Distribution method, device, equipment and storage medium of microgrid control system

Abstract

The embodiment of the present invention discloses a distribution method, device, equipment and storage medium of a microgrid control system. Among them, when it is determined that the current time of the current microgrid control system reaches the preset data processing cycle time, the amount of business data to be distributed is obtained; a probability density function is constructed according to the amount of business data, and the probability function is calculated to obtain the first business data concurrency, and the remaining business data amount to be distributed is calculated; according to the preset first optimization parameter model and at least one real-time operation parameter of the microgrid control system, the first proportion parameter and the second proportion parameter are calculated, and the remaining business data amount is distributed. The problem of fuzzy resource calculation and unreasonable allocation of charging pile control business in the microgrid control system is solved, and the reasonable allocation of computing resources and charging pile control business processing requirements is realized, and the processing capacity of the microgrid is improved to better meet the real-time and reliability requirements of microgrid control.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of power grid technology, and in particular to a distribution method, device, equipment and storage medium for a microgrid control system. Background Art

[0002] With the massive access of distributed power sources, charging piles, distributed energy storage, and intelligent power distribution devices, the types and number of microgrid services are showing an increasing trend, which has brought severe challenges to the control and service processing capabilities of microgrids. The microgrid control system based on edge computing technology is an effective means to meet the real-time and reliability of microgrid control. By processing charging pile control services nearby, the response time of microgrid control is greatly reduced. Due to the large amount of charging pile data connected to the microgrid, the microgrid charging pile control service has the characteristics of concurrency. A large number of charging pile control services need to be processed simultaneously in a time section to ensure the normal operation of the microgrid.

[0003] Existing research lacks concurrency modeling of microgrid charging pile control services. The control mode adopts a centralized cloud master station approach, lacks reasonable allocation of computing resources and charging pile control services, and is difficult to meet the real-time and reliability requirements of microgrid charging pile control services. It is difficult to adapt to the development trend of massive access objects and concurrent business request processing in the context of new power systems. Summary of the invention

[0004] The embodiments of the present invention provide a distribution method, device, equipment and storage medium for a microgrid control system, which solves the problems of fuzzy resource calculation and unreasonable distribution of charging pile control services in the microgrid control system, improves the processing capacity of the microgrid, and better meets the real-time and reliability requirements of the microgrid control.

[0005] In a first aspect, an embodiment of the present invention provides a distribution method for a microgrid control system, which is executed by the microgrid control system and includes:

[0006] When it is determined that the current time of the current microgrid control system reaches the preset data processing cycle time, the amount of business data to be allocated is obtained;

[0007] Constructing a probability density function according to the business data volume, and obtaining a first business data concurrency volume according to a probability function calculated by the probability density function;

[0008] Calculating the remaining amount of business data to be allocated according to the amount of business data to be allocated and the concurrent amount of the first business data;

[0009] Calculating a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system;

[0010] The remaining service data volume is distributed according to the first proportion parameter and the second proportion parameter.

[0011] In a second aspect, an embodiment of the present invention further provides a distribution device of a microgrid control system, which is executed by the microgrid control system. The distribution device of the microgrid control system includes:

[0012] A module for acquiring the amount of business data to be allocated, used to acquire the amount of business data to be allocated when it is determined that the current time of the current microgrid control system reaches a preset data processing cycle time;

[0013] A first service data concurrency determination module, configured to construct a probability density function according to the service data volume, and obtain a first service data concurrency according to a probability function calculated by the probability density function;

[0014] A module for calculating the amount of remaining business data to be allocated, used to calculate the amount of remaining business data to be allocated according to the amount of business data to be allocated and the concurrent amount of first business data;

[0015] A proportional parameter calculation module, used to calculate a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system;

[0016] The remaining service data volume allocation module is used to allocate the remaining service data volume according to the first proportion parameter and the second proportion parameter.

[0017] In a third aspect, an embodiment of the present invention further provides 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 distribution method of the microgrid control system as described in any embodiment of the present invention is implemented.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the distribution method of the microgrid control system as described in any embodiment of the present invention is implemented.

