Multi-scene linkage power grid simulation scheduling system and method

Abstract

The invention discloses a multi-scene linkage power grid simulation scheduling system and method, and relates to the technical field of power system simulation, and the system comprises a data unit which is used for obtaining power grid data of different regions and analyzing the power grid data to obtain heterogeneous data, and the heterogeneous data comprises a differential topological structure, standard equipment parameters and rule constraints; the processing unit is used for obtaining a region parameter set based on the heterogeneous data; the modeling unit is used for constructing a cross-regional interconnection topology model based on the regional parameter set; the event unit is used for acquiring a monitoring event based on the power grid data; and the scheduling unit is used for constructing a scene structural body, and obtaining a simulation result based on the cross-regional interconnection topology model, the monitoring event and the scene structural body, and solving the problems that a conventional power system simulation system cannot dynamically adapt to a multi-regional heterogeneous structure by adopting a unified standardized template or a fixed topology template, and the scheduling misjudgment rate is increased due to multi-scene independent analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of power system simulation, and in particular to a multi-scenario linked power grid simulation dispatching system and method. Background Art

[0002] Traditional power system simulation systems use unified standardized templates or fixed topology templates. However, with the expansion of regional power grid interconnection, the problem of grid topology heterogeneity has become increasingly prominent: due to differences in historical development, resource distribution, and load characteristics, different regions have formed mixed topologies such as ring networks and mesh networks (such as the 500kV double-ring network in East China and the radial collection network of wind farms in Northwest China). There are significant non-standard differences in equipment parameters (transformer impedance or line capacitance) and operating rules (N-1 criterion / voltage deviation limit). (Non-standard differences in equipment parameters, topologies, or operating rules in power grids in different regions due to historical development, technical standards, or management requirements) Traditional power system simulation systems are difficult to accommodate such heterogeneity and cannot dynamically adapt to multi-regional heterogeneous structures.

[0003] Moreover, traditional power system simulation systems are usually single simulation models, which independently simulate multiple scenarios such as voltage over-limit, renewable energy fluctuations, and short-circuit faults. They lack a dynamic linkage mechanism triggered by events, and independent analysis of multiple scenarios can easily lead to local optimal traps. For example, independent optimization of a single scenario (such as only solving voltage over-limit) may worsen other scenarios (such as increasing line losses), and the lack of an event linkage mechanism can easily lead to timing misalignment. For example, when event A (short-circuit fault) and event B (voltage sag) occur successively, independent simulation cannot capture the chain reaction of fault-induced voltage drop leading to protection malfunction, thereby increasing the dispatch misjudgment rate. Summary of the Invention

[0004] In order to solve the problem that traditional power system simulation systems use unified standardized templates or fixed topology templates and cannot dynamically adapt to multi-region heterogeneous structures, and independent analysis of multiple scenarios leads to an increased scheduling misjudgment rate, the present invention provides a multi-scenario linkage power grid simulation and scheduling system, which includes:

[0005] Data unit: used to obtain power grid data from different regions and parse the power grid data to obtain heterogeneous data, including differentiated topological structures, standard equipment parameters and rule constraints;

[0006] Processing unit: configured to obtain a regional parameter set based on the heterogeneous data;

[0007] Modeling unit: used for constructing a cross-region interconnection topology model based on the regional parameter set;

[0008] Event unit: used for obtaining monitoring events based on the power grid data;

[0009] Scheduling unit: used to construct a scenario structure, and obtain simulation results based on the cross-region interconnection topology model, the monitoring events and the scenario structure.

[0010] This system automatically identifies topological differences through topological adaptive analysis, uniformly adapts to the power grid structures of different regions, solves the problem of differentiated topological structures of power grids in different regions, and realizes seamless integration of heterogeneous topologies; converts the equipment parameters of each region into regional parameter sets with regional labels to solve the problem of differentiated equipment parameters in different regions; has a built-in rule standard library, uniformly converts regional custom rules into computable constraints, solves the problem of diversified operation rules of power grids in different regions, integrates regional heterogeneous data, and thus realizes dynamic adaptation of simulation models to multi-region parameters, improving the compatibility and fault tolerance of the model; distinguishes different event types and their corresponding trigger conditions, realizes standardized docking of events and modeling based on standardized scenario structures, realizes event-driven multi-scenario linkage mechanism, and thus realizes automatic linkage simulation of complex scenarios such as multiple scenarios, solves the problems of isolated scenarios and weak fault tolerance, reduces the scheduling misjudgment rate, and improves the accuracy of simulation analysis results.

