Power grid resource regulation and control method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a power grid resource regulation and control method and device, computer equipment, a readable storage medium and a program product, and relates to the technical field of power grid regulation and control. The method comprises the following steps: in response to a resource regulation and control instruction for a target power grid, obtaining a regulation and control demand indicated by the resource regulation and control instruction; for each candidate regulation and control object in the target power grid, screening out a target regulation and control object meeting a regulation and control requirement from each candidate regulation and control object; performing performance analysis on the target regulation and control object to obtain a performance analysis result of the target regulation and control object; and performing resource regulation and control on the target regulation and control object according to the regulation and control priority matched with the performance analysis result. By adopting the method, the power grid resource regulation efficiency can be improved.

Description

Technical Field

[0001] This application relates to the technical field of power grid regulation, and in particular, to a power grid resource regulation method, device, computer device, computer-readable storage medium, and computer program product. Background Art

[0002] Under the development prospect of new energy and renewable energy, the traditional power grid system is gradually transforming into a new type of power grid system. However, the access of a large amount of new energy has brought huge challenges to the operation stability of the power grid system. Based on this, how to conduct reasonable and efficient resource regulation on the power grid system has become an urgent problem to be solved at present.

[0003] Currently, centralized regulation is usually adopted to achieve power grid resource regulation. However, as the number of regulation objects in the power grid system gradually increases, the pressure on the regulation center gradually increases, which is likely to lead to a decline in the efficiency of power grid resource regulation. Summary of the Invention

[0004] Based on this, it is necessary to provide a power grid resource regulation method, device, computer device, computer-readable storage medium, and computer program product that can improve the efficiency of power grid resource regulation for the above technical problems.

[0005] In a first aspect, this application provides a power grid resource regulation method, including: in response to a resource regulation instruction for a target power grid, obtaining the regulation requirements indicated by the resource regulation instruction; for each candidate regulation object in the target power grid, screening out target regulation objects that meet the regulation requirements from the candidate regulation objects; performing performance analysis on the target regulation objects to obtain a performance analysis result of the target regulation objects; and performing resource regulation on the target regulation objects according to the regulation priority level matching the performance analysis result.

[0006] In one of the embodiments, screening out target regulation objects that meet the regulation requirements from the candidate regulation objects includes: classifying the candidate regulation objects to obtain at least one type of regulation object cluster; for each type of regulation object cluster, constructing a relationship structure diagram between the sub-regulation objects based on the association relationship between the sub-regulation objects in the regulation object cluster; and screening out target regulation objects that meet the regulation requirements from the sub-regulation objects based on the relationship structure diagram.

[0007] In one embodiment, the regulation requirement includes a regulation duration requirement; based on the relationship structure diagram, screening out target regulation objects that meet the regulation requirements from each sub-regulation object includes: extracting a minimum spanning tree from the relationship structure diagram; the nodes of the minimum spanning tree correspond to the sub-regulation objects one by one; for each child node in the minimum spanning tree, counting the communication duration between the child node and the root node in the minimum spanning tree, and taking the communication duration as the required duration for the sub-regulation object matching the child node to receive the resource regulation task; taking the sub-regulation object whose required duration meets the regulation duration requirement as the target regulation object.

[0008] In one embodiment, taking the sub-regulation object whose required duration meets the regulation duration requirement as the target regulation object includes: taking the sub-regulation object whose required duration meets the regulation duration requirement as the selected regulation object; performing duration error analysis on the selected regulation object to obtain the duration error of the selected regulation object receiving the resource regulation task; based on the required duration and the duration error, determining the resource regulation task receiving duration of the selected regulation object; and taking the selected regulation object as the target regulation object when the resource regulation task receiving duration meets the regulation duration constraint condition.

[0009] In one embodiment, performing performance analysis on the target regulation object to obtain the performance analysis result of the target regulation object includes: performing margin analysis on the target regulation object to obtain the resource regulation margin of the target regulation object; performing stability analysis on the target regulation object to obtain the resource regulation stability of the target regulation object; counting the number of resource regulations of the target regulation object; and taking the resource regulation margin, the resource regulation stability, and the number of resource regulations together as the performance analysis result of the target regulation object.

[0010] In one embodiment, performing resource regulation on the target regulation object according to the regulation priority matching the performance analysis result includes: performing resource allocation on the target regulation object according to the regulation priority matching the performance analysis result to obtain the adjustable resources of the target regulation object; and performing resource regulation on the target regulation object based on the adjustable resources.

[0011] In a second aspect, the present application also provides a power grid resource regulation device, including: a requirement acquisition module, configured to acquire a regulation requirement indicated by a resource regulation instruction in response to a resource regulation instruction for a target power grid; a regulation object screening module, configured to screen out target regulation objects that meet the regulation requirements from each candidate regulation object for each candidate regulation object in the target power grid; a regulation object performance analysis module, configured to perform performance analysis on the target regulation object to obtain the performance analysis result of the target regulation object; and a resource regulation module, configured to perform resource regulation on the target regulation object according to the regulation priority matching the performance analysis result.

[0012] In a third aspect, the present application also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: in response to a resource regulation instruction for a target power grid, obtain the regulation requirements indicated by the resource regulation instruction; for each candidate regulation object in the target power grid, screen out the target regulation objects that meet the regulation requirements from the candidate regulation objects; perform a performance analysis on the target regulation objects to obtain a performance analysis result of the target regulation objects; and perform resource regulation on the target regulation objects according to the regulation priority that matches the performance analysis result.

[0013] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: in response to a resource regulation instruction for a target power grid, obtain the regulation requirements indicated by the resource regulation instruction; for each candidate regulation object in the target power grid, screen out the target regulation objects that meet the regulation requirements from the candidate regulation objects; perform a performance analysis on the target regulation objects to obtain a performance analysis result of the target regulation objects; and perform resource regulation on the target regulation objects according to the regulation priority that matches the performance analysis result.

[0014] In a fifth aspect, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the following steps are implemented: in response to a resource regulation instruction for a target power grid, obtain the regulation requirements indicated by the resource regulation instruction; for each candidate regulation object in the target power grid, screen out the target regulation objects that meet the regulation requirements from the candidate regulation objects; perform a performance analysis on the target regulation objects to obtain a performance analysis result of the target regulation objects; and perform resource regulation on the target regulation objects according to the regulation priority that matches the performance analysis result.

