Instruction decomposition method and device, edge intelligent control terminal, medium and program product

Abstract

The embodiment of the invention discloses an instruction decomposition method and device, an edge intelligent control terminal, a medium and a program product. Comprising the steps of receiving a resource regulation instruction; decomposing the resource regulation and control instruction according to a regulation and control strategy in the resource regulation and control instruction and adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal; wherein the resource regulation and control instruction is an instruction directly sent to the edge intelligent control terminal by the power grid dispatching mechanism; the adjustable resources are resources which are located in the management range of the edge intelligent control terminal and belong to different virtual power plant providers. The number of regulation and control instructions needing to be sent by the power grid dispatching mechanism is reduced, the time needed for decomposing the regulation and control instructions is shortened, direct management of the power grid dispatching mechanism for local resources of the power grid is achieved through the edge intelligent control terminal, and the response speed of resource regulation and control is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of power resource regulation and control, and in particular to an instruction decomposition method, device, edge intelligent control terminal, medium and program product. Background Art

[0002] With the rapid development of renewable energy and the continuous advancement of smart grid technology, the power system is developing in a more complex and diversified direction. As a new type of energy management system, Virtual Power Plant (VPP) integrates distributed energy resources (such as photovoltaics, energy storage equipment, etc.) and demand response resources (industrial and commercial loads, charging stations, smart buildings, etc.) to achieve centralized management and scheduling of these decentralized resources. However, due to the diversity and randomness of distributed energy, virtual power plants face many challenges in practical applications, such as how to effectively perform real-time scheduling.

[0003] The current resource dispatching method mainly relies on the dispatching automation system, where the power grid dispatching organization issues comprehensive dispatching instructions to the virtual power plant operator, and then the virtual power plant operator disassembles the instructions and sends the disassembled instructions to the corresponding resources to respond to the power grid instructions. However, since there are often multiple virtual power plant operators in the area managed by the same power grid dispatching organization, in order to fully manage the resources in the management area, the power grid dispatching organization needs to send corresponding dispatching instructions to different virtual power plant operators respectively, resulting in a substantial increase in the instructions that the power grid dispatching organization needs to issue.

[0004] At the same time, the virtual power plant dispatching instructions issued by the power grid dispatching agency are usually global decisions based on macro parameters such as the overall load and power generation of the power grid. Although they can ensure the overall balance of the power system, it is difficult to respond quickly and accurately to the instantaneous demand of resources controlled by different virtual power plant operators, resulting in limited flexibility and response speed of system dispatching. Summary of the invention

[0005] The present invention provides an instruction decomposition method, device, edge intelligent control terminal, medium and program product. By setting up an edge intelligent control terminal that independently manages the resources of different virtual power plant providers, direct acquisition and decomposition of resource control instructions for power grid dispatching organizations are achieved, so that the power grid dispatching organization can reduce the number of control instructions required to be sent, reduce the time required for decomposing control instructions, realize direct management of local power grids, and improve the response speed of resource control.

[0006] In a first aspect, an embodiment of the present invention provides an instruction decomposition method, which is applied to an edge intelligent control terminal, including:

[0007] Receive resource control instructions;

[0008] Decompose the resource control instruction according to the control strategy in the resource control instruction and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal;

[0009] Among them, the resource regulation instructions are instructions sent directly by the power grid dispatching agency to the edge intelligent control terminal; each adjustable resource is a resource located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers.

[0010] In a second aspect, an embodiment of the present invention further provides an instruction decomposition device, which is applied to an edge intelligent control terminal, including:

[0011] An instruction receiving module, used for receiving resource control instructions;

[0012] An instruction decomposition module is used to decompose the resource control instruction according to the control strategy in the resource control instruction and the adjustable capacity information of each adjustable resource corresponding to the edge intelligent control terminal;

[0013] Among them, the resource regulation instructions are instructions sent directly by the power grid dispatching agency to the edge intelligent control terminal; each adjustable resource is a resource located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers.

[0014] In a third aspect, an embodiment of the present invention further provides an edge intelligent control terminal, including:

[0015] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can implement the instruction decomposition method of any embodiment of the present invention.

[0016] In a fourth aspect, an embodiment of the present invention further provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the instruction decomposition method of any embodiment of the present invention.

[0017] In a fifth aspect, an embodiment of the present invention further provides a computer program product, including a computer program, which is used to execute the instruction decomposition method of any embodiment of the present invention when executed by a processor.

