Power grid operation order intelligent anti-error generation method and system based on source compatibility principle

Abstract

The invention discloses a power grid operation order intelligent anti-error generation method and system based on a source compatibility principle, and relates to the technical field of electric power automation, and the method comprises the following steps: extracting first data from a scheduling instruction, the first data comprising an operation object and an equipment initial state; constructing a dynamic power grid model based on the first data, and performing source attribute labeling on each device in the model; performing analysis through a source compatibility rule engine in combination with the marked dynamic power grid model and a predefined source compatibility constraint criterion, and generating an operation framework containing a source matching requirement; searching and planning an operation sequence meeting a source matching requirement based on the operation framework, and converting the operation sequence into a specific operation item; and performing source compatibility verification on the specific operation item, optimizing the operation item according to a verification result, and generating a final operation ticket. The method is used for solving the problems that a traditional anti-misoperation system is insufficient in real-time matching of a power supply and a load, incomplete in operation sequence verification and lack of intelligent support in operation order generation.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and more particularly to a method and system for intelligently preventing error generation of power grid operation tickets based on the principle of source compatibility. Background Art

[0002] In power grid operation and dispatching, operation tickets are a key means to ensure operational safety and prevent misoperation. With the expansion of the power system and the large-scale access of new energy power sources, the topology and operating status of the power grid have become increasingly complex, and the difficulty of compiling and verifying operation tickets has increased significantly. Traditional operation tickets mainly rely on manual experience to generate and review. Although they can meet basic operational needs to a certain extent, the existing methods have obvious shortcomings in the face of complex power grid environments and multi-source access conditions: Insufficient support for dynamic power grid models. Current methods are usually based on static topology, which fails to effectively combine the operating status and source attributes of power grid equipment, cannot accurately reflect the real-time matching relationship between power supply and load during operation, and cannot meet the requirements of modern power grids for dynamic adaptability; the generation and verification of operation sequences are incomplete. Traditional operation ticket generation methods can often only provide sequential operation steps, but lack heuristic search and constraint-driven optimization processes, especially in terms of parallel operations, operation dependencies and path validity verification. As a result, the operation sequence may still have the risk of misoperation. The transformation from operation sequence to specific operation items lacks intelligent support. When generating operation tickets, existing technologies often stay at the operation step level, lacking further source compatibility verification and parallel correction mechanisms, resulting in the final operation ticket still requiring manual intervention and secondary review, reducing efficiency and reliability.

[0003] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for intelligent error-proof generation of power grid operation tickets based on the principle of source compatibility. The present invention solves the problems of insufficient real-time matching of power supply and load, incomplete operation sequence verification and lack of intelligent support for operation ticket generation in traditional error-proof systems through dynamic modeling, framework generation driven by a source compatibility rule engine, heuristic search and parallel constraint verification.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for intelligently preventing errors in generating power grid operation tickets based on the principle of source compatibility comprises the following steps: extracting first data from a dispatch instruction, the first data including an operation object and an initial state of a device; constructing a dynamic power grid model based on the first data, and labeling the source attributes of each device in the model; combining the labeled dynamic power grid model with predefined source compatibility constraint criteria, analyzing the results through a source compatibility rule engine, and generating an operation framework containing source matching requirements; searching and planning an operation sequence that meets the source matching requirements based on the operation framework, and converting the operation sequence into specific operation items; performing source compatibility verification on the specific operation items, optimizing the operation items based on the verification results, and generating a final operation ticket.

[0006] In a preferred embodiment, the source attribute labeling of each device in the model includes: constructing a source attribute labeling knowledge base and continuously updating it; traversing the dynamic power grid model, identifying and generating a target device set that needs to perform source attribute labeling based on model state changes; extracting the real-time topological connection relationship, device type information and operating status information of the target device set, and constructing a multidimensional feature vector for characterizing the source characteristics of the device; matching and calculating the multidimensional feature vector with the updated source attribute labeling knowledge base to generate the source attribute labeling results for each target device, and writing the labeling results into the corresponding target device node in the dynamic power grid model.

