Frequency stabilization emergency load shedding system and method based on rapid disturbance position identification

Abstract

The invention discloses a frequency stabilization emergency load shedding system based on rapid disturbance position identification, and the system comprises a frequency stability control measure total amount generation module which is used for reading the state information and frequency response data of a power system, identifying a system frequency response model, and calculating the stability control measure total amount meeting the frequency stability requirement; the frequency control sensitive point mining module is used for taking the key bus frequency time sequence data of the power system as the input and taking the load shedding position near the disturbance position as the output of the frequency stability control sensitive point mining network; the frequency stability control measure generation module is used for reading the stability control measure total amount which is calculated by the frequency stability control measure total amount generation module and meets the system frequency stability requirement and the sensitivity sequence of each control position output by the frequency control sensitive point mining module; when the power system is disturbed, corresponding emergency load shedding measures are made to recover the system frequency to a safe range.

Description

Technical Field

[0001] This invention relates to the field of power system frequency control technology, and more specifically, to a frequency stability emergency load shedding system and method based on rapid identification of disturbance location. Background Technology

[0002] As the proportion of renewable energy output continues to increase, the complexity and uncertainty of power grid operation will continue to rise. The complexity and variability of operating modes, the uncertainty of disturbances and faults, the weak immunity of power electronic equipment, and the high degree of control freedom make system-level stability control more difficult, posing a significant challenge to ensuring the safe and efficient operation of ultra-large AC / DC hybrid power grids. Driven by energy transition and technological progress, a high proportion of renewable energy and a high proportion of power electronic equipment are becoming important trends and key characteristics of power system development. The replacement of numerous synchronous generator units by renewable energy, characterized by volatility and randomness, leads to a decrease in system inertia and sudden large power shortages. This not only causes frequency fluctuations but may also cause large-scale shifts in AC power flow. Inappropriate control measures can severely deteriorate the system's safety status and even lead to system collapse. Therefore, rapid corrective or emergency control measures must be taken to eliminate abnormal operating conditions in the power system.

[0003] Following a severe fault, partially shedding load as needed has always been a key research focus in power system security defense. How to minimize load shedding under grid disturbances has become a major concern for grid planners and dispatchers. Correction measures for severe active power deficits include emergency load shedding as the second line of defense and low-frequency, low-voltage load reduction as the third line of defense. Load shedding requires coordinating implementation effectiveness with economic costs, essentially a nonlinear programming problem. How to implement reasonable load shedding measures to restore the frequency to the normal operating range is a pressing research issue. Therefore, the frequency stabilization emergency load shedding method based on rapid disturbance location identification has significant advantages in frequency stabilization control of today's complex power grids, as a control means that can balance control effectiveness and economy.

[0004] Currently, strategy-based pre-planned control is the most mature, lowest-cost, and most difficult-to-apply emergency control system, and it is widely used in the second line of defense of power systems. By taking necessary safety and stability control measures such as generator tripping and load shedding, it prevents the system from losing stability. However, this method involves hypothetical faults and pre-decision-making processes, which are difficult to cover all fault types in AC / DC hybrid power grids and carry the risk of decision-making errors. Fault-matching stability control measures cannot guarantee the safe operation of the power grid under complex unforeseen fault conditions. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a frequency stabilization emergency load shedding system and method based on rapid disturbance location identification. It demonstrates that, under the same frequency stabilization control measures and control action time, the closer the electrical distance between the location implementing the control measures and the disturbance location, the more beneficial it is to system frequency stabilization. This improves the accuracy of control strategies when power systems experience disturbances, reduces the control strategy time of power systems, and enhances frequency security and stability under complex power systems.

[0006] The frequency stabilization emergency load shedding system based on rapid disturbance location identification proposed in this invention includes:

[0007] The frequency stabilization measures total quantity generation module is used to read power system status information and frequency response data, identify the system frequency response model, and calculate the total quantity of stabilization control measures that meet the frequency stability requirements.

[0008] The frequency control sensitive point mining module, for simplified multi-zone equivalent systems, combines the power allocation principle after system disturbance, frequency response model and frequency distribution law in the network, and proposes system frequency analytical model after implementing stabilization control measures at different locations after system disturbance, to obtain the theoretical optimal emergency load shedding location, and thus obtain the frequency stability control sensitive point.