[0015] For the above power grid resource regulation method, device, computer device, computer-readable storage medium, and computer program product, in response to a resource regulation instruction for a target power grid, first obtain the regulation requirements indicated by the resource regulation instruction to screen out the target regulation objects that meet the regulation requirements from each candidate regulation object in the target power grid. Then perform a performance analysis on the target regulation objects, so as to perform resource regulation on the target regulation objects according to the regulation priority that matches the performance analysis result of the target regulation objects. In this way, compared with the current centralized regulation method, on the one hand, this solution screens out the regulation objects that meet the regulation requirements, and on the other hand, performs reasonable resource regulation on them according to the corresponding priority of the regulation objects, which can not only effectively improve the efficiency of power grid resource regulation, but also contribute to the stable operation of the power grid system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the accompanying drawings required for the description of the embodiments of the present application or related technologies. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0017] Figure 1 It is an application environment diagram of the power grid resource regulation method in an embodiment;

[0018] Figure 2 It is a flowchart of the power grid resource regulation method in an embodiment;

[0019] Figure 3 It is a flowchart of screening regulation objects in an embodiment;

[0020] Figure 4 It is a flowchart of calculating the information reception duration of regulation objects in an embodiment;

[0021] Figure 5 It is a flowchart of calculating the error of the information reception duration of regulation objects in an embodiment;

[0022] Figure 6 It is a flowchart of performing performance analysis on regulation objects in an embodiment;

[0023] Figure 7 It is a flowchart of resource regulation based on priority in an embodiment;

[0024] Figure 8 It is a schematic diagram of the architecture of the power grid resource scheduling system in a specific embodiment;

[0025] Figure 9 It is a flowchart of the power grid resource regulation in a specific embodiment;

[0026] Figure 10 It is a flowchart of calculating the information reception duration of user-controllable loads in a specific embodiment;

[0027] Figure 11 It is a block diagram of the structure of the power grid resource regulation device in an embodiment;

[0028] Figure 12 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0029] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0030] The power grid resource regulation method provided by the embodiment of the present application can be applied to an application environment as Figure 1 shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed in the cloud or other network servers. The terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers and Internet of Things devices. The server 104 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0031] Exemplarily, in response to a resource regulation instruction for a target power grid initiated by the terminal 102, the server 104 first obtains the regulation requirements indicated by the resource regulation instruction. Then, it screens out the target regulation objects that meet the regulation requirements from each candidate regulation object in the target power grid. Next, it performs a performance analysis on the target regulation objects to obtain the performance analysis results of the target regulation objects. Finally, it performs resource regulation on the target regulation objects according to the regulation priority matching the performance analysis results.

[0032] In an exemplary embodiment, as Figure 2 shown, a power grid resource regulation method is provided. Taking the method applied to the Figure 1 server 104 as an example, the method includes the following steps:

[0033] Step S202: In response to a resource regulation instruction for a target power grid, obtain the regulation requirements indicated by the resource regulation instruction.

[0034] Among them, the target power grid may refer to the power network that needs to conduct resource regulation. The resource regulation instruction may refer to the instruction for regulating the resources of the target power grid. Resource regulation refers to the management and adjustment of various resources in the power grid to ensure the safe, stable, and economic operation of the power grid. The resource regulation instruction carries regulation requirements, and the regulation requirement refers to the business requirements when conducting resource regulation on the target power grid, such as regulation duration, regulation power base point, peak shaving and frequency modulation requirements, regulation component, etc. Among them, the regulation duration may refer to the duration requirement for resource regulation, such as the need to complete resource regulation within 1 minute. The regulation power base point refers to the current real-time distribution power of the target power grid, or the current actual load demand of the target power grid. Peak shaving refers to adjusting the power generation to meet the demand during the peak period of power demand. The load of the power system changes with time and seasons, and there are usually situations where the demand surges during certain periods of a day (such as the peak electricity consumption periods in the morning and evening). To ensure the power supply at these high-demand moments, additional power generation capacity needs to be increased. The main goal of peak shaving is to ensure sufficient power supply when the power demand reaches the peak, and to avoid power outages or power rationing caused by insufficient power supply. Frequency modulation refers to the process of maintaining the frequency stability of the power system. The frequency of the power system should be maintained at a constant value, but the mismatch between the actual power consumption and power generation will cause the system frequency to fluctuate. If the power consumption suddenly increases and the power generation does not increase correspondingly, the frequency will decrease; conversely, if the power generation is excessive and the power consumption decreases, the frequency will increase. This change in frequency not only affects the power quality but may also damage equipment such as generators. Therefore, the frequency modulation service adjusts the power generation output to keep the system frequency within the set range by quickly responding to the changes in power supply and demand, thus ensuring the safe and stable operation of the power grid. The regulation component is the power distribution amount obtained by the server according to the peak shaving and frequency modulation requirements and the regulation power base point. For example, assuming that the peak shaving demand of the target power grid increases to 12 MW (megawatts), and the current regulation power base point is 10 MW, then the regulation component is 2 MW, indicating that 2 MW of power supply needs to be increased. Of course, in actual applications, the specific content of the regulation requirements can be determined according to the actual situation, and this implementation does not limit it.

[0035] Exemplarily, in response to the resource regulation instruction for the target power grid sent by the terminal, the server first parses the resource regulation instruction to obtain the regulation requirements carried by the resource regulation instruction.

[0036] In some embodiments, the regulation demand can also be calculated by the server based on the frequency of the target power grid and the tie-line power. The grid frequency refers to the number of times the voltage of the power grid changes periodically, usually 50 Hz (Hertz) or 60 Hz. The tie-line power refers to the power transmitted between the target power grid and other power grid systems through the tie-line, which can be used to represent the power exchange volume between power grids. Specifically, when the power supply and demand are unbalanced, the grid frequency will deviate from the rated value. An increase in frequency indicates that supply exceeds demand, and a decrease in frequency indicates that supply is less than demand. When the tie-line power deviates from the planned value, it indicates an imbalance in the power exchange between power grids. By monitoring the grid frequency deviation, the frequency regulation demand can be determined, and the grid frequency deviation is proportional to the frequency regulation demand. Similarly, by monitoring the tie-line power deviation, the tie-line power regulation demand can be determined, and the tie-line power deviation is proportional to the tie-line power regulation demand. Finally, the frequency regulation demand and the tie-line power regulation demand are summarized to obtain the final regulation demand.

[0037] Step S204: For each candidate regulation object in the target power grid, screen out the target regulation objects that meet the regulation demand from each candidate regulation object.

[0038] Among them, the regulation object refers to the objects in the target power grid that can be regulated for resources, including but not limited to user-controllable loads, energy storage objects, generator sets, etc. User-controllable loads refer to the loads of specific users that can limit power consumption for a period of time at the request of the power supply department. These loads can be controlled through agreements to balance power supply and demand. Especially during peak power consumption periods, the pressure on the power grid can be effectively relieved by adjusting the power consumption behavior of users. User-controllable loads can be further divided into user-switchable interruptible loads, user-continuous controllable loads, and user energy storage units. User-switchable interruptible loads are those where users submit power consumption plans to the control center of user-controllable loads according to their own power consumption needs, and this control center is communicatively connected to the server. Based on the users' power consumption plans and regulation requirements, this control center regulates this part of the user loads. User-continuous controllable loads mainly refer to user loads whose power consumption can be adjusted, such as air-conditioning loads, electric heating loads, electric water heater loads, etc. User energy storage units mainly refer to various energy storage devices on the user side. Energy storage objects mainly refer to shared energy storage power stations and pumped storage power stations. Shared energy storage power stations mainly refer to battery energy storage stations, which are mainly used to absorb poor-quality electric energy, provide power outage protection, etc. Pumped storage power stations mainly include pumped storage power stations, flywheel energy storage power stations, and thermal energy storage power stations, etc. Generator sets mainly include thermal power generator sets, hydraulic power generator sets, and renewable energy generator sets. These can all be used as candidate regulation objects. By screening these candidate regulation objects, the target regulation objects that meet the regulation requirements can be obtained. There can be multiple target regulation objects. It can be understood that in this embodiment, by considering different types of regulation objects, the defect of only considering a single load during current power grid regulation is overcome, and the practicality of power grid resource regulation is effectively improved.

