A cross-regional power supply and demand balance scheduling management and control system

Abstract

The present application relates to the technical field of power supply and demand scheduling, and more particularly to a cross-regional power supply and demand balance scheduling management and control system. The system comprises the following modules: a power grid topology modeling module, a scheduling decision module, a supply and demand monitoring module, and a scheduling evaluation and optimization module. By constructing a cross-regional transmission network reflecting the physical structure of the current target cross-regional power grid, key power transmission channels are screened out. The current supply and demand balance degree of each region is calculated in real time, and the transmission utilization rate of the key power transmission channels is combined to trigger power supply and demand balance scheduling control. The transmission utilization rate of the key power transmission channels and the regional supply and demand balance degree are continuously monitored to evaluate the execution effect of the current scheduling. The present application realizes accurate allocation of cross-regional power through imbalance and redundancy double condition judgment to improve the utilization rate of power grid channels.

Description

Technical Field

[0001] This invention relates to the field of power supply and demand dispatching technology, and in particular to a cross-regional power supply and demand balance dispatching and control system. Background Technology

[0002] Most existing power dispatching systems rely on static dispatching plans based on day-ahead or hour-ahead forecasts. These plans are often based on a pre-defined, fixed power grid topology. This dispatching mode is essentially an "open-loop" or "quasi-static" control method, unable to perceive and adapt to actual changes in the power grid topology in real time. When a critical transmission line in the power grid trips due to a fault, or a large power source suddenly disconnects from the grid, the actual topology and power flow paths of the power grid have fundamentally changed, but the original dispatching plan cannot be adjusted instantaneously. The system can only rely on manual intervention by dispatchers or the action of passive safety and stability control devices. This lagging response mechanism results in the inability to optimize and adjust the power allocation of inter-regional transmission channels in a timely and accurate manner, which not only greatly reduces the utilization efficiency of transmission assets but also causes overload problems in other channels due to the passive transfer of power flow. Summary of the Invention

[0003] Based on this, the present invention provides a cross-regional power supply and demand balance dispatch and control system to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a cross-regional power supply and demand balance dispatching and control system includes the following modules:

[0005] The power grid topology modeling module is used to perform regional boundary scanning and topology connection of the target cross-regional power grid, calculate the transmission capacity of each transmission channel, and use the transmission capacity as the connection weight value to construct a cross-regional transmission network that reflects the current physical structure of the power grid.

[0006] The scheduling decision module is used to synchronously collect and analyze the power parameters of the channel operation in order to identify transmission anomalies and predict the transmission capacity trend of each channel, thereby selecting key transmission channels from the cross-regional transmission network and constructing a dual scheduling channel strategy accordingly.

[0007] The supply and demand monitoring module is used to calculate the current supply and demand balance of each region in real time, and combined with the transmission utilization rate of the target dispatch channel in the dual dispatch channel strategy, it determines the dispatch triggering time based on the preset imbalance and redundancy conditions, and generates a dispatch start command; the dispatch start command is used to trigger the power supply and demand balance dispatch control.

[0008] The scheduling evaluation and optimization module is used to continuously monitor the transmission utilization rate of key transmission channels and the regional supply and demand balance after the scheduling start command is executed, and to evaluate the execution effect of this scheduling.

[0009] The beneficial effects of this invention are as follows:

[0010] On the one hand, by performing real-time boundary scanning and topology connection of cross-regional power grids, and constructing a transmission network using dynamically calculated actual transmission capacity as connection weight values, this invention overcomes the limitations of traditional scheduling systems that rely on static, preset power grid topology models. It can reflect in real time the changes in physical structure and transmission capacity of the power grid caused by factors such as line maintenance, faults, or fluctuations in new energy output, and achieves accurate and dynamic perception of the current state of complex power grids. This provides a high-fidelity data foundation for subsequent intelligent decision-making and control, and significantly improves the system's environmental adaptability and situational awareness.

[0011] On the other hand, by analyzing the line load transmission vector to predict the transmission capacity trend of each channel, and comparing the predicted trajectory with the 85% safety threshold, this invention can proactively screen potential transmission bottlenecks, i.e., critical transmission channels. Based on this, a "dual-dispatch channel strategy" combining primary and backup is constructed, and the timing of dispatch triggering is linked to the dual conditions of "regional supply-demand imbalance" and "channel capacity redundancy." This mechanism transforms dispatch decision-making from traditional passive response to proactive prediction and precise triggering, effectively preventing channel overload and cascading failure risks, avoiding ineffective dispatching when channels are congested, ensuring the necessity and executability of dispatch instructions, and significantly improving the stability and economy of cross-regional power grid operation.

[0012] On the other hand, this invention innovatively decomposes the target power for dispatching into a time-sequential control sequence when constructing the power dispatching execution scheme, and extracts real-time parameters such as grid frequency and voltage phase angle as "dynamic salt values" to generate a one-time dynamic dispatching execution key. This mechanism tightly binds dispatching commands to the instantaneous state of the grid, effectively preventing command replay attacks and unauthorized operation risks. This not only greatly enhances the security of dispatching command execution in an open network environment, but also achieves smooth and precise adjustment of power flow through time-sequential, step-by-step power control, avoiding secondary impacts on the grid caused by power surges, and ensuring a high degree of controllability and stability of the entire dispatching process. Attached Figure Description

[0013] Figure 1 This is a flowchart illustrating the steps of the cross-regional power supply and demand balance dispatch and control method of the present invention;

[0014] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0015] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0016] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0017] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0018] To achieve the above objectives, please refer to Figure 1 This invention provides a cross-regional power supply and demand balance dispatching and control system, comprising the following modules:

[0019] S1: Power grid topology modeling module, used to perform regional boundary scanning on the target cross-regional power grid, calculate the transmission capacity of each transmission channel, and use the transmission capacity as the connection weight value to construct a cross-regional transmission network that reflects the current physical structure of the power grid;

[0020] In this embodiment of the invention, assuming the target cross-regional power grid covers region A (power surplus) and region B (high power demand), the modeling process is as follows: Regional boundary scanning and topology connection: The system first initiates the regional boundary scanning function, and by accessing the SCADA (Supervisory Control and Data Acquisition) database of the State Grid Dispatch Center, identifies all physical transmission line connection points between region A and region B. Specifically, the scanning results identify two main connection points: "Substation A" located in region A and "Substation B" located in region B, which are connected by a ±800kV UHVDC transmission line (denoted as channel L1). The system records the GPS coordinates of the two substations and measures and calibrates the length of channel L1 to 1980 kilometers based on the line archive data. Based on the geographical information of these two connection points and channel L1, a connection relationship is established in the topology database: Node A (Substation A) -- [Channel L1] -- Node B (Substation B), thus initially obtaining the cross-regional topology.

[0021] Transmission Capacity Calculation and Network Construction: Identify the line type of channel L1 as "overhead DC line" and obtain its channel electrical parameters from the equipment parameter library, including conductor type (ACSR-720 / 50), line resistance (0.02Ω / km), line reactance (negligible), and conductor design current carrying capacity (5000A). Specifically, calculate the rated transmission capacity of channel L1 based on the channel electrical parameters. The calculation formula is: Among them, rated voltage 800kV, rated current It is 5000A. =800,000V × 5000A = 4000MW. Using the calculated 4000MW as the connection weight value for this topology, the final cross-regional transmission network can be represented as: Node A -- (Weight: 4000MW) -- Node B. This network model dynamically reflects the most critical physical connection and maximum power transmission capacity between regions A and B.

[0022] S2: The scheduling decision module is used to synchronously collect and analyze the power parameters of the channel operation in order to identify transmission anomalies and predict the transmission capacity trend of each channel, thereby selecting key transmission channels from the cross-regional transmission network and constructing a dual scheduling channel strategy accordingly.