[0007] In a preferred embodiment, the construction of the source attribute annotation knowledge base and its continuous updating specifically includes: constructing an initial source attribute annotation knowledge base based on historical equipment operation data, and revising and expanding the initial rules in combination with expert experience to form a first source attribute annotation knowledge base; based on the real-time collected equipment operation status data, dynamically optimizing and updating the rule set in the first source attribute annotation knowledge base through an online learning mechanism to form a second source attribute annotation knowledge base with stronger adaptability.

[0008] In a preferred embodiment, the combined annotated dynamic power grid model and predefined source compatibility constraint criteria are analyzed through a source compatibility rule engine to generate an operation framework including source matching requirements, specifically: integrating the device connection relationship, device source attributes and predefined source compatibility constraint criteria in the dynamic power grid model to form a unified data set; preprocessing and feature extraction are performed on the data set to obtain a parameter set; the parameter set is input into an energy balance calculator, constraint conditions are established, and a preliminary operation boundary between the power source and the load is calculated; the device connection relationship is input into a topology analysis unit for connectivity analysis, and paths that do not meet the energy matching conditions are eliminated to obtain topological connectivity logic; the preliminary operation boundary and the topological connectivity logic are integrated to generate an operation framework including source matching requirements.

[0009] In a preferred embodiment, the source compatibility rule engine includes: a topology analysis unit, which analyzes the device connection relationship in the dynamic power grid model and outputs connectivity information; an energy balance calculator, which is used to calculate the preliminary operating boundaries of the power source and the load based on the parameter set, while taking into account the energy balance constraints, voltage stability constraints and frequency constraints.

[0010] In a preferred embodiment, the source matching requirement refers to the source-load matching condition defined in the operation framework, which is formed by merging the preliminary operation boundary generated by the energy balance calculator and the topology connectivity logic generated by the topology analysis unit.

[0011] In a preferred embodiment, the operation sequence is processed by a parallel constraint processing method to generate specific operation items, specifically: the operation sequence is split into several subsequences according to the execution dependency and parallel feasibility of the operation steps in the operation sequence; an independent constraint verification logic is configured for each subsequence, and the core content of the constraint verification logic is the electrical constraint condition; each constraint verification logic performs constraint verification on its own subsequence operation steps in parallel, and outputs the subsequence that passes the verification; for the subsequence that fails the verification, parallel correction is performed according to preset rules and then a corrected sequence is output; the subsequences that pass the verification and the corrected sequence are integrated according to the execution dependency of the original operation sequence to generate specific operation items including the operation object and the operation type.

[0012] In a preferred embodiment, the heuristic search algorithm is used in the state space to generate an operation sequence that meets the electrical constraint conditions. Specifically, in the state space, the electrical constraint conditions are embedded in the evaluation function and pruning mechanism of the heuristic search algorithm to construct a fully configured heuristic search algorithm; based on the fully configured heuristic search algorithm, starting from the state node corresponding to the initial state, the state transition corresponding to the device operation is explored step by step to generate several candidate paths; the electrical constraint condition is checked on the candidate paths, and the paths that do not meet the conditions are eliminated through pruning, and finally an operation sequence that meets the electrical constraint conditions is obtained. In a preferred embodiment, the operation sequence is processed by the parallel constraint processing method to generate specific operation items, specifically: according to the execution dependency and parallel feasibility of the operation steps in the operation sequence, the operation sequence is split into several subsequences; an independent constraint verification logic is configured for each subsequence, and the core content of the constraint verification logic is the electrical constraint condition; each constraint verification logic performs constraint verification on the operation steps of its own subsequence in parallel, and outputs the subsequence that passes the verification; for the subsequence that fails the verification, parallel correction is performed according to preset rules and then a correction sequence is output; according to the execution dependency of the original operation sequence, the subsequences that pass the verification and the correction sequence are integrated to generate specific operation items including the operation object and the operation type. On the second aspect, the present application provides an intelligent and error-proof generation system for power grid operation tickets based on the source compatibility principle, including: a data extraction module for extracting first data from a dispatch instruction, the first data including an operation object and an initial state of the equipment; a dynamic power grid modeling and source attribute labeling module for constructing a dynamic power grid model based on the first data, and labeling the source attributes of each device in the model; an operation framework generation module for combining the labeled dynamic power grid model and predefined source compatibility constraint criteria, analyzing through a source compatibility rule engine, and generating an operation framework containing source matching requirements; an operation sequence planning module for searching and planning an operation sequence that meets the source matching requirements based on the operation framework, and converting the operation sequence into specific operation items; an operation item optimization and source compatibility verification module for performing source compatibility verification on specific operation items, optimizing the operation items according to the verification results, and generating a final operation ticket.