[0039] Exemplarily, after the server obtains the regulation requirements, it can screen each candidate regulation object in the target power grid to screen out the regulation object that meets the regulation requirements. Specifically, the server can first evaluate according to the regulation requirements whether user-controllable loads, energy storage objects, and generator sets need to participate in resource regulation. If the regulation requirement is relatively small, such as 10 MV, perhaps only energy storage objects or generator sets can meet the requirement, then there is no need to regulate user-controllable loads. If the regulation requirement is relatively large, such as 100 MW, then user-controllable loads need to participate in the regulation. Of course, the basis for evaluating whether these regulation objects need to participate in resource regulation is not limited to the size of the regulation requirement, and it can be evaluated according to the actual situation. This embodiment does not limit this. After determining that these candidate regulation objects need to participate in resource regulation, further analysis can be performed on these candidate regulation objects to screen out the optimal regulation object that meets the regulation requirements.

[0040] Step S206, perform performance analysis on the target regulation object to obtain the performance analysis result of the target regulation object.

[0041] Among them, performance analysis refers to the process of analyzing the performance of the target regulation object during the resource regulation process. The performance analysis results may include, but are not limited to, the resource regulation margin, resource regulation stability, resource regulation times, etc. of the target regulation object.

[0042] Exemplarily, considering that there are often multiple target regulation objects that meet the regulation requirements, in order to further improve the efficiency of resource regulation, performance analysis can be performed on each target regulation object to obtain performance analysis results such as the resource regulation margin, resource regulation stability, and resource regulation times of each target regulation object, so as to be used to determine the regulation priority of each target regulation object subsequently.

[0043] Step S208, perform resource regulation on the target regulation object according to the regulation priority matching the performance analysis result.

[0044] Among them, the regulation priority refers to the priority of performing resource regulation on the target regulation object. The higher the priority, the earlier the resource allocation and resource regulation are performed, and the lower the priority, the later the resource allocation and resource regulation are performed.

[0045] Exemplarily, after the server obtains the respective performance analysis results of each target regulation object, it can respectively query the regulation priorities matching the respective performance analysis results of each target regulation object based on the correspondence between the performance analysis result and the regulation priority, so as to perform resource allocation and resource regulation on each target regulation object in turn according to the regulation priority. Among them, the expression form of the correspondence is not limited, and it can be a correspondence table or a correspondence database.

[0046] In this embodiment, in response to a resource regulation instruction for a target power grid, first obtain the regulation requirements indicated by the resource regulation instruction to screen out the target regulation objects that meet the regulation requirements from each candidate regulation object in the target power grid. Then perform performance analysis on the target regulation objects, and thus perform resource regulation on the target regulation objects according to the regulation priority matching the performance analysis results of the target regulation objects. In this way, compared with the current centralized regulation method, on the one hand, this embodiment screens out the regulation objects that meet the regulation requirements, and on the other hand, performs reasonable resource regulation on them according to the corresponding priorities of the regulation objects, which can not only effectively improve the efficiency of power grid resource regulation, but also be beneficial to the stable operation of the power grid system.

[0047] In an exemplary embodiment, as Figure 3 shown, screening out the target regulation objects that meet the regulation requirements from each candidate regulation object includes:

[0048] Step S302, classify each candidate regulation object to obtain at least one type of regulation object cluster.

[0049] Among them, the regulated object cluster is a cluster composed of multiple candidate regulated objects belonging to the same category. For example, all user-controllable loads form a user-controllable load cluster, all energy storage objects form an energy storage cluster, and all generator sets form a generator set cluster. Classifying the candidate regulated objects is to screen out the optimal regulated objects in each type of regulated object cluster to participate in resource regulation, and the optimal regulated objects in all regulated object clusters are the target regulated objects.

[0050] Exemplarily, for each candidate regulated object in the target power grid, the server can first classify them, classify all user-controllable loads into the user-controllable load cluster, classify all energy storage objects into the energy storage cluster, and classify all generator sets into the generator set cluster. Classification can be performed according to the object identifier of each candidate regulated object, such as the name, or classified according to the use of each candidate regulated object. The specific classification method is not limited in this embodiment.

[0051] Step S304, for each type of regulated object cluster, based on the association relationship between the sub-regulated objects in the regulated object cluster, construct a relationship structure diagram between the sub-regulated objects.

[0052] Among them, the sub-regulated object refers to the regulated object in the regulated object cluster, and these regulated objects have the same category. The association relationship refers to the communication relationship between the sub-regulated objects. It should be noted that the regulated object cluster can be understood as a cluster network, where the nodes in the network are communicatively connected to exchange information. In the scenario of power grid resource regulation, the sub-regulated objects can transmit the resource regulation tasks issued by the server, and can also exchange information such as power consumption status (such as current power consumption, adjustable range), regulation ability (such as maximum regulation power, response speed), and priority, so as to achieve global information synchronization. In this embodiment, the regulated object cluster exchanges information based on a distributed communication architecture. Specifically, it is a communication network based on the Gossip algorithm. The Gossip algorithm is a communication protocol in a distributed system, mainly used to spread information in a distributed system to ensure that all nodes finally reach a consistent state, that is, all sub-regulated objects can receive the resource regulation tasks. The Gossip algorithm spreads information through random communication between nodes. Each node randomly selects other nodes to communicate and exchange information, and finally makes the information of all nodes consistent. The Gossip algorithm does not need to know the information of all nodes, as long as the network is connected, so it has the characteristic of decentralization.

[0053] The relationship structure diagram can be understood as a topological graph used to describe the communication relationships among sub-regulation objects. Taking the user-controllable load cluster as an example, assuming that the user-controllable load cluster is a cluster network randomly connected by N users, then its relationship structure diagram can be represented as a connected undirected graph G=(V, E), where the vertex set V={1, 2, ..., N} represents the N user nodes in the network, (u, v) represents that there is a direct communication link connecting vertex u and vertex v, (u, v)∈E, and w(u, v) represents the weight of the edge formed by vertex u and vertex v.

[0054] In a preferred example, the Gossip algorithm proposed above can meet the following restrictive conditions: First, there is a global clock in the cluster network, so that the information exchange process of all nodes can occur at the same moment, thus avoiding common asynchronous communication problems in distributed systems such as latency and clock drift. Second, in each information exchange, the node that newly receives the information will at least pass the information to one new node, so that the information can be quickly spread in the network, avoiding the stagnation of propagation and improving the efficiency of information dissemination. And through the constraint of "will at least pass the information to one new node", it can also ensure that the propagation process has a certain lower limit speed. Third, in each information exchange, a node can only have a single communication. Based on these restrictive conditions, the randomness of the Gossip algorithm is eliminated, and the information dissemination path becomes more deterministic, similar to the structure of a multi-way tree. In addition to setting restrictive conditions, information dissemination can also be achieved by fixing the routing table method, that is, each node maintains a routing table to record its communication objects (such as the next-hop node). The information is disseminated according to the instructions in the routing table, so as to avoid the uncertainty and redundant communication brought by random selection and reduce the communication cost.