[0009] The frequency stabilization measures generation module is used to read the total amount of stabilization control measures that meet the system frequency stability requirements calculated by the total amount of frequency stabilization control measures generation module, as well as the theoretical optimal load shedding position obtained from the system frequency analytical model after implementing stabilization control measures at different locations after the proposed system is disturbed. When the power system is disturbed, corresponding emergency load shedding measures are formulated to restore the system frequency to a safe range.

[0010] The power system status information and frequency response data include the system equivalent inertia, the primary frequency regulation aggregation parameters of each generating unit, and the system inertia center frequency, respectively. The system equivalent inertia is obtained through the aggregation calculation of the inertia of each operating component, such as the inertia time constant of a synchronous generator. If the component inertia cannot be obtained through model parameters, a data-driven inertia evaluation method is used to obtain the component inertia. For the primary frequency regulation aggregation parameters, a detailed frequency regulation model is established based on the actual operating generating units with primary frequency regulation functions. The aggregation parameters are determined by reducing the overall order of the detailed model.

[0011] The sensitivity is a parameter that measures the response of the power system to different load shedding measures, and is quantified according to the magnitude of the increase in the minimum point of the system inertia center frequency under the same load shedding amount and different load shedding positions.

[0012] The system frequency stability requirement is that the system inertia center frequency is not lower than a certain value, which is set to meet the system frequency stability requirement if the system inertia center frequency is not lower than 49.2Hz.

[0013] To address the aforementioned problems, this invention proposes a frequency stability emergency load shedding control method based on rapid disturbance location identification, comprising:

[0014] Step 1: Determine the frequency response model parameters including the stability control module, including the system equivalent inertia and the primary frequency regulation parameters of each unit;

[0015] Step 2: Obtain the power disturbance of the system based on the frequency change rate. Use the system disturbance and load shedding as inputs to the frequency response model, and the lowest frequency point as the output of the frequency response model. Obtain the minimum load shedding amount that meets the system frequency stability requirements through iterative calculation.

[0016] Step 3: Divide the power system into system partitions based on the correlation of electrical distance, select important bus nodes of each partition as observation nodes and several load shedding locations as load shedding sorting locations, extract the bus frequency time series data when the power system is disturbed as network input and each disturbance location as network output, and use it to construct a frequency control sensitive point mining dataset.

[0017] Step 4: Construct a CNN-based power system fault location fast identification model, namely a frequency control sensitive point mining model, and use the offline generated frequency control sensitive point mining dataset for network training.

[0018] Step 5: Input the key bus frequency time series data after the disturbance occurs into the frequency control sensitive point mining model, output the nearest load shedding control position for each disturbance location in the current scenario, and output the theoretical optimal load shedding position;

[0019] Step 6: Using the obtained load shedding amount that meets the system frequency stability requirements and the nearest load shedding control position at each disturbance location in the current scenario, formulate and generate control measures, and send the output instructions to the power system for execution, so that the system can provide corresponding load shedding measures online for different operating conditions to keep the system stable.

[0020] Beneficial effects

[0021] This invention uses frequency response models and CNNs as the decision-making body and the actual power system as the environment. By extracting bus frequency data from the power system node model, it identifies the frequency response model, calculates the load shedding amount that meets the system frequency stability requirements under the current operating conditions, and formulates corresponding frequency stability control measures. It can accurately and practically provide corresponding load shedding measures when the power system experiences disturbances, so that the system frequency can be restored to a safe range. Attached Figure Description

[0022] The accompanying drawings illustrate exemplary embodiments of the present disclosure and, together with their description, serve to explain the principles, including providing a further understanding of the disclosure. The drawings are included in and form part of this specification.

[0023] Figure 1 This is a flowchart of the frequency stabilization emergency load shedding method based on rapid identification of disturbance location proposed in this invention;

[0024] Figure 2 This is a schematic diagram of the three-zone system described in this invention;

[0025] Figure 3 This is the impedance diagram of the three-zone system described in this invention;

[0026] Figure 4 The example demonstration uses the CEPRI-LF node system as a computational example.