[0018] The embodiment of the present invention provides an instruction decomposition method, device, edge intelligent control terminal, medium and program product, which receives resource control instructions; decomposes the resource control instructions according to the control strategy in the resource control instructions and the adjustable capacity information of each adjustable resource corresponding to the edge intelligent control terminal; wherein the resource control instruction is an instruction directly sent by the power grid dispatching agency to the edge intelligent control terminal; each adjustable resource is a resource located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers. By adopting the above technical solution, an independently set edge intelligent control terminal for resource control management of part of the management scope required by the power grid dispatching agency is adopted, directly communicating with the power grid dispatching agency to receive the resource control instructions of the power grid dispatching agency for the resources within the management scope, and the resource control instructions can be directly decomposed in the edge intelligent control terminal to obtain instructions that can be directly used to control the resources belonging to different virtual power plant providers within the management scope. Since the virtual power plant providers to which the resources belong will not be affected in the instruction reception and decomposition process, the power grid dispatching agency does not need to send separate control instructions to all virtual power plant providers to which the resources need to be controlled, thereby reducing the number of control instructions required to be sent by the power grid dispatching agency. At the same time, since the edge intelligent control terminal only decomposes and manages instructions for resources within its manageable range, the amount of information contained in the resource control instructions it receives is less than the amount of information contained in the instructions sent to the virtual power plant provider for controlling all resources in the virtual power plant provider. Therefore, the time required for decomposing the control instructions can be reduced. Through the edge intelligent control terminal, the power grid dispatching agency can directly manage the local resources of the power grid, thereby improving the response speed of resource control.

[0019] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A flowchart of an instruction decomposition method provided in Embodiment 1 of the present invention;

[0022] Figure 2 A flowchart of an instruction decomposition method provided in Embodiment 2 of the present invention;

[0023] Figure 3 A schematic diagram of the structure of an instruction decomposition device provided in Embodiment 3 of the present invention;

[0024] Figure 4 A schematic diagram of the structure of an edge intelligent control terminal provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 This is a flowchart of an instruction decomposition method provided in the first embodiment of the present invention. The embodiment of the present invention can be applied to the situation of direct resource regulation and management of a part of the entire large-scale power grid that can be controlled by the power grid dispatching organization. The method can be executed by an instruction decomposition device, which can be implemented by software and / or hardware, and the instruction decomposition device can be configured in an edge intelligent control terminal. Optionally, the edge intelligent control terminal can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, and an edge computing device in a power network, etc. The embodiment of the present invention does not limit this.

[0029] In this embodiment, the edge intelligent control terminal can be specifically understood as a device that performs data processing and intelligent decision-making at the edge of the network. In the embodiment of the present invention, it can be understood as a device that is arranged at the edge node of the power network and is used to manage, control and make decisions on power resources within its coverage area.

[0030] like Figure 1 As shown, an instruction decomposition method provided by an embodiment of the present invention specifically includes the following steps:

[0031] S101: Receive resource control instructions.

[0032] Among them, the resource control instructions are instructions sent directly by the power grid dispatching agency to the edge intelligent control terminal.

[0033] In this embodiment, the power grid dispatching organization can be specifically understood as a specialized organization set up to ensure the safe and stable operation of the power grid, responsible for organizing, commanding, guiding and coordinating the operation of the power grid. In the embodiment of the present invention, it can be understood as an instruction issuing end for issuing control instructions to various areas in the power network. The resource control instruction can be specifically understood as an instruction issued by the power grid dispatching organization to regulate the power resources within the controllable range of the edge intelligent control terminal. Exemplarily, the resource control instructions received by the edge intelligent control terminal may include: control strategy, instruction start time, instruction end time, power adjustment target, adjustable resource type, real-time power, remaining power, chargeable amount, available charging power, available discharge power, charging power available time, discharge power available time, resource adjustable capacity (increase, decrease capacity), response speed, planned power, etc., and the embodiment of the present invention does not limit this.

[0034] Optionally, the edge intelligent control terminal can be securely connected to the power network through a wireless private network, and a communication profile can be used to realize information interaction between the edge intelligent control terminal and the power grid dispatching organization, wherein the communication profile can be a profile that can support the International Electrotechnical Commission (IEC) 104 and 101 protocols.

[0035] Specifically, when the power grid dispatching organization needs to regulate resources in a specific management area, it will send a resource regulation instruction to the edge intelligent control terminal that can manage the area, so that the edge intelligent control terminal can receive the resource regulation instruction.

[0036] S102: Decompose the resource control instruction according to the control strategy in the resource control instruction and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal.

[0037] Among them, each adjustable resource is located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers.

[0038] In this embodiment, the control strategy can be specifically understood as a strategy contained in the resource control instruction, which provides a basis for the decomposition of the resource control instruction and is used to indicate the target that the resource control instruction emphasizes during the resource control execution process. Exemplarily, the control strategy may include the shortest response time, the shortest total execution time, and the highest control stability, etc., which is not limited in the embodiment of the present invention.

[0039] In this embodiment, the adjustable resources can be specifically understood as power resources that are within the manageable range of the edge intelligent control terminal, can belong to different virtual power plant providers, and can be charged or discharged. Exemplarily, the adjustable resources may include distributed energy resources such as photovoltaic and energy storage equipment, and may also include demand response resources such as industrial and commercial loads, charging stations, and smart buildings.

[0040] In this embodiment, the adjustable capability information can be specifically understood as corresponding to the adjustable resource, including the characteristics of the adjustable resource itself, and the predicted information related to the adjustable capacity, time, power and other characteristics. Exemplarily, the adjustable capability information may include the resource name, resource type, real-time power, remaining power, chargeable capacity, available charging power, available discharge power, available charging power time, available discharge power time, adjustable capacity (upward or downward capacity), response time, resource type, instruction start time, instruction end time and adjustment power of the adjustable resource, which is not limited in the embodiment of the present invention.