[0013] It can be seen from the above technical solutions that the present invention solves the problem that traditional methods rely only on static topology and cannot reflect the real-time matching relationship between power supply and load by introducing dynamic power grid models and source attribute labeling; through the source compatibility rule engine combined with heuristic search, it solves the problem of lack of constraint-driven optimization and complete verification in the operation sequence generation process; through parallel constraint processing and source compatibility verification, it solves the problem that operation ticket generation relies on manual intervention and lacks intelligent support. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The figure is a flow chart of the method for intelligently preventing errors in generating power grid operation tickets based on the source compatibility principle of the present invention.

[0015] Figure 2 The diagram is a structural diagram of the intelligent error-proof generation system for power grid operation tickets based on the source compatibility principle of the present invention.

[0016] Figure 3 Label the flow chart for source attributes. DETAILED DESCRIPTION

[0017] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] Example 1, Figure 1 The present invention provides a method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle, comprising the following steps: S1, extracting first data from the scheduling instruction, where the first data includes an operation object and an initial state of the device; S2, constructing a dynamic power grid model based on the first data, and labeling source attributes of each device in the model; S3, combining the annotated dynamic power grid model and the predefined source compatibility constraint criteria, performs analysis through the source compatibility rule engine and generates an operation framework including source matching requirements; S4, based on the operation framework, searches and plans an operation sequence that meets the source matching requirements, and converts the operation sequence into specific operation items; S5: Perform source compatibility verification on specific operation items, optimize the operation items based on the verification results, and generate the final operation ticket.

[0019] It can be seen from the above technical solutions that the present invention solves the problem that traditional methods rely only on static topology and cannot reflect the real-time matching relationship between power supply and load by introducing dynamic power grid models and source attribute labeling; through the source compatibility rule engine combined with heuristic search, it solves the problem of lack of constraint-driven optimization and complete verification in the operation sequence generation process; through parallel constraint processing and source compatibility verification, it solves the problem that operation ticket generation relies on manual intervention and lacks intelligent support.

[0020] S1, extracting first data from a scheduling instruction, where the first data includes an operation object and an initial state of a device. In this embodiment, the dispatch instruction is a structured message issued by the power grid dispatch system, which includes identification information of the operation object and operating parameters of the equipment; The structured message is parsed to extract the operation object and the initial state of the device to form the first data. The above data extraction process can be implemented using existing data parsing technology and does not belong to the key content of this application.

[0021] S2: construct a dynamic power grid model based on the first data, and label each device in the model with a source attribute.

[0022] The constructing of the dynamic power grid model based on the first data is specifically as follows: Identify upstream and downstream devices that are electrically connected to the operation object and obtain the corresponding physical connection information from the power grid topology database; A graph structure model is constructed with devices as nodes and physical connection information as edges, and the initial state of each device is attached to the node as the node attribute information.

[0023] In this embodiment, the source attribute labeling of each device in the model includes: Build a source attribute annotation knowledge base and continuously update it; Traverse the dynamic power grid model, identify and generate the target device set that needs to perform source attribute labeling based on the model state changes; Extract the real-time topological connection relationship, device type information and operating status information of the target device set, and construct a multi-dimensional feature vector to characterize the source characteristics of the device; The multi-dimensional feature vector is matched with the updated source attribute annotation knowledge base to generate the source attribute annotation results of each target device, and the annotation results are written into the corresponding target device node in the dynamic power grid model.

[0024] Specifically: The specific process of labeling the source attributes of each device in the model is as follows: Figure 3 As shown; In this embodiment, the construction of the source attribute annotation knowledge base and its continuous updating specifically includes: An initial source attribute annotation knowledge base is constructed based on historical equipment operation data, and the initial rules are modified and expanded based on expert experience to form the first source attribute annotation knowledge base; Based on the real-time collected equipment operation status data, the rule set in the first source attribute annotation knowledge base is dynamically optimized and updated through an online learning mechanism to form a second source attribute annotation knowledge base with stronger adaptability.