[0019] The technical solution provided by the embodiment of the present invention obtains the amount of business data to be allocated when determining that the current time of the current microgrid control system reaches the preset data processing cycle time; constructs a probability density function according to the amount of business data, and obtains the first business data concurrency according to the probability function calculated by the probability density function; calculates the remaining business data amount to be allocated according to the amount of business data to be allocated and the first business data concurrency; calculates the first proportion parameter and the second proportion parameter according to the preset first optimization parameter model and at least one real-time operation parameter of the microgrid control system; and allocates the remaining business data amount according to the first proportion parameter and the second proportion parameter. The problem of fuzzy resource calculation and unreasonable allocation of charging pile control business in the microgrid control system is solved, and the reasonable allocation of computing resources and charging pile control business processing requirements is realized, and the processing capacity of the microgrid is improved to better meet the real-time and reliability requirements of microgrid control. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart of a distribution method of a microgrid control system provided in Embodiment 1 of the present invention;

[0021] Figure 2 A flow chart of another allocation method of a microgrid control system provided in Embodiment 2 of the present invention;

[0022] Figure 3 It is a structural schematic diagram of a distribution device of a microgrid control system provided by Embodiment 3 of the present invention;

[0023] Figure 4 It is a structural diagram of a computer device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0025] Embodiment 1

[0026] Figure 1 A flowchart of a distribution method of a microgrid control system provided in Embodiment 1 of the present invention. This embodiment is applicable to the reasonable allocation of computing resources and charging pile control business processing requirements. The method of this embodiment can be executed by a distribution device of a microgrid control system, which can be implemented by software and / or hardware, and can be configured in a server or terminal device.

[0027] Accordingly, the method specifically comprises the following steps:

[0028] S110. When it is determined that the current time of the current microgrid control system reaches a preset data processing cycle time, an amount of service data to be allocated is obtained.

[0029] The microgrid control system may refer to a small power generation and distribution control system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. The data processing cycle may be a data processing cycle pre-set in the microgrid control system, and the amount of business data may be acquired within one cycle. The amount of business data may be the amount of data that needs to be distributed and processed by the microgrid control system, and the amount of business data acquired in different data cycles is different.

[0030] Exemplarily, the amount of business data to be allocated that can be obtained in the current data processing cycle in the microgrid control system is A, and the amount of business data to be allocated that can be obtained in the next data processing cycle is B, where A and B can be the same or different, and are not limited in this embodiment.

[0031] S120. Construct a probability density function according to the business data volume, and obtain a first business data concurrency volume according to a probability function calculated by the probability density function.

[0032] Among them, the probability density function can be a function that describes the possibility of the output value of this random variable near a certain value point. The probability function can be that the probability that the value of the random variable in the probability density function falls within a certain area is the integral of the probability density function in this area. When the probability density function exists, the probability function is the integral of the probability density function. The first business data concurrency can be the current concurrent number of business data processed in the microgrid control system, which can be calculated by the probability function and the concurrent probability value.

[0033] Optionally, constructing a probability density function according to the business data volume, and obtaining the first business data concurrency according to a probability function calculated by the probability density function, including: according to the formula Construct the probability density function f(x,h); N is the amount of business data, K h is the kernel function, K(u) is the standard Gaussian kernel function, h is the preset bandwidth window, b i is the amount of business data in the i-th unit time; according to the formula Calculate the probability function F(x); according to the formula X = F -1 (λ), and calculate the concurrent volume X of the first business data, where λ is the concurrent probability value.

[0034] For example, assuming that the amount of service data to be allocated that can be obtained in the current data processing cycle in the microgrid control system is A, then according to the formula The calculated probability density function is According to the obtained probability density function, the obtained probability function is further calculated. And according to the formula X = F -1 (λ) and a preset concurrency probability value λ to further determine the concurrency volume of the first business data.

[0035] The advantage of such a setting is that the first concurrent amount of business data is obtained by constructing a probability density function based on the amount of business data to be allocated, and then further solving and calculating the concurrent amount of business data. In this way, the concurrent amount of business data that the microgrid control system can process can be determined, and the microgrid control system can be better utilized to process the most reasonable business data, thereby improving the processing capacity of the microgrid control system.

