Adjustable resource allocation method and device based on edge cluster system

Abstract

The invention provides an adjustable resource allocation method and device based on an edge cluster system, and the method comprises the steps: carrying out the classification according to the characteristics of all active adjustable resources, and obtaining a plurality of adjustable resource objects; resource allocation is carried out according to the distributed resource control quantity in combination with allocation control algorithms corresponding to different adjustable resource objects, an adjustable resource allocation strategy is generated, and the distributed resource control quantity represents the sum of the adjustable quantities of all the adjustable resource objects in different operation states. The adjustable quantity is the total quantity of the adjustable resource object which can participate in resource adjustment at present; and issuing an adjustable resource allocation strategy to the corresponding adjustable resource object in the distribution network area so as to complete active adjustment control of the distribution network area. According to the method, the problem that in the prior art, related research of a new energy active power automatic control adjustable resource analysis method is lacked, and the construction requirement of a cloud edge fusion intelligent scheduling operation platform edge cluster system cannot be met to carry out active power adjustment control is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy resource allocation, and in particular to an adjustable resource allocation method based on an edge cluster system, an adjustable resource allocation device based on an edge cluster system, a computer-readable storage medium, and a computer program product. Background Art

[0002] At present, the construction of the edge cluster system of the cloud-edge integrated intelligent dispatching and operation platform (CEP) requires the realization of monitoring and control functions for new grid-connected entities, providing important technical support for the "observable, measurable and controllable" source, network, load and storage resources under the new power system. However, there is currently a lack of relevant research on the analysis methods and systems of adjustable resources for automatic control of new energy active power, which cannot meet the construction requirements of the edge cluster system of the cloud-edge integrated intelligent dispatching and operation platform (CEP). It is urgent to carry out research on the analysis methods and systems of adjustable resources for automatic control of new energy active power, combine the classification of adjustable resource characteristics and conduct research on adjustable resource allocation algorithms, and realize the analysis, generation and distribution of adjustable resource strategies. Summary of the invention

[0003] The main purpose of this application is to provide an adjustable resource allocation method based on an edge cluster system, an adjustable resource allocation device based on an edge cluster system, a computer-readable storage medium and a computer program product, so as to at least solve the problem that there is a lack of relevant research on adjustable resource analysis methods for automatic control of active power of new energy in the prior art, and it is unable to meet the requirements of the edge cluster system construction of the cloud-edge fusion intelligent scheduling and operation platform to perform active regulation and control.

[0004] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for allocating adjustable resources based on an edge cluster system is provided, including: classifying all active adjustable resources according to their own characteristics to obtain a plurality of adjustable resource objects, wherein the adjustable resource objects are divided into at least energy storage resources, adjustable load resources and distributed power sources; allocating resources according to the distributed resource control amount combined with the allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, wherein the distributed resource control amount represents the sum of the adjustable amounts of all the adjustable resource objects under different operating states, and the adjustable amount is the total amount of resource regulation that the adjustable resource objects can currently participate in, and the allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; and issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active regulation control of the distribution network area.

[0005] Optionally, before allocating resources according to the distributed resource control amount in combination with the allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method also includes: real-time monitoring of the operating status of each of the adjustable resource objects, the operating status including a grid-connected operating status or an off-grid operating status; calculating the total adjustment amount corresponding to the adjustable resource object according to the grid resource demand of the distribution network area and the operating status corresponding to the adjustable resource object; adding the adjustable amounts of all the adjustable resource objects to obtain the distributed resource control amount.

[0006] Optionally, before allocating resources according to the distributed resource control amount in combination with the allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method further includes: determining a charging allocation algorithm according to the state of charge and maximum charging power of the energy storage station, wherein the charging allocation algorithm is to sort the energy storage stations from small to large according to the state of charge, and the energy storage stations with small state of charge are allocated preferentially until the maximum charging power is reached; determining a discharging allocation algorithm according to the state of charge and maximum discharging power of the energy storage stations, wherein the charging allocation algorithm is to sort the energy storage stations from large to small according to the state of charge, and the energy storage stations with large state of charge are allocated preferentially until the maximum discharging power is reached; and determining the energy storage resource allocation algorithm according to the charging allocation algorithm and the discharging allocation algorithm.

[0007] Optionally, before allocating resources according to the distributed resource control amount in combination with the allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method also includes: determining a first allocation condition, the first allocation condition including priority sorting, the size of the adjustable load resource and the adjustment rate of the adjustable load resource; when the first allocation condition is the priority sorting, determining a first adjustable load resource allocation algorithm according to the priority corresponding to the adjustable load resource, the first adjustable load resource allocation algorithm is to sort the adjustable load resources according to the priority and adjust the adjustable load resources with high priority with an adjustment step until the total adjustment demand is zero; when the first allocation condition is the size of the adjustable load resource In the following, a second adjustable load resource allocation algorithm is determined according to the size ratio of each of the adjustable load resources, and the second adjustable load resource allocation algorithm is to preferentially adjust the adjustable load resources with a higher proportion according to the size ratio of the adjustable load resources until the total adjustment demand is zero; when the first allocation condition is the adjustment rate of the adjustable load resources, a third adjustable load resource allocation algorithm is determined according to the adjustment rate of each of the adjustable load resources, and the third adjustable load resource allocation algorithm is to select the adjustable load resources corresponding to the corresponding adjustment rate according to the adjustment time requirement and the adjustment capability; the adjustable load resource allocation algorithm is determined according to the first adjustable load resource allocation algorithm, the second adjustable load resource allocation algorithm and the third adjustable load resource allocation algorithm.

[0008] Optionally, before allocating resources according to the distributed resource control amount in combination with the allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method further includes: determining a second allocation condition, the second allocation condition including the installed capacity ratio, real-time load rate ranking and utilization hour ranking of distributed power sources; when the second allocation condition is the installed capacity ratio, allocating the distributed resource control amount according to the installed capacity ratio of each distributed power source is determined as the first distributed power source allocation algorithm; when the second allocation condition is the installed capacity ratio and real-time load rate ranking, the distributed power sources are sorted according to their current load rates and the distributed power sources with the lowest current load rate are preferentially allocated the distributed resource control amount, which is determined as the second distributed power source allocation algorithm; when the second allocation condition is the utilization hour ranking, the distributed power sources are sorted according to their utilization hours, the distributed power sources with high utilization hours are preferentially assigned to the lower regulation demand and the distributed power sources with low utilization hours are preferentially assigned to the upper regulation demand, which is determined as the third distributed power source allocation algorithm; the distributed power source allocation algorithm is determined as the first distributed power source allocation algorithm, the second distributed power source allocation algorithm and the third distributed power source allocation algorithm.

[0009] Optionally, resource allocation is performed according to the distributed resource control amount in combination with the allocation control algorithms corresponding to different adjustable resource objects, and an adjustable resource allocation strategy is generated, including: determining a corresponding allocation strategy according to the distribution network state of the distribution network area, the allocation strategy being the adjustment sequence of the energy storage resources, the adjustable load resources and the distributed power sources, the distribution network state including at least one of the following: a voltage suppression reverse supply state and a low power output state, the voltage suppression reverse supply state being a phenomenon in which power is transmitted from a low-voltage power grid to a high-voltage power grid; performing resource allocation for different allocation strategies according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the adjustable resource objects, and generating an adjustable resource allocation strategy.

[0010] Optionally, a corresponding allocation strategy is determined according to the distribution network status of the distribution network area, and an adjustable resource allocation strategy is generated, including: when the distribution network status is the voltage suppression reverse supply state, determining the allocation strategy to give priority to local consumption processing, and secondly to adopt regulated external transmission processing, local consumption processing is to consume excess electricity in the distribution network area, and the regulated external transmission processing is to adjust the external transmission to other distribution network areas for processing when the distribution network area cannot completely consume the excess electricity; when the distribution network status is the low power output state, determining the allocation strategy to give priority to adjusting the energy storage resources, secondly to reducing the adjustable load resources, and finally to adjusting the distributed power sources.