[0041] Specifically, since the edge intelligent control terminal can obtain the adjustable capacity information of each adjustable resource within its management scope in advance before receiving the resource control instruction, after receiving the resource control instruction, it can determine the target and basis for decomposing the resource control instruction according to the control strategy in the resource control instruction. Then, the adjustable capacity information of each adjustable resource can be matched with the decomposition target and basis of the resource control instruction respectively, and the adjustable resources that can meet the resource demand for adjustment required by the resource control instruction and can meet the decomposition target and basis of the resource control instruction are determined from each adjustable resource, and then the resource control instruction is decomposed according to the adjustable capacity information of each selected adjustable resource, and the control instruction that can be used to adjust each selected adjustable resource is obtained, so as to realize targeted power resource control.

[0042] The technical solution of this embodiment is to receive resource control instructions; decompose the resource control instructions according to the control strategy in the resource control instructions and the adjustable capacity information of each adjustable resource corresponding to the edge intelligent control terminal; wherein the resource control instructions are instructions directly sent by the power grid dispatching agency to the edge intelligent control terminal; each adjustable resource is a resource belonging to different virtual power plant providers within the management scope of the edge intelligent control terminal. By adopting the above technical solution, an independently set edge intelligent control terminal for resource control management of part of the management scope required by the power grid dispatching agency is adopted, and it directly communicates with the power grid dispatching agency to receive the resource control instructions of the power grid dispatching agency for the resources within the management scope, and the resource control instructions can be directly decomposed in the edge intelligent control terminal to obtain instructions that can be directly used to control the resources belonging to different virtual power plant providers within the management scope. Since the virtual power plant providers to which the resources belong will not be affected in the process of receiving and decomposing the instructions, the power grid dispatching agency does not need to send separate control instructions to all virtual power plant providers to which the resources need to be controlled, thereby reducing the number of control instructions that the power grid dispatching agency needs to send. At the same time, since the edge intelligent control terminal only decomposes and manages instructions for resources within its manageable range, the amount of information contained in the resource control instructions it receives is less than the amount of information contained in the instructions sent to the virtual power plant provider for controlling all resources in the virtual power plant provider. Therefore, the time required for decomposing the control instructions can be reduced. Through the edge intelligent control terminal, the power grid dispatching agency can directly manage the local resources of the power grid, thereby improving the response speed of resource control.

[0043] Embodiment 2

[0044] Figure 2A flowchart of an instruction decomposition method provided for the second embodiment of the present invention, the embodiment of the present invention is further optimized on the basis of the above-mentioned optional technical solutions, through the target resource control information in the received resource control instruction, and the adjustable capacity information of each adjustable resource corresponding to the edge intelligent control terminal, each adjustable resource is screened, and the candidate adjustable resources that can meet the target resource control information requirements are determined. The resource control instruction can be targeted when the resource control instruction is decomposed, which reduces the amount of calculation when the resource control instruction is decomposed according to the control strategy in the resource control instruction. At the same time, since the candidate adjustable resources obtained by screening are all adjustable resources that can respond to the resource control instruction for control, the decomposed resource control instruction can be correctly responded to, and the stability of resource control is improved. At the same time, since the edge intelligent control terminal only decomposes and manages instructions for resources within its manageable range, the amount of information contained in the resource control instruction it receives is less than the amount of information sent to the virtual power plant provider for controlling all resources in the virtual power plant provider, so the time required for decomposing the control instruction can be reduced, and the power grid dispatching organization can directly manage the local resources of the power grid through the edge intelligent control terminal, thereby improving the response speed of resource control.

[0045] like Figure 2 As shown, an instruction decomposition method provided by an embodiment of the present invention specifically includes the following steps:

[0046] S201: Receive resource control instructions.

[0047] S202: Determine target resource control information according to the resource control instruction.

[0048] In this embodiment, the target resource control information can be specifically understood as information related to the actual resource control amount, control time, control power, and the type of required control resources in the resource control instruction. Exemplarily, the target resource control information may include: instruction start time, instruction end time, power adjustment target, adjustable resource type, remaining power, chargeable amount, available charging power, available discharge power, available charging power time, available discharge power time, resource adjustable capacity (upward or downward capacity), response speed, and planned power, etc., which can be used to screen each adjustable resource, and the embodiment of the present invention does not limit this.

[0049] Specifically, after the edge intelligent control terminal directly receives the resource control instruction from the power grid dispatching organization, it will analyze the resource control instruction, extract the information directly related to the resource control demand and determine it as the target resource control information.

[0050] S203: Determine at least one candidate adjustable resource from the adjustable resources according to the target resource control information and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal.

[0051] In this embodiment, the candidate adjustable resource may be specifically understood as an adjustable resource that satisfies the regulation requirement of the currently received resource regulation instruction among all adjustable resources.