[0011] Furthermore, the data unit specifically includes:

[0012] A topology unit is configured to obtain a regional ring network topology, a regional radial network topology, and a regional mesh network topology based on the power grid data;

[0013] Obtaining a regional node-branch structure based on the regional ring network topology, and obtaining a regional directed graph based on the regional node-branch structure; obtaining a regional tree structure based on the regional radial topology; and obtaining a regional mesh structure based on the regional mesh network topology;

[0014] Obtaining the differentiated topological structure based on the regional directed graph, the regional tree structure, and the regional mesh structure;

[0015] Parameter unit: used for obtaining device parameters based on the power grid data, converting the device parameters into per-unit values, and obtaining the standard device parameters;

[0016] Rule unit: used to construct a rule standard library, which contains a number of standard constraint rules;

[0017] and for obtaining regional operating rules based on the power grid data, matching the regional operating rules with the rule standard library, and if the match is successful, obtaining standard constraint rules based on the rule standard library; if the match fails, obtaining rule thresholds and rule variables based on the regional operating rules, and generating constraint rule expressions based on the rule thresholds and the rule variables;

[0018] and for matching the regional operation rules and keywords to obtain special variables and special keywords, generating special rules based on the special variables and the special keywords, and generating event triggering functions based on the special rules;

[0019] And it is used to obtain the rule constraint based on the standard constraint rule, the constraint rule expression and the event triggering function.

[0020] Different processing is performed for different topologies, and a structural differentiation deconstruction algorithm is used to be compatible with non-standard topology types, with a more accurate and clear structure and stronger applicability. Device parameters are normalized to achieve non-standard data consistency. Regional custom text rules are converted into mathematical constraints, and natural language actions are converted into mathematical conditional statements. Custom constraint functions are generated to be compatible with non-standard operation rules, enabling dynamic adaptation of simulation models to multi-region parameters and improving the compatibility and fault tolerance of the model.

[0021] Furthermore, the processing unit is specifically configured to:

[0022] Construct a mapping relationship table between the differentiated topology structure and the standard device parameters, and inject the regional identification code of the standard device parameters; based on the differentiated topology structure, the standard device parameters, the rule constraints, the mapping relationship table and the regional identification code, obtain the labeled regional parameter set.

[0023] Regional identification code injection prevents cross-region parameter confusion and reduces model mismatch rate.

[0024] Furthermore, the modeling unit is specifically used to:

[0025] Constructing a parameter compatibility layer, and converting the regional parameter set based on the parameter compatibility layer to obtain a cross-region parameter set;

[0026] Based on the differentiated topological structure, regional boundary nodes are obtained, regional connection lines are obtained based on the regional boundary nodes, and based on the regional connection lines and the cross-region parameter set, the cross-region interconnection topology model is constructed.

[0027] The parameter compatibility layer converts regional parameter sets to resolve unit system / benchmark value differences; boundary nodes are automatically identified, and the concept of virtual contact lines is proposed to simulate cross-region interactions, seamless cross-region topology splicing and multi-label regional connection detection, precise positioning of cross-region interaction points, and boundary positioning errors, reducing splicing time.

[0028] Furthermore, the event unit is specifically used to:

[0029] obtaining, based on the power grid data, a plurality of classified events, first event attributes of the classified events, first triggering conditions of the classified events, and first priorities of the classified events;

[0030] Setting a custom event, a second event attribute of the custom event, a second trigger condition of the custom event, a trigger action of the custom event, and a second priority of the custom event;

[0031] The first event attributes include event location, event time and severity, and the second event attributes include newly added load capacity, access point location and time plan;

[0032] The monitoring event is obtained based on the classified event and the custom event.

[0033] Generate modeling requirements based on real-time monitoring events or user-defined events.

[0034] Furthermore, the scheduling unit is specifically configured to:

[0035] Construct a model template library and an algorithm library; set mapping rules between the classified events and the custom events and the model template library, wherein the model template library contains modeling templates for different scenarios, and the algorithm library contains several power flow calculations, several reactive power optimization algorithms, and several source-grid-load-storage coordination algorithms;

[0036] Constructing the scenario structure, wherein the scenario structure includes event type, simulation mode, time span, spatial range, data dependency and output requirement fields;

[0037] obtaining a plurality of scenario models based on the first trigger condition, the second trigger condition, the mapping rule, and the model template library;

[0038] A simulation result is obtained based on the cross-region interconnection topology model, the scenario model, the monitoring event, the scenario structure and the algorithm library.

[0039] Constructing scenario structures reduces modeling barriers caused by topology and parameter differences between regions, breaking down data silos and enabling cross-scenario data connectivity. This supports automatic correlation of multi-scenario data, generating complex event response chains, and accurately quantifying computing requirements through structure fields for optimal resource scheduling. Modularly encapsulates algorithms for power flow calculations and reactive power optimization, supporting dynamic loading and replacement.

[0040] Furthermore, the scheduling unit is further configured to:

[0041] Constructing a two-layer optimization model, wherein the two-layer optimization model includes an upper layer model and a lower layer model;

[0042] Constructing an instruction mapping rule base, wherein the instruction mapping rule base includes a plurality of parameter variables, region types corresponding to the parameter variables, and instruction templates;

[0043] Obtaining optimization variables based on the simulation results, obtaining a change in the optimization variables, and obtaining a plurality of differentiated instructions based on the change and the instruction mapping rule base; and obtaining a scheduling strategy based on the differentiated instructions;

[0044] The first calculation formula of the upper model is:

[0045] ;

[0046] ;

[0047] in, represents the decision variable vector, Indicates the Periods, Indicates the time period, represents the power generation cost function, Indicates time period The active power output of the unit is represents the spare capacity cost, Indicates time period The spare capacity, represents the cascading risk penalty coefficient, represents the cascading failure risk indicator, Indicates the devices, Indicates the total number of devices. Indicates the degree of failure, Indicates the The interconnection line power of each device, Indicates the Safety margin of each device;

[0048] The second calculation formula of the lower model is:

[0049] ;

[0050] in, represents the constraint matrix of region A, represents the state variable, Represents a preset matrix.