[0027] Figure 5 It is a heatmap of the test set fault location prediction ranking and the actual ranking;

[0028] Figure 6 This example demonstrates the power system frequency recovery curve under the frequency stability emergency load shedding method based on rapid identification of disturbance locations proposed in this invention. Detailed Implementation

[0029] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, this invention is not limited to the following embodiments, and specific implementation methods can be determined according to the technical solutions of this invention and actual circumstances. To avoid obscuring the essence of this invention, well-known methods, processes, flows, components, and circuits are not described in detail.

[0030] A flowchart of a frequency stabilization emergency load shedding method based on rapid disturbance location identification is shown below. Figure 1 As shown, it includes:

[0031] 1. The expression for the frequency response model containing stability control measures: The system frequency response model uses an equivalent single machine to describe the dynamic response process of the power grid's inertial center frequency after the system suffers a large-scale power disturbance. It features single-machine, low-order, and linear characteristics. The frequency response model is widely used in the analysis of frequency characteristics during system transient processes to support frequency stability analysis and control decisions. The expression for the frequency response model containing stability control measures is as follows:

[0032]

[0033] In the formula: α, ω n ω rΦ are the calculation parameters; R and K are the model parameters, and K can be expressed as (K m +DR); F can be represented as T R (K m F H +DR), where D is the generator equivalent damping coefficient; Hsys is the system equivalent inertia; K m R is the mechanical power gain coefficient; F is the equivalent droop coefficient; H The equivalent high-pressure cylinder power ratio; T R ΔP is the equivalent reheat time constant; dist The active power disturbance that causes the frequency response; ΔP shed and Δt shed These represent the quantity of stabilization and control measures and the duration of their implementation; ΔP dist The active power disturbance that causes the frequency response.

[0034] 2. Proof of the theoretically optimal nearest emergency load shedding method: Based on frequency divider theory, a method is established as follows... Figure 2 The three-zone system shown is taken as the research object, and its system impedance diagram is as follows: Figure 3 As shown. At a certain moment, the load in region k suddenly increases by ΔP. L After Δt shed Emergency load shedding ΔP in the region shed Based on the initial distribution law of the disturbance power and the system frequency response model, the minimum frequency of bus k and the time to reach the minimum point are calculated using the frequency divider formula.

[0035]

[0036] In the formula, Δω max,i For the sudden increase in regional load ΔP L After Δt shed Emergency load shedding ΔP in the region shed After that, the lowest frequency of bus k; t max The time it takes for bus k to reach its lowest point.

[0037] Similarly, at a certain moment, the load in region k suddenly increases by ΔP. L After Δt shed Emergency load shedding ΔP is performed in region j. shed Based on the initial distribution law of the disturbance power and the system frequency response model, the minimum frequency of bus k and the time to reach the minimum point are calculated using the frequency divider formula:

[0038]

[0039] In the formula, Δω max,j For a sudden increase in load ΔP in region k L After Δt shedEmergency load shedding ΔP is performed in region j. shed Then, the lowest frequency of bus k.

[0040] Comparison of two transient processes:

[0041]

[0042] Therefore, we can conclude that when the load in region k suddenly increases by ΔP L When x ik <x kj When, after Δt shed Emergency load shedding ΔP is performed in region i. shed Compared to after Δt shed Emergency load shedding ΔP is performed in the regional area. shed The lowest frequency recovery is better, and the lowest frequency can be increased by a further value:

[0043]

[0044] When the load in region k suddenly increases by ΔP L When x ik <x kj When, after Δt shed Emergency load shedding ΔP is performed in region j. shed Compared to after Δt shed Emergency load shedding ΔP is performed in the regional area. shed The lowest frequency recovery is better, and the lowest frequency can be increased by a further value:

[0045]

[0046] Through the above-mentioned emergency load shedding method, the present invention can bring the following beneficial effects: For the simplified multi-machine equivalent system, by combining the power distribution law after system disturbance, the system frequency response model and the frequency distribution law in the network, an emergency load shedding method with theoretically optimal nearest load shedding position is proposed, which reduces the system frequency deviation and improves system stability.