[0023] In this embodiment of the invention, phasor measurement units (PMUs) deployed at the converter stations at both ends of "Substation A" and "Substation B" synchronously collect real-time power parameters such as voltage, current, and power of channel L1 at a frequency of 50 times per second. Assuming a surge in industrial production and residential cooling demand in area B during a summer afternoon, the system monitors that the power of channel L1 steadily increases from 2800MW to 3100MW within 10 minutes. Based on this, the system calculates the changing trend of the line load transmission vector and predicts its transmission capacity trend for the next hour. Through trend analysis and verification, the system predicts that the load will reach 300MW after one hour. The system then loads a pre-set spatial distribution map of the entire network's transmission capacity, and compares this predicted trajectory with the 85% safety threshold of channel L1. Overlay comparison was performed. Since the predicted value of 3280MW is close to the safety threshold, the system selected and marked channel L1 as a "critical transmission channel." Simultaneously, the system analyzed another parallel 500kV AC line (denoted as channel L2), whose regulation margin, although less than L1, still possessed dispatch potential. Based on this, the system constructed a dual-dispatch channel strategy: channel L1 was designated as the "first primary dispatch channel," and channel L2 as the "second backup dispatch channel," encapsulating their respective dispatch center IDs (State Grid Dispatch Center in Area A and State Grid Dispatch Center in Area B) and equipment identifiers.

[0024] S3: Supply and demand monitoring module, used to calculate the current supply and demand balance of each region in real time, and combine the transmission utilization rate of the target dispatch channel in the dual dispatch channel strategy, judge the dispatch triggering time based on the preset imbalance and redundancy dual conditions, and generate dispatch start command; trigger power supply and demand balance dispatch control through dispatch start command;

[0025] In this embodiment of the invention, the energy management system (EMS) connected to the regional power grid calculates in real time that the current supply-demand balance of region A is 1.15 (supply exceeds demand), while the supply-demand balance of region B has dropped to 0.84 due to peak load. At this time, the system enters the control logic of dual condition judgment of imbalance and redundancy: Imbalance condition judgment: Is the supply-demand balance of region B (0.84) less than the preset imbalance threshold of 0.85? Yes, the condition is met; Redundancy condition judgment: Is the current transmission utilization rate of the target main dispatch channel L1 (3100MW / 4000MW=77.5%) less than the preset redundancy threshold of 60%? No, the condition is not met. Logic flow: Since the redundancy condition is not met, it means that the main channel is already under high load, and direct transmission brings safety risks. Therefore, the system determines that the dispatch triggering time has not arrived and continues to monitor. Half an hour later, due to the increase in upstream water flow in region A, the hydropower output increased, resulting in a decrease in the planned power transmitted through L1, and the transmission utilization rate of channel L1 dropped to 58%. The supply-demand balance in region B further deteriorated to 0.83. At this point, the system made another assessment: the imbalance condition (0.83 < 0.85) was met, and the redundancy condition (58% < 60%) was also met. With both conditions satisfied, the system immediately generated a "scheduling start command".

[0026] S4: Dispatch evaluation and optimization module, used to continuously monitor the transmission utilization rate of key transmission channels and the regional supply and demand balance after the dispatch start command is executed, and to evaluate the execution effect of this dispatch.

[0027] In this embodiment of the invention, after the "dispatch start command" is executed, the system instructs to increase the power transmission from region A to region B through the main channel L1 by 1000MW. The dispatch evaluation and optimization module is immediately activated, continuously monitoring and recording key indicators at 1-minute intervals. Initial state (t=0): L1 transmission utilization rate = 57.5%, supply-demand balance in region B = 0.81. During dispatch (t=10 minutes): L1 transmission power increases to 2800MW, and the utilization rate rises to 2800 / 4000 = 70%. Region B receives 500MW of support, and its supply-demand balance improves to (70000+500) / 85000 = 0.829. Dispatch ends (t=20 minutes): L1 transmission power stabilizes at 3300MW, and the utilization rate reaches 3300 / 4000 = 82.5%. Region B received a total of 1000MW of support, with a final supply-demand balance of (70000+1000) / 85000=0.835. Scheduling Effectiveness Evaluation: After the scheduling task is completed, the module automatically generates an evaluation report of the scheduling effectiveness. Specifically, the report includes: Scheduling Objective: Improve the supply-demand balance of Region B, target value > 0.9. Execution Path: Main scheduling channel L1. Execution Process Data: Time-series change curves of key indicators (L1 utilization rate, Region B balance rate). Execution Results: The supply-demand balance rate of Region B increased from 0.81 to 0.835, an increase of 3%. The utilization rate of the main channel L1 increased from 57.5% to 82.5%, indicating effective utilization of channel resources.

[0028] Preferably, the power grid topology modeling module includes the following functions:

[0029] Perform regional boundary scanning on the target cross-regional power grid to identify the transmission line connection points between different regions;

[0030] The geographical locations of each transmission channel are marked according to the connection points of the transmission lines, and the channel lengths are measured at the same time;

[0031] Regional topology connections are made based on geographical location and channel length to obtain a cross-regional topology structure;

[0032] The transmission capacity of the transmission channels in the cross-regional topology is calculated, and the transmission capacity is used as the connection weight value of the cross-regional topology to construct the cross-regional transmission network.

[0033] In this embodiment of the invention, a regional boundary scanning procedure is initiated. This procedure sends data query commands to the power grid's energy management system (EMS) through a scheduling automation interface. The commands request a list of all substations with voltage levels of 500kV and above within their respective control areas, along with their geographical coordinates.

[0034] In one implementation of this invention, the system obtains a list from the EMS containing "Substation A" (ID: HB-S01, longitude: 118.5°E, latitude: 40.2°N); simultaneously, it obtains a list from the EMS containing "Substation B" (ID: DB-S02, longitude: 123.2°E, latitude: 41.3°N). The system queries the line ledger database to check if there exists a transmission line that connects both IDs "HB-S01" and "DB-S02". The system finds a 500kV AC transmission line named "Line A" and confirms it as an inter-regional transmission line. Therefore, "Substation A" and "Substation B" are identified as a pair of inter-regional transmission line connection points. Specifically, the system uses the Haversine formula to calculate the great circle distance between the two points, which is then used as the length of the transmission channel.

[0035] In one implementation of this invention, the system creates a graph (data structure) where each substation is treated as a node. The system creates two node objects for "Substation A" and "Substation B". Then, an edge is created between the two nodes, with its attributes recording the channel ID (e.g., "HL-Line-01"), line type (AC 500kV), and the calculated channel length (425km). By repeating this step for all identified inter-regional transmission lines, the system ultimately obtains an inter-regional topology containing all inter-regional connections and their physical attributes.

[0036] It is important to note that the calculation of transmission capacity requires comprehensive consideration of the thermal stability limit and static stability limit of the line. The system first obtains the detailed electrical parameters of "Line A" from the equipment parameter database, including: the conductor type is LGJ-400 / 50, its long-term allowable current carrying capacity at standard ambient temperature (25℃) is 800A; and the total reactance of the line is 130Ω.

[0037] In one implementation of this invention, the system first calculates the thermal stability limit capacity (…). ).

[0038] ;

[0039] in, It is the rated voltage of the line (500kV). This is the conductor's long-term allowable current carrying capacity (800A). Calculated as follows: .

[0040] In another implementation of this invention, the system then calculates the static stability limit capacity ( A simplified formula for the work angle characteristic is usually used: .