[0051] A two-layer optimization model for adaptive scheduling decisions is constructed. The upper-layer model uses mixed integer programming to process discrete decisions with the goal of minimizing the loss of the entire network. The lower-layer model uses the Lagrange multiplier method to process constraint coupling to meet regional differentiation constraints. The two-layer optimization model of economic upper layer + security lower layer breaks through the limitations of traditional single-layer optimization and realizes the coordinated optimization of economy and safety. The two-layer optimization outputs differentiated instructions according to the regional characteristic mapping rule library based on regional characteristics, realizes the precise adaptation of scheduling instructions, improves the accuracy of instructions, and makes cross-regional scheduling strategies more adaptable to each region in linkage scenarios, thereby improving decision-making accuracy.

[0052] Furthermore, the scheduling unit is further configured to:

[0053] Obtaining a real-time risk assessment value based on the scheduling strategy, adjusting the constraint boundary of the two-level optimization model based on the real-time risk assessment value, and obtaining an optimization decision based on the adjusted two-level optimization model;

[0054] The third calculation formula of the real-time risk assessment value is:

[0055] ;

[0056] in, Represents the real-time risk assessment value, represents the power of the inter-regional tie line, Indicates the degree of failure, Indicates the The safety margin of each device, Indicates the Safety limit values ​​for each device, Indicates the device number.

[0057] Through sensitivity analysis, risk warnings are converted into constraint boundary adjustments and then into specific scheduling instructions. A risk-driven real-time constraint boundary adjustment technology is proposed to solve the unsolvable optimization problem in high-risk scenarios and improve feasibility.

[0058] Furthermore, the system further includes a reconstruction unit, which is specifically configured to:

[0059] Obtaining a regional root node of the regional radial topology, and obtaining a regional mesh number based on the regional mesh structure;

[0060] Obtaining reconstruction data, and obtaining a reconstructed ring network topology, a reconstructed radial topology, and a reconstructed mesh network topology based on the reconstruction data; obtaining a reconstructed node-branch structure based on the reconstructed ring network topology, obtaining a reconstructed tree structure based on the reconstructed radial topology, marking a reconstructed root node of the reconstructed radial topology, and obtaining a reconstructed mesh structure and a reconstructed number of meshes based on the reconstructed mesh network topology;

[0061] Obtaining a first similarity based on the reconstructed ring network topology and the regional ring network topology, obtaining a second similarity based on the reconstructed tree structure and the regional tree structure, and obtaining a third similarity based on the reconstructed number of meshes and the number of regional meshes;

[0062] determining whether the first similarity exceeds a first threshold, and if so, obtaining a first similar region based on the first similarity, and obtaining a first adjusted structure based on the reconstructed node-branch structure, the regional node-branch structure, and the first similar region;

[0063] determining whether the second similarity exceeds a second threshold, and if so, obtaining a second similar region based on the second similarity, and obtaining a second adjusted structure based on the reconstruction root node, the regional root node, and the second similar region;

[0064] Determining whether the third similarity exceeds a third threshold, and if so, obtaining a third similar region based on the third similarity, obtaining a first node of the reconstructed mesh structure and a first connecting edge of the first node, and obtaining a second node of the regional mesh structure and a second connecting edge of the second node;

[0065] Obtaining a third adjustment structure based on the first node, the first connecting edge, the second node, and the second connecting edge;

[0066] A reconstructed topology model is obtained based on the first adjustment structure, the second adjustment structure, the third adjustment structure, and the reconstruction data, and the cross-region interconnection topology model is updated to the reconstructed topology model.

[0067] Based on the existing simulation model, the similarity of the topological structures of different regions is judged, and reconstruction is carried out on the original basis according to the similarity, which reduces the reconstruction time and improves efficiency.

[0068] The present invention also provides a multi-scenario linkage power grid simulation scheduling method, the method comprising:

[0069] Acquiring power grid data from different regions and parsing the power grid data to obtain heterogeneous data, wherein the heterogeneous data includes differentiated topological structures, standard equipment parameters, and rule constraints;

[0070] obtaining a regional parameter set based on the heterogeneous data;

[0071] Based on the regional parameter set, constructing a cross-region interconnection topology model;

[0072] obtaining a monitoring event based on the power grid data;

[0073] A scenario structure is constructed, and simulation results are obtained based on the cross-region interconnection topology model, the monitoring events, and the scenario structure.

[0074] The principle and effect of this method are similar to those of this system, and therefore no further description will be given of this method.