[0036] S130. Calculate the remaining amount of business data to be allocated according to the amount of business data to be allocated and the concurrent amount of first business data.

[0037] Among them, the remaining business data volume can be the business data volume that needs to be processed by the cloud computing center system and the edge device system, which can be obtained by subtracting the first business data concurrency volume from the business data volume to be allocated.

[0038] For example, assuming that the amount of business data to be allocated that can be obtained in the current data processing cycle in the microgrid control system is A, and the concurrent amount of the first business data that needs to be processed by the microgrid control system is X, the remaining business data to be allocated can be calculated to be AX. That is to say, the amount of business data that needs to be processed by the cloud computing center system and the edge device system is AX, but how to reasonably allocate the remaining business data, that is, to reasonably allocate the business data amount of AX to the cloud computing center system and the edge device system is crucial.

[0039] S140. Calculate a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system.

[0040] Among them, the first optimization parameter model can be a model that can optimize parameters, so as to obtain the best objective function value, that is, the minimum calculation and communication delay. The real-time operation parameter can be an operation parameter calculated in the microgrid control system, which can include the cloud computing center system calculation delay, the cloud computing center system communication delay, the edge device system calculation delay and the edge device system communication delay. The first proportional parameter can be the size of the proportion of the remaining business data volume allocated to the cloud computing center system. The second proportional parameter can be the size of the proportion of the remaining business data volume allocated to the edge device system. The sum of the first proportional parameter and the second proportional parameter is 1.

[0041] Optionally, according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system, calculating the first proportional parameter and the second proportional parameter includes: according to the preset first optimization parameter model formula Get the first proportional parameter and the second proportional parameter; where T1 is the calculation and communication delay, T C Calculate the latency for the cloud computing center system, T b,C is the communication delay of the cloud computing center system, T E Calculate the latency for edge device systems, T b,E is the edge device system communication delay, r C The amount of computing resources provided to the cloud computing center system, r E The amount of computing resources provided to the edge device system, α C is the first scale parameter, α E is the second proportional parameter, B is the available channel bandwidth of the edge computing terminal, h is the channel gain, and P e is the edge computing terminal transmission power, σ 2 Represents the noise power of Gaussian white noise.

[0042] Among them, the computing and communication delays may be the delays generated by the cloud computing center system or the edge device system during the computing process and the communication process. The computing delay of the cloud computing center system may be the delay generated by the cloud computing center system during the computing process. The communication delay of the cloud computing center system may be the delay generated by the cloud computing center system during the communication process. The computing delay of the edge device system may be the delay generated by the edge device system during the computing process. The communication delay of the edge device system may be the delay generated by the edge device system during the communication process. The amount of computing resources provided by the cloud computing center system may be the amount of computing resources provided by the cloud computing center system during the business data processing process. The amount of computing resources provided by the edge device system may be the amount of computing resources provided by the edge device system during the business data processing process.

[0043] Specifically, constraints C1 and C2 indicate that the range of the allocation coefficients of the cloud computing center system and the edge device system is between [0, 1]. Constraint C3 indicates that the sum of the allocation coefficients of the microgrid control system is 1. Constraint C4 indicates that the sum of the computing delay and communication delay corresponding to the cloud computing center system calculated first is T C +T b,C , and the sum of the computational delay and communication delay corresponding to the edge device system T E +T b,E , and take the maximum delay between the two to ensure that the cloud computing center system and the edge device system have enough time to process the business data. Constraints C5 represent the calculation delay T corresponding to the cloud computing center system. C and communication delay T b,C Constraints C6 represent the computing delay T of the edge device system. E and communication delay T b,E .