[0041] It should be noted that, and It is the voltage amplitude of the substations at both ends of the line (usually taken as the rated voltage of 500kV). It is the total line reactance (130Ω). It's the power angle difference. To ensure stable system operation, the power angle difference... The stable operating limit is typically taken as 30 degrees. Calculations show: The calculated thermal stability limit (693MW) and static stability limit (961MW) are compared, and the minimum value is taken as the final transmission capacity of the transmission channel. Specifically, the determined transmission capacity is 693MW. This value is used as the weight of the connection between "Substation A" and "Substation B". After assigning weights to all channels, a weighted inter-regional transmission network reflecting the current power grid physical structure and transmission capacity is constructed.

[0042] Preferably, the scheduling decision module includes the following functions:

[0043] Synchronously collect the channel operating power parameters of the transmission lines in the substation; among which, the channel operating power parameters include voltage, current and power parameters;

[0044] The three-dimensional spatial coordinates of the transmission lines are extracted based on the target cross-regional power grid, and the line load transmission vector is calculated based on the channel operating power parameters.

[0045] Based on the line load transmission vector, the trend analysis and verification of the line load transmission vector within the preset sampling time window are continuously performed to identify transmission channels with abnormal transmission.

[0046] High-reliability transmission status points are extracted from cross-regional transmission networks based on transmission channels that identify transmission anomalies.

[0047] Collect power transmission sampling timing values ​​of each transmission channel in the cross-regional transmission network;

[0048] Key transmission channels are selected based on line load transmission vectors, high-reliability transmission status points, and power transmission sampling timing values.

[0049] In an embodiment of the present invention, by scheduling the data network, a synchronization acquisition instruction is sent to the phasor measurement unit (PMU) deployed at the substation on the boundary between Area A and Area B. The acquisition instruction sets a synchronization period of 50 milliseconds. At a certain synchronization moment t = t0, the system acquires a set of channel operation power parameters from the cross-region power transmission channel (ID: AB-01) connecting Substation A (ID: A-S01) in Area A and Substation B (ID: B-S01) in Area B. This set of parameters includes: the voltage U_A at the outlet side of Substation A = 505 kV, the current I_A at the outlet side = 1200 A, and the active power P_A at the outlet side = 1040 MW.

[0050] In an embodiment of the present invention, from the cross-region transmission network constructed by the power grid topology modeling module, the three-dimensional spatial coordinates of the channel "AB-01" are extracted. It should be noted that these coordinates are obtained by fitting the geographical information of the line towers during the modeling stage and describe the actual trend of the power transmission line in space. According to the acquired channel operation power parameters, the line load transmission vector (F) is calculated. This vector aims to describe the intensity and direction of power transmission.

[0051] Specifically, the calculation model of this vector is as follows:

[0052] ;

[0053] Where, is the transmission power of the channel (taking P_A = 1040 MW), is a unit direction vector representing the spatial direction from Substation A to Substation B.

[0054] In another implementation manner of an embodiment of the present invention, assuming the three-dimensional coordinates of Substation A are ([ ), and the coordinates of Substation B are ([ ), then the unit direction vector is obtained through the following method:

[0055] Vector ; ;

[0056] After calculation, the system obtains the line load transmission vector at the moment of .

[0057] In an embodiment of the present invention, a preset sampling time window is set, for example, 10 seconds. Within this window, the system continuously calculates the line load transmission vector.

[0058] It should be noted that the trend analysis verification is achieved by comparing the change rate between two consecutive vectors within the window. The system calculates the change rate . If the modulus of this change rate If the abnormal fluctuation exceeds a preset threshold, it is considered a transmission anomaly. This abnormal fluctuation threshold is calculated based on historical operating data of the line and is typically three times the standard deviation of its normal power fluctuation.

[0059] In one implementation of this invention, assuming the historical power fluctuation standard deviation of channel "AB-01" is 5 MW / s, the abnormal fluctuation threshold is set to 15 MW / s. arrive Within the specified time window, the system detected a sharp drop in the magnitude of the line load transmission vector from 1040MW to 980MW, with a rate of change reaching -6MW / s, accompanied by slight directional fluctuations. Since -6MW / s did not exceed the threshold, the system determined it to be a normal load fluctuation.

[0060] In another scenario, if a remote fault causes the power to drop from 1000MW to 800MW within 2 seconds, with a change rate as high as -100MW / s, far exceeding the threshold of 15MW / s, the system will immediately mark the transmission channel as "transmission abnormal".

[0061] In this embodiment of the invention, when a transmission channel is identified as having a "transmission anomaly," the system immediately extracts a state point from its stable operation phase before the anomaly occurred. Specifically, the system retrieves a complete PMU data snapshot of the channel at a point in time (e.g., 1 minute before the anomaly occurred) when it was in a stable transmission state before the anomaly occurred. This snapshot contains a series of high-precision data such as the precise voltage phase angle, current phase angle, and frequency at that time. This data snapshot is defined as a high-reliability transmission state point.

[0062] In this embodiment of the invention, regardless of whether the channel is abnormal, the system continuously records the power transmission sample values ​​for each transmission channel in the cross-regional transmission network, forming a time series. For channel "AB-01", the system maintains a queue of power transmission sample timing values ​​with a length of 60 sampling points (i.e., the past 60 seconds). At that time, the queue stored data from... arrive The active power value at each sampling point, for example: [..., 1035MW, 1038MW, 1040MW, 1039MW, ...].

[0063] In this embodiment of the invention, critical transmission channels are screened using line load transmission vectors, high-confidence transmission state points (if they exist), and power transmission sampling time-series values. The screening logic is as follows: Stability judgment: The system calculates the variance of the power transmission sampling time-series values. If the variance is less than a preset stability variance threshold, the channel is considered to be transmitting stably. Trend prediction: For channels with stable transmission, the system performs linear regression analysis on their power transmission sampling time-series values ​​to predict the transmission power 5 minutes later. Criticality judgment: If the predicted transmission power will exceed 85% of the channel's rated transmission capacity (safety threshold), the channel is screened as a critical transmission channel. Priority for abnormal channels: All channels marked as "transmission abnormal" are directly and unconditionally screened as critical transmission channels, regardless of their predicted load, because their state uncertainty constitutes the greatest risk to the power grid.

[0064] In one implementation of this invention, the power sequence variance of channel "AB-01" is small, indicating it is stable. Linear regression predicts its power will reach 1150MW in 5 minutes. Assuming the channel's rated transmission capacity is 1200MW and its 85% safety threshold is 1020MW, since 1150MW > 1020MW, the system ultimately filters and marks channel "AB-01" as a critical transmission channel.

[0065] Preferably, the selection of key transmission channels based on line load transmission vectors, high-confidence transmission status points, and power transmission sampling timing values ​​includes:

[0066] Calculate the variance of the line load transmission vector within the preset sampling time window, and denote this variance as the channel transmission stability.

[0067] Determine whether the channel transmission stability is less than the preset stability threshold; if so, generate a stable transmission identifier code.

[0068] Based on stable transmission identification codes and high-reliability transmission status points and power transmission sampling timing values, the transmission capability trend of each channel is identified as a predictive transmission trajectory.

[0069] Based on the pre-set spatial distribution map of the entire network transmission capacity, the predicted transmission trajectory is compared and superimposed with the load to screen out the transmission channels whose transmission capacity will exceed the 85% safety threshold, thus forming the key transmission channels; the pre-set spatial distribution map of the entire network transmission capacity is marked with the geographical location of each transmission channel and the contour line of 85% safe transmission capacity.

