a control device for an electric power device according to a third embodiment of the present invention;

[0026] Figure 4 It is a structural diagram of an electronic device for implementing the control method of the power device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Example 1

[0030] Figure 1A flowchart of a control method for an electric power device is provided for the first embodiment of the present invention. This embodiment is applicable to the case where an electric power device in an electric power system is controlled based on multi-dimensional data. The method can be executed by a control device of the electric power device. The control device of the electric power device can be implemented in the form of hardware and / or software, and the control device of the electric power device can be configured in a computer. Figure 1 As shown, the method includes:

[0031] S110: Determine a target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device.

[0032] The target power device may be understood as a power device in a target power system.

[0033] It is understandable that the power system includes a variety of power devices. The embodiment of the present invention is a method for controlling the target energy storage device and the target distribution transformer to solve the problem of distribution transformer overload due to capacity limitation of the distribution transformer.

[0034] The target energy storage device can be understood as an energy storage device in the target power system. In an embodiment of the present invention, the target energy storage device includes at least an energy storage battery.

[0035] The target distribution transformer may be understood as a distribution transformer in a target power system. In an embodiment of the present invention, the target energy storage device and the target energy storage device may be connected in parallel.

[0036] S120: Determine the predicted load data of the target distribution transformer in a target prediction time period and the predicted energy storage capacity of the target energy storage device in the target prediction time period.

[0037] The target prediction time period can be understood as the target prediction time period. In embodiments of the present invention, the target prediction time period is a preset time period based on scenario requirements and user needs. In power application scenarios, power consumption is typically associated with a date. Therefore, in embodiments of the present invention, the target preset time period can be a prediction date, which can be a day in the future.

[0038] The predicted load data may be understood as predicted load data, wherein the predicted load data may include a predicted load value.

[0039] In an embodiment of the present invention, the predicted load data may be determined based on real-time load data of the target distribution transformer.

[0040] The predicted energy storage energy can be understood as the predicted energy storage energy, or can be understood as the predicted energy storage power.

[0041] In an embodiment of the present invention, the predicted energy storage capacity may be determined based on the real-time charge and discharge power, the real-time remaining energy, and the real-time charge and discharge efficiency of the target energy storage device.

[0042] Optionally, determining the predicted load data of the target distribution transformer in a target prediction time period includes:

[0043] Determining real-time load data of the target distribution transformer;

[0044] The load forecasting model is used to perform load forecasting on the input real-time load data to obtain the predicted load data of the target distribution transformer in the target forecasting time period, wherein the load forecasting model is obtained by training a deep learning model based on historical load samples.

[0045] The real-time load data may be understood as load data acquired in real time. Optionally, the real-time load data may include a real-time point in time and a real-time load value corresponding to the real-time point in time.

[0046] The load forecasting model can be understood as a model capable of load forecasting. For the load forecasting model, the input data can be the real-time load value corresponding to the real-time time point, and the output data can be the predicted load value for a predicted date in the future that is adjacent to the real-time date corresponding to the real-time time point.

[0047] The historical load samples can be used to train the deep learning model to obtain the load forecasting model. Optionally, the historical load samples can be historical load data corresponding to the target distribution transformer. Exemplarily, the historical load samples can include load data within the past one year, two years, or three years.

[0048] The deep learning model can be understood as a machine learning model. The deep learning model can include a supervised learning model or an unsupervised learning model. The selection of the machine learning model can be based on user needs or scenario requirements, and is not specifically limited here.

[0049] Optionally, determining the predicted energy storage capacity of the target energy storage device in the target prediction time period includes:

[0050] Determining the real-time charge and discharge power, real-time remaining energy, and real-time charge and discharge efficiency of the target energy storage device;

[0051] The predicted stored energy of the energy storage device in the target prediction time period is determined according to the real-time charging and discharging power, the real-time remaining energy, and the real-time charging and discharging efficiency.

[0052] The real-time charge and discharge power may include real-time charge power and / or real-time discharge power. In the embodiment of the present invention, the real-time charge and discharge power may be directly obtained, and the specific acquisition method is not specifically limited herein.

[0053] The real-time remaining energy can be understood as real-time remaining energy, or can be understood as real-time remaining power.

[0054] The real-time charge and discharge efficiency can be understood as the real-time charge and discharge efficiency, which can be determined based on the real-time charge amount and the real-time discharge amount.