[0075] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0076] 1. This system automatically identifies topological differences through topological adaptive analysis, uniformly adapts to the power grid structures of different regions, solves the problem of differentiated topological structures of power grids in different regions, and realizes seamless integration of heterogeneous topologies; converts the equipment parameters of each region into regional parameter sets with regional labels to solve the problem of differentiated equipment parameters in different regions; has a built-in rule standard library, uniformly converts regional custom rules into computable constraints, solves the problem of diversified operation rules of power grids in different regions, integrates regional heterogeneous data, and thus realizes dynamic adaptation of simulation models to multi-region parameters, improving the compatibility and fault tolerance of the model; distinguishes different event types and their corresponding trigger conditions, realizes standardized docking of events and modeling based on standardized scenario structures, realizes event-driven multi-scenario linkage mechanism, and thus realizes automatic linkage simulation of complex scenarios such as multiple scenarios, solves the problems of isolated scenarios and weak fault tolerance, reduces the scheduling misjudgment rate, and improves the accuracy of simulation analysis results.

[0077] 2. Build a scenario structure to reduce modeling barriers caused by topology / parameter differences between regions, break down data silos, achieve cross-scenario data connectivity, support automatic association of multi-scenario data, generate a composite event response chain, and accurately quantify computing requirements through structure fields to optimize resource scheduling.

[0078] 3. Construct a two-layer optimization model for adaptive scheduling decisions. The upper-layer model uses mixed integer programming to handle discrete decisions with the goal of minimizing network-wide losses. The lower-layer model uses the Lagrange multiplier method to handle constraint coupling to meet regional differentiation constraints. The two-layer optimization model of economic upper layer + security lower layer breaks through the limitations of traditional single-layer optimization and achieves coordinated optimization of economy and safety. The two-layer optimization outputs differentiated instructions based on the regional characteristic mapping rule library based on regional characteristics, realizes precise adaptation of scheduling instructions, improves instruction accuracy, and makes cross-regional scheduling strategies more adaptable to each region in linkage scenarios, thereby improving decision-making accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation of the embodiments of the present invention;

[0080] Figure 1 It is a schematic diagram of the operation of the multi-scenario linkage power grid simulation dispatching system in the present invention. DETAILED DESCRIPTION

[0081] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features therein can be combined with each other without conflict.

[0082] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0083] Example 1

[0084] refer to Figure 1 This embodiment provides a multi-scenario linkage power grid simulation dispatching system, the system comprising:

[0085] Data unit: used to obtain power grid data from different regions and parse the power grid data to obtain heterogeneous data, which includes differentiated topological structures, standard equipment parameters and rule constraints; for example, through methods such as node degree analysis, loop detection and connected component analysis, to determine the topology type, or through topological feature extraction and classification using features.

[0086] The data unit specifically includes:

[0087] A topology unit is configured to obtain a regional ring network topology, a regional radial network topology, and a regional mesh network topology based on the power grid data;

[0088] Obtaining a regional node-branch structure based on the regional ring network topology, and obtaining a regional directed graph based on the regional node-branch structure; obtaining a regional tree structure based on the regional radial topology; and obtaining a regional mesh structure based on the regional mesh network topology;

[0089] Obtaining the differentiated topological structure based on the regional directed graph, the regional tree structure, and the regional mesh structure;

[0090] Parameter unit: used to obtain device parameters based on the power grid data, convert the device parameters into per-unit values, and obtain the standard device parameters; for example, converting the transformer short-circuit impedance into per-unit values, the calculation formula can be:

[0091] ;

[0092] in, It represents the normalized per-unit impedance, which is dimensionless and enables the parameter comparability of devices with different capacities. Indicates the percentage of transformer short-circuit impedance, which is essentially the percentage of impedance voltage drop and is dimensionless. Dividing by 100 converts the percentage to a per-unit basis. Indicates the system baseline capacity, Indicates the reference voltage, which is usually the rated value of the voltage level of the equipment.

[0093] Rule unit: used to construct a rule standard library, which contains a number of standard constraint rules;

[0094] Based on the power grid data, regional operating rules are obtained, and the regional operating rules are matched with the rule standard library. If the match is successful, standard constraint rules are obtained based on the rule standard library. If the match fails, rule thresholds and rule variables are obtained based on the regional operating rules, and constraint rule expressions are generated based on the rule thresholds and rule variables. For example, NLP (natural language processing, a type of artificial intelligence that specializes in analyzing human language) is used to extract key thresholds and variables and construct inequality constraints. For example, the regulation text: wind farm curtailment rate ≤ 15% → conversion constraint wind ≤ 0.15.

[0095] The regional operation rules and keywords are matched to obtain special variables and special keywords, special rules are generated based on the special variables and special keywords, and event trigger functions are generated based on the special rules. If there is a special rule: photovoltaic power is prioritized when the fluctuation of new energy exceeds the limit, NLP is used to obtain the trigger conditions through new energy, fluctuation and exceeding the limit, and the trigger action is obtained by priority, photovoltaic power switching and photovoltaic power switching. An IF-THEN structure (logical control structure) is constructed to generate an event trigger function.

[0096] The rule constraint is obtained based on the standard constraint rule, the constraint rule expression and the event triggering function.