[0044] Continuing from the previous example, since it is necessary to reasonably distribute the remaining business data volume AX to the cloud computing center system and the edge device system. Substitute the remaining business data volume AX into the first optimization parameter model formula to obtain That is, the first scale parameter α can be used C and the second scale parameter α E After determining the minimum computation and communication delay, the first proportional parameter α can be obtained accordingly. C and the second scale parameter α E The specific value of can be used to allocate the remaining service data volume AX. Assume that the minimum computing and communication delay corresponds to α C =0.65, and α E =0.35, it can be determined that the first proportional parameter is 0.65 and the second proportional parameter is 0.35.

[0045] S150. Allocate the remaining service data volume according to the first proportion parameter and the second proportion parameter.

[0046] Optionally, the distribution of the remaining business data volume according to the first proportion parameter and the second proportion parameter includes: multiplying the remaining business data volume by the first proportion parameter to obtain a second business data concurrency, and distributing it to the cloud computing center system; multiplying the remaining business data volume by the second proportion parameter to obtain a third business data concurrency, and distributing it to the edge device system.

[0047] The second concurrent volume of business data may be the concurrent volume that needs to be allocated to the cloud computing center system for business data processing, and the third concurrent volume of business data may be the concurrent volume that needs to be allocated to the edge device system for business data processing.

[0048] Continuing with the previous example, according to the determined first ratio parameter 0.65 and second ratio parameter 0.35, and the remaining business data volume is AX, therefore, 0.65 (AX) can be allocated to the cloud computing center system, and 0.35 (AX) can be allocated to the edge device system to process the business data.

[0049] The technical solution provided by the embodiment of the present invention obtains the amount of business data to be allocated when determining that the current time of the current microgrid control system reaches the preset data processing cycle time; constructs a probability density function according to the amount of business data, and obtains the first business data concurrency according to the probability function calculated by the probability density function; calculates the remaining business data amount to be allocated according to the amount of business data to be allocated and the first business data concurrency; calculates the first proportion parameter and the second proportion parameter according to the preset first optimization parameter model and at least one real-time operation parameter of the microgrid control system; and allocates the remaining business data amount according to the first proportion parameter and the second proportion parameter. The problem of fuzzy resource calculation and unreasonable allocation of charging pile control business in the microgrid control system is solved, and the reasonable allocation of computing resources and charging pile control business processing requirements is realized, and the processing capacity of the microgrid is improved to better meet the real-time and reliability requirements of microgrid control.

[0050] Embodiment 2

[0051] Figure 2 This is a flow chart of another allocation method of a microgrid control system provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment further optimizes the concurrent volume of business data by constructing a probability density function according to the business data volume and obtaining a probability function calculated by the probability density function. Figure 2 , the method specifically comprises the following steps:

[0052] S210. When it is determined that the current time of the current microgrid control system reaches a preset data processing cycle time, obtain the amount of service data to be allocated.

[0053] Optionally, after obtaining the amount of business data to be allocated, it also includes: obtaining the computational complexity of the business data amount and the data processing value of the business data amount; calculating the computational amount L of the business data amount according to the formula L=θb, where θ is the computational complexity and b is the data processing value.

[0054] The computational complexity may be a parameter for measuring the complexity of the business data volume calculation, and the parameter may be obtained through the microgrid control system. The data processing value may be the speed at which the microgrid control system can process business data per unit time. Specifically, the computational complexity θ is in cycle / bit, and the data processing value b is in bit.

[0055] The advantage of this setting is that by determining the computational complexity of the amount of business data to be allocated in the microgrid control system and the data processing value of the microgrid control system, the computational amount of the business data can be determined, thereby further determining the amount of resource configuration that the microgrid control system needs to provide. This allows for more reasonable allocation and processing of business data, reduces latency, and improves the reliability and timeliness of the microgrid control system.

[0056] S220. Construct a probability density function according to the business data volume, and obtain a first business data concurrency volume according to a probability function calculated by the probability density function.

[0057] S230. Obtain a resource configuration amount of the microgrid control system according to the first business data concurrency amount, the calculation amount of the business data amount, and a preset second optimization parameter model.

[0058] The second optimization parameter model may be a model that can optimize parameters, so as to obtain the best objective function value, that is, the minimum resource configuration amount of the microgrid control system. The resource configuration amount may be the business data of the microgrid control system processing the concurrent amount of the first business data, and the size of the resource configuration amount that needs to be provided.