[0052] Specifically, since the edge intelligent control terminal can only regulate the adjustable resources that are online when the resource regulation instruction is received, the adjustable resources that are not online at that moment can be screened out based on the online status of each adjustable resource corresponding to the edge intelligent control terminal at the time of receiving the resource regulation instruction. At the same time, since the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal already contains the type of adjustable resource, as well as the supported regulation time, regulation power and adjustable capacity, the adjustable capability information of each online adjustable resource can be compared with the target resource regulation information, and the adjustable resources that cannot meet any type of information in the target resource regulation information can be screened out, and the adjustable resources obtained after screening can be determined as candidate adjustable resources that can be used to receive the decomposed resource regulation instruction for resource regulation.

[0053] In an embodiment of the present invention, before decomposing the resource control instruction according to the control strategy in the resource control instruction, the adjustable resources corresponding to the edge intelligent control terminal are first screened, and the adjustable resources that are not online or do not meet the control requirements of the resource control instruction are screened out, and the candidate adjustable resources that can meet the target resource control information requirements are determined when the resource control instruction is decomposed, thereby reducing the amount of calculation when decomposing the resource control instruction according to the control strategy in the resource control instruction.

[0054] S204: Determine a target adjustable resource from among the candidate adjustable resources according to the regulation strategy in the resource regulation instruction, the adjustable capability information of each candidate adjustable resource, and the target resource regulation information.

[0055] In this embodiment, the target adjustable resource can be specifically understood as the adjustable resource that is finally determined after screening and matching and needs to be regulated by the decomposed resource regulation instruction.

[0056] Specifically, according to the different control strategies in the resource control instructions, each candidate adjustable resource is sorted and screened in the same way as the control strategy based on the adjustable capability information of each candidate adjustable resource. At the same time, the target resource control information is used as a constraint condition, and each candidate adjustable resource is selected starting from the candidate adjustable resource that best meets the control strategy preference after sorting and screening, until the demand corresponding to the target resource control information is met, the selected candidate adjustable resource is determined as the target adjustable resource.

[0057] Optionally, when the control strategy in the resource control instruction is a response priority strategy, determining the target adjustable resource from the candidate adjustable resources according to the control strategy in the resource control instruction, the adjustable capability information of each candidate adjustable resource, and the target resource control information can be implemented in the following manner:

[0058] 1) According to the adjustable capability information of each candidate adjustable resource, the response time and adjustable capacity corresponding to each candidate adjustable resource are determined.

[0059] 2) Select each candidate adjustable resource in order of response time from short to long, and accumulate the adjustable capacities of the selected candidate adjustable resources to obtain the accumulated adjustable capacity, until the accumulated adjustable capacity reaches the target resource regulation amount in the target resource regulation information.

[0060] 3) Determine each selected candidate adjustable resource as a target adjustable resource.

[0061] In this embodiment, the response priority strategy can be specifically understood as a strategy that aims to select resources that can respond as quickly as possible and achieve the control target required by the resource control instruction as soon as possible after receiving the resource control instruction. It can be understood that when the response priority strategy is adopted, it can ensure that resources can be adjusted quickly to cope with emergency situations or rapid fluctuations in short-term power demand.

[0062] In this embodiment, the response time can be specifically understood as the duration of the entire adjustment process from the start time of the instruction to the time when the adjustable resource is adjusted to the time when the adjustment target is reached. The adjustable capacity can be specifically understood as the maximum amount of resources that can be increased or decreased for the candidate adjustable resources predicted based on weather, longitude and latitude, resource type, resource characteristic information, etc. that can affect the resource adjustment state. The target resource regulation amount can be specifically understood as the value in the target resource regulation information that indicates the total amount of resources that actually need to be regulated in the resource regulation instruction. For example, assuming that the resource regulation instruction is "increase 5MW within 10 minutes", the target resource regulation amount can be considered to be 5MW.

[0063] Specifically, when the control strategy in the resource control instruction is a response priority strategy, it is equivalent to clarifying the need to screen each candidate adjustable resource based on the response time in the adjustable capacity information of each candidate adjustable resource. At this time, the response time and adjustable capacity corresponding to each candidate adjustable resource can be determined according to the adjustable capacity information of each candidate adjustable resource. Then, the candidate adjustable resources can be sorted according to their response time, and the candidate adjustable resource with the shortest response time can be selected, and the adjustable capacity of each selected candidate adjustable resource is accumulated and summed to obtain the accumulated adjustable capacity. The accumulated adjustable capacity is compared with the target resource control amount in the target resource control information. When the accumulated adjustable capacity reaches the target resource control amount, it can be considered that the currently selected candidate adjustable resource can meet the control requirements of the resource control instruction within the shortest response time. At this time, each selected candidate adjustable resource can be determined as the target adjustable resource.