[0070] In this embodiment of the invention, a preset sampling time window of 30 seconds is set for the inter-regional power transmission channel "CD-01" (connecting regions C and D). Within this window, the system continuously collects 600 samples of line load transmission vectors at a period of 50 milliseconds. Specifically, the system extracts the modulus (i.e., instantaneous active power value) of these 600 vector samples to form a power time series. Then, the system calculates the variance of the sequence and records it as the channel transmission stability. The formula for calculating variance is as follows:

[0071] ;

[0072] It should be noted that in the formula It is the first One power sample value, It is the average of these 600 sample values. It is the total number of samples ( =600).

[0073] In one implementation of this invention, it is assumed that within a 30-second window, the average power of channel "CD-01" is... The variance was calculated for 800MW. The value is 25 MW². Therefore, the transmission stability of this channel is denoted as 25.

[0074] In this embodiment of the invention, the calculated channel transmission stability is compared with a preset stability threshold. It should be noted that this stability threshold is obtained by statistically analyzing power fluctuations under different operating conditions based on historical power grid operating data. For 500kV AC lines, this threshold is typically set to 100MW².

[0075] In one implementation of this invention, the system compares the transmission stability (25) of channel "CD-01" with a stability threshold (100). Since 25 < 100, the condition is met. The system then generates a stable transmission identifier for channel "CD-01". Specifically, this identifier is a Boolean value or a specific enumeration type; for example, the system writes it into the status attribute of channel "CD-01". If the variance is greater than the threshold, then write... .

[0076] In one implementation of this invention, since channel "CD-01" has obtained... The system uses a time series prediction model to identify the transmission capacity trend of the channel based on its identification code. The system extracts the power transmission sampling time series values ​​of the channel over the past 5 minutes and applies an autoregressive moving average model (ARMA(p,q)) for fitting. It should be noted that the order (p,q) of the ARMA model is predetermined during the model training phase using the Akaike Information Criterion (AIC). Assume the final determined model is ARMA(2,1). The system inputs the latest time series data into the model to predict the power value 15 minutes ahead, generating a series of discrete time points and corresponding predicted power values. Connecting these points constitutes the predicted transmission trajectory of the channel. For example, the prediction results show that the transmission power of channel "CD-01" will steadily increase from the current 810MW to 880MW in 15 minutes.

[0077] In another implementation of this invention, it is assumed that another channel "EF-01" was affected by a previous disturbance. Furthermore, the system has already extracted high-confidence transmission state points for this purpose. In this case, the system will not perform time series prediction, but will instead initiate transient stability simulation. Using the high-confidence transmission state points as initial conditions, the system simulates the dynamic response of the power grid in the simulation model, thereby generating a more conservative and secure predicted transmission trajectory. The generated predicted transmission trajectory is then overlaid and compared with a pre-set spatial distribution map of the entire network's transmission capacity. It is important to note that this spatial distribution map is a GIS layer, which not only marks the geographical direction of each inter-regional transmission channel, but also draws contour lines representing 85% of its safe transmission capacity around each line.

[0078] In one implementation of this invention, the rated transmission capacity of channel "CD-01" is 1000MW, therefore the value corresponding to its 85% safe transmission capacity contour line is 850MW. The system overlays the predicted transmission trajectory of channel "CD-01" (increasing from 810MW to 880MW) onto the GIS map. Specifically, the system detects that the power value of the predicted transmission trajectory will cross the 850MW contour line in approximately 10 minutes. This means that the transmission capacity of the channel will exceed its safe threshold in the near future. Based on this comparison result, the system immediately filters out channel "CD-01" and officially marks its status as a "critical transmission channel".

[0079] Preferably, identifying the transmission capability trend of each channel based on stable transmission identification codes and high-reliability transmission status points and power transmission sampling timing values ​​includes:

[0080] The gradient of change within a preset sampling time window is calculated based on the power transmission sampling timing value, thereby obtaining the slope of the transmission capability trend;

[0081] The sign of the slope of the transmission capacity trend is analyzed to identify whether the transmission channel is increasing or decreasing the transmission power, as a trend of the channel relative to the load.

[0082] Cross-validation of grid frequency deviation is performed based on the relative load trend of the channel. If the changes of the two are consistent, a verified load vector is constructed based on the stable transmission identifier code.

[0083] Based on the verified load vector and the line load transmission vector, the predicted load status of each channel after the preset prediction time window is deduced;

[0084] The predicted transmission trajectory is predicted by linear interpolation based on the predicted load status and high-confidence transmission status points.

[0085] In this embodiment of the invention, the operation is performed on the inter-regional power transmission channel "GH-01" (connecting regions G and H) that has obtained a "stable transmission identification code". The system sets a preset sampling time window with a duration of 60 seconds. Specifically, the system extracts the starting point of the window from the power transmission sampling timing values ​​of the channel. ) and end point ( The power value of the transmission capacity is then calculated. Next, the gradient of change within this time window is calculated using a simple linear fit; this gradient is the slope of the transmission capacity trend. The calculation formula is:

[0086] ;

[0087] It should be noted that, It is the power value at the end of the window. It is the power value at the starting point. It is the length of the time window (60 seconds).

[0088] In one implementation of this invention, it is assumed that... At any given time, the power of channel "GH-01" For 1500MW; in Time, power The calculated transmission capacity trend slope is 1530MW. .

[0089] In one implementation of this invention, the sign of the transmission capacity trend slope is analyzed to determine the direction of load change in the channel. For example, if the calculated slope of 0.5 MW / s is positive, the system identifies the channel relative load trend of channel "GH-01" as "increasing load". If the calculated result is negative, it is identified as "decreasing load"; if it is close to zero, it is identified as "stable".

[0090] In this embodiment of the invention, grid frequency is introduced as a cross-validation metric. It is important to note that the operating pattern of the power grid is as follows: when the load increases, if the generator output fails to keep up, the system frequency tends to decrease; conversely, it increases. The system synchronously acquires the average grid frequency deviation data for regions G and H within the same time window from a wide-area measurement system (WAMS). Frequency deviation refers to the difference between the actual frequency and the nominal frequency (e.g., 50.00 Hz).

[0091] In one implementation of this invention, the system obtains that within a window from t0 to t0+60s, the average frequency deviation of region G (sender end) is -0.01Hz, and the average frequency deviation of region H (receiver end) is -0.02Hz. This indicates that the entire interconnection system is generally in a trend of load increase and frequency decrease. Specifically, the system performs cross-validation to determine if the change in the channel's relative load trend (increase) and the system's frequency deviation trend (decrease) are consistent. The judgment condition is met. The system then constructs a verified load vector based on the channel's "stable transmission identifier code." This vector is essentially a verified and reliable transmission capacity trend slope, with a value of 0.5MW / s.

[0092] In one implementation of this invention, the system extrapolates 10 minutes forward based on the line load transmission vector (with a magnitude of 1530MW) at the current time (t0+60s) and the verified load vector (0.5MW / s).

[0093] Predicted load status The calculation is as follows:

[0094] ;

[0095] in, This is the current power (1530MW). It is the verified slope (0.5MW / s). The predicted time window is 600 seconds. The calculation yields: 1530MW + 0.5MW / s × 600s = 1830MW. Therefore, the predicted load status of channel "GH-01" 10 minutes later is 1830MW.

[0096] In one implementation of this invention, for a channel like "GH-01" that has a stable transmission identification code, its predicted transmission trajectory is a straight line segment connecting the current state point (time t0+60s, power 1530MW) and the predicted load state point (time t0+60s+600s, power 1830MW).

[0097] In another implementation of this invention, suppose another channel "IJ-01" experienced a disturbance previously. Although it has now stabilized (obtaining a stable transmission identifier code), the system retains a high-confidence transmission state point for it (e.g., a stable operating point at a certain moment before the disturbance, with a power of 1450MW). In this case, the system considers the long-term trend of this channel to be more closely related to its historical stable operating level. Therefore, the predicted transmission trajectory will be a straight line connecting the current state point (1530MW) and the historical high-confidence transmission state point (1450MW), indicating that the system predicts the load of this channel will gradually return to its historical normal level, rather than continuously increasing.