[0055] For example, assume that the user-controllable load cluster includes users A, B, C, and D. Initially, user A holds the information, and other users are not infected, that is, they have not received the information. Then user A starts to conduct information exchange, and user A selects user B for communication. User A and user B can only participate in one communication at this time step. Result: User B receives the information. User B continues to conduct information exchange, and user B selects user C for communication exchange. User B and user C can only participate in one communication at this time step. Result: User C is infected. User C continues to conduct information exchange, and user C selects user D for communication exchange. User C and user D can only participate in one communication at this time step. Result: User D is infected. Finally, the information spreads from user A to all users.

[0056] Step S306, based on the relationship structure diagram, screen out the target regulation objects that meet the regulation requirements from each sub-regulation object.

[0057] Exemplarily, after constructing the relationship structure diagram among the sub-regulation objects, the server can further construct a connected sub-graph with the minimum communication cost among the sub-regulation objects from this relationship structure diagram. Based on this connected sub-graph, the target regulation objects that meet the regulation requirements are screened out from the sub-regulation objects.

[0058] In this embodiment, by constructing the structure diagram of the communication relationship among the sub-regulation objects in the regulation object cluster, the information transmission situation among the sub-regulation objects is clearly reflected, which is beneficial to quickly screening out the target regulation objects that meet the regulation requirements from the sub-regulation objects.

[0059] In an exemplary embodiment, as Figure 4 shown, based on the relationship structure diagram, screening out the target regulation objects that meet the regulation requirements from the sub-regulation objects includes:

[0060] Step S402, extracting the minimum spanning tree from the relationship structure diagram; the nodes of the minimum spanning tree correspond to the sub-regulation objects one by one.

[0061] Among them, the minimum spanning tree refers to a connected sub-graph composed of all vertices in a connected undirected graph. This sub-graph is a tree, and the sum of the weights of all its edges is the smallest. In other words, the minimum spanning tree is a tree that minimizes the total weight of the edges connecting these vertices on the premise of ensuring the connectivity of all vertices in the graph. In this embodiment, it is to minimize the communication cost of these sub-regulation objects on the premise of ensuring the connectivity of all sub-regulation objects. By extracting the minimum spanning tree, the optimal information transmission path among all sub-regulation objects is constructed. Each node in the minimum spanning tree corresponds to a sub-regulation object.

[0062] In some embodiments, if there exists T as a subset of E, that is, T ∈ E, and it satisfies that (V, T) is a tree and satisfies the following expression, then T is considered the minimum spanning tree of G.

[0063]

[0064] Among them, the right side of the expression represents the total weight of the spanning tree T, that is, the sum of the weights of all edges.

[0065] Exemplarily, after constructing the relationship structure diagram among the sub-regulation objects, the server can further extract the minimum spanning tree from this relationship structure diagram to minimize the communication cost among the sub-regulation objects. Specifically, the server can use a greedy algorithm such as the Prim algorithm to extract the minimum spanning tree. The Prim algorithm starts constructing the minimum spanning tree from a certain vertex, and then continuously adds edges to other nodes that have not been added to the minimum spanning tree until the entire graph is covered.

[0066] For example, assume that the relationship structure diagram G contains 4 vertices V = {A, B, C, D} and 5 edges E = {(A, B), (A, C), (B, C), (B, D), (C, D)}, and the weights of the edges are as follows: w(A, B) = 1; w(A, C) = 2; w(B, C) = 3; w(B, D) = 4; w(C, D) = 5. The edge weights can be flexibly set according to specific situations. The steps of constructing a minimum spanning tree using Prim's algorithm include: First, initial selection, that is, selecting vertex A as the starting point. Then, select the edge (A, B) with the smallest weight and add B to the spanning tree. Starting from A and B, select the edge (A, C) with the smallest weight and add C to the spanning tree. Continuing from A, B, and C, select the edge (B, D) with the smallest weight and add D to the spanning tree. At this time, all vertices are included in the spanning tree. The generated spanning tree is T = {(A, B), (A, C), (B, D)}, and the total weight w(T) = 1 + 2 + 4 = 7. It can be further verified based on the above expression whether the total weight of the spanning tree T is the smallest among all spanning trees. If T satisfies the expression, then T is considered the minimum spanning tree.

[0067] Step S404: For each child node in the minimum spanning tree, count the communication duration between the child node and the root node in the minimum spanning tree, and use the communication duration as the required duration for the sub-regulation object matching the child node to receive the resource regulation task.

[0068] Among them, the root node refers to the first node in the minimum spanning tree, that is, the starting node. The child node is a node in the minimum spanning tree other than the root node. Information starts from the root node and is transmitted to each child node along the path of the minimum spanning tree. The communication duration refers to the duration when the child node receives the information transmitted by the root node. In this embodiment, it can be understood as the duration when the sub-regulation object receives the resource regulation task. The resource regulation task will be propagated by the first sub-regulation object, and the first sub-regulation object refers to any regulation object that first receives the resource regulation task sent by the server. The resource regulation task can be encapsulated into a control signal and sent to each regulation object. The resource regulation task refers to the task of this resource regulation, such as the increased or decreased load.

[0069] For example, taking the user-controllable load cluster as an example, the server can extract the electricity consumption that needs to be regulated this time from the regulation requirements. Suppose it is to increase by 50 MV. The server will send "increase by 50 MV" as a resource regulation task to any user-controllable load in the user-controllable load cluster. This user will spread "increase by 50 MV" to the next user-controllable load connected to it along the path of the minimum spanning tree until all user-controllable loads receive the resource regulation task of "increase by 50 MV". Each user-controllable load can perform resource regulation according to its own status. Of course, in actual applications, the resource regulation task can also include the specific amount of resources to be regulated for each regulation object, and each regulation object can perform regulation according to the corresponding amount of resources. In addition, the resource regulation task can also include information such as the resource regulation time and the resource regulation area. The specific task content is not limited in this embodiment.

[0070] Exemplarily, after constructing the minimum spanning tree, the server can calculate the information reception duration of each node in the minimum spanning tree. Specifically, the root node in the minimum spanning tree is used as the starting node for information dissemination, and its layer is the first layer. The root node will pass the information to the nodes connected to it in the next layer, that is, the second layer. Then the nodes in the second layer will continue to pass the information to the connected nodes in the third layer until the last layer of the minimum spanning tree. In this process, the communication rounds of each node, that is, the rounds in which the node participates in communication, can be counted, so as to calculate the information reception duration of each node according to the communication rounds and the communication step size.