[0064] Optionally, when the control strategy in the resource control instruction is a quality priority strategy, the target adjustable resource is determined from the candidate adjustable resources according to the control strategy in the resource control instruction, the adjustable capability information of each candidate adjustable resource, and the target resource control information, which can be implemented in the following manner:

[0065] 1) Determine the adjustable capability value of each candidate adjustable resource, and determine the adjustable capacity corresponding to each candidate adjustable resource according to the adjustable capability information of each candidate adjustable resource.

[0066] 2) Selecting each candidate adjustable resource in descending order of adjustment capability value, and accumulating the adjustable capacity of the selected candidate adjustable resources to obtain the accumulated adjustable capacity, until the accumulated adjustable capacity reaches the target resource adjustment amount in the target resource adjustment information.

[0067] 3) Determine each selected candidate adjustable resource as a target adjustable resource.

[0068] In this embodiment, the adjustment capability value can be specifically understood as a comprehensive evaluation index value that is determined based on the execution response of the candidate adjustable resource to the instruction in the historical time and is used to reflect the resource adjustment quality. Optionally, the adjustment capability value can be determined based on the instruction response of each candidate adjustable resource in a historical time through a pre-established resource adjustment quality comprehensive evaluation model.

[0069] Exemplarily, the pre-established comprehensive evaluation model for resource regulation quality can be a mathematical model established based on evaluation indicators such as regulation accuracy, response speed, regulation stability, historical performance and reliability. Among them, regulation accuracy can be specifically understood as the degree of deviation between the actual output or load adjustment and the instruction requirements when the resource executes the scheduling instruction; response speed can be specifically understood as the time when the resource starts to execute after receiving the scheduling instruction and the time required to reach the target regulation state; regulation stability can be specifically understood as the ability of the resource to maintain the target state during the regulation process, especially in the face of load changes or external disturbances; historical performance can be specifically understood as the performance of the resource in past scheduling tasks, including successful execution rate, common failure rate, etc.; reliability can be specifically understood as the reliability of the resource in long-term operation, which refers to the ability of the resource to continue to work stably for a long time. When constructing a comprehensive evaluation model for resource regulation quality, it is necessary to comprehensively consider various indicators and influencing factors that affect the regulation quality. Different indicators may have different effects on the regulation quality, so it is necessary to assign appropriate weights to each indicator. These weights can be determined based on expert experience, historical data analysis, or multi-criteria decision analysis methods (such as hierarchical analysis).

[0070] Continuing with the above example, assume that there are n evaluation indicators, and the weight of each indicator is w i , then each weight needs to meet the following conditions:

[0071]

[0072] Since the units and dimensions of different indicators may be different, each indicator must be standardized so that they can be weighted and summed. Among them, the standard division method can be implemented by normalization method.

[0073] For each resource, according to the standardized indicator data X′ i and the corresponding weight w i , calculate the resource's adjustment quality score Q on a single indicator i It can be expressed as:

[0074] Q i =w i ×X′ i

[0075] By weighting and summing the scores of each individual indicator, we can get the comprehensive adjustment quality score Q of the resource:

[0076]

[0077] This comprehensive score Q represents the regulation quality of the resource. The higher the score, the better the regulation quality of the resource.

[0078] It is understandable that after the model is initially established, it can be verified through a large amount of historical data, and the accuracy of the model can be evaluated by comparing the model score and the actual adjustment effect. If it is found that some indicators or weight settings are unreasonable, the weights can be adjusted through feedback or new evaluation indicators can be introduced to improve the accuracy of the model.

[0079] Specifically, when it is clear that the control strategy in the resource control instruction is a quality priority strategy, it is equivalent to clarifying the need to screen each candidate adjustable resource based on the adjustment capability value determined by each candidate adjustable resource in the historical processing process. At this time, the adjustment capability value of each candidate adjustable resource can be obtained from the storage of the edge intelligent control terminal, and the adjustable capacity corresponding to each candidate adjustable resource can be determined according to the adjustable capability information of each candidate adjustable resource. Then, the candidate adjustable resources can be sorted according to their adjustment capability values, and the candidate adjustable resource with the highest adjustment capability value can be selected, and the adjustable capacity of each selected candidate adjustable resource is accumulated and summed to obtain the cumulative adjustable capacity. The cumulative adjustable capacity is compared with the target resource control amount in the target resource control information. When the cumulative adjustable capacity reaches the target resource control amount, it can be considered that the currently selected candidate adjustable resource can meet the control requirements of the resource control instruction under the highest execution quality. At this time, each selected candidate adjustable resource can be determined as the target adjustable resource.

[0080] S205 . Decompose the resource control instruction into target resource control instructions for each target adjustable resource according to the adjustable capacity information of each target adjustable resource.

[0081] Specifically, based on the adjustable capacity information of different target adjustable resources, the resource quantity, execution time and power, etc. that need to be adjusted for different target adjustable resources based on the resource control instructions can be clarified, and then the resource control instructions can be decomposed based on the above-defined information to obtain the target resource control instructions for each target adjustable resource contained in the above-defined information.