[0098] Preferably, the scheduling decision module further includes the following functions:

[0099] For each transmission channel in the critical transmission channels, the range of intersection between its adjustable transmission capacity and the margin of the predicted transmission trajectory is calculated to obtain the adjustment depth index; where the adjustable transmission capacity is the range in the transmission channel where the transmission capacity is better than 90% of the rated capacity.

[0100] Based on the adjustment depth index, all transmission channels in the key transmission channels are arranged in descending order to form the preferred channel ranking;

[0101] Searching the pre-set spatial distribution map of the entire network transmission capacity, the optimal transmission channel in the preferred channel ranking is identified as the first main dispatch channel;

[0102] After determining the first primary dispatch channel, the second-best transmission channel in the preferred channel ranking is retrieved and identified, and is recorded as the second backup dispatch channel.

[0103] Obtain the dispatch center IDs of the first primary dispatch channel and the second backup dispatch channel;

[0104] The device identifiers of the first primary scheduling channel and the second backup scheduling channel are combined with the scheduling center ID, and an expected scheduling timestamp is appended to construct a dual scheduling channel strategy.

[0105] In this embodiment of the invention, it is assumed that three key transmission channels have been selected, namely "KL-01", "MN-01", and "OP-01". For each key transmission channel, its adjustment depth index is calculated. It should be noted that this index is used to quantify how much adjustment space the channel can provide while meeting high reliability requirements. In one implementation of this embodiment, channel "KL-01" is taken as an example. The rated transmission capacity of this channel is 2000MW. Determine the adjustable transmission capacity range: The adjustable transmission capacity is defined as the range in which the transmission capacity of the transmission channel is better than 90% of the rated capacity. Specifically, the lower limit of this range is 2000MW × 90% = 1800MW, and the upper limit is the rated capacity of 2000MW. Therefore, the adjustable range is [1800MW, 2000MW]. Obtain the predicted transmission trajectory: From the previous steps, the system obtains the predicted transmission trajectory of channel "KL-01". This trajectory shows that its power will linearly increase from the current 1750MW to 1900MW in the next 15 minutes. Calculating the margin intersection range: The system compares the predicted transmission trajectory [1750MW, 1900MW] with the adjustable transmission capacity range [1800MW, 2000MW] and calculates their intersection. The intersection range is [max(1750, 1800), min(1900, 2000)] = [1800MW, 1900MW]. The width of this intersection range is the adjustment depth index. Adjustment depth index = 1900MW - 1800MW = 100MW.

[0106] In another implementation of this invention, the system also performs the same calculations for two other key channels, "MN-01" and "OP-01". Assuming the predicted trajectory of channel "MN-01" (rated capacity 3000MW) will increase from 2600MW to 2800MW, with an adjustable range of [2700MW, 3000MW], the calculated adjustment depth index is 2800MW - 2700MW = 100MW. Similarly, the predicted trajectory of channel "OP-01" (rated capacity 2500MW) will increase from 2200MW to 2400MW, with an adjustable range of [2250MW, 2500MW], and the calculated adjustment depth index is 2400MW - 2250MW = 150MW.

[0107] In one implementation of this invention, all critical transmission channels are ranked in descending order based on the calculated regulation depth index. Specifically, the regulation depth indices for the three channels are as follows: Channel "OP-01": 150MW; Channel "KL-01": 100MW; Channel "MN-01": 100MW. It should be noted that when the indices are the same, the system will perform a secondary ranking based on the channel's rated capacity, prioritizing those with larger capacities. Therefore, the final preferred channel ranking is: "OP-01" > "MN-01" > "KL-01".

[0108] In this embodiment of the invention, in a preset spatial distribution map of the entire network transmission capacity, primary and backup scheduling channels are identified according to the preferred channel ranking. The GIS layers are retrieved, and the layer "OP-01," which ranks first in the preferred channel ranking, is highlighted with a specific color, and its attribute label is written as "First Primary Scheduling Channel." Subsequently, the system retrieves again, setting the layer "MN-01," which ranks second in the ranking, to the next most highlighted color, and labeling it "Second Backup Scheduling Channel."

[0109] In this embodiment of the invention, the dispatch center ID is obtained as follows: The system queries the power grid asset database to obtain the dispatch center IDs connected to both ends of "OP-01" and "MN-01". Assume the query results are: channel "OP-01" connects to dispatch center O (ID: O-DCC) and dispatch center P (ID: P-DCC); channel "MN-01" connects to dispatch center M (ID: M-DCC) and dispatch center N (ID: N-DCC). Information combination and encapsulation: The system combines the device identifiers (i.e., channel IDs) of the primary and backup channels with their corresponding dispatch center IDs. Simultaneously, the system generates an estimated dispatch timestamp. It should be noted that this timestamp is determined based on the predicted time point when the transmission trajectory crosses the safety threshold, with an added safety lead time (e.g., 5 minutes). Assuming "OP-01" is expected to cross the threshold at 15:30:00, the estimated dispatch timestamp is set to 15:25:00.

[0110] Preferably, the supply and demand monitoring module includes the following functions:

[0111] Real-time active and reactive power data of each area are collected using smart meters in substations.

[0112] Based on the collected real-time active and reactive power data of each region, the regional power supply capacity and regional power demand are calculated, and regional power supply capacity data and regional power demand data are obtained respectively.

[0113] The current supply and demand balance of each region is determined based on regional power supply capacity data and regional electricity demand data.

[0114] In this embodiment of the invention, a periodic data collection task is issued to the smart meters at the upstream gateway points of all power plants and the tie-line gateway points connecting to the external power grid within the Q area power grid via a data acquisition front-end unit of the scheduling data network. It should be noted that the period of this collection task is set to 5 seconds to ensure data real-time performance. For example, at time... The system collected real-time active and reactive power data from all relevant smart meters in the Q area.

[0115] In one implementation of this invention, the total power supply capacity and total power demand of region Q are calculated based on the collected real-time power data. Specifically, the regional power supply capacity is equal to the sum of the total on-grid active power of all generator units in the region and the active power input from all tie lines.

[0116] The calculation model is as follows: ;

[0117] It is important to note that To meet regional electricity demand, It refers to the grid connection power of generator sets within the region. This refers to the power input from the external area via the tie line, and its sign is defined as positive. If the tie line supplies power to other areas, its power value is negative and is not included in the supply capacity.

[0118] Regional electricity demand ( Specifically, the regional electricity demand is calculated as the total active power consumed by all loads within the region. It should be noted that in real-world systems, load data is often not fully obtainable through metering; therefore, an estimation method based on "generation + net tie-line input - network losses" is used. For simplicity, it is assumed that all major load points are metered. The calculation model is as follows:

[0119] ;

[0120] in, This represents the active power consumed by all loads within the region. The electricity demand for region Q is calculated based on the collected data, and the result is recorded as regional electricity demand data.

[0121] In one implementation of this invention, the supply-demand balance is a dimensionless indicator used to intuitively reflect the degree of matching between electricity supply and demand within a region. Its calculation model is as follows:

[0122] ;

[0123] When the ratio is equal to 1, it indicates that supply and demand are perfectly balanced; a value greater than 1 indicates that supply exceeds demand and there is a surplus of electricity; a value less than 1 indicates that supply falls short of demand and there is a power shortage.