[0011] According to another aspect of the present application, there is provided an adjustable resource allocation device based on an edge cluster system, the device comprising: a classification unit, for classifying all active adjustable resources according to their own characteristics to obtain a plurality of adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources; a generation unit, for performing resource allocation according to a distributed resource control amount in combination with an allocation control algorithm corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, wherein the distributed resource control amount represents the sum of the adjustable amounts of all the adjustable resource objects under different operating states, the adjustable amount is the total amount of resource regulation that the adjustable resource objects can currently participate in, and the allocation control algorithm comprises an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; a issuing unit, for issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in a distribution network area to complete the active regulation control of the distribution network area.

[0012] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0013] According to another aspect of the present application, a computer program product is provided, comprising computer instructions, wherein when the computer instructions are executed by a processor, any one of the methods described above is implemented.

[0014] Applying the technical solution of the present application, in an adjustable resource allocation method based on an edge cluster system, first, all active adjustable resources are classified according to their own characteristics to obtain a variety of adjustable resource objects, and the above-mentioned adjustable resource objects are divided into at least energy storage resources, adjustable load resources and distributed power sources; then, according to the distributed resource control amount combined with the allocation control algorithms corresponding to the different above-mentioned adjustable resource objects to perform resource allocation, an adjustable resource allocation strategy is generated, the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; finally, the above-mentioned adjustable resource allocation strategy is issued to the above-mentioned adjustable resource objects corresponding to the distribution network area to complete the active regulation control of the above-mentioned distribution network area. This application classifies active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources, in combination with the characteristics of adjustable resources, and studies the adjustable resource allocation algorithm, thereby realizing the analysis and generation of adjustable resource strategies. Under the premise of ensuring the safe operation of the regional power grid, it monitors the reverse transmission of active power flow, voltage over-limit, and load rate over-limit, and manages the absorption status of distributed new energy, supporting the peak-shaving capacity and power balancing capacity of the regional power grid. This application solves the problem that the prior art lacks relevant research on the analysis method of adjustable resources for active automatic control of new energy, and cannot meet the requirements of the construction of the edge cluster system of the cloud-edge fusion intelligent scheduling and operation platform for active regulation and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A hardware structure block diagram of a mobile terminal for executing an adjustable resource allocation method based on an edge cluster system provided in an embodiment of the present application is shown;

[0016] Figure 2 A schematic diagram of a process of an adjustable resource allocation method based on an edge cluster system provided according to an embodiment of the present application is shown;

[0017] Figure 3 A structural block diagram of an adjustable resource allocation device based on an edge cluster system provided according to an embodiment of the present application is shown.

[0018] The above drawings include the following reference numerals:

[0019] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising 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.

[0023] As introduced in the background technology, the prior art lacks relevant research on the analysis method and system of adjustable resources for automatic active control of new energy, and cannot meet the requirements for building an edge cluster system of a cloud-edge fusion intelligent scheduling and operation platform (CEP). In order to solve the problem that there is a lack of relevant research on the analysis method and system of adjustable resources for automatic active control of new energy, and cannot meet the requirements for building an edge cluster system of a cloud-edge fusion intelligent scheduling and operation platform to perform active regulation and control, the embodiments of the present application provide an adjustable resource allocation method based on an edge cluster system, an adjustable resource allocation device based on an edge cluster system, a computer-readable storage medium and a computer program product.

[0024] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0025] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 1 is a hardware structure block diagram of a mobile terminal according to an embodiment of the present invention, based on an adjustable resource allocation method in an edge cluster system. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0026] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the adjustable resource allocation method based on the edge cluster system in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal 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 a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific network example may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0027] In this embodiment, an adjustable resource allocation method based on an edge cluster system running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0028] Figure 2 1 is a flow chart of an adjustable resource allocation method based on an edge cluster system according to an embodiment of the present application. Figure 2As shown, the method comprises the following steps:

[0029] Step S201, classifying all active adjustable resources according to their own characteristics to obtain a plurality of adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources.

[0030] Specifically, identify and list all active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources. Classify these resource objects according to their own characteristics (such as response time, adjustment capability, operating status, etc.). For example, energy storage resources can be classified according to their charge and discharge power and SOC (State of Charge) status; adjustable loads can be classified according to their adjustment capability and priority; and distributed power sources can be classified according to their installed capacity and real-time load rate. Ensure that different types of resources are reasonably used at the right time and place.

[0031] Step S202, performing resource allocation according to the distributed resource control quantity in combination with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects, and generating an adjustable resource allocation strategy, wherein the above-mentioned distributed resource control quantity represents the sum of the adjustable quantities of all the above-mentioned adjustable resource objects under different operating states, and the above-mentioned adjustable quantity is the total amount of resource regulation that the above-mentioned adjustable resource objects can currently participate in, and the above-mentioned allocation control algorithms include energy storage resource allocation algorithm, adjustable load resource allocation algorithm and distributed power supply allocation algorithm.

[0032] Specifically, based on resource classification, the system will allocate resources according to the distributed resource control quantity (i.e., the sum of the adjustable quantities of all adjustable resource objects under different operating conditions) and the allocation control algorithms corresponding to different resource objects. The energy storage resource allocation algorithm determines the priority of charging or discharging, as well as the allocated power, based on the SOC (State of Charge) of the energy storage device. The adjustable load resource allocation algorithm allocates adjustment tasks based on the priority, size, and adjustment rate of the load. The distributed power supply allocation algorithm allocates power generation tasks based on the installed capacity ratio, real-time load rate, and utilization hours.

[0033] Step S203: issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control in the distribution network area.

[0034] Specifically, after the adjustable resource allocation strategy is generated, the system sends these adjustable resource allocation strategies to the corresponding adjustable resource objects in the distribution network area to complete the active regulation control in the distribution network area, ensure the stable operation of the power grid and optimize resource utilization. The purpose of the entire process is to effectively manage and control the active adjustable resources below 10kV, monitor the active power flow reverse transmission, voltage limit and load rate limit, and control the consumption status of distributed new energy, thereby supporting the peak regulation capacity and power balance capacity of the regional power grid.

[0035] In this embodiment, first, all active adjustable resources are classified according to their own characteristics to obtain a variety of adjustable resource objects, and the above-mentioned adjustable resource objects are divided into at least energy storage resources, adjustable load resources and distributed power sources; then, according to the distributed resource control amount and the allocation control algorithms corresponding to the different above-mentioned adjustable resource objects, resources are allocated to generate an adjustable resource allocation strategy, the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; finally, the above-mentioned adjustable resource allocation strategy is issued to the above-mentioned adjustable resource objects corresponding to the distribution network area to complete the active regulation control of the above-mentioned distribution network area. This application classifies active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources, in combination with the characteristics of adjustable resources, and studies the adjustable resource allocation algorithm, thereby realizing the analysis and generation of adjustable resource strategies. Under the premise of ensuring the safe operation of the regional power grid, it monitors the reverse transmission of active power flow, voltage over-limit, and load rate over-limit, and manages the absorption status of distributed new energy, supporting the peak-shaving capacity and power balancing capacity of the regional power grid. This application solves the problem that the prior art lacks relevant research on the analysis method of adjustable resources for active automatic control of new energy, and cannot meet the requirements of the construction of the edge cluster system of the cloud-edge fusion intelligent scheduling and operation platform for active regulation and control.

[0036] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the adjustable resource allocation method based on the edge cluster system of the present application will be described in detail below in combination with specific embodiments.

[0037] In order to ensure that the regulation amount of each resource object matches its capacity and grid demand and avoid excessive or insufficient regulation, in an optional implementation manner, before the above step S202, the method further includes:

[0038] Step S301, real-time monitoring of the operating state of each of the above adjustable resource objects, the above operating state including a grid-connected operating state or an off-grid operating state;

[0039] Step S302, calculating the total adjustment amount corresponding to the above adjustable resource object according to the grid resource demand of the above distribution network area and the operating state corresponding to the above adjustable resource object;

[0040] Step S303: Add the adjustable amounts of all the adjustable resource objects to obtain the distributed resource control amount.