[0055] Specifically, the real-time charge capacity and the real-time discharge capacity of the target energy storage device are obtained; and the ratio between the real-time discharge capacity and the real-time charge capacity is used as the real-time charge and discharge efficiency.

[0056] In the embodiment of the present invention, the real-time discharge amount and the real-time charge amount can be directly obtained, and the specific acquisition method is not specifically limited here.

[0057] Specifically, the formula for determining the predicted stored energy of the energy storage device in the target prediction time period may be as follows:

[0058]

[0059] Among them, E(t+1) represents the predicted energy storage capacity, E(t) represents the real-time remaining energy, and P ch (t) represents the real-time charging power, Δt represents the prediction time interval, η represents the real-time charging and discharging efficiency, P disch (t) represents the real-time discharge power.

[0060] In the embodiment of the present invention, the prediction time interval represented by Δt can be preset according to the scenario requirements and is not specifically limited here. Optionally, the prediction time interval can be 24 hours, or the prediction time interval can also be the time interval between the real time point and the target prediction time period.

[0061] S130: Determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device.

[0062] The real-time state of charge (SOC) can be understood as a real-time state of charge (SOC). Optionally, the real-time SOC can be determined based on the rated capacity and real-time remaining energy of the battery of the target energy storage device.

[0063] The real-time load rate can be understood as a real-time load rate. Optionally, the real-time load rate can be determined based on the transformer rated capacity and real-time load data of the target distribution transformer, and the corresponding real-time charge and discharge power of the target energy storage device.

[0064] Optionally, determining the real-time state of charge of the target energy storage device includes:

[0065] Determining a rated capacity of a battery of the target energy storage device;

[0066] The real-time state of charge of the target energy storage device is determined according to the rated capacity of the battery and the real-time remaining energy.

[0067] The rated capacity of the battery may be understood as the rated capacity of the target energy storage device.

[0068] In an embodiment of the present invention, according to scenario requirements and user needs, the target energy storage device with different battery rated capacities can be selected in the target power system.

[0069] Specifically, the ratio between the real-time remaining energy and the rated capacity of the battery is used as the real-time state of charge.

[0070] Optionally, determining the real-time load rate of the target distribution transformer includes:

[0071] Determining the transformer rated capacity of the target distribution transformer;

[0072] The real-time load rate of the target distribution transformer is determined according to the rated capacity of the transformer, the real-time load data, and the real-time charge and discharge power.

[0073] The rated capacity of the transformer may be understood as the rated capacity of the target distribution transformer.

[0074] In the embodiment of the present invention, according to scenario requirements and user requirements, the target distribution transformers with different transformer rated capacities may be selected in the target power system.

[0075] Specifically, the formula for determining the real-time load rate of the target distribution transformer may be as follows:

[0076]

[0077] Where, f represents the real-time load rate, P load (t) represents real-time load data, P disch (t) represents the real-time discharge power, P ch (t) represents the real-time charging power, S N Indicates the rated capacity of the transformer.

[0078] S140. Control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate, and the real-time state of charge.

[0079] The technical solution of the embodiment of the present invention is to determine the target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device; determine the predicted load data of the target distribution transformer in the target prediction time period and the predicted energy storage energy of the target energy storage device in the target prediction time period; determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device; and control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge. The present invention monitors the power system from multiple dimensions of predicted load data, predicted energy storage energy, real-time load rate and real-time state of charge and makes adaptive adjustments to the power devices. Controlling the power devices based on the technical solution of the present invention can effectively solve the problem of heavy overload of the distribution transformer and ensure the safe and stable operation of the power system.

[0080] Example 2

[0081] Figure 2 This is a flowchart of a control method for an electric power device provided in the second embodiment of the present invention. This embodiment refines the control of the target electric power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge as described in the above embodiment. Figure 2 As shown, the method includes:

[0082] S210: Determine a target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device.

[0083] S220: Determine the predicted load data of the target distribution transformer in a target prediction time period and the predicted energy storage capacity of the target energy storage device in the target prediction time period.

[0084] S230: Determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device.

[0085] S240: When the real-time load rate meets a first preset condition, adjust the electric power of the target energy storage device.

[0086] The first preset condition may be understood as a constraint condition related to the real-time load rate.

[0087] In the embodiment of the present invention, the first preset condition can be preset according to the scenario requirements and is not specifically limited here. Optionally, the first preset condition can be that the real-time load rate exceeds the target load rate range, or the real-time load rate is not equal to the target load rate.