[0059] Optionally, the resource configuration amount of the microgrid control system is obtained according to the first business data concurrency, the calculation amount of the business data amount and the preset second optimization parameter model, including: according to the preset second optimization parameter model formula Optimize the parameters and obtain the resource configuration of the microgrid control system, where R E is the resource allocation of the microgrid control system, r e The amount of computing resources provided for the edge computing microgrid control system, T e is the time delay of the microgrid control system, T max is the maximum delay required by the microgrid control system.

[0060] The delay of the microgrid control system may be the size of the calculation delay generated by calculating the business data of the first business data concurrency. The amount of computing resources may be the amount of resources configured by the microgrid control system for business data processing.

[0061] Specifically, the required maximum delay of the microgrid control system can be the maximum delay allowed by the microgrid control system, and the delay of controlling the microgrid control system is less than the required maximum delay of the microgrid control system, which can ensure that the business data of the first business data concurrency volume is processed more reasonably and effectively.

[0062] In this embodiment, specifically, constraint C1 ensures that the resource configuration amount of the microgrid control system is not a negative value, constraint C2 ensures that the computing resources provided by the edge computing microgrid control system do not exceed the resource configuration amount of the microgrid control system, and constraint C3 ensures that the delay of the microgrid control system is less than the delay constraint of the maximum delay required by the microgrid control system. Constraint C4 indicates that the delay of the microgrid control system is calculated by the concurrent amount of the first business data, the amount of business data, and the amount of computing resources provided by the edge computing microgrid control system.

[0063] The advantage of such a setting is that the resource configuration amount of the microgrid control system is obtained by the first business data concurrency, the calculation amount of the business data amount and the preset second optimization parameter model. In this way, the resource configuration amount obtained by the second optimization parameter model is more accurate, and the microgrid control system can configure resources more reasonably, thereby improving the utilization rate and business allocation capability of the microgrid control system.

[0064] S240: Calculate the remaining amount of business data to be allocated according to the amount of business data to be allocated and the concurrent amount of the first business data.

[0065] S250, calculating a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system.

[0066] S260. Allocate the remaining service data volume according to the first proportion parameter and the second proportion parameter.

[0067] The technical solution provided by the embodiment of the present invention obtains the amount of business data to be allocated when determining that the current time of the current microgrid control system reaches the preset data processing cycle time; constructs a probability density function according to the amount of business data, and obtains the first business data concurrency according to the probability function calculated by the probability density function; obtains the resource configuration amount of the microgrid control system according to the first business data concurrency, the calculation amount of the business data amount and the preset second optimization parameter model; calculates the remaining business data amount to be allocated according to the amount of business data to be allocated and the first business data concurrency; calculates the first proportion parameter and the second proportion parameter according to the preset first optimization parameter model and at least one real-time operation parameter of the microgrid control system; and allocates the remaining business data amount according to the first proportion parameter and the second proportion parameter. It can further determine the size of the resource configuration amount that the microgrid control system needs to provide, so that the allocation and processing of the business data amount can be more reasonably carried out, the delay can be reduced, and the reliability and timeliness of the microgrid control system can be improved. The microgrid control system can more reasonably configure resources, thereby improving the utilization rate and business allocation capability of the microgrid control system to better meet the real-time and reliability requirements of microgrid control.

[0068] Embodiment 3

[0069] Figure 3 : is a structural diagram of a distribution device of a microgrid control system provided in the third embodiment of the present invention. The distribution device of a microgrid control system provided in this embodiment can be implemented by software and / or hardware, and can be configured in a server or terminal device to implement a distribution method of a microgrid control system in the embodiment of the present invention. Figure 3 As shown, the device may specifically include: a business data volume acquisition module 310 to be allocated, a first business data concurrent volume determination module 320, a remaining business data volume calculation module 330 to be allocated, a ratio parameter calculation module 340 and a remaining business data volume allocation module 350.