[0041] In the above embodiment, the operation data of adjustable resource objects such as energy storage, adjustable load, and distributed power source are collected in real time through intelligent sensors and monitoring systems. It is identified whether each resource object is in a grid-connected operation state or an off-grid operation state. The grid-connected operation state refers to the resource object being connected to the grid and participating in the power supply and distribution of the grid, while the off-grid operation state refers to the resource object operating independently of the grid. The monitoring system needs to be able to update the status of each resource object in real time so as to respond to changes in grid demand in a timely manner. According to the real-time demand of the grid, the amount of power support that each adjustable resource object needs to provide is analyzed. The grid resource demand is matched with the operating state of each resource object, and the adjustment amount that each resource object should bear is calculated. For each resource object, the total adjustment amount that it can provide is calculated according to its characteristics and capabilities, ensuring that the adjustment amount of each resource object matches its capabilities and grid demand, and avoiding excessive or insufficient adjustment. The adjustable amounts of all adjustable resource objects are added together to obtain the distributed resource control amount. By summarizing the adjustment amounts of all resources, the grid operator can respond to changes in grid demand more flexibly.

[0042] In order to optimize the use of energy storage resources and improve the energy efficiency of energy storage resources, in an optional implementation manner, before the above step S202, the method further includes:

[0043] Step S401, determining a charging allocation algorithm according to the state of charge and maximum charging power of the energy storage stations, wherein the charging allocation algorithm is to sort the energy storage stations according to the state of charge from small to large, and the energy storage stations with small state of charge are allocated first until the maximum charging power is reached;

[0044] Step S402, determining a discharge allocation algorithm according to the state of charge and maximum discharge power of the energy storage stations, wherein the charge allocation algorithm is to sort the energy storage stations according to the state of charge from large to small, and the energy storage stations with large state of charge are allocated first until the maximum discharge power is reached;

[0045] Step S403: determining the energy storage resource allocation algorithm according to the charging allocation algorithm and the discharging allocation algorithm.

[0046] In the above embodiment, the energy storage resource allocation algorithm is an algorithm for allocating energy storage stations according to the state of charge of the energy storage stations and the maximum charge and discharge power. Charging allocation: charging is sorted from small to large according to the percentage of energy storage stations; the energy storage stations with a small percentage of energy are allocated first, and the target power is the maximum charging power of each energy storage station. The energy storage stations that have been fully charged are excluded in each allocation. Discharging allocation: discharging is sorted from large to small according to the percentage of energy storage stations; the energy storage stations with a large percentage of energy are allocated first, and the target power is the maximum discharge power of each energy storage station. The energy storage stations that have been fully discharged are excluded in each allocation. The implementation process of the charging allocation algorithm: First, the state of charge (SOC) of all energy storage stations is monitored and sorted from small to large according to the SOC value. The SOC value represents the percentage of the current power of the energy storage station. A lower SOC value means that the energy storage station has less power. After sorting, the energy storage stations with smaller SOC values ​​are given priority for charging allocation, because these stations have lower power and need to be replenished first. For each energy storage station, the allocated charging power will not exceed its maximum charging power. Once the energy storage station reaches its maximum charging power, or the SOC value reaches the preset threshold, the station will be removed from the charging queue and no longer be allocated for charging. By giving priority to charging energy storage stations with lower power, energy storage resources can be used more effectively and over-discharge of some stations can be avoided. The implementation process of the discharge allocation algorithm: Similar to charging allocation, the SOC values ​​of all energy storage stations are first monitored and sorted from large to small according to the SOC value. A higher SOC value means that the energy storage station has more power. After sorting, the energy storage stations with larger SOC values ​​are preferentially allocated for discharge, because these stations have more power and can be released first. For each energy storage station, the allocated discharge power will not exceed its maximum discharge power. Once the energy storage station reaches its maximum discharge power, or the SOC value drops to the preset threshold, the station will be removed from the discharge queue and no longer be allocated for discharge. By giving priority to discharging energy storage stations with more power, the frequency regulation needs of the power grid can be quickly responded to and the necessary power support can be provided. Combine the determined charging allocation algorithm and discharging allocation algorithm to form a complete energy storage resource allocation algorithm. Through reasonable charging and discharging allocation, the energy efficiency of energy storage resources can be improved and energy waste can be reduced.

[0047] In order to improve the energy efficiency of adjustable load resources, in an optional implementation manner, before the above step S202, the method further includes:

[0048] Step S501, determining a first allocation condition, wherein the first allocation condition includes priority sorting, the size of the adjustable load resource, and the adjustment rate of the adjustable load resource;

[0049] Step S502, when the first allocation condition is the priority sorting, determining a first adjustable load resource allocation algorithm according to the priority corresponding to the adjustable load resources, wherein the first adjustable load resource allocation algorithm is to sort the adjustable load resources according to the priority and adjust the adjustable load resources with high priority by an adjustment step until the total adjustment demand is zero;

[0050] Step S503, when the first allocation condition is the size of the adjustable load resources, a second adjustable load resource allocation algorithm is determined according to the size ratio of each of the adjustable load resources, wherein the second adjustable load resource allocation algorithm is to preferentially adjust the adjustable load resources with a high proportion according to the size ratio of the adjustable load resources until the total adjustment demand is zero;

[0051] Step S504: when the first allocation condition is the adjustment rate of the adjustable load resources, a third adjustable load resource allocation algorithm is determined according to the adjustment rate of each of the adjustable load resources, wherein the third adjustable load resource allocation algorithm is to select the adjustable load resources corresponding to the corresponding adjustment rate according to the adjustment time requirement and the adjustment capability;

[0052] Step S505: determining the adjustable load resource allocation algorithm according to the first adjustable load resource allocation algorithm, the second adjustable load resource allocation algorithm and the third adjustable load resource allocation algorithm.

[0053] In the above embodiment, the above adjustable load resource allocation algorithm is an algorithm that adjusts according to the above adjustable load resources until the total adjustment demand is zero. The above total adjustment demand is the adjustment amount that other business systems need the local edge cluster system to participate in. The adjustable load resource allocation algorithm mainly includes: (1) Manual priority sorting: sorting according to the manually preset priority, the load with high priority bears the adjustment amount according to the adjustment step until the total adjustment demand is zero, and the manual priority adjustment can be achieved by modifying the priority factor; the priority is the default setting, and manual adjustment is supported at the same time. The proportion of the influence factor of the manual adjustment priority is adjusted to achieve the priority adjustment. Priority sorting ensures that key load resources (such as hospitals, data centers, etc.) are met first when resources are tight. By adjusting the step control, the total adjustment demand can be gradually met to avoid excessive use of resources. (2) Adjustable load size: according to the size ratio of the adjustable load, the allocation strategy is determined. The load with a large proportion is adjusted first, and the load with a small proportion is adjusted later until the total adjustment demand is zero. By considering the size ratio of resources, the adjustment tasks can be allocated more reasonably to avoid excessive burden on small-scale resources. Prioritizing the adjustment of large resources can quickly respond to adjustment needs and improve adjustment efficiency. (3) Adjustable load adjustment rate: The adjustment capacity of the adjustable load can be divided into seconds, minutes, and hours. When adjusting the load, the adjustment rate of the load must be taken into consideration. According to the adjustment time requirements, the load with the appropriate adjustment rate should be called. Considering the adjustment rate can ensure that resources respond to the adjustment requirements within the appropriate time and improve the response speed. Selecting resources according to the adjustment rate can avoid the ineffective use of resources and improve resource utilization efficiency. The final adjustable load resource allocation algorithm is determined by combining the above three allocation algorithms (priority sorting, resource size ratio, and adjustment rate). The adjustable load resource allocation algorithm will comprehensively consider all factors to achieve the optimal resource allocation.

[0054] In order to optimize the control and allocation of distributed resources in the power system, in an optional implementation manner, before the above step S202, the method further includes:

[0055] Step S601, determining a second allocation condition, wherein the second allocation condition includes the installed capacity ratio, real-time load rate ranking and utilization hours ranking of distributed power sources;

[0056] Step S602, when the second allocation condition is the installed capacity ratio, allocating the distributed resource control amount according to the installed capacity ratio of each of the distributed power sources is determined as a first distributed power source allocation algorithm;

[0057] Step S603, when the second allocation condition is the real-time load rate ranking of the installed capacity ratio, the distributed resource control amount is allocated preferentially to the distributed power sources ranked according to the current load rates of the distributed power sources and the distributed power sources with the lowest current load rates, and the second distributed power source allocation algorithm is determined;

[0058] Step S604, when the second allocation condition is the sorting by utilization hours, the distributed power sources are sorted by utilization hours, the distributed power sources with high utilization hours take priority to bear the lower regulation demand and the distributed power sources with low utilization hours take priority to bear the upper regulation demand, and the third distributed power source allocation algorithm is determined;

[0059] Step S605: determining the distributed power allocation algorithm as the distributed power allocation algorithm according to the first distributed power allocation algorithm, the second distributed power allocation algorithm and the third distributed power allocation algorithm.