[0071] In actual applications, considering that there may be multiple nodes in the network communicating with other nodes in parallel, in order to ensure that the transmission of instructions is completed as quickly as possible, it can be set that the user nodes that receive new information give priority to communicating with the nodes with more subsequent node links to improve the information dissemination efficiency. Based on this, for different nodes in the k-1 column of the path matrix, the communication rounds of their connected nodes in the k column can be incremented by l respectively. l is the sorting result of the maximum length among all paths where the node is located under the nodes in the same layer. That is to say, the larger the value of l, the longer the path of the node and the more the communication rounds increase. Among them, the communication rounds represent the rounds in which the node participates in communication, indicating in which round of communication the node participates in information transmission. The path matrix is a two-dimensional array that stores the path information from the starting node to other nodes. Specifically, it can be an (N - 1) * R matrix, where N is the number of nodes and R is the number of nodes included in the longest path. k is an iterative variable used to represent the current processed path level.

[0072] Step S406, use the sub-regulation objects whose required duration meets the regulation duration requirement as the target regulation objects.

[0073] Among them, the regulation duration requirement refers to the requirement for the resource regulation duration. For example, it is required to complete the resource regulation within a specified duration. If the duration required for a sub-regulation object to receive the resource regulation task is within this specified duration, it can be considered that the sub-regulation object meets the regulation duration requirement and can participate in this resource regulation.

[0074] Exemplarily, after calculating the information reception duration of each node in the minimum spanning tree, the duration required for each sub-regulation object to receive the resource regulation task can be obtained. Determine whether this duration is less than or equal to the duration indicated in the regulation duration requirement. If so, this sub-regulation object can be used as the target regulation object. Otherwise, it is not used as the target regulation object.

[0075] In this embodiment, by extracting the minimum spanning tree from the relationship structure diagram, the path with the minimum communication cost between each sub-regulation object can be obtained. Then, based on the minimum spanning tree, the communication duration of each node, that is, the duration required for each sub-regulation object to receive the resource regulation task, can be calculated, which can improve the accuracy and reliability of the resource regulation task reception duration. Finally, the sub-regulation object whose duration meets the regulation duration requirement is used as the target regulation object. In this way, high-quality regulation objects that meet the regulation duration requirement can be screened out, thereby improving the efficiency of resource regulation.

[0076] In an exemplary embodiment, as Figure 5 shown, using the sub-regulation object whose required duration meets the regulation duration requirement as the target regulation object includes:

[0077] Step S502, using the sub-regulation object whose required duration meets the regulation duration requirement as the selected regulation object.

[0078] Step S504, perform duration error analysis on the selected regulation object to obtain the duration error of the selected regulation object receiving the resource regulation task.

[0079] Among them, the selected regulation object refers to the sub-regulation object whose required duration meets the regulation duration requirement. It can be understood that in practical applications, there are often problems such as output uncertainty, many intermediate regulation links, and long network delays when regulation objects in the power grid participate in regulation, which leads to errors or delays in the duration of the regulation object receiving the resource regulation task. Therefore, in order to ensure that the regulation object can execute the resource regulation task more efficiently, this embodiment further analyzes the duration error of the regulation object. It should be noted that if the time delay of the energy storage cluster and the conventional generator set cluster in receiving the resource regulation task is much smaller than that of the user-controllable load, the duration error analysis can focus on the user-controllable load. Of course, the duration error analysis can also be performed on the energy storage cluster and the conventional generator set cluster, which is specifically determined according to the actual situation.

[0080] Exemplarily, the server first filters out the sub-regulation objects whose required duration meets the regulation duration requirement as the selected regulation objects, and then performs further duration error analysis on the selected regulation objects. The duration error mainly consists of the server regulation delay, the control center regulation delay, and the device delay of the regulation object itself.

[0081] In one example, the expression for the duration error is:

[0082]

[0083] Where, represents the duration error of the selected regulation object (node) i. represents the server regulation delay, that is, the regulation delay of the control center. represents the regulation delay of the control center, that is, the control center of the cluster. represents the device delay of the regulation object itself.

[0084] Step S506, based on the required duration and the duration error, determine the resource regulation task reception duration of the selected regulation object.

[0085] Among them, the resource regulation task reception duration refers to the total duration for the selected regulation object to receive the resource regulation task, and this duration is the sum of the required duration and the duration error. The server will send the resource regulation task to the control center of the cluster, and the control center will distribute it to the regulation object cluster, and then the individual regulation objects in the regulation object cluster will transfer the resource regulation task to each other.

[0086] In one example, the calculation expression for the resource regulation task reception duration is:

[0087]

[0088]

[0089] Where, is the required duration for communication between the starting node and node i, is the starting time, represents the communication round of node i.

[0090] Step S508, when the resource regulation task reception duration meets the regulation duration constraint condition, regard the selected regulation object as the target regulation object.

[0091] Among them, the regulation duration constraint condition refers to the constraint condition for the regulation duration. In one example, the expression for the regulation duration constraint condition can be:

[0092]

[0093] Where, Denotes the limit value of the regulation duration. The resource regulation task receiving duration of the regulation object needs to be less than or equal to this limit value. It can be understood that It can be a preset standard limit value or a threshold set in real time according to the actual situation.

[0094] That is to say, the server will calculate the required duration for each node, that is, each sub-regulation object, to receive the resource regulation task based on the minimum spanning tree. This duration can be understood as an ideal value. Based on this duration, a batch of regulation objects that meet the regulation duration requirements can be screened out. Then, considering that in actual applications, during the process of the regulation object receiving the resource regulation task, due to various influencing factors, there will be a delay in the receiving duration. Therefore, it is necessary to further calculate the duration error of the regulation object. The sum of the duration error and the required duration is the final resource regulation task receiving duration of the regulation object. This duration needs to meet the duration constraint condition, that is, be less than or equal to the duration limit value. The regulation objects screened based on the duration constraint condition are the final objects for resource regulation. Through multiple screenings, high-quality regulation objects can be obtained, thereby improving the efficiency of power grid resource regulation and ensuring the stable operation of the power grid system.

[0095] In an exemplary embodiment, as Figure 6 shown, perform a performance analysis on the target regulation object to obtain the performance analysis result of the target regulation object, including:

[0096] Step S602, perform a margin analysis on the target regulation object to obtain the resource regulation margin of the target regulation object.

[0097] Among them, the margin analysis refers to the process of analyzing the adjustable resource range of the target regulation object. The resource regulation margin refers to the adjustable resource range of the target regulation object, such as power range, load range, current range, etc.

[0098] Exemplarily, the server performs a margin analysis on the target regulation object. Specifically, according to the direction of the regulation deviation (increasing or decreasing resources), calculate the regulation margin of each target regulation object, that is, the adjustable resource range. The target regulation object with a larger resource regulation margin is preferentially regulated. For example, assuming that 10 MW of power needs to be increased, regulation object A can increase 5 MW, and regulation object B can increase 3 MW. Regulation object A has a larger margin and is preferentially regulated.

[0099] Step S604, perform a stability analysis on the target regulation object to obtain the resource regulation stability of the target regulation object.

[0100] Among them, stability analysis refers to the process of analyzing the stability of the target regulation object during the resource regulation process. Resource regulation stability is used to characterize the stability degree, or rather, the fluctuation degree, of the target regulation object during the resource regulation process. The smaller the fluctuation, the more stable it is; the larger the fluctuation, the less stable it is. Priority is given to regulating the target regulation object with high stability.