[0082] Optionally, before receiving the resource control instruction, the following is further included:

[0083] Receive the resource adjustable capacity prediction model sent by the power grid dispatching agency; for each adjustable resource corresponding to the edge intelligent control terminal, input the resource type and resource characteristic information of the adjustable resource, as well as the longitude and latitude, weather information and current load curve corresponding to the edge intelligent control terminal into the resource adjustable capacity prediction model according to a preset period to determine the adjustable capacity information of the adjustable resource.

[0084] In this embodiment, the resource adjustable capacity prediction model can be specifically understood as a neural network model used to predict the adjustable resource capacity of resources in the future based on input information such as weather, location, resource type, resource characteristics and load conditions.

[0085] Exemplarily, the resource adjustable capacity prediction model can be a model trained by the power grid dispatching agency based on the real-time operation data and historical data regularly collected from various distributed energy resources in its jurisdiction. The resource characteristic information of the resource equipment (such as power generation, energy storage status, installed capacity and load conditions, etc.), environmental parameters (such as wind speed, sunshine intensity, etc.), resource type and load curve can be used as input samples, and the historical adjustable capacity in the historical data is used as a label to construct a training sample of the resource adjustable capacity prediction model, and the resource adjustable capacity prediction model is trained through the constructed training samples. Optionally, when constructing the training sample, external information such as weather forecasts, electricity market prices and user needs can also be added to the input sample to increase the model richness of the resource adjustable capacity prediction model obtained by training. Optionally, the resource adjustable capacity prediction model can be a long short-term memory network (Long Short-Term Memory, LSTM) model, or it can be other types of neural network models, which are not limited in the embodiments of the present invention.

[0086] Specifically, before the edge intelligent control terminal decomposes the resource control instructions received this time, it will first receive the resource adjustable capacity prediction model sent by the power grid dispatching organization. The resource adjustable capacity prediction model can be periodically updated according to actual conditions. After each update, the power grid dispatching organization will send the new resource adjustable capacity prediction model to the edge intelligent control terminal. Furthermore, for each adjustable resource corresponding to the edge intelligent control terminal, its adjustable capacity information will be periodically predicted through the resource adjustable capacity prediction model configured in the edge intelligent control terminal. In each prediction process, the resource type and resource characteristic information of the adjustable resource, as well as the longitude and latitude, weather information and current load curve corresponding to the edge intelligent control terminal can be used as inputs of the resource adjustable capacity prediction model to complete the determination of the adjustable capacity information of each adjustable resource.

[0087] Optionally, after decomposing the resource control instructions, the following is further included:

[0088] Send the decomposed resource control instructions to the corresponding target adjustable resources respectively, monitor the execution status of each target adjustable resource, and determine the monitoring execution result;

[0089] The monitoring execution results are fed back to the power grid dispatching agency so that the power grid dispatching agency can update the resource adjustable capacity prediction model.

[0090] In this embodiment, the monitoring execution result can be specifically understood as the execution status and effect of each adjustable resource when the edge intelligent control terminal performs targeted resource regulation on each adjustable resource it manages. Optionally, during the monitoring process, the response time, execution result, and deviation from the expected target of the adjustable resource can be monitored as the monitoring execution result.

[0091] Specifically, after the edge intelligent control terminal completes the decomposition of the received resource control instructions, it will obtain the decomposed resource control instructions that can be sent to different target adjustable resources. When each target adjustable resource is regulated according to the decomposed resource control instructions, the edge intelligent control terminal will monitor its execution status and effect, and obtain the monitoring execution result after its execution. The edge intelligent control terminal will then feed back the monitoring execution results of each target adjustable resource to the power grid regulation agency, and the power grid regulation agency will analyze the execution effect. If it is found that there is a large deviation between the execution result and the expected target, the power grid regulation agency can optimize the resource adjustable capacity prediction model. The optimization process may include adjusting strategy weights, modifying control parameters, reconfiguring resources, and supplementing training, etc., to achieve the update of the resource adjustable capacity prediction model.

[0092] The technical solution of this embodiment is to screen each adjustable resource through the target resource control information in the received resource control instruction and the adjustable capacity information of each adjustable resource corresponding to the edge intelligent control terminal, and determine the candidate adjustable resources that can meet the target resource control information requirements and can be targeted when the resource control instruction is decomposed, thereby reducing the amount of calculation when the resource control instruction is decomposed according to the control strategy in the resource control instruction. At the same time, since the candidate adjustable resources obtained by screening are all adjustable resources that can respond to the resource control instruction for control, the decomposed resource control instruction can be correctly responded to, thereby improving the stability of resource control. At the same time, since the edge intelligent control terminal only decomposes and manages instructions for resources within its manageable range, the amount of information contained in the resource control instruction it receives is less than the amount of information sent to the virtual power plant provider for controlling all resources in the virtual power plant provider, thereby reducing the time required for decomposing the control instruction, and realizing the direct management of local resources of the power grid by the power grid dispatching organization through the edge intelligent control terminal, thereby improving the response speed of resource control.

[0093] Embodiment 3

[0094] Figure 3 A schematic diagram of the structure of an instruction decomposition device provided in Embodiment 3 of the present invention is shown in FIG. Figure 3 As shown, the instruction decomposition device includes an instruction receiving module 31 and an instruction decomposition module 32.