[0025] First, historical equipment operation data, including power output, load changes, switch status, and fault records, is collected from each device in the power grid. The collected data is then preprocessed, including data cleaning, outlier removal, normalization, and statistical analysis, to provide basic data for rule generation. Perform statistical analysis on the voltage, current, power factor, and load response characteristic parameters recorded in historical equipment operation data to identify their stable intervals, abnormal intervals, and change trends. Combined with expert experience or preset threshold conditions, frequently occurring feature patterns are extracted to form a first source attribute annotation knowledge base. Furthermore, real-time device status data is continuously acquired during grid operation. Through an online learning mechanism, the thresholds, weights, and rules in the source attribute annotation knowledge base are dynamically adjusted, enabling the first source attribute annotation knowledge base to be adaptively updated as the grid operation status evolves, thus forming a second source attribute annotation knowledge base. Then, all devices in the dynamic power grid model are traversed to select the target devices that require source attribute labeling, forming a target device set. For each device in the target device set, its topological connection relationship, device type, and real-time operating status are extracted. This information is integrated and encoded into a multidimensional feature vector, which serves as the input for the rule matching calculation. Finally, the constructed multi-dimensional feature vector is matched with the second source attribute annotation knowledge base: The target device's multidimensional feature vector is parsed and compared against the rule conditions in the second source attribute annotation knowledge base. If the feature vector meets the threshold conditions in a rule item, the device is determined to have the corresponding source attribute. If there are multiple candidate rule items, a similarity calculation (such as Euclidean distance or cosine similarity) can be used for further identification. The rule item with the highest similarity is selected as the final annotation result, and this result is written to the corresponding target device.

[0026] Figure 3 The overall processing path and logical relationship of the above process are intuitively displayed.

[0027] S3 combines the annotated dynamic grid model with predefined source compatibility constraints and performs analysis through the source compatibility rule engine to generate an operational framework that includes source matching requirements, including: Integrate the device connection relationships, device source attributes and predefined source compatibility constraints in the dynamic power grid model to form a unified data set; Preprocessing and feature extraction are performed on the data set to obtain a parameter set; Input the parameter set into the energy balance calculator, establish the constraints, and calculate the preliminary operating boundaries between the power source and the load; The device connection relationship is input into the topology analysis unit for connectivity analysis, and the paths that do not meet the energy matching conditions are eliminated to obtain the topology connectivity logic; The preliminary operational boundaries are integrated with the topological connectivity logic to generate an operational framework that includes source matching requirements.

[0028] Specifically: First, the device connectivity and source attributes in the dynamic power grid model are integrated with predefined source compatibility constraints to construct a unified dataset. This dataset reflects the topological structure between devices, records the power source attributes of each device, and includes compatibility constraints between the power source and the load, providing a complete input for subsequent calculations. Next, the dataset is normalized and feature extracted to form a parameter set. Normalization eliminates the effects of different dimensions, while feature extraction preserves key parameters that influence energy distribution and system stability, such as voltage amplitude, power factor, and rated capacity. The parameter set is then input into the energy balance calculator built into the source compatibility rule engine. Under the constraints of the source compatibility rules, the energy balance calculator calculates the parameter set formed by integrating the dynamic power grid model and the constraints to obtain a preliminary operating boundary between the power source and the load. This boundary describes the feasible range of power source output and load demand under the constraints. On this basis, combined with the topology analysis unit, the device connection relationship is analyzed for connectivity, eliminating links that do not meet the energy matching conditions. For example, a link whose power output is insufficient to support the load demand of the path, or a link whose voltage drops beyond the allowable range, will be determined as an unavailable path, thus forming the topological connectivity logic.

[0029] Finally, the preliminary operational boundaries are integrated with the topological connectivity logic to generate an operational framework that includes source matching requirements. This operational framework provides a basis for power scheduling and load distribution, ensuring that the scheduling strategy meets the constraints in terms of energy supply and demand balance, topological accessibility, and power stability.

[0030] In this embodiment, the source compatibility rule engine includes: Topology analysis unit, which analyzes the device connection relationship in the dynamic power grid model and outputs connectivity information; Energy balance calculator, used to calculate preliminary operating boundaries of sources and loads based on parameter sets while considering energy balance constraints, voltage stability constraints, and frequency constraints.