[0124] In one implementation of this invention, the current supply-demand balance of region Q is calculated, assuming it to be 1.042. Since the calculated supply-demand balance of 1.042 is greater than 1, the system determines that region Q is currently in a state of power surplus. This balance value will be continuously updated and will serve as one of the core bases for subsequently determining whether cross-regional dispatch needs to be initiated. If the balance calculation result of another region S is 0.95, the system will identify region Q as a potential sending end and region S as a potential receiving end.

[0125] Preferably, after determining the current supply and demand balance in each region, the process also includes constructing a power dispatch execution plan:

[0126] Identify the substations that have the first primary scheduling channel and the second backup scheduling channel in the dual scheduling channel strategy, and initiate a scheduling resource reservation request to the intelligent control terminal in the substation.

[0127] After the intelligent control terminal checks its own equipment status and channel margin, if the reservation conditions are met, it returns a resource reservation confirmation receipt containing the equipment ready status code and the current timestamp.

[0128] Based on the current supply and demand balance in each region, the absolute value of the supply and demand difference in the region with the largest power deficit will be used as the target power for this dispatch.

[0129] Based on the resource reservation confirmation receipt, the target power for this scheduling is decomposed into a time-sequential control sequence with adjustment rate and execution time steps;

[0130] Extract the grid frequency and voltage phase angle from the current first primary scheduling channel and second backup scheduling channel as dynamic salt values, and perform a hash operation on the dynamic salt value and the core identifier of the dual scheduling channel strategy to generate a dynamic scheduling execution key;

[0131] By binding and encapsulating time-sequential control sequences with dynamic scheduling execution keys, a power dispatch execution scheme is constructed.

[0132] In one implementation of this invention, the parsing strategy "YZ-DCS-002" identifies substations C and D at both ends of the main dispatch channel "YZ-01". The system then initiates a dispatch resource reservation request to the intelligent control terminals (e.g., station domain control systems or PMU-built-in computing units) within these two substations. Upon receiving the request, the intelligent control terminal of substation C immediately executes a self-check procedure. It should be noted that this procedure checks the real-time operating status of its managed STATCOM equipment (e.g., no alarms currently), whether the cooling system is functioning properly, and calculates its currently available reactive power adjustment range.

[0133] In one implementation of this invention, the supply-demand balance of region Y is 1.06, and that of region Z is 0.92, obtained from the supply-demand monitoring module. Region Z is the region with the largest power deficit. It should be noted that the absolute value of the supply-demand difference in region Z is obtained as follows: Supply-demand difference = |Regional power supply capacity - Regional power demand|. Assuming the power supply capacity of region Z is 18400MW and the power demand is 20000MW, then the absolute value of the supply-demand difference is |18400 - 20000| = 1600MW. The system determines this 1600MW as the target power for this dispatch.

[0134] In one implementation of this invention, the decomposition result is a time-stepped control sequence: 0-1 minute: The STATCOM of substation C is instructed to output 50Mvar capacitive reactive power to increase voltage, indirectly increasing transmission capacity by approximately 100MW. 1-5 minutes: The fast-response units (such as gas turbine units) in area Y are instructed to increase active power generation by 800MW. 5-15 minutes: The conventional thermal power units in area Y are instructed to smoothly increase the remaining 700MW of power generation. This set of instructions, including time, equipment, actions, and parameters, is constructed into a time-sequential control sequence.

[0135] In one implementation of this invention, while generating the control sequence, the system collects real-time power grid status parameters at both ends of the main dispatch channel "YZ-01" via WAMS: the bus frequency of substation C: =49.98Hz; Bus voltage phase angle of substation D: The system converts these real-time floating-point numbers into strings of specific precision (e.g., 4998 and -152), and concatenates them with the core identifier YZ-DCS-002 of the dual-scheduling channel strategy to form a dynamic salt value. The system then applies the SHA-256 hash algorithm to the dynamic salt value.

[0136] In this embodiment of the invention, an encrypted container is created, using the time-series control sequence as the plaintext payload and the dynamic scheduling execution key as the content encryption key to encrypt the payload. The header of the encrypted container also includes metadata such as policy ID and timestamp.

[0137] It should be noted that the time-sequential control sequence includes the main dispatch sequence and the backup dispatch sequence; the power dispatch execution scheme can only be activated and executed when the key matches the field key calculated in real time at the receiving end.

[0138] Of particular importance, the issuance of timing-based control sequence instructions also includes:

[0139] Within the preset first timing window, a power compensation device switching command is generated and issued to establish a power angle stability margin.

[0140] Within the preset second timing window, a transformer tap adjustment command is issued to optimize the voltage distribution of the channel;

[0141] Within the preset third time window, the generator set active power output adjustment command is issued to perform cross-regional power redistribution;

[0142] After each instruction is executed, the scheduling execution status is checked in real time. If the execution deviation exceeds the preset range, a rollback operation is performed.

[0143] In this embodiment of the invention, the preset first timing window has a time range of 0 to 30 seconds after the scheduling is initiated. The goal of this stage is to rapidly improve the voltage stability and transient power angle stability margin of the transmission channel.

[0144] In this embodiment of the invention, the system enters a preset second timing window, ranging from 30 seconds to 2 minutes after scheduling is initiated. This stage aims to finely adjust the voltage distribution along the channel and reduce line losses.

[0145] In this embodiment of the invention, the system enters the core power transfer phase, which is the preset third timing window, with a time range of 2 to 15 minutes after the scheduling is started.

[0146] In one implementation of this invention, assuming that during the second step of transformer voltage adjustment, the voltage at substation B drops instead of rising after the command is issued, exceeding the preset range, the system immediately determines that the execution deviation exceeds the limit and triggers a rollback operation.

[0147] The specific operations are as follows: Immediate Abort: The system sends an abort signal to any subsequent unexecuted instructions (such as instructions in the third time-sequence window). Perform Reverse Operation: The system generates and issues a reverse instruction: {Target: B-TR-01, Action: TapDown, Value: 1, Timestamp: Immediately}, to attempt to restore the transformer tap to its original position. Status Lock and Alarm: The system marks the status of channel "AB-01" and related equipment as "Dispatch Abnormal - Locked" and pushes a high-priority alarm to the dispatcher's workstation, including: "Dispatch of channel AB-01 failed, rollback has been initiated, please intervene manually."

[0148] Most importantly, following the power dispatch execution plan, it also includes:

[0149] The first primary dispatch request is triggered according to the power dispatch execution plan;

[0150] After receiving confirmation of the first master scheduling request, the scheduling status is determined to be that the master channel is normal;

[0151] When the validity period of the first primary dispatch request in the power dispatch execution plan expires, the dispatch of the first primary channel is determined to have failed, and a dispatch failure flag is generated.

[0152] After the dispatch failure flag is generated, a switching procedure is triggered to the second backup dispatch channel in the power dispatch execution plan, and a second backup dispatch request is issued;

[0153] Upon receiving the second backup scheduling request, a second scheduling confirmation is returned;

[0154] Upon receiving confirmation from the second dispatch center, the system automatically triggers power control commands to adjust the transmission of active power between regions.

[0155] In this embodiment of the invention, the system encapsulates this information into a "control block enable" request conforming to IEC61850MMS (Manufacturing Message Specification) and simultaneously sends it to the intelligent electronic devices (IEDs) of substations P and Q at both ends of the main dispatch channel "PQ-01". This request is the first main dispatch request.

[0156] In one implementation of this invention, within 5 seconds of receiving a request, the IEDs of substations P and Q successfully reconstruct the dynamic scheduling execution key using locally acquired real-time power grid status parameters (frequency, phase angle) and decrypt the time-sequential control sequence.

[0157] In another implementation of this invention, it is assumed that the IED of substation P returned an acknowledgment normally, but due to momentary congestion in the communication network, the acknowledgment message of substation Q failed to reach the main system within the 30-second validity period. When the clock reaches the 31st second, the response timeout timer inside the main system triggers an interrupt.