[0095] Among them, the instruction receiving module 31 is used to receive resource control instructions; the instruction decomposition module 32 is used to decompose the resource control instructions according to the control strategy in the resource control instructions and the adjustable capacity information of each adjustable resource corresponding to the edge intelligent control terminal; wherein the resource control instructions are instructions sent directly by the power grid dispatching agency to the edge intelligent control terminal; each adjustable resource is a resource located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers.

[0096] The technical solution of the embodiment of the present invention adopts an independently set edge intelligent control terminal for resource regulation and management of part of the management scope required by the power grid dispatching organization, directly communicates with the power grid dispatching organization to receive the resource regulation instructions of the power grid dispatching organization for the resources within the management scope, and can directly decompose the resource regulation instructions in the edge intelligent control terminal to obtain instructions that can be directly used to control the resources belonging to different virtual power plant providers within the management scope. Since the instruction reception and decomposition process will not be affected by the different virtual power plant providers to which the resources belong, the power grid dispatching organization does not need to send separate regulation instructions to all virtual power plant providers to which the resources need to be controlled, thereby reducing the number of regulation instructions that the power grid dispatching organization needs to send. At the same time, since the edge intelligent control terminal only decomposes and manages instructions for resources within its manageable scope, the amount of information contained in the resource regulation instructions it receives is less than the amount of information sent to the virtual power plant provider for regulating all resources in the virtual power plant provider, so the time required for decomposing the regulation instructions can be reduced, and the power grid dispatching organization can directly manage the local resources of the power grid through the edge intelligent control terminal, thereby improving the response speed of resource regulation.

[0097] Optionally, the instruction decomposition module 32 is specifically used for:

[0098] Determine target resource control information according to the resource control instruction;

[0099] Determine at least one candidate adjustable resource from each adjustable resource according to the target resource control information and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal;

[0100] Determine the target adjustable resource from the candidate adjustable resources according to the control strategy in the resource control instruction, the adjustable capability information of each candidate adjustable resource and the target resource control information;

[0101] According to the adjustable capacity information of each target adjustable resource, the resource control instruction is decomposed into target resource control instructions for each target adjustable resource.

[0102] Optionally, when the control strategy in the resource control instruction is a response priority strategy, determining the target adjustable resource from the candidate adjustable resources according to the control strategy in the resource control instruction, the adjustable capability information of each candidate adjustable resource, and the target resource control information includes:

[0103] Determine the response time and adjustable capacity corresponding to each candidate adjustable resource according to the adjustable capability information of each candidate adjustable resource;

[0104] Selecting each candidate adjustable resource in the order of response time from short to long, and accumulating the adjustable capacities of the selected candidate adjustable resources to obtain the accumulated adjustable capacity, until the accumulated adjustable capacity reaches the target resource regulation amount in the target resource regulation information;

[0105] Each selected candidate adjustable resource is determined as a target adjustable resource.

[0106] Optionally, when the control strategy in the resource control instruction is a quality priority strategy, determining the target adjustable resource from the candidate adjustable resources according to the control strategy in the resource control instruction, the adjustable capability information of each candidate adjustable resource, and the target resource control information includes:

[0107] Determine an adjustable capability value of each candidate adjustable resource, and determine an adjustable capacity corresponding to each candidate adjustable resource according to the adjustable capability information of each candidate adjustable resource;

[0108] Selecting each candidate adjustable resource in descending order of adjustment capability value, and accumulating the adjustable capacity of the selected candidate adjustable resources to obtain the accumulated adjustable capacity, until the accumulated adjustable capacity reaches the target resource adjustment amount in the target resource adjustment information;

[0109] Each selected candidate adjustable resource is determined as a target adjustable resource.

[0110] Optionally, before receiving the resource control instruction, the following is further included:

[0111] Receive the resource adjustable capacity prediction model sent by the power grid dispatching agency; for each adjustable resource corresponding to the edge intelligent control terminal, input the resource type and resource characteristic information of the adjustable resource, as well as the longitude and latitude, weather information and current load curve corresponding to the edge intelligent control terminal into the resource adjustable capacity prediction model according to a preset period to determine the adjustable capacity information of the adjustable resource.

[0112] Optionally, after decomposing the resource control instructions, the following is further included:

[0113] The decomposed resource control instructions are sent to the corresponding target adjustable resources respectively, and the execution status of each target adjustable resource is monitored to determine the monitoring execution result; the monitoring execution result is fed back to the power grid dispatching agency so that the power grid dispatching agency can update the resource adjustable capacity prediction model.

[0114] The instruction decomposition device provided in the embodiment of the present invention can execute the instruction decomposition method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0115] Embodiment 4

[0116] Figure 4 A schematic diagram of the structure of an edge intelligent control terminal provided for Embodiment 4 of the present invention. The edge intelligent control terminal 40 may be intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The edge intelligent control terminal 40 may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided for example only and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0117] like Figure 4 As shown, the edge intelligent control terminal 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In RAM 43, various programs and data required for the operation of the edge intelligent control terminal 40 can also be stored. The processor 41, ROM 42 and RAM 43 are connected to each other via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0118] Multiple components in the edge intelligent control terminal 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the edge intelligent control terminal 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0119] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as the instruction decomposition method.