[0031] The topology analysis unit is used to analyze the device connection relationship in the dynamic power grid model and output connectivity information. Input the connection relationship matrix and device number information of each device in the dynamic power grid model.

[0032] Analyze the reachability and path connectivity of each node in the network through graph theory methods (such as connected component extraction or shortest path calculation).

[0033] Output connectivity information, including the reachable links from each power source to the load and their corresponding connection status identifiers, for subsequent power source and load matching calculations.

[0034] The energy balance calculator is used to calculate the preliminary operating boundary between the power source and the load based on the parameter set under the constraints of the source compatibility constraint criteria: Energy balance constraints:

[0035] in, For the Power supply power, For the Load power, is network loss; Voltage stability constraints:

[0036] in, For the Node voltage, and are the minimum and maximum voltage values ​​allowed respectively; Frequency Constraints:

[0037] in is the system frequency, is the rated frequency, is the maximum allowable deviation; In this embodiment, the source matching requirement refers to the source-load matching condition defined in the operation framework, which is formed by merging the preliminary operation boundary generated by the energy balance calculator and the topology connectivity logic generated by the topology analysis unit.

[0038] It should be noted that the predefined source compatibility constraint criteria refer to a set of operating conditions that must be followed when matching and scheduling power sources and loads to ensure safe and stable operation of the power grid, specifically including: Energy balance constraint: The total power output should be balanced with the total load demand and network losses; Voltage stability constraint: The voltage of each node should be within the allowable deviation range; Frequency constraint: The system operating frequency should be maintained within the allowable deviation range of the rated value.

[0039] It should be noted that the device source attributes refer to a set of basic parameters used to characterize the supply and demand characteristics of power supply equipment or load equipment in power grid operation. Device source attributes include: For power supply equipment: rated capacity, upper and lower output limits, node voltage level, and regulation capability; For load equipment: rated demand power, demand fluctuation range, and interruptibility.

[0040] S4, based on the operation framework, searches and plans an operation sequence that meets the source matching requirements, and converts the operation sequence into specific operation items, specifically: Translate source matching requirements in the operational framework into electrical constraints; Based on electrical constraints, the device connection relationships in the dynamic power grid model are screened and a state space containing the device connection relationships is constructed. A heuristic search algorithm is used in the state space to generate an operation sequence that satisfies the electrical constraint condition, wherein the operation sequence includes continuous operation steps from an initial state to a target state; The operation sequence is processed by a parallel constraint processing method to generate specific operation items.

[0041] The source matching requirements in the operation framework are converted into electrical constraints, specifically: First, extract two types of key constraint information in the source matching requirements: One type is source property constraint parameters, which correspond to the preliminary operating boundaries generated by the energy balance calculator, including quantitative constraints such as power, voltage, and frequency; The other category is topology connectivity constraint parameters, which correspond to the topology logic rules generated by the topology analysis unit, including path validity, operation dependency, and device type matching.

[0042] Perform standardized conversion processing based on different constraint information: Quantitative requirements such as power, voltage, and frequency are converted into numerical interval constraints; For logical requirements such as path validity and device dependency, convert them into logical conditional expressions; The device type matching relationship is converted into a type constraint.

[0043] In this way, the abstract matching requirements become a set of constraint rules that can be directly processed by computers, namely electrical constraints.

[0044] Based on the electrical constraints, the device connection relationships in the dynamic power grid model are screened to construct a state space containing the device connection relationships: First, all devices and their connection relationships are extracted from the dynamic power grid model to form the original network; Then, electrical constraints are applied to the original network, eliminating lines that do not meet the power, voltage, frequency, and other numerical range requirements, removing connections that do not provide effective power supply paths, and introducing logical constraints such as operation dependencies and device type matching in the state space to prevent illegal connections. On this basis, the device operating state that meets the constraints is defined as a state node, and the device operation that can be legally executed under the constraints is defined as a state transition, thereby constructing a state space that only contains valid connection relationships and feasible state evolution paths.

[0045] In this embodiment, a heuristic search algorithm is used in the state space to generate an operation sequence that satisfies the electrical constraints, specifically: In the state space, electrical constraints are embedded into the evaluation function and pruning mechanism of the heuristic search algorithm to construct a fully configured heuristic search algorithm. Based on a fully configured heuristic search algorithm, starting from the state node corresponding to the initial state, the state transition corresponding to the device operation is explored step by step to generate several candidate paths; Electrical constraint checks are performed on candidate paths, and paths that do not meet the conditions are eliminated through pruning, ultimately obtaining an operation sequence that meets the electrical constraint conditions.