[0158] In one implementation of this invention, the same method is used to encapsulate the information of the backup channel into a new MMS request, which is then sent to the IEDs of substations R and S at both ends of the backup channel "PQ-02". This request is the second backup scheduling request. This request also includes a new 30-second timeout timer. After receiving the second backup scheduling request, key reconstruction, instruction decryption, and legality verification are successfully completed at 3 seconds and 4 seconds, respectively. The backup channel scheduling status is determined to be "backup channel normal". Upon confirmation of this status, the system immediately and automatically triggers the execution of power control instructions.

[0159] Preferably, after determining the current supply and demand balance in each region, the process also includes power supply and demand balance dispatching decisions:

[0160] Continuously monitor the current supply and demand balance in each region and the transmission utilization rate of the target scheduling channel in the dual-channel scheduling plan to obtain real-time supply and demand balance.

[0161] Based on the real-time supply and demand balance, determine the imbalance source region, adjustment target region, and execution voucher pending scheduling group in the cross-regional transmission network;

[0162] Determine whether the current supply and demand balance in the decision-making scheduling group is less than 0.85, and whether the transmission utilization rate of the target scheduling channel in the dual scheduling channel strategy is less than 60%; if so, the scheduling trigger condition is determined to be met, and a scheduling start command is generated; if not, the supply and demand status of each region is continuously monitored.

[0163] Power supply and demand balance dispatch control is triggered by a dual dispatch channel strategy based on the dispatch start command.

[0164] In this embodiment of the invention, the system enters a continuous monitoring mode, performing the following two operations simultaneously at 5-second intervals: It calls the supply and demand monitoring module to obtain the current supply and demand balance of regions T and U; and it calls the scheduling decision module to obtain the real-time transmission utilization rate of channel "TU-01".

[0165] In one implementation of this invention, at time... The system obtained a set of real-time data: the current supply and demand balance in region T. (Electricity surplus); Current supply and demand balance in region U: 0.84 (Power shortage); Real-time transmission utilization of the "TU-01" channel: 55%; the system combines these related data into a real-time supply and demand balance pair.

[0166] In this embodiment of the invention, the supply and demand balance of all regions is traversed to find the minimum value. It is found that the balance of region U, at 0.84, is the lowest among all monitored regions, thus region U is identified as the source of imbalance (i.e., the region with the most severe power shortage). Subsequently, the system searches for the region with the highest balance and a direct transmission channel to region U. The system finds that region T has the highest balance of 1.05 and is connected to region U through the "TU-01" channel, thus region T is identified as the target region for regulation (i.e., the region providing power support). Simultaneously, the system extracts core information related to this scheduling from the dual-channel scheduling strategy "TU-DCS-001" as the basis for the execution credential. These three elements—the source of imbalance (U), the target region for regulation (T), and the execution credential (TU-DCS-001)—together constitute a scheduling group to be decided.

[0167] In this embodiment of the invention, a dual-condition logical judgment is performed for the scheduling group to be decided. It should be noted that these two conditions aim to ensure that scheduling is both necessary (due to severe imbalance) and feasible (due to sufficient transmission channel margin). Condition 1 (Imbalance Severity): Whether the current supply-demand balance of the imbalance source region is less than a preset severe imbalance threshold of 0.85. Condition 2 (Channel Redundancy): Whether the transmission utilization rate of the target scheduling channel is less than a preset channel redundancy threshold of 60%.

[0168] In one implementation of this invention, the system substitutes real-time data into the judgment logic: Judgment condition one: This condition is met. Judgment condition two: This condition is also met. Since both conditions are met, the system determines that the scheduling trigger condition is met.

[0169] In another implementation of the present invention, it is assumed that at another moment... The supply and demand balance in region U is 0.86, and the channel utilization rate is 58%. At this time, since 0.86 is not less than 0.85, condition one is not met. Even if there is channel redundancy, the system will not trigger scheduling, but will continue to return to monitoring. This mechanism avoids overreaction to slight fluctuations.

[0170] In this embodiment of the invention, after determining that the scheduling trigger condition is met, the system immediately generates a structured scheduling start instruction. The system broadcasts this scheduling start instruction to the system's scheduling execution module. Upon receiving the instruction, the module will, based on the instructions... (i.e., "TU-DCS-001") is used to analyze the dual-channel dispatch strategy and initiate the specific power supply and demand balance dispatch control process.

[0171] Preferably, calculating the transmission capacity of power transmission channels in a cross-regional topology further includes:

[0172] Identify the types of transmission lines in cross-regional topologies; these types include overhead lines, cable lines, and hybrid line types.

[0173] Based on the type of transmission line, obtain the corresponding electrical parameters of the transmission channel in the cross-regional topology; among which, the channel electrical parameters include line resistance value, line reactance value and conductor current carrying capacity;

[0174] Calculate the transmission capacity of the power transmission channel based on its electrical parameters.

[0175] In this embodiment of the invention, the power grid asset management database is accessed, and the channel identifier "VW-01" is used as a query index to retrieve the line type information of the channel. For example, the records returned by the database indicate that the line type of channel "VW-01" is "overhead line". Suppose that the record of another channel "XY-01" shows that it contains a section of submarine cable and a section of onshore overhead line, the system will identify it as a "mixed line type".

[0176] In one implementation of this invention, for channel "VW-01" identified as an "overhead line", the system needs to obtain the following three core parameters: line resistance value ( Line reactance value () ); conductor current carrying capacity ( The parameters for channel "VW-01" obtained from the query are as follows: Conductor type: ACSR-720 / 50 (a type of steel-cored aluminum stranded wire); Total line length: 350km; Resistance per unit length: 0.042Ω / km; Reactance per unit length: 0.410Ω / km; Long-term allowable current carrying capacity of the conductor: 1500A (this value is calculated from the conductor type and preset environmental conditions, such as ambient temperature 25℃ and wind speed 0.5m / s, through the heat balance equation and stored in the database); Based on the unit length parameters and the total length, the total resistance and total reactance of the line are calculated. For example, the line resistance value... Line reactance value ( =0.410Ω / km × 350km = 143.5Ω; Conductor current carrying capacity ( =1500A.

[0177] In one implementation of this invention, the final transmission capacity is calculated by comprehensively considering two main physical constraints based on the acquired channel electrical parameters.

[0178] Calculation of thermal stability limit capacity based on conductor current carrying capacity It should be noted that this is the upper limit of transmission determined by the heating effect of the conductor, to ensure that the conductor will not be damaged or excessively sag due to overheating.

[0179] Calculation of static stability limit capacity based on line reactance ( It should be noted that this is the upper limit of transmission determined by the system's ability to maintain synchronous and stable operation, in order to prevent system collapse due to power angle instability.

[0180] The two calculated limit values ​​are compared, and the minimum value is taken as the final transmission capacity of the transmission channel. The specific operation is as follows: Transmission Capacity .