[0120] In some embodiments, the instruction decomposition method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the computing power distribution device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the instruction decomposition method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to perform the instruction decomposition method in any other appropriate manner (e.g., by means of firmware).

[0121] Optionally, an embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the instruction decomposition method provided by any embodiment of the present invention.

[0122] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0123] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0124] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0125] In order to provide interaction with the user, the systems and techniques described herein can be implemented on a computing power distribution device, which has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball), through which the user can provide input to the computing power distribution device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0126] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0127] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0128] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0129] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for decomposing instructions, characterized in that: Applied to edge intelligent control terminals, including: Receive resource control instructions; Decomposing the resource control instruction according to the control strategy in the resource control instruction and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal; Among them, the resource regulation instruction is an instruction sent directly by the power grid dispatching organization to the edge intelligent control terminal; each of the adjustable resources is a resource located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers.

2. The instruction decomposition method according to claim 1, characterized in that: Decomposing the resource control instruction according to the control strategy in the resource control instruction and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal includes: Determining target resource control information according to the resource control instruction; Determine at least one candidate adjustable resource from the adjustable resources according to the target resource regulation information and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal; Determine a target adjustable resource from the candidate adjustable resources according to the regulation strategy in the resource regulation instruction, the adjustable capability information of each candidate adjustable resource and the target resource regulation information; According to the adjustable capability information of each of the target adjustable resources, the resource control instruction is decomposed into target resource control instructions for each of the target adjustable resources.

3. The instruction decomposition method according to claim 2, characterized in that: When the control strategy in the resource control instruction is a response priority strategy, The determining the target adjustable resource from the candidate adjustable resources according to the regulation strategy in the resource regulation instruction, the adjustable capability information of each candidate adjustable resource and the target resource regulation information includes: Determining the response time and the adjustable capacity corresponding to each of the candidate adjustable resources according to the adjustable capability information of each of the candidate adjustable resources; Selecting each of the candidate adjustable resources in order of response time from short to long, and accumulating the adjustable capacities of the selected candidate adjustable resources to obtain an accumulated adjustable capacity, until the accumulated adjustable capacity reaches the target resource regulation amount in the target resource regulation information; Each selected candidate adjustable resource is determined as a target adjustable resource.

4. The instruction decomposition method according to claim 2, characterized in that: When the control strategy in the resource control instruction is a quality priority strategy, The determining the target adjustable resource from the candidate adjustable resources according to the regulation strategy in the resource regulation instruction, the adjustable capability information of each candidate adjustable resource and the target resource regulation information includes: Determine an adjustable capability value of each of the candidate adjustable resources, and determine an adjustable capacity corresponding to each of the candidate adjustable resources according to the adjustable capability information of each of the candidate adjustable resources; Selecting each of the candidate adjustable resources in descending order of adjustment capability value, and accumulating the adjustable capacities of the selected candidate adjustable resources to obtain an accumulated adjustable capacity, until the accumulated adjustable capacity reaches the target resource adjustment amount in the target resource adjustment information; Each selected candidate adjustable resource is determined as a target adjustable resource.

5. The instruction decomposition method according to claim 1, characterized in that: Before receiving the resource control instruction, the method further includes: Receiving a resource adjustable capacity prediction model sent by the power grid dispatching organization; For each adjustable resource corresponding to the edge intelligent control terminal, the resource type and resource characteristic information of the adjustable resource, as well as the longitude and latitude, weather information and current load curve corresponding to the edge intelligent control terminal are input into the resource adjustable capacity prediction model according to a preset period to determine the adjustable capacity information of the adjustable resource.

6. The instruction decomposition method according to claim 5, characterized in that: After decomposing the resource control instruction, the method further includes: Sending the decomposed resource control instructions to the corresponding target adjustable resources respectively, and monitoring the execution status of each target adjustable resource to determine the monitoring execution result; The monitoring execution result is fed back to the power grid dispatching organization so that the power grid dispatching organization updates the resource adjustable capacity prediction model.

7. An instruction decomposition device, characterized in that: Applied to edge intelligent control terminals, including: An instruction receiving module, used for receiving resource control instructions; An instruction decomposition module, used to decompose the resource control instruction according to the control strategy in the resource control instruction and the adjustable capability information of each adjustable resource corresponding to the edge intelligent control terminal; Among them, the resource regulation instruction is an instruction sent directly by the power grid dispatching organization to the edge intelligent control terminal; each of the adjustable resources is a resource located within the management scope of the edge intelligent control terminal and belongs to different virtual power plant providers.

8. An edge intelligent control terminal, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the instruction decomposition method described in any one of claims 1 to 6.

9. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the instruction decomposition method according to any one of claims 1 to 6 when executed by a computer processor.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the instruction decomposition method according to any one of claims 1 to 6.

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