[0046] In the state space, the electrical constraints are embedded into the evaluation function and pruning mechanism of the heuristic search algorithm to construct a fully configured heuristic search algorithm, specifically: Extract source attribute constraint parameters from electrical constraints and topology connectivity constraint parameters ; Construct an evaluation function containing constraint weights based on source attribute constraint parameters and topological connectivity constraint parameters; the evaluation function is:

[0047] Where, is the operating cost (basic cost); and is the constraint weight ( , giving priority to ensuring source matching and topology compliance), dynamically adjusting the priority of source matching requirements based on the operation framework; is a constant term used to implement global policy preferences, such as giving priority to paths with fewer operation steps. This coefficient can be configured according to the overall scheduling strategy; Furthermore, we design hierarchical pruning logic for two types of constraints: Source attribute hard constraint pruning: When an operation in a path violates source type incompatibility or power limit, the path search is terminated immediately; Topology connectivity soft constraint pruning: When a path violates non-core topology rules, such as when the path redundancy slightly exceeds a threshold, it is marked as a low-priority path and retained only when no better solution exists. Paths that meet topology constraints are prioritized for expansion. Based on the evaluation function and pruning mechanism after the above-mentioned embedded heuristic search algorithm, a fully configured heuristic search algorithm is generated.

[0048] The heuristic search algorithm based on complete configuration starts from the state node corresponding to the initial state, explores the state transition corresponding to the device operation step by step, and generates several candidate paths, specifically: Based on a fully configured heuristic search algorithm, it gradually explores from the initial state. In the state space, the operating state of each device can be abstracted as a state node, and each operation action (such as opening, closing, switching) can be abstracted as a state transition. The heuristic search algorithm starts from the initial state node and expands the state transition path step by step according to the constraints and evaluation function, thereby generating several candidate paths.

[0049] The electrical constraint condition check is performed on the candidate paths, and the paths that do not meet the condition are eliminated through pruning, and finally an operation sequence that meets the electrical constraint condition is obtained, specifically: Each operating parameter and topological relationship involved in the candidate path is checked item by item. For example, the power, voltage, and frequency of each node in the path are checked to see if they are within the permitted range and whether the power supply and load matching requirements are met. At the same time, the topological connectivity is verified to ensure that the power supply path is valid and does not violate the operational dependencies or type matching rules between devices. Candidate paths that do not meet electrical constraints are eliminated through a pruning mechanism; Through the constraint checking and pruning mechanism, the final set of candidate paths obtained is the operation sequence that meets the electrical constraint conditions. The operation sequence contains continuous operation steps from the initial state to the target state.

[0050] In this embodiment, the operation sequence is processed by the parallel constraint processing method to generate specific operation items, specifically: Split the operation sequence into several subsequences based on the execution dependencies and parallel feasibility of the operation steps in the operation sequence; Configuring independent constraint verification logic for each subsequence, wherein the core content of the constraint verification logic is electrical constraint conditions; Each constraint verification logic performs constraint verification on its own subsequence operation steps in parallel and outputs the subsequences that pass the verification; For subsequences that fail the verification, parallel correction is performed according to the preset rules and the corrected sequence is output; According to the execution dependency of the original operation sequence, the verified subsequences and the modified sequence are integrated to generate specific operation items including the operation object and operation type.

[0051] Specifically: First, based on the execution dependencies between the steps in the sequence and the parallel feasibility of devices, the sequence is split into several independent or partially independent subsequences. For example, if two operations act on different electrical islands and have no dependencies, they can be divided into parallel subsequences. If an operation must depend on the previous device state, it remains in the same subsequence. Subsequently, independent constraint verification logic is configured for each subsequence. The core content of this verification logic is electrical constraints, including numerical constraints such as power, voltage, and frequency, as well as logical constraints such as topological connectivity and device type matching. Each constraint verification logic can run synchronously, verifying the corresponding subsequence operation steps one by one and outputting the subsequences that pass the verification; Subsequences that fail verification can be processed according to pre-set parallel correction rules. Correction rules may include: reordering the operation sequence to make it consistent with dependencies; replacing certain incompatible operation objects or devices; or inserting additional compensating operations (such as inserting a voltage recovery operation before closing the circuit breaker) when necessary to ensure that the subsequence meets the constraints. The corrected subsequence is then rejoined to the overall sequence. Finally, according to the execution dependency in the original operation sequence, the verified subsequence and the corrected subsequence are integrated to obtain the operation item containing the specific operation object and operation type.