[0047] By analyzing a simple system, the impact of implementing stabilization measures at different locations on the frequency at the disturbance point after a power disturbance is proposed. It is proven that, under the same frequency stabilization measure amount and stabilization action time, the closer the stabilization measure is to the disturbance point by electrical distance, the more beneficial it is to the system frequency stability.

[0048]

[0049] 3. Determine the frequency response model parameters including the stability control module, including the system equivalent inertia and the primary frequency regulation parameters of each unit. The system equivalent inertia can be obtained by aggregating the inertia of each operating generator in the coordinate system of the center of inertia. The calculation formula is as follows:

[0050]

[0051] Where: H sys H is the equivalent inertia of the system. i Let S be the inertia of the i-th generator. N,i Let i be the capacity of unit i.

[0052] For the primary frequency regulation aggregation parameters, a detailed frequency regulation model is established based on the actual operating generator units that have primary frequency regulation functions. In a multi-machine power system, the primary frequency regulation process is jointly regulated by each synchronous generator and converter. Among them, the generators equipped with primary frequency regulation and the converters with control respond to frequency deviations by changing mechanical power and output power. Since the detailed frequency regulation model is relatively complex, from the perspective of input-output equivalence, the aggregation parameters are obtained by replacing the high-order model with a low-order transfer function.

[0053] 4. Obtain the system power disturbance based on the frequency change rate. Use the system disturbance and load shedding as inputs to the frequency response model, and the lowest frequency point as the output. Obtain the minimum load shedding amount that satisfies the system frequency stability requirements through iterative calculation. The formula for calculating the disturbance power is as follows:

[0054]

[0055] Where: ΔP dist Let f be the system disturbance power, f be the system frequency, and t0 be the time when the disturbance occurs.

[0056] 5. Select several bus nodes in the power system as observation nodes. If there is a disturbance, extract the bus frequency time series data before the disturbance as the network input and the nearest load shedding control location at the disturbance location as the network output to construct a frequency control sensitive point mining dataset.

[0057] 6. Construct a CNN-based frequency control sensitive point mining model and train the network using an offline-generated frequency control sensitive point mining dataset. The main parameters of the model include training batch size, learning rate, optimizer, number of encoder layers, input feature dimension, number of attention heads, and dimension of the hidden layers in the feedforward neural network.

[0058] 7. Read the frequency deviation time series data of the key bus within 1 second after the disturbance occurs, input it into the frequency control sensitive point mining model, and output the sensitivity ranking of each control position.

[0059] 8. Utilize the obtained load shedding amount that meets the system frequency stability requirements and the control positions under the current scenario to formulate and generate control measures. The total load shedding amount should be the load shedding control position closest to the disturbance position, and the total load shedding amount should not be less than the load shedding amount that meets the system frequency stability requirements.

[0060] 9. The generated frequency stabilization control measures are distributed to the power system for execution, enabling the system to provide corresponding load shedding measures online for different operating conditions to maintain system stability.

[0061] Example Demonstration

[0062] To demonstrate the effect, a structure such as Figure 4 The CEPRI-LF example power system shown has the following settings:

[0063] 1. Optimizer: Adam optimizer;

[0064] 2: Number of encoder layers: 6;

[0065] 3: Input feature dimension size: 100;

[0066] 4: Fault occurrence time: 1 second;

[0067] 5: Number of heads to focus on: 5;

[0068] 6: Hidden layer dimension of feedforward neural network: 2048;

[0069] 7: Buses to be observed: Bus1B-1, Bus1B-2, Bus1B-3, Bus1B-4, Bus1B-5, Bus1B-6, Bus1B-7, Bus1B-8, Bus1B-9, Bus1B-10, Bus1B-11, Bus1B-12;

[0070] 8: Control positions: Bus1B-1, Bus1B-5, Bus1B-7, Bus1B-8, Bus1B-10;

[0071] 9: Deep learning parameters: learning rate 0.001, batch size 64, number of iterations 1000;

[0072] Figure 5 The frequency control model test set is a heatmap of the predicted and actual order of fault location results under system switching faults based on CNN. The frequency control sensitive point mining model can achieve an accuracy of 98%.