[0088] For the case where the first preset condition is that the real-time load rate exceeds the target load rate range:

[0089] The target load rate range can be preset according to the scenario requirements and is not specifically limited here. For example, the target load rate range can be [20%, 100%].

[0090] Optionally, the adjusting the electric power of the target energy storage device may include: when the real-time load rate is lower than 20%, increasing the charging power of the target energy storage device; when the real-time load rate is higher than 20%, increasing the discharging power of the target energy storage device.

[0091] For the case where the first preset condition is that the real-time load rate is not equal to the target load rate:

[0092] The target load rate can be preset according to the scenario requirements and is not specifically limited here. For example, the target load rate range can be 50%.

[0093] Optionally, the electric power of the target energy storage device is adjusted based on the following target formula:

[0094]

[0095] Among them, min f1 represents the minimum load rate, P load (t) represents real-time load data, P disch (t) represents the real-time discharge power, P ch (t) represents the real-time charging power, S N Indicates the rated capacity of the transformer.

[0096] Specifically, based on the above target formula, the real-time discharge power P disch (t) and / or the real-time charging power P ch (t) Adjustment is performed to make the real-time load rate closer to the minimum load rate min f1. For example, the minimum load rate min f1 may be 0.

[0097] That is, the charging and discharging power is adjusted in real time based on the target formula so that the real-time load rate of the target distribution transformer approaches 50%, so as to avoid the occurrence of a heavy overload situation of the distribution transformer.

[0098] S250: When the predicted load data meets the second preset condition, the predicted energy storage energy meets the third preset condition, or the real-time state of charge meets the fourth preset condition, perform switching control on the target distribution transformer.

[0099] The second preset condition can be understood as a constraint condition related to the predicted load data. In the embodiment of the present invention, the second preset condition can be preset according to the scenario requirements and is not specifically limited here.

[0100] Optionally, the second preset condition may be that the predicted load value exceeds a target load value. The preset target load value may be associated with the transformer rated capacity of the target distribution transformer. Optionally, the preset target load value may be positively correlated with the transformer rated capacity of the target distribution transformer.

[0101] Specifically, when the predicted load value exceeds the target load value, the target distribution transformer is controlled to reduce charging and / or increase discharging.

[0102] In the embodiment of the present invention, the switching control method of the target distribution transformer is related to the actual connection structure between the target distribution transformer and the target energy storage device, and is not specifically limited here.

[0103] The third preset condition can be understood as a constraint condition related to the predicted energy storage energy. In the embodiment of the present invention, the third preset condition can be preset according to the scenario requirements and is not specifically limited here.

[0104] Optionally, the third preset condition may be that the predicted energy storage capacity exceeds a preset maximum energy storage capacity. The maximum energy storage capacity may be related to the rated capacity of the battery of the target energy storage device.

[0105] Specifically, the constraint condition related to the third preset condition can be expressed based on the following formula:

[0106] 0≤E(t+1)≤E max

[0107] Among them, E(t+1) represents the predicted energy storage capacity, E max Indicates the maximum stored energy.

[0108] Specifically, when the predicted energy storage energy exceeds the maximum energy storage energy, the target distribution transformer is controlled to reduce charging and / or increase discharging.

[0109] The fourth preset condition can be understood as a constraint condition related to the real-time state of charge. In the embodiment of the present invention, the third preset condition can be preset according to the scenario requirements and is not specifically limited here.

[0110] Optionally, the fourth preset condition may include that the ratio corresponding to the real-time state of charge exceeds a target ratio range (including a lower limit and an upper limit). In an embodiment of the present invention, the target ratio range can be preset according to scenario requirements and is not specifically limited here.

[0111] Specifically, when the ratio corresponding to the real-time state of charge is lower than the lower limit of the target ratio range, the target distribution transformer is controlled to stop discharging; when the ratio corresponding to the real-time state of charge is higher than the upper limit of the target ratio range, the target distribution transformer is controlled to stop charging.

[0112] Optionally, the control method of the power device further includes:

[0113] The electric power of the target energy storage device is adjusted according to the real-time charging and discharging power.

[0114] Specifically, when the real-time charge and discharge power meets the fifth setting condition, the electric power of the target energy storage device is adjusted.

[0115] The fifth preset condition can be understood as a constraint condition related to the real-time charge and discharge power. Specifically, the constraint condition related to the fifth preset condition can be expressed based on the following formula:

[0116]

[0117] Among them, P ch (t) represents the real-time charging power, P disch (t) represents the real-time discharge power, Indicates the preset maximum charging power. Indicates the preset maximum discharge power.