[0052] S5: Perform source compatibility verification on specific operation items, optimize the operation items based on the verification results, and generate the final operation ticket.

[0053] In this embodiment, the source compatibility check of specific operation items refers to the review and correction of the execution level of the operation sequence generated based on the operation framework after it is converted into specific operation items, so as to ensure that the final generated operation ticket is executable and safe in the actual power grid operation environment. Specifically, it includes: First, a source compatibility check is performed on each operation item. This check not only verifies whether the operation item meets energy balance constraints such as power, voltage, and frequency under steady-state conditions, but also further checks the safety of the operation steps during the transition process, such as transient voltage drops caused by parallel operations and transient frequency fluctuations caused by switching between operation objects. Secondly, operations involving multiple devices executing in parallel must be rechecked based on their dependencies and topological constraints to determine whether they will cause islanding, loops, or illegal connections. For risky operations, adjustments are made based on pre-set correction rules, such as modifying the operation sequence, inserting compensation steps, or replacing the operation objects, to ensure that each step consistently meets source compatibility requirements during the dynamic process. Finally, the verified or corrected operation items are integrated into the final operation ticket to clarify the operation object, operation method and execution sequence, ensuring that the actual dispatching process meets the power grid operation safety and error prevention requirements.

[0054] Example 2, Figure 2 The present invention provides an intelligent error-proof generation system for power grid operation tickets based on the source compatibility principle, comprising: A data extraction module is used to extract first data from the scheduling instruction, where the first data includes an operation object and an initial state of the device; A dynamic power grid modeling and source attribute labeling module, configured to construct a dynamic power grid model based on the first data and label the source attributes of each device in the model; The operation framework generation module is used to combine the annotated dynamic power grid model and the predefined source compatibility constraint criteria, analyze them through the source compatibility rule engine, and generate an operation framework that includes source matching requirements; The operation sequence planning module is used to search and plan operation sequences that meet source matching requirements based on the operation framework, and convert the operation sequences into specific operation items; The operation item optimization and source compatibility verification module is used to perform source compatibility verification on specific operation items, optimize the operation items based on the verification results, and generate the final operation ticket.

[0055] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0056] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design electrical constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0057] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0058] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0059] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for intelligently preventing errors in generating power grid operation tickets based on the principle of source compatibility, characterized in that: The following steps are involved: extracting first data from the scheduling instruction, the first data including an operation object and an initial state of the device; Building a dynamic power grid model based on the first data, and labeling source attributes of each device in the model; Combining the annotated dynamic power grid model with predefined source compatibility constraints, the source compatibility rule engine performs analysis to generate an operational framework that includes source matching requirements. Search and plan operation sequences that meet source matching requirements based on the operation framework, and convert the operation sequences into specific operation items; Perform source compatibility check on specific operation items, optimize the operation items based on the check results, and generate the final operation ticket.

2. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 1 is characterized in that: The source attribute labeling of each device in the model includes: Build a source attribute annotation knowledge base and continuously update it; Traverse the dynamic power grid model, identify and generate the target device set that needs to perform source attribute labeling based on the model state changes; Extract the real-time topological connection relationship, device type information and operating status information of the target device set, and construct a multi-dimensional feature vector to characterize the source characteristics of the device; The multi-dimensional feature vector is matched with the updated source attribute annotation knowledge base to generate the source attribute annotation results of each target device, and the annotation results are written into the corresponding target device node in the dynamic power grid model.

3. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 2 is characterized in that: The construction of the source attribute annotation knowledge base and its continuous updating specifically include: An initial source attribute annotation knowledge base is constructed based on historical equipment operation data, and the initial rules are modified and expanded based on expert experience to form the first source attribute annotation knowledge base; Based on the real-time collected equipment operation status data, the rule set in the first source attribute annotation knowledge base is dynamically optimized and updated through an online learning mechanism to form a second source attribute annotation knowledge base with stronger adaptability.

4. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 3 is characterized in that: The combined annotated dynamic power grid model and predefined source compatibility constraint criteria are analyzed through the source compatibility rule engine to generate an operation framework containing source matching requirements, specifically: Integrate the device connection relationships, device source attributes and predefined source compatibility constraints in the dynamic power grid model to form a unified data set; Preprocessing and feature extraction are performed on the data set to obtain a parameter set; Input the parameter set into the energy balance calculator, establish the constraints, and calculate the preliminary operating boundaries between the power source and the load; The device connection relationship is input into the topology analysis unit for connectivity analysis, and the paths that do not meet the energy matching conditions are eliminated to obtain the topology connectivity logic; The preliminary operational boundaries are integrated with the topological connectivity logic to generate an operational framework that includes source matching requirements.

5. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 4 is characterized in that: The source compatibility rule engine includes: Topology analysis unit, which analyzes the device connection relationship in the dynamic power grid model and outputs connectivity information; Energy balance calculator, used to calculate preliminary operating boundaries of sources and loads based on parameter sets while considering energy balance constraints, voltage stability constraints, and frequency constraints.

6. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 5 is characterized in that: The source matching requirement refers to the source-load matching condition defined in the operation framework, which is formed by merging the preliminary operation boundary generated by the energy balance calculator and the topology connectivity logic generated by the topology analysis unit.

7. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 6 is characterized in that: The operation framework-based search and planning process includes an operation sequence that meets the source matching requirements, and converts the operation sequence into specific operation items, specifically: Translate source matching requirements in the operational framework into electrical constraints; Based on electrical constraints, the device connection relationships in the dynamic power grid model are screened and a state space containing the device connection relationships is constructed. A heuristic search algorithm is used in the state space to generate an operation sequence that satisfies the electrical constraint condition, wherein the operation sequence includes continuous operation steps from an initial state to a target state; The operation sequence is processed by a parallel constraint processing method to generate specific operation items.

8. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 7 is characterized in that: The heuristic search algorithm is used in the state space to generate an operation sequence that meets the electrical constraints, specifically: In the state space, electrical constraints are embedded into the evaluation function and pruning mechanism of the heuristic search algorithm to construct a fully configured heuristic search algorithm. Based on a fully configured heuristic search algorithm, starting from the state node corresponding to the initial state, the state transition corresponding to the device operation is explored step by step to generate several candidate paths; Electrical constraint checks are performed on candidate paths, and paths that do not meet the conditions are eliminated through pruning, ultimately obtaining an operation sequence that meets the electrical constraint conditions.

9. The method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to claim 8 is characterized in that: The operation sequence is processed by the parallel constraint processing method to generate specific operation items, specifically: Split the operation sequence into several subsequences based on the execution dependencies and parallel feasibility of the operation steps in the operation sequence; Configuring independent constraint verification logic for each subsequence, wherein the core content of the constraint verification logic is electrical constraint conditions; Each constraint verification logic performs constraint verification on its own subsequence operation steps in parallel and outputs the subsequences that pass the verification; For subsequences that fail the verification, parallel correction is performed according to the preset rules and the corrected sequence is output; According to the execution dependency of the original operation sequence, the verified subsequences and the modified sequence are integrated to generate specific operation items including the operation object and operation type.

10. A system using the method for intelligently preventing error generation of power grid operation tickets based on the source compatibility principle according to any one of claims 1 to 9, comprising: A data extraction module is used to extract first data from the scheduling instruction, where the first data includes an operation object and an initial state of the device; A dynamic power grid modeling and source attribute labeling module, configured to construct a dynamic power grid model based on the first data and label the source attributes of each device in the model; The operation framework generation module is used to combine the annotated dynamic power grid model and the predefined source compatibility constraint criteria, analyze them through the source compatibility rule engine, and generate an operation framework that includes source matching requirements; The operation sequence planning module is used to search and plan operation sequences that meet source matching requirements based on the operation framework, and convert the operation sequences into specific operation items; The operation item optimization and source compatibility verification module is used to perform source compatibility verification on specific operation items, optimize the operation items based on the verification results, and generate the final operation ticket.

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