[0097] Processing unit: configured to obtain a regional parameter set based on the heterogeneous data;

[0098] The processing unit is specifically configured to:

[0099] A mapping relationship table between the differentiated topology structure and the standard device parameters is constructed, as shown in Table 1:

[0100] Table 1 Mapping relationship between device parameters and topology nodes

[0101] Device ID Area Connecting Nodes Parameter Type Parameter value T_EC_501 East China Bus501 K_T (transformer ratio) 525 / 230 L_NW_332 northwest Bus332 R+jX (line impedance) 0.12+j0.25

[0102] Here, R represents resistance, X represents reactance, and j represents an imaginary unit.

[0103] The regional identification code of the standard device parameters is injected, such as East China: EC, Northwest China: NW.

[0104] The labeled regional parameter set is obtained based on the differentiated topology, the standard device parameters, the rule constraints, the mapping relationship table, and the regional identification code.

[0105] Modeling unit: used for constructing a cross-region interconnection topology model based on the regional parameter set;

[0106] Wherein, the modeling unit is specifically used for:

[0107] A parameter compatibility layer is constructed, and the regional parameter set is converted based on the parameter compatibility layer to obtain a cross-region parameter set; the parameter compatibility layer solves the unit system / reference value difference, such as converting the normalized per-unit impedance transformer short-circuit impedance, and its calculation formula can be:

[0108] ;

[0109] in, represents the dimensionless impedance after conversion to be compatible with the new reference system, represents the normalized per-unit impedance, Indicates the baseline capacity of the new system, Indicates the raw system baseline capacity.

[0110] Based on the differentiated topological structure, regional boundary nodes are obtained. For example, regional boundary nodes are automatically identified using a graph theory algorithm or a breadth-first search (BFS) algorithm. The regional identification codes of the branches connected to the nodes are obtained. If the branch connects two or more nodes with regional identification codes, the node is determined to be a boundary node. Regional tie lines are obtained based on the regional boundary nodes. If the node is a boundary node between any two adjacent regions, a virtual tie line is added, and its impedance can be the average of the impedances of the two regional boundaries. Based on the regional tie lines and the cross-region parameter set, the cross-region interconnection topology model is constructed. The cross-region interconnection topology model can adopt an existing dynamic equivalent model.

[0111] Event unit: used for obtaining monitoring events based on the power grid data;

[0112] The event unit is specifically used for:

[0113] obtaining, based on the power grid data, a plurality of classified events, first event attributes of the classified events, first triggering conditions of the classified events, and first priorities of the classified events;

[0114] For example, it can be divided into voltage events (detecting voltage exceeding the limit), equipment events (identifying load rate) and short-circuit events (capturing circuit breaker tripping or fault current abnormalities).

[0115] Setting a custom event, a second event attribute of the custom event, a second trigger condition of the custom event, a trigger action of the custom event, and a second priority of the custom event;

[0116] Custom events can include: business expansion (new load / power supply access, such as industrial park expansion), new energy events (photovoltaic fluctuation > threshold, abnormal energy storage charging and discharging), EV charging events (centralized operation of charging piles leads to a sudden increase in local load > threshold), three-phase imbalance events (uneven three-phase load distribution, uneven single-phase load distribution, total load balance coefficient less than threshold), and power factor limit-exceeding events (power factor deviates from the design range).

[0117] Assign priorities to incidents based on their urgency and scope of impact.

[0118] The first event attributes include event location, event time and severity, and the second event attributes include newly added load capacity, access point location and time plan;

[0119] The monitoring event is obtained based on the classified event and the custom event.

[0120] Scheduling unit: used to construct a scenario structure, and obtain simulation results based on the cross-region interconnection topology model, the monitoring events and the scenario structure.

[0121] The scheduling unit is specifically configured to:

[0122] Construct a model template library and an algorithm library; set mapping rules between the classified events and the custom events and the model template library, such as:

[0123] The voltage event corresponds to the need to call the reactive compensation optimization model to perform voltage adjustment simulation;

[0124] When equipment is severely overloaded, the load transfer model needs to be called to analyze the load redistribution plan;

[0125] Business expansion events require the use of a grid expansion model to analyze the impact of the new load on the grid.

[0126] When a new energy source is connected, a new energy fluctuation analysis model needs to be used to assess its impact on voltage stability.

[0127] Electric vehicle charging events require calling the load response optimization model to optimize the charging strategy.

[0128] The model template library contains modeling templates for different scenarios, and the algorithm library contains several power flow calculations, several reactive power optimization algorithms, and several source-grid-load-storage coordination algorithms;

[0129] Construct the scenario structure, which includes event type, simulation mode, time span, spatial scope, data dependency and output requirement fields; such as: event type: such as low voltage, business expansion access, etc.; simulation mode: such as power flow calculation, time series power flow calculation, reactive power optimization, etc.; time span: determine the time range of simulation according to the nature of the event, such as real-time events are real-time, and predictive events are the next 24 hours; spatial scope: the area affected by the event, such as the area where the 10kV line L12 and transformer T5 are located; data dependency: specify the data source required for modeling, such as real-time measurement data, historical load curves, equipment parameter libraries, etc.; output requirement field: specify the key indicators that need to be output from the simulation results, such as voltage distribution, load rate and optimization plan, etc.