[0070] The module 310 for acquiring the amount of business data to be allocated is used to acquire the amount of business data to be allocated when it is determined that the current time of the current microgrid control system reaches the preset data processing cycle time;

[0071] A first service data concurrency determination module 320, configured to construct a probability density function according to the service data volume, and obtain a first service data concurrency according to a probability function calculated by the probability density function;

[0072] The remaining service data volume calculation module 330 is used to calculate the remaining service data volume to be allocated according to the service data volume to be allocated and the first service data concurrency volume;

[0073] A proportional parameter calculation module 340, configured to calculate a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system;

[0074] The remaining service data volume allocation module 350 is used to allocate the remaining service data volume according to the first proportion parameter and the second proportion parameter.

[0075] The technical solution provided by the embodiment of the present invention obtains the amount of business data to be allocated when determining that the current time of the current microgrid control system reaches the preset data processing cycle time; constructs a probability density function according to the amount of business data, and obtains the first business data concurrency according to the probability function calculated by the probability density function; calculates the remaining business data amount to be allocated according to the amount of business data to be allocated and the first business data concurrency; calculates the first proportion parameter and the second proportion parameter according to the preset first optimization parameter model and at least one real-time operation parameter of the microgrid control system; and allocates the remaining business data amount according to the first proportion parameter and the second proportion parameter. The problem of fuzzy resource calculation and unreasonable allocation of charging pile control business in the microgrid control system is solved, and the reasonable allocation of computing resources and charging pile control business processing requirements is realized, and the processing capacity of the microgrid is improved to better meet the real-time and reliability requirements of microgrid control.

[0076] Based on the above embodiments, the first service data concurrency determination module 320 can be specifically used to: Construct the probability density function f(x,h); N is the amount of business data, K h is the kernel function, K(u) is the standard Gaussian kernel function, h is the preset bandwidth window, b i is the amount of business data in the i-th unit time; according to the formula Calculate the probability function F(x); according to the formula X = F -1 (λ), and calculate the concurrent volume X of the first business data, where λ is the concurrent probability value.

[0077] On the basis of the above embodiments, it also includes a business data volume calculation module, which can be specifically used to: after obtaining the business data volume to be allocated, obtain the calculation complexity of the business data volume and the data processing value of the business data volume; according to the formula L=θb, calculate the calculation volume L of the business data volume, where θ is the calculation complexity and b is the data processing value.

[0078] On the basis of the above embodiments, it also includes a resource configuration amount determination module, which can be specifically used to: after constructing a probability density function according to the business data volume and obtaining the first business data concurrency according to the probability function calculated by the probability density function, obtain the resource configuration amount of the microgrid control system according to the first business data concurrency, the calculation amount of the business data volume and the preset second optimization parameter model.

[0079] Based on the above embodiments, the resource allocation amount determination module can be specifically used to: according to the preset second optimization parameter model formula Optimize the parameters and obtain the resource configuration of the microgrid control system, where R E is the resource allocation of the microgrid control system, r e The amount of computing resources provided for the edge computing microgrid control system, T e is the time delay of the microgrid control system, T max is the maximum delay required by the microgrid control system.

[0080] Based on the above embodiments, the proportional parameter calculation module 340 can be specifically used to: calculate the proportional parameter according to the preset first optimization parameter model formula Get the first proportional parameter and the second proportional parameter; where T1 is the calculation and communication delay, T C Calculate the latency for the cloud computing center system, T b,C is the communication delay of the cloud computing center system, T E Calculate the latency for edge device systems, T b,E is the edge device system communication delay, r C The amount of computing resources provided to the cloud computing center system, r E The amount of computing resources provided to the edge device system, α C is the first scale parameter, α E is the second proportional parameter, B is the available channel bandwidth of the edge computing terminal, h is the channel gain, and P e is the edge computing terminal transmission power, σ 2 Represents the noise power of Gaussian white noise.

[0081] Based on the above embodiments, the remaining business data volume allocation module 350 can be specifically used to: multiply the remaining business data volume by the first proportional parameter to obtain the second business data concurrency, and allocate it to the cloud computing center system; multiply the remaining business data volume by the second proportional parameter to obtain the third business data concurrency, and allocate it to the edge device system.