[0118] Optionally, the target power device further includes a main switch, and the method further includes:

[0119] When the first operating data of the target energy storage device meets the first fault condition and / or the second operating data of the target distribution transformer meets the second fault condition, the main switch is controlled.

[0120] The main switch may be understood as a main switch in a target power system, and may control the operation of power devices in the target power system.

[0121] The first operating data may be understood as data related to the real-time operation of the target energy storage device. Optionally, the first operating data may include the temperature of the energy storage device.

[0122] The second operating data may be understood as data related to the real-time operation of the target distribution transformer. Optionally, the second operating data may include transformer temperature, etc.

[0123] Correspondingly, the first fault condition may be that the energy storage device temperature of the target energy storage device exceeds a preset first fault temperature value. The second fault condition may be that the transformer temperature of the target distribution transformer exceeds a preset second fault temperature value.

[0124] In the embodiment of the present invention, the operating data may also be load data, energy storage data, state of charge data, etc. Correspondingly, the fault condition may also be a constraint condition related to the above data.

[0125] Specifically, the main switch is controlled to suspend the operation of the power devices in the target power system.

[0126] Based on the above technical solution, when a target power device has a risk of failure, the operation of the power device in the target power system can be suspended to avoid the occurrence of safety failures.

[0127] Optionally, the control method of the power device may further include:

[0128] During periods when the value of electricity is higher, discharge is prioritized; during periods when the value of electricity is lower, charging is prioritized to reduce energy storage costs and improve economic benefits.

[0129] Optionally, the control method of the power device may further include:

[0130] By adding new communication devices, data can be shared between the power system and other systems to achieve global optimal scheduling. For example, the coordinated control of distribution transformers in other systems can achieve a wider range of power scheduling optimization.

[0131] The technical solution of an embodiment of the present invention adjusts the electric power of the target energy storage device when the real-time load rate meets a first preset condition; and controls the switching of the target distribution transformer when the predicted load data meets a second preset condition, the predicted energy storage capacity meets a third preset condition, or the real-time state of charge meets a fourth preset condition. By controlling power devices based on multi-dimensional constraints, the present invention can effectively ensure the safe and stable operation of the power system.

[0132] Example 3

[0133] Figure 3 This is a schematic diagram of the structure of a control device for an electric power device provided in the third embodiment of the present invention. Figure 3 As shown, the device includes: an electric device determination module 310 , a predicted data determination module 320 , a real-time data determination module 330 and an electric device control module 340 .

[0134] Among them, the power device determination module 310 is used to determine the target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device; the prediction data determination module 320 is used to determine the predicted load data of the target distribution transformer in the target prediction time period and the predicted energy storage energy of the target energy storage device in the target prediction time period; the real-time data determination module 330 is used to determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device; the power device control module 340 is used to control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge.

[0135] The technical solution of the embodiment of the present invention is to determine the target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device; determine the predicted load data of the target distribution transformer in the target prediction time period and the predicted energy storage energy of the target energy storage device in the target prediction time period; determine the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device; and control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge. The present invention monitors the power system from multiple dimensions of predicted load data, predicted energy storage energy, real-time load rate and real-time state of charge and makes adaptive adjustments to the power devices. Controlling the power devices based on the technical solution of the present invention can effectively solve the problem of heavy overload of the distribution transformer and ensure the safe and stable operation of the power system.

[0136] Optionally, the predicted data determination module 320 is specifically configured to:

[0137] Determining real-time load data of the target distribution transformer;

[0138] The load forecasting model is used to perform load forecasting on the input real-time load data to obtain the predicted load data of the target distribution transformer in the target forecasting time period, wherein the load forecasting model is obtained by training a deep learning model based on historical load samples.

[0139] Optionally, the predicted data determination module 320 is specifically configured to:

[0140] Determining the real-time charge and discharge power, real-time remaining energy, and real-time charge and discharge efficiency of the target energy storage device;

[0141] The predicted stored energy of the energy storage device in the target prediction time period is determined according to the real-time charging and discharging power, the real-time remaining energy, and the real-time charging and discharging efficiency.

[0142] Optionally, the real-time data determination module 330 is specifically configured to:

[0143] Determining a rated capacity of a battery of the target energy storage device;

[0144] The real-time state of charge of the target energy storage device is determined according to the rated capacity of the battery and the real-time remaining energy.