[0060] In the above embodiment, the above distributed power allocation algorithm is an algorithm for allocating resources according to the above distributed power. The distributed power allocation algorithm mainly includes: (1) installed capacity ratio: share the total regulation amount according to the installed capacity ratio. (2) real-time load rate sorting: sort according to the current load rate of the power source, and the power source with a low load rate shall take the regulation amount first. (3) utilization hours sorting: sort according to the utilization hours of the power source, and the power source with a high utilization hour shall take the lower regulation demand first, and vice versa. The above first distributed power allocation algorithm allocates the control amount according to the installed capacity ratio of each distributed power source, ensuring that the power source with a larger installed capacity takes more regulation responsibility, which is proportional to its capacity. The above second distributed power allocation algorithm sorts according to the current load rate of the distributed power source, and preferentially allocates the control amount to the power source with the lowest load rate. The power sources that have not been fully utilized can be used preferentially, thereby improving the overall efficiency. By giving priority to the power sources with a low load rate, the pressure on the high-load power source can be reduced and its service life can be extended. The second distributed power allocation algorithm is to sort the distributed power sources according to their utilization hours. Power sources with high utilization hours take priority in taking on the downward regulation demand, while power sources with low utilization hours take priority in taking on the upward regulation demand. This method takes into account the frequency of use of power sources and ensures the balanced use of power sources. It can avoid overuse of some power sources and underuse of other power sources, thereby extending the service life of all power sources and improving the reliability of the system. The first distributed power allocation algorithm, the second distributed power allocation algorithm and the third distributed power allocation algorithm are combined to form a complete distributed power allocation algorithm, which aims to optimize the control and allocation of distributed resources in the power system and improve the efficiency, stability and reliability of the system. By considering different allocation conditions, the algorithm can adapt to different grid states and needs, thereby achieving better power resource management.

[0061] Explanation of terms: Utilization hours refers to the number of operating hours of the average power generation equipment capacity in a region under full load operation regulation within a certain period of time, that is, the ratio of power generation to average installed capacity. It reflects the utilization rate of power generation equipment in the region and is also one of the main indicators reflecting the power supply and demand situation in the region.

[0062] The installed capacity ratio refers to the proportion of the installed capacity of a distributed power source to the total installed capacity.

[0063] In order to help improve the stability and efficiency of the power grid, in an optional implementation manner, the above step S202 includes:

[0064] Step S2021, determining a corresponding allocation strategy according to the distribution network state of the distribution network area, the allocation strategy being the adjustment sequence of the energy storage resources, the adjustable load resources and the distributed power sources, the distribution network state including at least one of the following: a voltage suppression reverse supply state and a low power output state, the voltage suppression reverse supply state being a phenomenon in which power is transmitted from a low voltage power grid to a high voltage power grid;

[0065] Step S2022: performing resource allocation for different allocation strategies according to the distributed resource control amount and the allocation control algorithm corresponding to the adjustable resource object, and generating an adjustable resource allocation strategy.

[0066] In the above embodiment, the system first needs to monitor the grid status of the distribution network area in real time, including key parameters such as voltage level, power flow direction and power output. According to the monitored data, the system identifies whether the current distribution network status belongs to the voltage suppression reverse supply state or the low power output state. The voltage suppression reverse supply state refers to the phenomenon that power is transmitted from the low-voltage power grid to the high-voltage power grid, which may cause power grid stability problems. The low power output state refers to the state where the power supply is insufficient and cannot meet the current demand. According to the identified distribution network status, the system determines the corresponding resource allocation strategy. These strategies will guide the subsequent resource allocation to optimize the performance of the power grid. By identifying the power grid status and determining the corresponding strategy, the instability of the power grid caused by voltage suppression reverse supply and low power output can be prevented. According to different power grid states, the energy storage resources, adjustable load resources and distributed power sources are reasonably allocated to improve resource utilization efficiency and reduce energy waste. According to the determined allocation strategy, the system will apply the corresponding allocation control algorithm to allocate resources to the energy storage resources, adjustable load resources and distributed power sources. Based on the results calculated by the above algorithm, the system generates a specific adjustable resource allocation strategy, which helps to improve the stability and efficiency of the power grid, while supporting the peak-shaving and power balancing capabilities of the power grid, and providing technical support for the absorption of new energy and the sustainable development of the power grid.

[0067] In order to flexibly adjust resource allocation, in an optional implementation manner, the above step S2022 includes:

[0068] Step S20221, when the distribution network state is the voltage suppression reverse supply state, determine the allocation strategy to preferentially adopt local consumption processing, and secondly adopt regulation and external transmission processing, the local consumption processing is to consume excess power in the distribution network area, and the regulation and external transmission processing is to adjust and transmit to other distribution network areas for processing when the distribution network area cannot completely consume the excess power;

[0069] Step S20222, when the distribution network state is the low power output state, determine the allocation strategy to prioritize adjusting the energy storage resources, then reduce the adjustable load resources, and finally adjust the distributed power sources.

[0070] In the above embodiment, when suppressing reverse supply, local consumption is preferred, followed by regulating external transmission; when increasing output, energy storage is preferred, followed by reducing adjustable loads. Automatically issue control strategies to adjustable resources in the distribution network area to complete active regulation and control in the distribution network area. Specific implementation process: First, the system needs to identify whether the current distribution network state is a voltage suppression reverse supply state. This is usually achieved by monitoring the voltage level and flow direction of the distribution network. Local consumption processing: After confirming that the distribution network is in a voltage suppression reverse supply state, the system will give priority to the local consumption strategy. This means looking for resources that can consume excess power in the distribution network area, such as adjustable loads or energy storage devices, to reduce or eliminate reverse power. Regulating external transmission processing: If the resources in the distribution network area cannot completely consume the excess power, the system will start the regulation external transmission strategy. This involves transmitting excess power to other distribution network areas through the power grid to reduce the pressure on the current distribution network. Through local consumption and regulated external transmission, the voltage level can be effectively controlled to prevent equipment damage or safety accidents caused by excessive voltage. The system identifies whether the current distribution network status is a low power output state, usually by monitoring power generation and load demand. After confirming that the power output is low, the system will give priority to adjusting energy storage resources. This may include starting the discharge program of energy storage equipment to supplement the power supply of the power grid. If the energy storage resources are not sufficient to meet the power demand, the system will cut the adjustable load resources, that is, reduce the power consumption of certain non-critical loads. Finally, if the first two steps still cannot meet the power demand, the system will adjust distributed power sources, such as wind or solar power generation, to increase the power supply. When facing different operating conditions, the power grid can flexibly adjust resource allocation to ensure the safe, stable and efficient operation of the power grid.

[0071] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0072] The embodiment of the present application also provides an adjustable resource allocation device based on an edge cluster system. It should be noted that the adjustable resource allocation device based on an edge cluster system in the embodiment of the present application can be used to execute the adjustable resource allocation method based on an edge cluster system provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and those that have been described will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0073] The following introduces an adjustable resource allocation device based on an edge cluster system provided in an embodiment of the present application.

[0074] Figure 3 It is a structural block diagram of an adjustable resource allocation device based on an edge cluster system according to an embodiment of the present application.

[0075] like Figure 3 As shown, the device comprises:

[0076] The classification unit 10 is used to classify all active adjustable resources according to their own characteristics to obtain a variety of adjustable resource objects, and the above adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources.

[0077] Specifically, identify and list all active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources. Classify these resource objects according to their own characteristics (such as response time, adjustment capability, operating status, etc.). For example, energy storage resources can be classified according to their charge and discharge power and SOC (State of Charge) status; adjustable loads can be classified according to their adjustment capability and priority; and distributed power sources can be classified according to their installed capacity and real-time load rate. Ensure that different types of resources are reasonably used at the right time and place.