[0130] obtaining a plurality of scenario models based on the first trigger condition, the second trigger condition, the mapping rule, and the model template library;

[0131] A simulation result is obtained based on the cross-region interconnection topology model, the scenario model, the monitoring event, the scenario structure, and the algorithm library. For example, multiple scenario models and scenario structures are obtained based on the monitoring event and mapping rules, and then the corresponding algorithm library algorithm is called according to the simulation mode. The multiple scenario models are combined with the cross-region interconnection topology model for analysis to obtain the simulation result.

[0132] Example 2

[0133] On the basis of the first embodiment, in this embodiment, the scheduling unit is further configured to:

[0134] Constructing a two-layer optimization model, wherein the two-layer optimization model includes an upper layer model and a lower layer model;

[0135] Constructing an instruction mapping rule base, wherein the instruction mapping rule base includes a plurality of parameter variables, region types corresponding to the parameter variables, and instruction templates;

[0136] Based on the simulation results, optimization variables are obtained, variations of the optimization variables are obtained, and based on the variations and the instruction mapping rule base, a plurality of differentiated instructions are obtained; and a scheduling strategy is obtained based on the differentiated instructions. The instruction mapping rule base is shown in Table 2:

[0137] Table 2 Instruction mapping rule base

[0138] Optimize variable changes Region Type Generate instruction templates Active power>0 Thermal power-dominated areas Start and stop instructions Active power < 0 New Energy Zone Wind / solar curtailment directive Reactive power>0 Weak power grid area Reactive power compensation instruction

[0139] The first calculation formula of the upper model is:

[0140] ;

[0141] ;

[0142] in, represents the decision variable vector, Indicates the Periods, Indicates the time period, represents the power generation cost function, Indicates time period The active power output of the unit is represents the spare capacity cost, Indicates time period The spare capacity, represents the cascading risk penalty coefficient, represents the cascading failure risk indicator, Indicates the devices, Indicates the total number of devices. Indicates the degree of failure, Indicates the The interconnection line power of each device, Indicates the Safety margin of each device;

[0143] The second calculation formula of the lower model is:

[0144] ;

[0145] in, represents the constraint matrix of region A, represents the state variable, Represents the preset matrix of area A.

[0146] In this embodiment, if there are multiple regions, the constraints of the corresponding regions can be superimposed in the lower model, such as

[0147] ;

[0148] in, represents the constraint matrix of region B, represents the state variable, Represents the preset matrix of area B.

[0149] The scheduling unit is further configured to:

[0150] Obtaining a real-time risk assessment value based on the scheduling strategy, adjusting the constraint boundary of the two-level optimization model based on the real-time risk assessment value, and obtaining an optimization decision based on the adjusted two-level optimization model;

[0151] The third calculation formula of the real-time risk assessment value is:

[0152] ;

[0153] in, Represents the real-time risk assessment value, represents the power of the inter-regional tie line, Indicates the degree of failure, Indicates the The safety margin of each device, Indicates the Safety limit values ​​for each device, Indicates the device number.

[0154] Initial decisions output by the upper-level optimization layer (such as unit output and tie-line power) serve as inputs to risk assessments, triggering dynamic adjustments to constraint boundaries. For example, if a region's real-time risk assessment value exceeds 0.9, the voltage constraint limit is automatically relaxed (from 10% to 12%) and reinjected into the lower-level constraints for iteration. These adjusted constraints directly influence the instruction generation logic. For example, after the East China region's constraints are relaxed, the instruction template library prioritizes deep peak shaving of thermal power units over load shedding, reducing economic costs.

[0155] Example 3

[0156] Based on the above embodiment, in this embodiment, the system further includes a reconstruction unit, and the reconstruction unit is specifically configured to:

[0157] Obtaining a regional root node of the regional radial topology, and obtaining a regional mesh number based on the regional mesh structure;

[0158] Obtain reconstruction data, and obtain a reconstructed ring network topology, a reconstructed radial topology, and a reconstructed mesh network topology based on the reconstruction data; obtain a reconstructed node-branch structure based on the reconstructed ring network topology, obtain a reconstructed tree structure based on the reconstructed radial topology, mark a reconstructed root node of the reconstructed radial topology, and obtain a reconstructed mesh structure and a reconstructed number of meshes based on the reconstructed mesh network topology; if the number of meshes satisfies a graph theory formula, the number of meshes = the number of branches - the number of nodes + the number of connected components, the number of connected components can be obtained according to a depth-first search (DFS) or a union-find algorithm.