[0101] Exemplarily, the server performs stability analysis on the target regulation object. Specifically, its stability can be analyzed according to the load volatility of the target regulation object. The higher the value of the load volatility, the greater the fluctuation and the lower the stability. The lower the value of the load volatility, the smaller the fluctuation and the higher the stability. Priority is given to regulating the target regulation object with higher stability. Of course, in addition to the load volatility, in practical applications, the stability of the regulation object can also be analyzed according to other parameters or other methods, and this embodiment does not limit this.

[0102] Step S606: Count the number of resource regulations of the target regulation object.

[0103] Among them, the number of resource regulations refers to the number of resource regulations. For example, regulation object A has been regulated once in the past week, and regulation object B has been regulated five times. Priority is given to regulating the regulation object with fewer resource regulation times to reduce the frequent interference to the regulation object.

[0104] Step S608: Use the resource regulation margin, resource regulation stability, and the number of resource regulations together as the performance analysis result of the target regulation object.

[0105] Exemplarily, use the resource regulation margin, resource regulation stability, and the number of resource regulations together as the performance analysis result of the target regulation object, so as to determine the regulation priority of the target regulation object according to these performance analysis results. It should be noted that the analysis order of the resource regulation margin, resource regulation stability, and the number of resource regulations can be set according to the actual situation. The priority can be matched in a certain order. For example, first match the priority according to the resource regulation margin, followed by resource regulation stability, and finally the number of resource regulations. Of course, the resource regulation margin, resource regulation stability, and the number of resource regulations can also be combined, and the priority can be matched according to the combined result of the three.

[0106] In this embodiment, a comprehensive performance analysis of the regulation object is carried out from three dimensions: the resource regulation margin, resource regulation stability, and the number of resource regulations, which improves the accuracy of the performance analysis, thereby improving the accuracy of the regulation priority, and further improving the accuracy and efficiency of the power grid resource regulation.

[0107] In an exemplary embodiment, such as Figure 7As shown, resource regulation is performed on the target regulation object according to the regulation priority matching the performance analysis result, including:

[0108] Step S702, allocate resources to the target regulation object according to the regulation priority matching the performance analysis result to obtain the adjustable resources of the target regulation object.

[0109] Step S704, perform resource regulation on the target regulation object based on the adjustable resources.

[0110] Among them, resource allocation can refer to the process of allocating regulation resources to the target regulation object, and can be allocated according to the regulation priority and the maximum resource allocation step size. The adjustable resources refer to the regulation target of the target regulation object, that is, the amount of resources that need to be increased or decreased.

[0111] Exemplarily, after the server obtains the regulation priority matching the performance analysis result of the target regulation object, it can allocate corresponding regulation resources to the target regulation object according to this priority and the preset maximum resource allocation step size. And generate a corresponding resource regulation task and send it to the cluster control center, which is forwarded by the control center to the target regulation object for resource regulation.

[0112] In some embodiments, the adjustable resources of the target regulation object can be calculated through the regulation power base point and the regulation component, and the calculation expression can be:

[0113]

[0114] Among them, represents the adjustable resources of the target regulation object, that is, the regulation target. represents the regulation power base point. represents the regulation component.

[0115] In some embodiments, corresponding priorities can also be set for different types of regulation object clusters. For example, resource regulation is preferentially performed on the user-controllable load cluster. After the user-controllable load cluster completes resource regulation, if there are still remaining regulation resources, resource regulation is performed on the energy storage cluster. After the energy storage cluster completes resource regulation, if there are still remaining regulation resources, resource regulation is performed on the generator set cluster.

[0116] In this embodiment, the regulation priority of the regulation object is fully considered, and resource allocation and regulation are performed according to the priority, which can effectively improve the efficiency of resource regulation. And the regulation priority is determined based on the performance of each regulation object, so as to ensure the accuracy and reliability of the regulation priority.

[0117] In a specific embodiment, the server is the server of the power grid dispatching center.Figure 8 The schematic diagram of the architecture of the power grid resource scheduling system is shown. It includes a power grid dispatching center and a cluster control center for controlling the user-controllable load cluster. The power grid dispatching center is connected to the cluster control center to transmit the regulation signal carrying the resource regulation task to the user-controllable load cluster through the cluster control center. The figure also includes an energy storage cluster and a generator set cluster, both of which can be directly controlled by the power grid dispatching center and corresponding regulation signals are sent. Among them, the regulation objects in the user-controllable load cluster mainly include User 1, User 2... User N, and each user can be further divided into user start-stop interruptible load, user continuously controllable load, and user energy storage unit. The regulation objects in the energy storage cluster are mainly the shared energy storage power station and the energy storage power station, and the regulation objects in the generator set cluster are mainly thermal power generator sets, hydropower generator sets, and renewable energy generator sets.

[0118] To realize the remote transmission and analysis of power grid data, in this embodiment, all data transmission and storage devices can collect power generation and load data to the intranet cloud platform through the intelligent gateway. The cloud platform terminal only allows intranet access to ensure user data security and effectively protect privacy. The intelligent gateway supports multiple network modes, including GPRS (general packet radio service), 5G / 4G / 3G, 1.8 GHz (gigahertz) power line wireless private network, 230 MHz (megahertz) power wireless private network, and fiber optic private network, and is compatible with multiple communication protocols such as TCP (Transmission Control Protocol), DL / T645, DL / T698, Modbus, UDP.

[0119] Figure 9 The schematic diagram of the process of power grid resource regulation is shown.

[0120] S1. In response to the resource regulation instruction for the regional power grid, the power grid dispatching center first calculates the regulation demand of the regional power grid.

[0121] S2. Classify all regulation objects in the regional power grid to obtain at least one type of regulation object cluster (user-controllable load cluster, energy storage cluster, generator set cluster). And judge whether to preferentially conduct resource regulation on the user-controllable load cluster.

[0122] S3. If so, screen out the target objects participating in this resource regulation from the user-controllable load cluster. If not, go to step S6.

[0123] Specifically, based on the association relationships among users in the user-controllable load cluster, a relationship structure diagram among users is constructed. Then, using the Prim algorithm, a minimum spanning tree is extracted from this relationship structure diagram. Next, for each child node in the minimum spanning tree, the communication duration between the child node and the root node in the minimum spanning tree is counted, and this communication duration is used as the required duration for the user object matching the child node to receive the resource regulation task. Figure 10 A flowchart for calculating the information reception duration of user-controllable loads is shown. Among them, first, an N*N connectivity matrix is constructed according to the relationship structure diagram, where N represents the number of users in the user-controllable load cluster. Then, a minimum spanning tree is constructed, and the shortest paths from the starting node to the remaining nodes in the minimum spanning tree are calculated, thereby forming an (N - 1)*R path matrix, and let k = 2. For different nodes in the (k - 1)-th column of the path matrix, the communication rounds between the k-th column and its connected nodes can be incremented by l respectively, where l is the sorting result of the maximum length among all paths where the node is located under the same layer of nodes. That is to say, the larger the l value, the longer the path of the node and the more the communication rounds increase. Among them, the communication round represents the order in which the node participates in communication, indicating in which round of communication the node participates in information transmission. k is an iterative variable used to represent the current path level being processed. Until k is greater than R (the number of nodes included in the longest path), the communication ends. The duration calculation is mainly based on the communication round n and the communication step Δt, and the starting time t = t0. Until it is calculated that t is greater than or equal to t N (regulation duration requirement), the current set of user-controllable loads is output, and this set is composed of user loads that meet the regulation duration requirement.