[0082] The distribution device of the microgrid control system described above can execute the distribution method of the microgrid control system provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0083] Embodiment 4

[0084] Figure 4 is a structural diagram of a computer device provided by Embodiment 4 of the present invention. Figure 4 As shown, the device includes a processor 410, a memory 420, an input device 430, and an output device 440; the number of processors 410 in the device can be one or more. Figure 4 A processor 410 is taken as an example; the processor 410, memory 420, input device 430 and output device 440 in the device can be connected via a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0085] The memory 420, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the allocation method of the microgrid control system in the embodiment of the present invention (for example, a business data volume acquisition module 310 to be allocated, a first business data concurrent volume determination module 320, a remaining business data volume calculation module 330 to be allocated, a proportional parameter calculation module 340 and a remaining business data volume allocation module 350). The processor 410 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 420, that is, realizes the above-mentioned allocation method of the microgrid control system, which includes: when it is determined that the current time of the current microgrid control system reaches the preset data processing cycle time, obtaining the amount of business data to be allocated; constructing a probability density function according to the amount of business data, and obtaining the first business data concurrency according to the probability function calculated by the probability density function; calculating the remaining business data amount to be allocated according to the amount of business data to be allocated and the first business data concurrency; calculating the first proportion parameter and the second proportion parameter according to the preset first optimization parameter model and at least one real-time operation parameter of the microgrid control system; and allocating the remaining business data amount according to the first proportion parameter and the second proportion parameter.

[0086] The memory 420 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 420 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 420 may further include a memory remotely arranged relative to the processor 410, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0087] The input device 430 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 440 may include a display device such as a display screen.

[0088] Embodiment 5

[0089] Embodiment 5 of the present invention also provides a computer-readable storage medium, wherein the computer-readable instructions are used to execute a distribution method for a microgrid control system when executed by a computer processor, the method comprising: obtaining distribution network parameters of the distribution network to be tested at a preset time point, wherein the distribution network parameters include: obtaining the amount of business data to be allocated when it is determined that the current time of the current microgrid control system reaches a preset data processing cycle time; constructing a probability density function according to the amount of business data, and obtaining a first business data concurrency according to a probability function calculated by the probability density function; calculating the remaining business data amount to be allocated according to the amount of business data to be allocated and the first business data concurrency; calculating a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system; and allocating the remaining business data amount according to the first proportional parameter and the second proportional parameter.

[0090] Of course, the computer executable instructions of a storage medium containing computer-readable instructions provided in an embodiment of the present invention are not limited to the method operations described above, but can also execute related operations in the distribution method of the microgrid control system provided in any embodiment of the present invention.

[0091] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (FLASH), a hard disk or an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0092] It is worth noting that in the embodiment of the distribution device of the above-mentioned microgrid control system, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0093] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A distribution method for a microgrid control system, characterized in that: Executed by the microgrid control system, including: When it is determined that the current time of the current microgrid control system reaches the preset data processing cycle time, the amount of business data to be allocated is obtained; Constructing a probability density function according to the service data volume, and obtaining a first service data concurrency volume according to a probability function calculated by the probability density function; Calculating the remaining amount of business data to be allocated according to the amount of business data to be allocated and the concurrent amount of the first business data; Calculating a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system; Allocating the remaining service data volume according to the first proportion parameter and the second proportion parameter; The calculating of the first proportional parameter and the second proportional parameter according to the preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system includes: According to the preset first optimization parameter model formula Get a first scale parameter and a second scale parameter; Among them, T1 is the calculation and communication delay, T C Calculate the latency for the cloud computing center system, T b,C is the communication delay of the cloud computing center system, T E Calculate the latency for edge device systems, T b,E is the edge device system communication delay, r C The amount of computing resources provided to the cloud computing center system, r E The amount of computing resources provided to the edge device system, α C is the first scale parameter, α E is the second proportional parameter, B is the available channel bandwidth of the edge computing terminal, h is the channel gain, and P e is the edge computing terminal transmission power, σ 2 represents the noise power of Gaussian white noise, x off is the remaining business data volume, L is the calculation amount of the business data volume, and b is the data processing value.