[0145] Optionally, the real-time data determination module 330 is specifically configured to:

[0146] Determining the transformer rated capacity of the target distribution transformer;

[0147] The real-time load rate of the target distribution transformer is determined according to the rated capacity of the transformer, the real-time load data, and the real-time charge and discharge power.

[0148] Optionally, the power device control module 340 is specifically configured to:

[0149] When the real-time load rate meets a first preset condition, adjusting the electric power of the target energy storage device;

[0150] When the predicted load data meets the second preset condition, the predicted energy storage energy meets the third preset condition, or the real-time state of charge meets the fourth preset condition, the target distribution transformer is controlled to switch.

[0151] Optionally, the target power device also includes a main switch, and the control device of the power device further includes: a fault control module, which is used to control the main switch when the first operating data of the target energy storage device meets the first fault condition and / or the second operating data of the target distribution transformer meets the second fault condition.

[0152] The control device of the electric power device provided in the embodiment of the present invention can execute the control method of the electric power device provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0153] Example 4

[0154] Figure 4A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0155] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0156] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0157] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the control method for the power device.

[0158] In some embodiments, the method for controlling an electric power device may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for controlling an electric power device described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the method for controlling an electric power device in any other appropriate manner (e.g., by means of firmware).

[0159] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0160] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0161] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0162] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0163] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0164] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0165] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0166] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A control method for an electric power device, characterized in that: include: Determining a target power device, wherein the target power device includes a target energy storage device and a target distribution transformer connected to the target energy storage device; Determining predicted load data of the target distribution transformer in a target prediction time period and predicted energy storage capacity of the target energy storage device in the target prediction time period; Determining the real-time load rate of the target distribution transformer and the real-time state of charge of the target energy storage device; The target power device is controlled according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge.

2. The method according to claim 1, characterized in that The step of determining the predicted load data of the target distribution transformer in the target prediction time period includes: Determining real-time load data of the target distribution transformer; The load forecasting model is used to perform load forecasting on the input real-time load data to obtain the forecasted load data of the target distribution transformer in the target forecasting time period, wherein the load forecasting model is obtained by training a deep learning model based on historical load samples.

3. The method according to claim 1, characterized in that The determining the predicted energy storage capacity of the target energy storage device in the target prediction time period includes: Determine the real-time charge and discharge power, real-time remaining energy, and real-time charge and discharge efficiency of the target energy storage device; The predicted energy storage energy of the energy storage device in the target prediction time period is determined according to the real-time charging and discharging power, the real-time remaining energy, and the real-time charging and discharging efficiency.

4. The method according to claim 1, characterized in that: Determining the real-time state of charge of the target energy storage device includes: Determining a battery rated capacity of the target energy storage device; The real-time state of charge of the target energy storage device is determined according to the rated capacity of the battery and the real-time remaining energy.

5. The method according to claim 1, characterized in that Determining the real-time load rate of the target distribution transformer includes: Determining the transformer rated capacity of the target distribution transformer; The real-time load rate of the target distribution transformer is determined according to the rated capacity of the transformer, the real-time load data and the real-time charging and discharging power.

6. The method according to claim 1, characterized in that The controlling the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge includes: When the real-time load rate meets the first preset condition, adjusting the electric power of the target energy storage device; When the predicted load data meets the second preset condition, the predicted energy storage energy meets the third preset condition, or the real-time charge state meets the fourth preset condition, the target distribution transformer is switched on and off.

7. The method according to claim 1, characterized in that The target power device further includes a main switch, and the method further includes: When the first operating data of the target energy storage device meets the first fault condition and / or the second operating data of the target distribution transformer meets the second fault condition, the main switch is controlled.

8. A control device for an electric power device, characterized in that: include: An electric power device determination module, configured to determine a target electric power device, wherein the target electric power device comprises a target energy storage device and a target distribution transformer connected to the target energy storage device; A forecast data determination module, used to determine the forecast load data of the target distribution transformer in a target forecast time period and the forecast energy storage capacity of the target energy storage device in the target forecast time period; A real-time data determination module, used to determine the real-time load rate of the target distribution transformer and the real-time charge state of the target energy storage device; The power device control module is used to control the target power device according to the predicted load data, the predicted energy storage energy, the real-time load rate and the real-time state of charge.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the control method of the power device according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the control method of the power device according to any one of claims 1 to 7 when executed.

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