[0124] For each user in the set of user-controllable loads, further duration error analysis is carried out to obtain the duration errors of these users . For each user corresponding to and the sum of t is used as the final resource regulation task reception duration. When is less than or equal to the regulation duration limit value , this user is used as the target object participating in this resource regulation. The screening process for the regulation objects in the energy storage cluster and the generator set cluster is the same as that of the user-controllable load cluster, and will not be elaborated here.

[0125] S4. Analyze the resource regulation margin, resource regulation stability, and resource regulation times of the users participating in this resource regulation, so as to match a suitable regulation priority. According to this regulation priority, resources are allocated to users.

[0126] S5: After the resource regulation in the user-controllable load cluster is completed, if there are remaining regulation resources, then enter step S6.

[0127] S6, determine whether to perform resource regulation on the energy storage cluster. If so, proceed to step S7. If not, proceed to step S9.

[0128] S7, similar to the user-controllable load cluster, the energy storage cluster also performs regulation object screening and resource allocation.

[0129] S8, after the energy storage cluster completes resource regulation, if there are remaining regulation resources, execute S9.

[0130] S9, perform resource regulation on the generator set cluster.

[0131] S10, generate a control signal and send it to each cluster. End the entire resource regulation process.

[0132] In this embodiment, in response to a resource regulation instruction for the regional power grid, first obtain the regulation requirements indicated by the resource regulation instruction to screen out the target regulation objects that meet the regulation requirements from each candidate regulation object in the regional power grid. Then perform performance analysis on the target regulation objects, and thus perform resource regulation on the target regulation objects according to the regulation priority that matches the performance analysis results of the target regulation objects. In this way, compared with the current centralized regulation method, on the one hand, this embodiment screens out the regulation objects that meet the regulation requirements, and on the other hand, performs reasonable resource regulation on them according to the corresponding priorities of the regulation objects, which can not only effectively improve the efficiency of power grid resource regulation, but also contribute to the stable operation of the power grid system.

[0133] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same moment, but can be executed at different moments, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0134] Based on the same inventive concept, the embodiments of the present application also provide a power grid resource regulation device for implementing the above-mentioned power grid resource regulation method. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the power grid resource regulation device provided below can refer to the limitations on the power grid resource regulation method in the above text, and will not be repeated here.

[0135] In an exemplary embodiment, as Figure 11 shown, a power grid resource regulation device is provided, including: a demand acquisition module 1102, configured to acquire a regulation demand indicated by a resource regulation instruction in response to a resource regulation instruction for a target power grid; a regulation object screening module 1104, configured to screen out a target regulation object that meets the regulation demand from each candidate regulation object in the target power grid; a regulation object performance analysis module 1106, configured to perform performance analysis on the target regulation object to obtain a performance analysis result of the target regulation object; and a resource regulation module 1108, configured to perform resource regulation on the target regulation object according to a regulation priority matching the performance analysis result.

[0136] Each module in the above power grid resource regulation device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in a processor in a computer device in a hardware form or be independent of the processor, or can be stored in a memory in the computer device in a software form, so as to be called by the processor to execute the operations corresponding to the above respective modules.

[0137] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 12 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store power grid resource regulation data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a power grid resource regulation method is implemented.

[0138] Those skilled in the art can understand that Figure 12 the structure shown in

[0139] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented: in response to a resource regulation instruction for a target power grid, obtain the regulation requirements indicated by the resource regulation instruction; for each candidate regulation object in the target power grid, screen out the target regulation objects that meet the regulation requirements from the candidate regulation objects; perform performance analysis on the target regulation objects to obtain the performance analysis results of the target regulation objects; and perform resource regulation on the target regulation objects according to the regulation priority matching the performance analysis results.

[0140] In one embodiment, when the processor executes the computer program, the following steps are further implemented: classify each candidate regulation object to obtain at least one type of regulation object cluster; for each type of regulation object cluster, based on the association relationship between the sub-regulation objects in the regulation object cluster, construct a relationship structure diagram between the sub-regulation objects; and based on the relationship structure diagram, screen out the target regulation objects that meet the regulation requirements from the sub-regulation objects.

[0141] In one embodiment, when the processor executes the computer program, the following steps are further implemented: extract the minimum spanning tree from the relationship structure diagram; the nodes of the minimum spanning tree correspond to the sub-regulation objects one by one; for each child node in the minimum spanning tree, count the communication duration between the child node and the root node in the minimum spanning tree, and use the communication duration as the required duration for the sub-regulation object matching the child node to receive the resource regulation task; and use the sub-regulation objects whose required duration meets the regulation duration requirement as the target regulation objects.

[0142] In one embodiment, when the processor executes the computer program, the following steps are further implemented: use the sub-regulation objects whose required duration meets the regulation duration requirement as the selected regulation objects; perform duration error analysis on the selected regulation objects to obtain the duration error of the selected regulation objects receiving the resource regulation task; based on the required duration and the duration error, determine the resource regulation task receiving duration of the selected regulation objects; and when the resource regulation task receiving duration meets the regulation duration constraint condition, use the selected regulation objects as the target regulation objects.

[0143] In one embodiment, when the processor executes the computer program, the following steps are further implemented: perform margin analysis on the target regulation objects to obtain the resource regulation margin of the target regulation objects; perform stability analysis on the target regulation objects to obtain the resource regulation stability of the target regulation objects; count the resource regulation times of the target regulation objects; and use the resource regulation margin, the resource regulation stability, and the resource regulation times together as the performance analysis results of the target regulation objects.

[0144] In one embodiment, when the processor executes the computer program, the following steps are further implemented: allocate resources to the target regulation object according to the regulation priority matching the performance analysis result to obtain the adjustable resources of the target regulation object; based on the adjustable resources, perform resource regulation on the target regulation object.

[0145] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: in response to a resource regulation instruction for a target power grid, obtain the regulation requirements indicated by the resource regulation instruction; for each candidate regulation object in the target power grid, screen out the target regulation object that meets the regulation requirements from the candidate regulation objects; perform performance analysis on the target regulation object to obtain the performance analysis result of the target regulation object; perform resource regulation on the target regulation object according to the regulation priority matching the performance analysis result.

[0146] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: classify each candidate regulation object to obtain at least one type of regulation object cluster; for each type of regulation object cluster, based on the association relationship between the sub-regulation objects in the regulation object cluster, construct a relationship structure diagram between the sub-regulation objects; based on the relationship structure diagram, screen out the target regulation object that meets the regulation requirements from the sub-regulation objects.