[0073] After generating and implementing a frequency stabilization control strategy based on rapid disturbance location identification, such as... Figure 6 As shown, the effectiveness of the frequency stabilization control method proposed in this invention for the frequency stabilization recovery of power systems is demonstrated.

[0074] Those skilled in the art should understand that the above embodiments are merely for illustrative purposes and are not intended to limit the scope of this disclosure. The system capacity, system voltage, line parameters, etc., shown may vary depending on the specific parameters of the power electronic grid-connected generator set and the power grid it is connected to. Those skilled in the art can make other changes or modifications based on the above disclosure, and these changes or modifications are still within the scope of this disclosure.

Claims

1. A frequency stabilization emergency load shedding system based on rapid disturbance location identification, characterized in that, include: The frequency stabilization measures total quantity generation module is used to read power system status information and frequency response data, identify the system frequency response model, and calculate the total quantity of stabilization control measures that meet the frequency stability requirements. The frequency control sensitive point mining module is used to take the frequency time series data of the key bus of the power system as input and the nearest load shedding location of the disturbance location as the output of the frequency stability control sensitive point mining network. The frequency stabilization and control measures generation module is used to read the total amount of stabilization and control measures that meet the system frequency stability requirements calculated by the total amount of frequency stabilization and control measures generation module, as well as the sensitivity ranking of each control position output by the frequency control sensitive point mining module. When a disturbance occurs in the power system, corresponding emergency load shedding measures are formulated to restore the system frequency to a safe range.

2. The frequency stabilization emergency load shedding system based on rapid disturbance location identification according to claim 1, characterized in that: The power system status information and frequency response data are the system equivalent inertia, the primary frequency regulation aggregation parameters of each unit, and the system inertia center frequency, respectively. The system equivalent inertia is obtained by aggregating the inertia of each operating component, such as the inertia time constant of a synchronous generator. If the component inertia cannot be obtained through model parameters, a data-driven inertia evaluation method is used to obtain the component inertia. For the primary frequency regulation aggregation parameters, a detailed frequency regulation model is established based on the actual operating generating units with primary frequency regulation functions. The aggregation parameters are determined by reducing the overall order of the detailed model.

3. The frequency stabilization emergency load shedding system based on rapid disturbance location identification according to claim 2, characterized in that: The sensitivity is a parameter that measures the response of the power system to different load shedding measures, and is quantified according to the magnitude of the increase in the minimum point of the system inertia center frequency under the same load shedding amount and different load shedding positions.

4. The frequency stabilization emergency load shedding system based on rapid disturbance location identification according to claim 3, characterized in that: The system frequency stability requirement is that the system inertia center frequency is not lower than 49.2Hz.

5. A method for using a frequency stabilization emergency load shedding system based on rapid identification of disturbance location according to any one of claims 1-4, characterized in that, include: Step 1: Determine the frequency response model parameters including the stability control module, including the system equivalent inertia and the primary frequency regulation parameters of each unit; Step 2: Obtain the power disturbance of the system based on the frequency change rate. Use the system disturbance and load shedding as inputs to the frequency response model, and the lowest frequency point as the output of the frequency response model. Obtain the minimum load shedding amount that meets the system frequency stability requirements through iterative calculation. Step 3: Select several bus nodes in the power system as observation nodes and several load shedding locations as load shedding sorting locations. Extract the bus frequency time series data before the power system is disturbed as the network input and the nearest load shedding location at each disturbance location as the network output to construct a frequency control sensitive point mining dataset. Step 4: Construct a CNN-based frequency control sensitive point mining model and train the network using an offline-generated fault location frequency control sensitive point mining dataset. Step 5: Input the key bus frequency time series data after the disturbance occurs into the frequency control sensitive point mining model, and output the nearest load shedding position for each disturbance location in the current scenario; Step 6: Using the obtained load shedding amount that meets the system frequency stability requirements and the nearest load shedding location at each disturbance location in the current scenario, formulate and generate control measures, and send the output instructions to the power system for execution, so that the system can provide corresponding load shedding measures online for different operating conditions to keep the system stable.

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