[0078] The generation unit 20 is used to perform resource allocation according to the distributed resource control quantity in combination with the allocation control algorithms corresponding to the different adjustable resource objects, and generate an adjustable resource allocation strategy. The distributed resource control quantity represents the sum of the adjustable quantities of all the adjustable resource objects under different operating conditions. The adjustable quantity is the total amount of resource regulation that the adjustable resource objects can currently participate in. The allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm.

[0079] Specifically, based on resource classification, the system will allocate resources according to the distributed resource control quantity (i.e., the sum of the adjustable quantities of all adjustable resource objects under different operating conditions) and the allocation control algorithms corresponding to different resource objects. The energy storage resource allocation algorithm determines the priority of charging or discharging, as well as the allocated power, based on the SOC (State of Charge) of the energy storage device. The adjustable load resource allocation algorithm allocates adjustment tasks based on the priority, size, and adjustment rate of the load. The distributed power supply allocation algorithm allocates power generation tasks based on the installed capacity ratio, real-time load rate, and utilization hours.

[0080] The issuing unit 30 is used to issue the above-mentioned adjustable resource allocation strategy to the above-mentioned adjustable resource objects corresponding to the above-mentioned adjustable resource objects in the distribution network area, so as to complete the active power regulation control of the above-mentioned distribution network area.

[0081] Specifically, after the adjustable resource allocation strategy is generated, the system sends these adjustable resource allocation strategies to the corresponding adjustable resource objects in the distribution network area to complete the active regulation control in the distribution network area, ensure the stable operation of the power grid and optimize resource utilization. The purpose of the entire process is to effectively manage and control the active adjustable resources below 10kV, monitor the active power flow reverse transmission, voltage limit and load rate limit, and control the consumption status of distributed new energy, thereby supporting the peak regulation capacity and power balance capacity of the regional power grid.

[0082] In this embodiment, a classification unit is used to classify all active adjustable resources according to their own characteristics to obtain a variety of adjustable resource objects, and the above-mentioned adjustable resource objects are divided into at least energy storage resources, adjustable load resources and distributed power sources; a generation unit is used to perform resource allocation according to the distributed resource control amount combined with the allocation control algorithms corresponding to the different above-mentioned adjustable resource objects to generate an adjustable resource allocation strategy, the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; a sending unit is used to send the above-mentioned adjustable resource allocation strategy to the above-mentioned adjustable resource objects corresponding to the distribution network area to complete the active regulation control of the above-mentioned distribution network area. This application classifies active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources, in combination with the characteristics of adjustable resources, and studies the adjustable resource allocation algorithm, thereby realizing the analysis and generation of adjustable resource strategies. Under the premise of ensuring the safe operation of the regional power grid, it monitors the reverse transmission of active power flow, voltage over-limit, and load rate over-limit, and manages the absorption status of distributed new energy, supporting the peak-shaving capacity and power balancing capacity of the regional power grid. This application solves the problem that the prior art lacks relevant research on the analysis method of adjustable resources for active automatic control of new energy, and cannot meet the requirements of the construction of the edge cluster system of the cloud-edge fusion intelligent scheduling and operation platform for active regulation and control.

[0083] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the adjustable resource allocation method based on the edge cluster system of the present application will be described in detail below in combination with specific embodiments.

[0084] In order to ensure that the regulation amount of each resource object matches its capacity and grid demand and avoid excessive or insufficient regulation, in an optional implementation manner, the device further includes:

[0085] A monitoring unit, configured to monitor in real time the operating state of each of the above-mentioned adjustable resource objects before performing resource allocation according to the distributed resource control amount combined with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects to generate an adjustable resource allocation strategy, wherein the above-mentioned operating state includes a grid-connected operating state or an off-grid operating state;

[0086] A first calculation unit, configured to calculate a total adjustment amount corresponding to the above-mentioned adjustable resource object according to the power grid resource demand of the above-mentioned distribution network area and the operation status corresponding to the above-mentioned adjustable resource object;

[0087] The second calculation unit is used to add the above adjustable amounts of all the above adjustable resource objects to obtain the above distributed resource control amount.

[0088] In the above embodiment, the operation data of adjustable resource objects such as energy storage, adjustable load, and distributed power source are collected in real time through intelligent sensors and monitoring systems. It is identified whether each resource object is in a grid-connected operation state or an off-grid operation state. The grid-connected operation state refers to the resource object being connected to the grid and participating in the power supply and distribution of the grid, while the off-grid operation state refers to the resource object operating independently of the grid. The monitoring system needs to be able to update the status of each resource object in real time so as to respond to changes in grid demand in a timely manner. According to the real-time demand of the grid, the amount of power support that each adjustable resource object needs to provide is analyzed. The grid resource demand is matched with the operating state of each resource object, and the adjustment amount that each resource object should bear is calculated. For each resource object, the total adjustment amount that it can provide is calculated according to its characteristics and capabilities, ensuring that the adjustment amount of each resource object matches its capabilities and grid demand, and avoiding excessive or insufficient adjustment. The adjustable amounts of all adjustable resource objects are added together to obtain the distributed resource control amount. By summarizing the adjustment amounts of all resources, the grid operator can respond to changes in grid demand more flexibly.

[0089] In order to optimize the use of energy storage resources and improve the energy efficiency of energy storage resources, in an optional implementation manner, the device further includes:

[0090] A first determining unit is used to determine a charging allocation algorithm according to the state of charge and the maximum charging power of the energy storage station before generating an adjustable resource allocation strategy by performing resource allocation according to the distributed resource control amount combined with the allocation control algorithms corresponding to the different adjustable resource objects, wherein the charging allocation algorithm is to sort the energy storage stations from small to large according to the state of charge of the energy storage stations, and the energy storage stations with small states of charge are preferentially allocated until the maximum charging power is reached;

[0091] A second determining unit is used to determine a discharge allocation algorithm according to the charge state and maximum discharge power of the energy storage station, wherein the charge allocation algorithm is to sort the energy storage stations according to the charge state from large to small, and the energy storage stations with large charge state are allocated first until the maximum discharge power is reached;

[0092] The third determining unit is used to determine the energy storage resource allocation algorithm according to the charging allocation algorithm and the discharging allocation algorithm.

[0093] In the above embodiment, the energy storage resource allocation algorithm is an algorithm for allocating energy storage stations according to the state of charge of the energy storage stations and the maximum charge and discharge power. Charging allocation: charging is sorted from small to large according to the percentage of energy storage stations; the energy storage stations with a small percentage of energy are allocated first, and the target power is the maximum charging power of each energy storage station. The energy storage stations that have been fully charged are excluded in each allocation. Discharging allocation: discharging is sorted from large to small according to the percentage of energy storage stations; the energy storage stations with a large percentage of energy are allocated first, and the target power is the maximum discharge power of each energy storage station. The energy storage stations that have been fully discharged are excluded in each allocation. The implementation process of the charging allocation algorithm: First, the state of charge (SOC) of all energy storage stations is monitored and sorted from small to large according to the SOC value. The SOC value represents the percentage of the current power of the energy storage station. A lower SOC value means that the energy storage station has less power. After sorting, the energy storage stations with smaller SOC values ​​are given priority for charging allocation, because these stations have lower power and need to be replenished first. For each energy storage station, the allocated charging power will not exceed its maximum charging power. Once the energy storage station reaches its maximum charging power, or the SOC value reaches the preset threshold, the station will be removed from the charging queue and no longer be allocated for charging. By giving priority to charging energy storage stations with lower power, energy storage resources can be used more effectively and over-discharge of some stations can be avoided. The implementation process of the discharge allocation algorithm: Similar to charging allocation, the SOC values ​​of all energy storage stations are first monitored and sorted from large to small according to the SOC value. A higher SOC value means that the energy storage station has more power. After sorting, the energy storage stations with larger SOC values ​​are preferentially allocated for discharge, because these stations have more power and can be released first. For each energy storage station, the allocated discharge power will not exceed its maximum discharge power. Once the energy storage station reaches its maximum discharge power, or the SOC value drops to the preset threshold, the station will be removed from the discharge queue and no longer be allocated for discharge. By giving priority to discharging energy storage stations with more power, the frequency regulation needs of the power grid can be quickly responded to and the necessary power support can be provided. Combine the determined charging allocation algorithm and discharging allocation algorithm to form a complete energy storage resource allocation algorithm. Through reasonable charging and discharging allocation, the energy efficiency of energy storage resources can be improved and energy waste can be reduced.