[0147] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: extract the minimum spanning tree from the relationship structure diagram; the nodes of the minimum spanning tree correspond to the sub-regulation objects one by one; for each child node in the minimum spanning tree, count the communication duration between the child node and the root node in the minimum spanning tree, and use the communication duration as the required duration for the sub-regulation object corresponding to the child node to receive the resource regulation task; use the sub-regulation object whose required duration meets the regulation duration requirement as the target regulation object.

[0148] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: use the sub-regulation object whose required duration meets the regulation duration requirement as the selected regulation object; perform duration error analysis on the selected regulation object to obtain the duration error of the selected regulation object receiving the resource regulation task; based on the required duration and the duration error, determine the resource regulation task receiving duration of the selected regulation object; when the resource regulation task receiving duration meets the regulation duration constraint condition, use the selected regulation object as the target regulation object.

[0149] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: performing margin analysis on a target regulation object to obtain the resource regulation margin of the target regulation object; performing stability analysis on the target regulation object to obtain the resource regulation stability of the target regulation object; counting the number of resource regulations of the target regulation object; and using the resource regulation margin, the resource regulation stability, and the number of resource regulations together as the performance analysis result of the target regulation object.

[0150] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: allocating resources to the target regulation object according to the regulation priority matching the performance analysis result to obtain the adjustable resources of the target regulation object; and performing resource regulation on the target regulation object based on the adjustable resources.

[0151] In one embodiment, a computer program product is provided, including a computer program, which when executed by a processor, implements the following steps: responding to a resource regulation instruction for a target power grid, obtaining the regulation requirements indicated by the resource regulation instruction; screening out target regulation objects that meet the regulation requirements from each candidate regulation object in the target power grid; performing performance analysis on the target regulation objects to obtain the performance analysis results of the target regulation objects; and performing resource regulation on the target regulation objects according to the regulation priority matching the performance analysis results.

[0152] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: classifying each candidate regulation object to obtain at least one type of regulation object cluster; for each type of regulation object cluster, constructing a relationship structure diagram between each sub-regulation object based on the association relationship between the sub-regulation objects in the regulation object cluster; and screening out target regulation objects that meet the regulation requirements from each sub-regulation object based on the relationship structure diagram.

[0153] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: extracting a minimum spanning tree from the relationship structure diagram; the nodes of the minimum spanning tree correspond to the sub-regulation objects one by one; for each child node in the minimum spanning tree, counting the communication duration between the child node and the root node in the minimum spanning tree, and using the communication duration as the required duration for the sub-regulation object matching the child node to receive a resource regulation task; and using the sub-regulation objects whose required duration meets the regulation duration requirement as the target regulation objects.

[0154] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: taking a sub-regulation object whose required duration meets the regulation duration requirement as a selected regulation object; performing duration error analysis on the selected regulation object to obtain the duration error of the selected regulation object receiving a resource regulation task; determining the resource regulation task receiving duration of the selected regulation object based on the required duration and the duration error; and taking the selected regulation object as a target regulation object when the resource regulation task receiving duration meets the regulation duration constraint condition.

[0155] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: performing margin analysis on the target regulation object to obtain the resource regulation margin of the target regulation object; performing stability analysis on the target regulation object to obtain the resource regulation stability of the target regulation object; counting the resource regulation times of the target regulation object; and taking the resource regulation margin, the resource regulation stability, and the resource regulation times together as the performance analysis result of the target regulation object.

[0156] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: allocating resources to the target regulation object according to a regulation priority matching the performance analysis result to obtain the adjustable resources of the target regulation object; and performing resource regulation on the target regulation object based on the adjustable resources.

[0157] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0158] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., and are not limited thereto.

[0159] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this application.

[0160] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A power grid resource regulation method, characterized in that, The method includes: In response to a resource regulation instruction for a target power grid, obtaining the regulation requirements indicated by the resource regulation instruction; For each candidate regulation object in the target power grid, screening out target regulation objects that meet the regulation requirements from the candidate regulation objects; Performing performance analysis on the target regulation objects to obtain performance analysis results of the target regulation objects; Performing resource regulation on the target regulation objects according to the regulation priority matching the performance analysis results.

2. The method according to claim 1, wherein The screening out target regulation objects that meet the regulation requirements from the candidate regulation objects includes: Classifying each candidate regulation object to obtain at least one type of regulation object cluster; For each type of regulation object cluster, based on the association relationship between the sub-regulation objects in the regulation object cluster, constructing a relationship structure diagram between the sub-regulation objects; Based on the relationship structure diagram, screening out target regulation objects that meet the regulation requirements from the sub-regulation objects.

3. The method according to claim 2, wherein The regulation requirements include a regulation duration requirement; the screening out target regulation objects that meet the regulation requirements from the sub-regulation objects based on the relationship structure diagram includes: Extracting a minimum spanning tree from the relationship structure diagram; the nodes of the minimum spanning tree correspond one-to-one with the sub-regulation objects; For each child node in the minimum spanning tree, counting the communication duration between the child node and the root node in the minimum spanning tree, and taking the communication duration as the required duration for the sub-regulation object matching the child node to receive a resource regulation task; Taking the sub-regulation objects whose required duration meets the regulation duration requirement as target regulation objects.

4. The method according to claim 3, wherein The taking the sub-regulation objects whose required duration meets the regulation duration requirement as target regulation objects includes: Taking the sub-regulation objects whose required duration meets the regulation duration requirement as selected regulation objects; Performing duration error analysis on the selected regulation objects to obtain the duration error of the selected regulation objects receiving the resource regulation task; Based on the required duration and the duration error, determining the resource regulation task receiving duration of the selected regulation objects; When the resource regulation task receiving duration meets the regulation duration constraint condition, taking the selected regulation objects as target regulation objects.

5. The method according to claim 1, wherein The performing performance analysis on the target regulation objects to obtain performance analysis results of the target regulation objects includes: Performing margin analysis on the target regulation objects to obtain the resource regulation margin of the target regulation objects; Performing stability analysis on the target regulation objects to obtain the resource regulation stability of the target regulation objects; Counting the number of resource regulations of the target regulation objects; Taking the resource regulation margin, the resource regulation stability, and the number of resource regulations together as the performance analysis results of the target regulation objects.

6. The method according to claim 1, wherein The performing resource regulation on the target regulation objects according to the regulation priority matching the performance analysis results includes: Allocate resources to the target regulation object according to the regulation priority matching the performance analysis result, and obtain the adjustable resources of the target regulation object; Based on the adjustable resources, perform resource regulation on the target regulation object.

7. A power grid resource regulation device, characterized in that, The device includes: A demand acquisition module, configured to acquire the regulation demand indicated by the resource regulation instruction in response to a resource regulation instruction for a target power grid; A regulation object screening module, configured to screen out a target regulation object that meets the regulation demand from each candidate regulation object among the candidate regulation objects in the target power grid; A regulation object performance analysis module, configured to perform performance analysis on the target regulation object to obtain a performance analysis result of the target regulation object; A resource regulation module, configured to perform resource regulation on the target regulation object according to the regulation priority matching the performance analysis result.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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