[0159] Based on the reconstructed ring network topology and the regional ring network topology, a first similarity is obtained, such as dividing the ring network topology into regions and calculating their similarity based on a feature vector method or a node / edge centrality metric comparison; based on the reconstructed tree structure and the regional tree structure, a second similarity is obtained, such as dividing the tree structure into different regions and calculating their similarity using a tree isomorphism (AHU algorithm), a tree edit distance (TED) or a feature method or a tree core method; based on the reconstructed mesh number and the regional mesh number, a third similarity is obtained, such as the reconstructed mesh number / regional mesh number;

[0160] determining whether the first similarity exceeds a first threshold, and if so, obtaining a first similar region based on the first similarity, and obtaining a first adjusted structure based on the reconstructed node-branch structure, the regional node-branch structure, and the first similar region;

[0161] determining whether the second similarity exceeds a second threshold, and if so, obtaining a second similar region based on the second similarity, and obtaining a second adjusted structure based on the reconstruction root node, the regional root node, and the second similar region;

[0162] Determining whether the third similarity exceeds a third threshold, and if so, obtaining a third similar region based on the third similarity, obtaining a first node of the reconstructed mesh structure and a first connecting edge of the first node, and obtaining a second node of the regional mesh structure and a second connecting edge of the second node;

[0163] Obtaining a third adjustment structure based on the first node, the first connecting edge, the second node, and the second connecting edge;

[0164] Based on the first adjusted structure, the second adjusted structure, the third adjusted structure, and the reconstructed data, a reconstructed topology model is obtained, and the cross-region interconnection topology model is updated to the reconstructed topology model. That is, based on the cross-region interconnection topology model, similar structures are adjusted, and dissimilar structures are regenerated based on the reconstructed data.

[0165] Example 4

[0166] Based on the above embodiment, this embodiment further provides a multi-scenario linkage power grid simulation scheduling method, the method comprising:

[0167] Acquiring power grid data from different regions and parsing the power grid data to obtain heterogeneous data, wherein the heterogeneous data includes differentiated topological structures, standard equipment parameters, and rule constraints;

[0168] obtaining a regional parameter set based on the heterogeneous data;

[0169] Based on the regional parameter set, constructing a cross-region interconnection topology model;

[0170] obtaining a monitoring event based on the power grid data;

[0171] A scenario structure is constructed, and simulation results are obtained based on the cross-region interconnection topology model, the monitoring events, and the scenario structure.

[0172] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0173] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. Multi-scenario linkage power grid simulation dispatching system, characterized by: The system comprises: Data unit: used to obtain power grid data from different regions and parse the power grid data to obtain heterogeneous data, including differentiated topological structures, standard equipment parameters and rule constraints; Processing unit: configured to obtain a regional parameter set based on the heterogeneous data; Modeling unit: used for constructing a cross-region interconnection topology model based on the regional parameter set; Event unit: used for obtaining monitoring events based on the power grid data; Scheduling unit: used to construct a scenario structure, and obtain simulation results based on the cross-region interconnection topology model, the monitoring events and the scenario structure.

2. The multi-scenario linkage power grid simulation dispatching system according to claim 1 is characterized in that: The data unit specifically includes: A topology unit is configured to obtain a regional ring network topology, a regional radial network topology, and a regional mesh network topology based on the power grid data; Obtaining a regional node-branch structure based on the regional ring network topology, and obtaining a regional directed graph based on the regional node-branch structure; obtaining a regional tree structure based on the regional radial topology; and obtaining a regional mesh structure based on the regional mesh network topology; Obtaining the differentiated topological structure based on the regional directed graph, the regional tree structure, and the regional mesh structure; Parameter unit: used for obtaining device parameters based on the power grid data, converting the device parameters into per-unit values, and obtaining the standard device parameters; Rule unit: used to construct a rule standard library, which contains a number of standard constraint rules; and for obtaining regional operating rules based on the power grid data, matching the regional operating rules with the rule standard library, and if the match is successful, obtaining standard constraint rules based on the rule standard library; if the match fails, obtaining rule thresholds and rule variables based on the regional operating rules, and generating constraint rule expressions based on the rule thresholds and the rule variables; and for matching the regional operation rules and keywords to obtain special variables and special keywords, generating special rules based on the special variables and the special keywords, and generating event triggering functions based on the special rules; And it is used to obtain the rule constraint based on the standard constraint rule, the constraint rule expression and the event triggering function.

3. The multi-scenario linkage power grid simulation dispatching system according to claim 1 is characterized in that: The processing unit is specifically configured to: Construct a mapping relationship table between the differentiated topology structure and the standard device parameters, and inject the regional identification code of the standard device parameters; based on the differentiated topology structure, the standard device parameters, the rule constraints, the mapping relationship table and the regional identification code, obtain the labeled regional parameter set.

4. The multi-scenario linkage power grid simulation dispatching system according to claim 1 is characterized in that: The modeling unit is specifically used for: Constructing a parameter compatibility layer, and converting the regional parameter set based on the parameter compatibility layer to obtain a cross-region parameter set; Based on the differentiated topological structure, regional boundary nodes are obtained, regional connection lines are obtained based on the regional boundary nodes, and based on the regional connection lines and the cross-region parameter set, the cross-region interconnection topology model is constructed.

5. The multi-scenario linkage power grid simulation dispatching system according to claim 1 is characterized in that: The event unit is specifically used for: obtaining, based on the power grid data, a plurality of classified events, first event attributes of the classified events, first triggering conditions of the classified events, and first priorities of the classified events; Setting a custom event, a second event attribute of the custom event, a second trigger condition of the custom event, a trigger action of the custom event, and a second priority of the custom event; The first event attributes include event location, event time and severity, and the second event attributes include newly added load capacity, access point location and time plan; The monitoring event is obtained based on the classified event and the custom event.