[0094] In order to improve the energy efficiency of the adjustable load resources, in an optional implementation manner, the device further includes:

[0095] a fourth determining unit, configured to determine a first allocation condition before generating an adjustable resource allocation strategy by performing resource allocation according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the different adjustable resource objects, wherein the first allocation condition includes priority sorting, the size of the adjustable load resource, and the adjustment rate of the adjustable load resource;

[0096] a fifth determining unit, configured to determine a first adjustable load resource allocation algorithm according to the priorities corresponding to the adjustable load resources when the first allocation condition is the priority sorting, wherein the first adjustable load resource allocation algorithm is to sort the adjustable load resources according to the priorities and adjust the adjustable load resources with high priorities by an adjustment step until the total adjustment demand is zero;

[0097] A sixth determining unit is used to determine a second adjustable load resource allocation algorithm according to a size ratio of each of the adjustable load resources when the first allocation condition is the size of the adjustable load resources, wherein the second adjustable load resource allocation algorithm is to preferentially adjust the adjustable load resources with a high proportion according to the size ratio of the adjustable load resources until the total adjustment demand is zero;

[0098] a seventh determining unit, configured to determine, when the first allocation condition is the adjustment rate of the adjustable load resources, a third adjustable load resource allocation algorithm according to the adjustment rate of each of the adjustable load resources, wherein the third adjustable load resource allocation algorithm is to select the adjustable load resource corresponding to the corresponding adjustment rate according to the adjustment time requirement and the adjustment capability;

[0099] An eighth determining unit is used to determine the adjustable load resource allocation algorithm according to the first adjustable load resource allocation algorithm, the second adjustable load resource allocation algorithm and the third adjustable load resource allocation algorithm.

[0100] In the above embodiment, the above adjustable load resource allocation algorithm is an algorithm that adjusts according to the above adjustable load resources until the total adjustment demand is zero. The above total adjustment demand is the adjustment amount that other business systems need the local edge cluster system to participate in. The adjustable load resource allocation algorithm mainly includes: (1) Manual priority sorting: sorting according to the manually preset priority, the load with high priority bears the adjustment amount according to the adjustment step until the total adjustment demand is zero, and the manual priority adjustment can be achieved by modifying the priority factor; the priority is the default setting, and manual adjustment is supported at the same time. The proportion of the influence factor of the manual adjustment priority is adjusted to achieve the priority adjustment. Priority sorting ensures that key load resources (such as hospitals, data centers, etc.) are met first when resources are tight. By adjusting the step control, the total adjustment demand can be gradually met to avoid excessive use of resources. (2) Adjustable load size: according to the size ratio of the adjustable load, the allocation strategy is determined. The load with a large proportion is adjusted first, and the load with a small proportion is adjusted later until the total adjustment demand is zero. By considering the size ratio of resources, the adjustment tasks can be allocated more reasonably to avoid excessive burden on small-scale resources. Prioritizing the adjustment of large resources can quickly respond to adjustment needs and improve adjustment efficiency. (3) Adjustable load adjustment rate: The adjustment capacity of the adjustable load can be divided into seconds, minutes, and hours. When adjusting the load, the adjustment rate of the load must be taken into consideration. According to the adjustment time requirements, the load with the appropriate adjustment rate should be called. Considering the adjustment rate can ensure that resources respond to the adjustment requirements within the appropriate time and improve the response speed. Selecting resources according to the adjustment rate can avoid the ineffective use of resources and improve resource utilization efficiency. The final adjustable load resource allocation algorithm is determined by combining the above three allocation algorithms (priority sorting, resource size ratio, and adjustment rate). The adjustable load resource allocation algorithm will comprehensively consider all factors to achieve the optimal resource allocation.

[0101] In order to optimize the control and allocation of distributed resources in the power system, in an optional implementation manner, the device further includes:

[0102] A ninth determining unit, configured to determine a second allocation condition before generating an adjustable resource allocation strategy by performing resource allocation according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects, wherein the above-mentioned second allocation condition includes the installed capacity ratio, real-time load rate ranking and utilization hours ranking of the distributed power sources;

[0103] a tenth determining unit, configured to, when the second allocation condition is the installed capacity ratio, allocate the distributed resource control amount according to the installed capacity ratio of each of the distributed power sources as a first distributed power source allocation algorithm;

[0104] an eleventh determining unit, for, when the second allocation condition is the real-time load rate sorting of the installed capacity ratio, preferentially allocating the distributed resource control amount to the distributed power sources which are sorted according to the current load rates of the distributed power sources and have the lowest current load rate, and determining the second distributed power source allocation algorithm;

[0105] A twelfth determining unit is used for, when the second allocation condition is the sorting by utilization hours, sorting the distributed power sources by utilization hours, the distributed power sources with high utilization hours take priority to bear the lower regulation demand and the distributed power sources with low utilization hours take priority to bear the upper regulation demand, and determining it as a third distributed power source allocation algorithm;

[0106] A thirteenth determining unit is configured to determine the distributed power supply allocation algorithm according to the first distributed power supply allocation algorithm, the second distributed power supply allocation algorithm and the third distributed power supply allocation algorithm.

[0107] In the above embodiment, the above distributed power allocation algorithm is an algorithm for allocating resources according to the above distributed power. The distributed power allocation algorithm mainly includes: (1) installed capacity ratio: share the total regulation amount according to the installed capacity ratio. (2) real-time load rate sorting: sort according to the current load rate of the power source, and the power source with a low load rate shall take the regulation amount first. (3) utilization hours sorting: sort according to the utilization hours of the power source, and the power source with a high utilization hour shall take the lower regulation demand first, and vice versa. The above first distributed power allocation algorithm allocates the control amount according to the installed capacity ratio of each distributed power source, ensuring that the power source with a larger installed capacity takes more regulation responsibility, which is proportional to its capacity. The above second distributed power allocation algorithm sorts according to the current load rate of the distributed power source, and preferentially allocates the control amount to the power source with the lowest load rate. The power sources that have not been fully utilized can be used preferentially, thereby improving the overall efficiency. By giving priority to the power sources with a low load rate, the pressure on the high-load power source can be reduced and its service life can be extended. The second distributed power allocation algorithm is to sort the distributed power sources according to their utilization hours. Power sources with high utilization hours take priority in taking on the downward regulation demand, while power sources with low utilization hours take priority in taking on the upward regulation demand. This method takes into account the frequency of use of power sources and ensures the balanced use of power sources. It can avoid overuse of some power sources and underuse of other power sources, thereby extending the service life of all power sources and improving the reliability of the system. The first distributed power allocation algorithm, the second distributed power allocation algorithm and the third distributed power allocation algorithm are combined to form a complete distributed power allocation algorithm, which aims to optimize the control and allocation of distributed resources in the power system and improve the efficiency, stability and reliability of the system. By considering different allocation conditions, the algorithm can adapt to different grid states and needs, thereby achieving better power resource management.

[0108] Explanation of terms: Utilization hours refers to the number of operating hours of the average power generation equipment capacity in a region under full load operation regulation within a certain period of time, that is, the ratio of power generation to average installed capacity. It reflects the utilization rate of power generation equipment in the region and is also one of the main indicators reflecting the power supply and demand situation in the region.

[0109] The installed capacity ratio refers to the proportion of the installed capacity of a distributed power source to the total installed capacity.

[0110] In order to help improve the stability and efficiency of the power grid, in an optional implementation, the generation unit includes:

[0111] A determination module, configured to determine a corresponding allocation strategy according to the distribution network state of the distribution network area, wherein the allocation strategy is an adjustment sequence of the energy storage resources, the adjustable load resources and the distributed power sources, and the distribution network state includes at least one of the following: a voltage suppression reverse supply state and a low power output state, wherein the voltage suppression reverse supply state is a phenomenon in which power is transmitted from a low-voltage power grid to a high-voltage power grid;

[0112] A generation module is used to perform resource allocation for different allocation strategies according to the distributed resource control amount combined with the allocation control algorithm corresponding to the adjustable resource object, and generate an adjustable resource allocation strategy.