[0181] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0182] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A cross-regional power supply and demand balance dispatching and control system, characterized in that, Includes the following modules: The power grid topology modeling module is used to perform regional boundary scanning on the target cross-regional power grid, calculate the transmission capacity of each transmission channel, and use the transmission capacity as the connection weight value to construct a cross-regional transmission network that reflects the current physical structure of the power grid. The scheduling decision module is used to synchronously collect and analyze the power parameters of the transmission channels to identify transmission anomalies and predict the transmission capacity trend of each channel, thereby selecting key transmission channels from the cross-regional transmission network. Specifically, it synchronously collects the power parameters of the transmission lines in the substations; the power parameters of the channels include voltage, current and power parameters. The three-dimensional spatial coordinates of the transmission lines are extracted based on the target cross-regional power grid, and the line load transmission vector is calculated based on the channel operating power parameters. Based on the line load transmission vector, the trend analysis and verification of the line load transmission vector within the preset sampling time window are continuously performed to identify transmission channels with abnormal transmission. High-reliability transmission status points are extracted from cross-regional transmission networks based on transmission channels that identify transmission anomalies. Collect power transmission sampling timing values ​​of each transmission channel in the cross-regional transmission network; Key transmission channels are selected based on line load transmission vectors, high-reliability transmission status points, and power transmission sampling time series values. Based on this, a dual-schedule channel strategy is constructed, including: for each key transmission channel, the range of intersection between its adjustable transmission capacity and the margin of the predicted transmission trajectory is calculated to obtain the adjustment depth index; where the adjustable transmission capacity is the range in the transmission channel where the transmission capacity is better than 90% of the rated capacity. Based on the adjustment depth index, all transmission channels in the key transmission channels are arranged in descending order to form the preferred channel ranking; Searching the pre-set spatial distribution map of the entire network transmission capacity, the optimal transmission channel in the preferred channel ranking is identified as the first main dispatch channel; After determining the first primary dispatch channel, the second-best transmission channel in the preferred channel ranking is retrieved and identified, and is recorded as the second backup dispatch channel. Obtain the dispatch center IDs of the first primary dispatch channel and the second backup dispatch channel; The device identifiers of the first primary scheduling channel and the second backup scheduling channel are combined with the scheduling center ID, and an expected scheduling timestamp is appended to construct a dual scheduling channel strategy. The supply and demand monitoring module is used to calculate the current supply and demand balance of each region in real time, and combined with the transmission utilization rate of the target dispatch channel in the dual dispatch channel strategy, it determines the dispatch triggering time based on the preset imbalance and redundancy conditions, and generates a dispatch start command; the dispatch start command is used to trigger the power supply and demand balance dispatch control. The scheduling evaluation and optimization module is used to continuously monitor the transmission utilization rate of key transmission channels and the regional supply and demand balance after the scheduling start command is executed, and to evaluate the execution effect of this scheduling.

2. The cross-regional power supply and demand balance dispatching and control system according to claim 1, characterized in that, The power grid topology modeling module includes the following functions: Perform regional boundary scanning on the target cross-regional power grid to identify the transmission line connection points between different regions; The geographical locations of each transmission channel are marked according to the connection points of the transmission lines, and the channel lengths are measured at the same time; Regional topology connections are made based on geographical location and channel length to obtain a cross-regional topology structure; The transmission capacity of the transmission channels in the cross-regional topology is calculated, and the transmission capacity is used as the connection weight value of the cross-regional topology to construct the cross-regional transmission network.

3. The cross-regional power supply and demand balance dispatching and control system according to claim 1, characterized in that, Key transmission channels were selected based on line load transmission vectors, high-reliability transmission status points, and power transmission sampling time series values, including: Calculate the variance of the line load transmission vector within the preset sampling time window, and denote this variance as the channel transmission stability. Determine whether the channel transmission stability is less than the preset stability threshold; if so, generate a stable transmission identifier code. Based on stable transmission identification codes and high-reliability transmission status points and power transmission sampling timing values, the transmission capability trend of each channel is identified as a predictive transmission trajectory. Based on the pre-set spatial distribution map of the entire network transmission capacity, the predicted transmission trajectory is compared and superimposed with the load to screen out the transmission channels whose transmission capacity will exceed the 85% safety threshold, thus forming the key transmission channels; the pre-set spatial distribution map of the entire network transmission capacity is marked with the geographical location of each transmission channel and the contour line of 85% safe transmission capacity.

4. The cross-regional power supply and demand balance dispatching and control system according to claim 3, characterized in that, Identifying the transmission capability trend of each channel based on stable transmission identification codes, high-reliability transmission status points, and power transmission sampling timing values ​​includes: The gradient of change within a preset sampling time window is calculated based on the power transmission sampling timing value, thereby obtaining the slope of the transmission capability trend; The sign of the slope of the transmission capacity trend is analyzed to identify whether the transmission channel is increasing or decreasing its transmission power, as a reflection of the channel's relative load trend. Cross-validation of grid frequency deviation is performed based on the relative load trend of the channel. If the changes of the two are consistent, a verified load vector is constructed based on the stable transmission identifier code. Based on the verified load vector and the line load transmission vector, the predicted load status of each channel after the preset prediction time window is deduced; The predicted transmission trajectory is predicted by linear interpolation based on the predicted load status and high-confidence transmission status points.

5. The cross-regional power supply and demand balance dispatching and control system according to claim 1, characterized in that, The supply and demand monitoring module includes the following functions: Real-time active and reactive power data of each area are collected using smart meters in substations. Based on the collected real-time active and reactive power data of each region, the regional power supply capacity and regional power demand are calculated, and regional power supply capacity data and regional power demand data are obtained respectively. The current supply and demand balance of each region is determined based on regional power supply capacity data and regional electricity demand data.

6. The cross-regional power supply and demand balance dispatching and control system according to claim 5, characterized in that, After determining the current supply and demand balance in each region, the process also includes constructing a power dispatch execution plan: Identify the substations that have the first primary scheduling channel and the second backup scheduling channel in the dual scheduling channel strategy, and initiate a scheduling resource reservation request to the intelligent control terminal in the substation. After the intelligent control terminal checks its own equipment status and channel margin, if the reservation conditions are met, it returns a resource reservation confirmation receipt containing the equipment ready status code and the current timestamp. Based on the current supply and demand balance in each region, the absolute value of the supply and demand difference in the region with the largest power deficit will be used as the target power for this dispatch. Based on the resource reservation confirmation receipt, the target power for this scheduling is decomposed into a time-sequential control sequence with adjustment rate and execution time steps; Extract the grid frequency and voltage phase angle from the current first primary scheduling channel and second backup scheduling channel as dynamic salt values, and perform a hash operation on the dynamic salt value and the core identifier of the dual scheduling channel strategy to generate a dynamic scheduling execution key; By binding and encapsulating time-sequential control sequences with dynamic scheduling execution keys, a power dispatch execution scheme is constructed.

7. The cross-regional power supply and demand balance dispatching and control system according to claim 6, characterized in that, After determining the current supply and demand balance in each region, the next step is to make decisions on power supply and demand balance scheduling: Continuously monitor the current supply and demand balance in each region and the transmission utilization rate of the target scheduling channel in the dual-channel scheduling plan to obtain real-time supply and demand balance. Based on the real-time supply and demand balance, determine the imbalance source region, adjustment target region, and execution voucher pending scheduling group in the cross-regional transmission network; Determine whether the current supply and demand balance in the decision-making scheduling group is less than 0.85, and whether the transmission utilization rate of the target scheduling channel in the dual scheduling channel strategy is less than 60%; if so, the scheduling trigger condition is determined to be met, and a scheduling start command is generated; if not, the supply and demand status of each region is continuously monitored. Power supply and demand balance dispatch control is triggered by a dual dispatch channel strategy based on the dispatch start command.

8. The cross-regional power supply and demand balance dispatching and control system according to claim 2, characterized in that, Calculating the transmission capacity of power transmission channels in inter-regional topologies also includes: Identify the types of transmission lines in cross-regional topologies; these types include overhead lines, cable lines, and hybrid line types. Based on the type of transmission line, obtain the corresponding electrical parameters of the transmission channel in the cross-regional topology; among which, the channel electrical parameters include line resistance value, line reactance value and conductor current carrying capacity; Calculate the transmission capacity of the power transmission channel based on its electrical parameters.

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