6. The multi-scenario linkage power grid simulation dispatching system according to claim 5 is characterized in that: The scheduling unit is specifically used for: Construct a model template library and an algorithm library; set mapping rules between the classified events and the custom events and the model template library, wherein the model template library contains modeling templates for different scenarios, and the algorithm library contains several power flow calculations, several reactive power optimization algorithms, and several source-grid-load-storage coordination algorithms; Constructing the scenario structure, wherein the scenario structure includes event type, simulation mode, time span, spatial range, data dependency and output requirement fields; obtaining a plurality of scenario models based on the first trigger condition, the second trigger condition, the mapping rule, and the model template library; A simulation result is obtained based on the cross-region interconnection topology model, the scenario model, the monitoring event, the scenario structure and the algorithm library.

7. The multi-scenario linkage power grid simulation dispatching system according to claim 6, characterized in that: The scheduling unit is further specifically configured to: Constructing a two-layer optimization model, wherein the two-layer optimization model includes an upper layer model and a lower layer model; Constructing an instruction mapping rule base, wherein the instruction mapping rule base includes a plurality of parameter variables, region types corresponding to the parameter variables, and instruction templates; Obtaining optimization variables based on the simulation results, obtaining a change in the optimization variables, and obtaining a plurality of differentiated instructions based on the change and the instruction mapping rule base; and obtaining a scheduling strategy based on the differentiated instructions; The first calculation formula of the upper model is: ； ； in, represents the decision variable vector, Indicates the Periods, Indicates the time period, represents the power generation cost function, Indicates time period The active power output of the unit is represents the spare capacity cost, Indicates time period The spare capacity, represents the cascading risk penalty coefficient, represents the cascading failure risk indicator, Indicates the devices, Indicates the total number of devices. Indicates the degree of failure, Indicates the The interconnection line power of each device, Indicates the Safety margin of each device; The second calculation formula of the lower model is: ； in, represents the constraint matrix of region A, represents the state variable, Represents a preset matrix.

8. The multi-scenario linkage power grid simulation dispatching system according to claim 7, characterized in that: The scheduling unit is further specifically configured to: Obtaining a real-time risk assessment value based on the scheduling strategy, adjusting the constraint boundary of the two-level optimization model based on the real-time risk assessment value, and obtaining an optimization decision based on the adjusted two-level optimization model; The third calculation formula of the real-time risk assessment value is: ； in, Represents the real-time risk assessment value, represents the power of the inter-regional tie line, Indicates the degree of failure, Indicates the The safety margin of each device, Indicates the Safety limit values ​​for each device, Indicates the device number.

9. The multi-scenario linkage power grid simulation dispatching system according to claim 2, characterized in that: The system further includes a reconstruction unit, which is specifically configured to: Obtaining a regional root node of the regional radial topology, and obtaining a regional mesh number based on the regional mesh structure; Obtaining reconstruction data, and obtaining a reconstructed ring network topology, a reconstructed radial topology, and a reconstructed mesh network topology based on the reconstruction data; obtaining a reconstructed node-branch structure based on the reconstructed ring network topology, obtaining a reconstructed tree structure based on the reconstructed radial topology, marking a reconstructed root node of the reconstructed radial topology, and obtaining a reconstructed mesh structure and a reconstructed number of meshes based on the reconstructed mesh network topology; Obtaining a first similarity based on the reconstructed ring network topology and the regional ring network topology, obtaining a second similarity based on the reconstructed tree structure and the regional tree structure, and obtaining a third similarity based on the reconstructed number of meshes and the number of regional meshes; determining whether the first similarity exceeds a first threshold, and if so, obtaining a first similar region based on the first similarity, and obtaining a first adjusted structure based on the reconstructed node-branch structure, the regional node-branch structure, and the first similar region; determining whether the second similarity exceeds a second threshold, and if so, obtaining a second similar region based on the second similarity, and obtaining a second adjusted structure based on the reconstruction root node, the regional root node, and the second similar region; Determining whether the third similarity exceeds a third threshold, and if so, obtaining a third similar region based on the third similarity, obtaining a first node of the reconstructed mesh structure and a first connecting edge of the first node, and obtaining a second node of the regional mesh structure and a second connecting edge of the second node; Obtaining a third adjustment structure based on the first node, the first connecting edge, the second node, and the second connecting edge; A reconstructed topology model is obtained based on the first adjustment structure, the second adjustment structure, the third adjustment structure, and the reconstruction data, and the cross-region interconnection topology model is updated to the reconstructed topology model.

10. A multi-scenario linked power grid simulation scheduling method, characterized in that: The method comprises: Acquiring power grid data from different regions and parsing the power grid data to obtain heterogeneous data, wherein the heterogeneous data includes differentiated topological structures, standard equipment parameters, and rule constraints; obtaining a regional parameter set based on the heterogeneous data; Based on the regional parameter set, constructing a cross-region interconnection topology model; obtaining a monitoring event based on the power grid data; A scenario structure is constructed, and simulation results are obtained based on the cross-region interconnection topology model, the monitoring events, and the scenario structure.

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