2. The method according to claim 1, characterized in that Constructing a probability density function according to the service data volume, and obtaining a first service data concurrency volume according to a probability function calculated by the probability density function, including: According to the formula Construct the probability density function f(x,h); N is the amount of business data, K h is the kernel function, K(u) is the standard Gaussian kernel function, h is the preset bandwidth window, b i is the amount of business data in the i-th unit time; According to the formula Calculate the probability function F(x); According to the formula X = F -1 (λ), and calculate the concurrent volume X of the first business data, where λ is the concurrent probability value.

3. The method according to claim 2, characterized in that After obtaining the amount of service data to be allocated, the method further includes: Obtaining the computational complexity of the business data volume and the data processing value of the business data volume; According to the formula L=θb, the calculation amount L of the business data volume is calculated, where θ is the calculation complexity and b is the data processing value.

4. The method according to claim 3, characterized in that After constructing a probability density function according to the service data volume, and obtaining the first service data concurrency volume according to a probability function calculated by the probability density function, the method further includes: The resource configuration amount of the microgrid control system is obtained according to the first business data concurrency amount, the calculation amount of the business data amount and the preset second optimization parameter model.

5. The method according to claim 4, characterized in that The method of obtaining the resource configuration amount of the microgrid control system according to the first business data concurrency amount, the calculation amount of the business data amount and a preset second optimization parameter model includes: According to the preset second optimization parameter model formula Optimize the parameters to obtain the resource configuration of the microgrid control system, where R E is the resource allocation of the microgrid control system, r e The amount of computing resources provided for the edge computing microgrid control system, T e is the time delay of the microgrid control system, T max is the maximum delay required by the microgrid control system.

6. The method according to claim 1, characterized in that The allocating of the remaining service data volume according to the first proportion parameter and the second proportion parameter includes: The second concurrent business data volume is obtained by multiplying the first ratio parameter by the remaining business data volume, and the second concurrent business data volume is allocated to the cloud computing center system; The third business data concurrency is obtained by multiplying the second ratio parameter by the remaining business data volume, and is distributed to the edge device system.

7. A distribution device for a microgrid control system, characterized in that: Executed by the microgrid control system, including: A module for acquiring the amount of business data to be allocated, used to acquire the amount of business data to be allocated when it is determined that the current time of the current microgrid control system reaches a preset data processing cycle time; A first service data concurrency determination module, configured to construct a probability density function according to the service data volume, and obtain a first service data concurrency according to a probability function calculated by the probability density function; A module for calculating the amount of remaining business data to be allocated, used to calculate the amount of remaining business data to be allocated according to the amount of business data to be allocated and the concurrent amount of first business data; A proportional parameter calculation module, used to calculate a first proportional parameter and a second proportional parameter according to a preset first optimization parameter model and at least one real-time operating parameter of the microgrid control system; A remaining service data volume allocation module, used for allocating the remaining service data volume according to the first proportion parameter and the second proportion parameter; The proportional parameter calculation module is specifically used for: According to the preset first optimization parameter model formula Get a first scale parameter and a second scale parameter; Among them, T1 is the calculation and communication delay, T C Calculate the latency for the cloud computing center system, T b,C is the communication delay of the cloud computing center system, T E Calculate the latency for edge device systems, T b,E is the edge device system communication delay, r C The amount of computing resources provided to the cloud computing center system, r E The amount of computing resources provided to the edge device system, α C is the first scale parameter, α E is the second proportional parameter, B is the available channel bandwidth of the edge computing terminal, h is the channel gain, and P e is the edge computing terminal transmission power, σ 2 represents the noise power of Gaussian white noise, x off is the remaining business data volume, L is the calculation amount of the business data volume, and b is the data processing value.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the allocation method of the microgrid control system according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the distribution method of the microgrid control system as described in any one of claims 1 to 6 is implemented.

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