[0113] In the above embodiment, the system first needs to monitor the grid status of the distribution network area in real time, including key parameters such as voltage level, power flow direction and power output. According to the monitored data, the system identifies whether the current distribution network status belongs to the voltage suppression reverse supply state or the low power output state. The voltage suppression reverse supply state refers to the phenomenon that power is transmitted from the low-voltage power grid to the high-voltage power grid, which may cause power grid stability problems. The low power output state refers to the state where the power supply is insufficient and cannot meet the current demand. According to the identified distribution network status, the system determines the corresponding resource allocation strategy. These strategies will guide the subsequent resource allocation to optimize the performance of the power grid. By identifying the power grid status and determining the corresponding strategy, the instability of the power grid caused by voltage suppression reverse supply and low power output can be prevented. According to different power grid states, the energy storage resources, adjustable load resources and distributed power sources are reasonably allocated to improve resource utilization efficiency and reduce energy waste. According to the determined allocation strategy, the system will apply the corresponding allocation control algorithm to allocate resources to the energy storage resources, adjustable load resources and distributed power sources. Based on the results calculated by the above algorithm, the system generates a specific adjustable resource allocation strategy, which helps to improve the stability and efficiency of the power grid, while supporting the peak-shaving and power balancing capabilities of the power grid, and providing technical support for the absorption of new energy and the sustainable development of the power grid.

[0114] In order to flexibly adjust resource allocation, in an optional implementation manner, the generation module includes:

[0115] The first determination submodule is used to determine the above allocation strategy as giving priority to local consumption processing and secondly adopting regulation and external transmission processing when the above distribution network state is the above voltage suppression reverse supply state, the local consumption processing is to consume excess power in the above distribution network area, and the above regulation and external transmission processing is to regulate and transmit to other distribution network areas for processing when the above distribution network area cannot completely consume the above excess power;

[0116] The second determination submodule is used to determine the allocation strategy to prioritize adjusting the energy storage resources, then reduce the adjustable load resources, and finally adjust the distributed power source when the distribution network state is the low power output state.

[0117] In the above embodiment, when suppressing reverse supply, local consumption is preferred, followed by regulating external transmission; when increasing output, energy storage is preferred, followed by reducing adjustable loads. Automatically issue control strategies to adjustable resources in the distribution network area to complete active regulation and control in the distribution network area. Specific implementation process: First, the system needs to identify whether the current distribution network state is a voltage suppression reverse supply state. This is usually achieved by monitoring the voltage level and flow direction of the distribution network. Local consumption processing: After confirming that the distribution network is in a voltage suppression reverse supply state, the system will give priority to the local consumption strategy. This means looking for resources that can consume excess power in the distribution network area, such as adjustable loads or energy storage devices, to reduce or eliminate reverse power. Regulating external transmission processing: If the resources in the distribution network area cannot completely consume the excess power, the system will start the regulation external transmission strategy. This involves transmitting excess power to other distribution network areas through the power grid to reduce the pressure on the current distribution network. Through local consumption and regulated external transmission, the voltage level can be effectively controlled to prevent equipment damage or safety accidents caused by excessive voltage. The system identifies whether the current distribution network status is a low power output state, usually by monitoring power generation and load demand. After confirming that the power output is low, the system will give priority to adjusting energy storage resources. This may include starting the discharge program of energy storage equipment to supplement the power supply of the power grid. If the energy storage resources are not sufficient to meet the power demand, the system will cut the adjustable load resources, that is, reduce the power consumption of certain non-critical loads. Finally, if the first two steps still cannot meet the power demand, the system will adjust distributed power sources, such as wind or solar power generation, to increase the power supply. When facing different operating conditions, the power grid can flexibly adjust resource allocation to ensure the safe, stable and efficient operation of the power grid.

[0118] The above-mentioned adjustable resource allocation device based on the edge cluster system includes a processor and a memory. The above-mentioned classification unit, generation unit and sending unit are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions. The above-mentioned modules are all located in the same processor; or, the above-mentioned modules are located in different processors in any combination.

[0119] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to solve the problem that the existing technology lacks relevant research on the analysis method of adjustable resources for new energy active automatic control, and cannot meet the requirements of the edge cluster system construction of the cloud-edge fusion intelligent scheduling operation platform for active regulation and control.

[0120] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0121] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the adjustable resource allocation method based on the edge cluster system.

[0122] Specifically, the adjustable resource allocation method based on the edge cluster system includes:

[0123] Step S201, classifying all active adjustable resources according to their own characteristics to obtain multiple adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources;

[0124] Step S202, performing resource allocation according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects, generating an adjustable resource allocation strategy, wherein the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, and the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithms include energy storage resource allocation algorithm, adjustable load resource allocation algorithm and distributed power source allocation algorithm;

[0125] Step S203: issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control in the distribution network area.

[0126] An embodiment of the present invention provides a processor, which is used to run a program, wherein the program executes the adjustable resource allocation method based on the edge cluster system when running.

[0127] Specifically, the adjustable resource allocation method based on the edge cluster system includes:

[0128] Step S201, classifying all active adjustable resources according to their own characteristics to obtain multiple adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources;

[0129] Step S202, performing resource allocation according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects, generating an adjustable resource allocation strategy, wherein the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, and the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithms include energy storage resource allocation algorithm, adjustable load resource allocation algorithm and distributed power source allocation algorithm;

[0130] Step S203: issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control in the distribution network area.

[0131] An embodiment of the present invention provides a power distribution network system, the power distribution network system includes a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, at least the following steps are implemented:

[0132] Step S201, classifying all active adjustable resources according to their own characteristics to obtain multiple adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources;

[0133] Step S202, performing resource allocation according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects, generating an adjustable resource allocation strategy, wherein the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, and the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithms include energy storage resource allocation algorithm, adjustable load resource allocation algorithm and distributed power source allocation algorithm;

[0134] Step S203: issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control in the distribution network area.

[0135] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0136] Step S201, classifying all active adjustable resources according to their own characteristics to obtain multiple adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources;

[0137] Step S202, performing resource allocation according to the distributed resource control amount in combination with the allocation control algorithms corresponding to the above-mentioned different adjustable resource objects, generating an adjustable resource allocation strategy, wherein the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, and the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithms include energy storage resource allocation algorithm, adjustable load resource allocation algorithm and distributed power source allocation algorithm;

[0138] Step S203: issuing the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control in the distribution network area.

[0139] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0140] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0141] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0142] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0144] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0145] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0146] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0147] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0148] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0149] 1) The adjustable resource allocation method based on the edge cluster system of the present application first classifies all active adjustable resources according to their own characteristics to obtain multiple adjustable resource objects, and the above-mentioned adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources; then, according to the distributed resource control amount combined with the allocation control algorithms corresponding to the different above-mentioned adjustable resource objects to perform resource allocation, an adjustable resource allocation strategy is generated, the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, the above-mentioned adjustable amount is the total amount of the above-mentioned adjustable resource objects that can currently participate in resource regulation, and the above-mentioned allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; finally, the above-mentioned adjustable resource allocation strategy is issued to the above-mentioned adjustable resource objects corresponding to the distribution network area to complete the active regulation control of the above-mentioned distribution network area. This application classifies active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources, in combination with the characteristics of adjustable resources, and studies the adjustable resource allocation algorithm, thereby realizing the analysis and generation of adjustable resource strategies. Under the premise of ensuring the safe operation of the regional power grid, it monitors the reverse transmission of active power flow, voltage over-limit, and load rate over-limit, and manages the absorption status of distributed new energy, supporting the peak-shaving capacity and power balancing capacity of the regional power grid. This application solves the problem that the prior art lacks relevant research on the analysis method of adjustable resources for active automatic control of new energy, and cannot meet the requirements of the construction of the edge cluster system of the cloud-edge fusion intelligent scheduling and operation platform for active regulation and control.

[0150] 2) The adjustable resource allocation device based on the edge cluster system of the present application, the classification unit is used to classify according to the own characteristics of all active adjustable resources to obtain multiple adjustable resource objects, and the above-mentioned adjustable resource objects are divided into at least energy storage resources, adjustable load resources and distributed power sources; the generation unit is used to perform resource allocation according to the distributed resource control amount combined with the allocation control algorithms corresponding to the different above-mentioned adjustable resource objects to generate an adjustable resource allocation strategy, the above-mentioned distributed resource control amount represents the sum of the adjustable amounts of all the above-mentioned adjustable resource objects under different operating states, the above-mentioned adjustable amount is the total amount of resource regulation that the above-mentioned adjustable resource objects can currently participate in, and the above-mentioned allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm and a distributed power source allocation algorithm; the issuing unit is used to issue the above-mentioned adjustable resource allocation strategy to the above-mentioned adjustable resource objects corresponding to the distribution network area to complete the active regulation control of the above-mentioned distribution network area. This application classifies active adjustable resources below 10kV, including energy storage, adjustable loads, and distributed power sources, in combination with the characteristics of adjustable resources, and studies the adjustable resource allocation algorithm, thereby realizing the analysis and generation of adjustable resource strategies. Under the premise of ensuring the safe operation of the regional power grid, it monitors the reverse transmission of active power flow, voltage over-limit, and load rate over-limit, and manages the absorption status of distributed new energy, supporting the peak-shaving capacity and power balancing capacity of the regional power grid. This application solves the problem that the prior art lacks relevant research on the analysis method of adjustable resources for active automatic control of new energy, and cannot meet the requirements of the construction of the edge cluster system of the cloud-edge fusion intelligent scheduling and operation platform for active regulation and control.

[0151] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for allocating adjustable resources based on an edge cluster system, characterized in that: include: Classifying all active adjustable resources according to their own characteristics to obtain a plurality of adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources; According to the distributed resource control amount combined with the allocation control algorithms corresponding to the different adjustable resource objects to perform resource allocation, an adjustable resource allocation strategy is generated, wherein the distributed resource control amount represents the sum of the adjustable amounts of all the adjustable resource objects under different operating states, and the adjustable amount is the total amount of resource regulation that the adjustable resource objects can currently participate in, and the allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm, and a distributed power source allocation algorithm; The adjustable resource allocation strategy is issued to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control of the distribution network area.

2. The method according to claim 1, characterized in that Before performing resource allocation according to the distributed resource control amount combined with the allocation control algorithms corresponding to the different adjustable resource objects to generate the adjustable resource allocation strategy, the method further includes: Real-time monitoring of the operating state of each of the adjustable resource objects, wherein the operating state includes a grid-connected operating state or an off-grid operating state; Calculate the total adjustment amount corresponding to the adjustable resource object according to the power grid resource demand of the distribution network area and the operating state corresponding to the adjustable resource object; The adjustable amounts of all the adjustable resource objects are added together to obtain the distributed resource control amount.

3. The method according to claim 1, characterized in that Before performing resource allocation according to the distributed resource control amount combined with allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method further includes: Determine a charging allocation algorithm according to the state of charge and maximum charging power of the energy storage station, wherein the charging allocation algorithm is to sort the energy storage stations according to the state of charge from small to large, and the energy storage stations with small state of charge are allocated first until the maximum charging power is reached; Determine a discharge allocation algorithm according to the state of charge and maximum discharge power of the energy storage station, wherein the charge allocation algorithm is to sort the energy storage stations from large to small according to the state of charge, and the energy storage stations with large state of charge are allocated first until the maximum discharge power is reached; The energy storage resource allocation algorithm is determined according to the charging allocation algorithm and the discharging allocation algorithm.

4. The method according to claim 1, characterized in that Before performing resource allocation according to the distributed resource control amount combined with allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method further includes: Determining a first allocation condition, the first allocation condition comprising a priority ranking, a size of an adjustable load resource, and an adjustment rate of the adjustable load resource; In the case where the first allocation condition is the priority sorting, a first adjustable load resource allocation algorithm is determined according to the priority corresponding to the adjustable load resource, and the first adjustable load resource allocation algorithm is to sort the adjustable load resources according to the priority and adjust the adjustable load resources with high priority by an adjustment step until the total adjustment demand is zero; In the case where the first allocation condition is the size of the adjustable load resources, a second adjustable load resource allocation algorithm is determined according to the size ratio of each adjustable load resource, and the second adjustable load resource allocation algorithm is to preferentially adjust the adjustable load resources with a high proportion according to the size ratio of the adjustable load resources until the total adjustment demand is zero; In the case where the first allocation condition is the adjustment rate of the adjustable load resource, a third adjustable load resource allocation algorithm is determined according to the adjustment rate of each adjustable load resource, and the third adjustable load resource allocation algorithm is to select the adjustable load resource corresponding to the corresponding adjustment rate according to the adjustment time requirement and the adjustment capability; The adjustable load resource allocation algorithm is determined according to the first adjustable load resource allocation algorithm, the second adjustable load resource allocation algorithm and the third adjustable load resource allocation algorithm.

5. The method according to claim 1, characterized in that Before performing resource allocation according to the distributed resource control amount combined with allocation control algorithms corresponding to different adjustable resource objects to generate an adjustable resource allocation strategy, the method further includes: Determining a second allocation condition, wherein the second allocation condition includes an installed capacity ratio, a real-time load rate ranking, and a utilization hour ranking of distributed power sources; In the case where the second allocation condition is the installed capacity ratio, allocating the distributed resource control amount according to the installed capacity ratio of each of the distributed power sources is determined as a first distributed power source allocation algorithm; In the case where the second allocation condition is the real-time load rate sorting of the installed capacity ratio, the distributed resource control amount is preferentially allocated to the distributed power source which is sorted according to the current load rate of the distributed power sources and has the lowest current load rate, which is determined as the second distributed power source allocation algorithm; In the case where the second allocation condition is the sorting by utilization hours, the distributed power sources will be sorted according to their utilization hours, the distributed power sources with high utilization hours will take priority in taking the lower regulation demand, and the distributed power sources with low utilization hours will take priority in taking the upper regulation demand, and the third distributed power source allocation algorithm will be determined; The distributed power supply allocation algorithm is determined according to the first distributed power supply allocation algorithm, the second distributed power supply allocation algorithm and the third distributed power supply allocation algorithm.

6. The method according to claim 1, characterized in that Generating an adjustable resource allocation strategy according to the distributed resource control amount combined with allocation control algorithms corresponding to different adjustable resource objects to allocate resources includes: Determine a corresponding allocation strategy according to the distribution network state of the distribution network area, the allocation strategy is the adjustment sequence of the energy storage resources, the adjustable load resources and the distributed power source, the distribution network state includes at least one of the following: a voltage suppression reverse supply state and a low power output state, the voltage suppression reverse supply state is a phenomenon in which power is transmitted from a low-voltage power grid to a high-voltage power grid; According to the distributed resource control amount and the allocation control algorithm corresponding to the adjustable resource object, resources are allocated to different allocation strategies to generate an adjustable resource allocation strategy.

7. The method according to claim 6, characterized in that Determining a corresponding allocation strategy according to the network distribution state of the network distribution area and generating an adjustable resource allocation strategy includes: When the distribution network state is the voltage suppression reverse supply state, the allocation strategy is determined to preferentially adopt local consumption processing, and secondly adopt regulation and external transmission processing, the local consumption processing is to consume excess power in the distribution network area, and the regulation and external transmission processing is to regulate and transmit to other distribution network areas for processing when the distribution network area cannot completely consume the excess power; When the distribution network state is the low power output state, the allocation strategy is determined to first adjust the energy storage resources, then reduce the adjustable load resources, and finally adjust the distributed power source.

8. An adjustable resource allocation device based on an edge cluster system, characterized in that: The device comprises: A classification unit, used for classifying all active adjustable resources according to their own characteristics to obtain a plurality of adjustable resource objects, wherein the adjustable resource objects are at least divided into energy storage resources, adjustable load resources and distributed power sources; A generating unit, configured to generate an adjustable resource allocation strategy according to a distributed resource control amount combined with allocation control algorithms corresponding to different adjustable resource objects to perform resource allocation, wherein the distributed resource control amount represents the sum of the adjustable amounts of all the adjustable resource objects under different operating states, the adjustable amount is the total amount of resource regulation that the adjustable resource objects can currently participate in, and the allocation control algorithm includes an energy storage resource allocation algorithm, an adjustable load resource allocation algorithm, and a distributed power source allocation algorithm; The issuing unit is used to issue the adjustable resource allocation strategy to the corresponding adjustable resource objects in the distribution network area to complete the active power regulation control of the distribution network area.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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