New energy electric power robustness control method, system and device for preventing chain overload of power transmission section and medium

Abstract

The invention discloses a new energy electric power robustness control method, system and device for preventing chain overload of a power transmission section and a medium. The method comprises the following steps: obtaining the active power flow size and the operation state of each branch in the power transmission section; calculating the comprehensive sensitivity of all the controllable nodes to each branch in the power transmission section, and generating a composite priority index based on the calculated comprehensive sensitivity, the classification of the nodes and the new energy fluctuation risk; performing priority ranking on the generator nodes to generate a node sequence; in combination with a reverse equivalent pairing principle, selecting an adjustment node pair, and calculating an adjustment amount of node output by considering an adjustment amount dynamic margin constraint of new energy output uncertainty; recalculating the active power flow and the operation state of each branch in the section; and judging whether the section power flow and the margin meet a termination condition or not to realize optimal control. According to the method, the operation robustness of the new energy power system is improved, and the overload of the transmission section can be quickly and efficiently eliminated.

Description

Technical Field

[0001] This invention relates to the field of power system safety and stability technology, and in particular to a robust control method, system, equipment and medium for preventing cascading overload of transmission sections in new energy power. Background Technology

[0002] Existing technologies have the following main drawbacks when dealing with transmission line overload problems, especially in the context of large-scale integration of new energy sources:

[0003] Inadequate robustness to address the uncertainty of renewable energy output: Traditional emergency control methods, such as those based on sensitivity analysis or optimization control, often face challenges in robustness under uncertain renewable energy output scenarios. These methods typically rely on deterministic models for adjustments, making it difficult to effectively mitigate the risk of secondary overloads caused by random fluctuations in renewable energy output. Existing methods neglect the impact of renewable energy output fluctuations on cross-sectional power flow during node sequencing, potentially leading to the omission of high-flyback risk renewable energy nodes during pairing adjustments, thus weakening the robustness of the adjustment scheme.

[0004] Limited by computational efficiency and applicability, the optimized emergency control method for overloaded branch power flow, while offering good safety and economy, suffers from excessively long computation times as system scale increases and control variables grow, making it difficult to meet the speed requirements of transmission section safety protection. While sensitivity-based analysis methods offer shorter computation times, traditional methods only analyze the most severely overloaded branch within the section. This may lead to increased power flow in other normal branches within the section, or even the emergence of new overloads, while eliminating the original overloaded branch. Furthermore, existing methods fail to consider the overall system perspective. In node sequencing, they neglect the impact of renewable energy output fluctuations on the power flow of the section, potentially leading to the neglect of high-fluctuation-risk renewable energy nodes during pairing adjustments, thus weakening the robustness of the adjustment scheme.

[0005] The adjustment strategy has limitations. Traditional sensitivity algorithms do not fully consider the impact of system parameter uncertainties when determining the order of adjustment nodes, and the ranking index is relatively singular. In terms of adjustment amount calculation, existing constraints do not fully account for the worst-case impact of renewable energy output uncertainty on branch power flow, which may lead to the adjustment scheme failing to reserve sufficient margin, thus failing to ensure the safety of the section under extreme renewable energy fluctuation scenarios. Summary of the Invention

[0006] In view of the aforementioned existing problems, the present invention is proposed.

[0007] Therefore, this invention provides a robust control method and system for new energy power to prevent cascading overload of transmission sections, which solves the problems of insufficient robustness, computational efficiency and limitations of adjustment strategies in existing methods under uncertain new energy output scenarios.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0009] In a first aspect, the present invention provides a robust control method for new energy power to prevent cascading overload of transmission sections, comprising:

[0010] Obtain the active power flow magnitude and operating status of each branch within the transmission section, and identify overloaded branches;

[0011] Calculate the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, and generate a composite priority index based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk.

[0012] The generator nodes are prioritized according to the composite priority index to generate a node sequence;

[0013] Based on the node sequence and combined with the reverse equal-quantity pairing principle, the adjustment node pairs are selected, the sensitivity and output requirements of the adjustment node pairs are adjusted, and the dynamic margin constraint of the adjustment amount due to the uncertainty of the new energy output is taken into account, and the adjustment amount of the node output is calculated.

[0014] Based on the adjustment of node output, the active power flow and operating status of each branch within the cross section are recalculated.

[0015] Determine whether the cross-sectional power flow and margin meet the termination conditions. If not, iterate and adjust or cut off the load. If they meet, stop the iteration to achieve optimized control.

[0016] As a preferred embodiment of the robust control method for preventing cascading overload of transmission sections in new energy power according to the present invention, the method includes: calculating the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, including calculating the sensitivity of nodes to branch power flow, specifically:

[0017] Based on the AC power flow model, the relationship between node injection power and branch power flow is obtained;

[0018] By using the inverse of the Jacobian matrix, the changes in node injection power are mapped to the changes in branch power flow;

[0019] For each controllable node, the impact of its injected power change on the active power flow of a specific branch is calculated, and the sensitivity data of each node to the branch power flow is obtained.

[0020] As a preferred embodiment of the robust control method for preventing cascading overload of transmission sections in new energy power according to the present invention, the method further includes: calculating the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, and calculating the comprehensive sensitivity of nodes to the transmission section, specifically:

[0021] Identify branches within the transmission section, classifying them into overloaded branches and normal branches with high load rates;

[0022] Based on the sensitivity data of each node to the branch power flow, a weight is assigned to each branch. The weight of an overloaded branch is based on its overload level, and the weight of a normal branch with a high load rate is based on its remaining margin.

[0023] Calculate the overall sensitivity of each node to the entire transmission section.

[0024] As a preferred embodiment of the robust control method for preventing cascading overload of new energy power transmission sections as described in this invention, a composite priority index is generated based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk, including:

[0025] Considering the risks posed by the efficiency of adjusting node output to eliminate cross-sectional overload and the uncertainty of new energy output, a risk suppression coefficient is introduced to balance the proportion of comprehensive sensitivity and fluctuation risk in the index.

[0026] Composite Priority Index R T,i Represented as:

[0027]

[0028] In the formula, α∈[0,1] is the risk suppression coefficient, used to adjust the proportion of comprehensive sensitivity and volatility risk in the composite priority calculation; B T,i Let be the fluctuation risk of node i relative to section T, representing the maximum potential impact of node output fluctuations on the power flow of the section.

[0029] The beneficial effects of this preferred technical solution are: by introducing a composite priority index that couples comprehensive sensitivity with new energy volatility risk, the selection and ranking of adjustment nodes can proactively consider and suppress new energy volatility risk.

[0030] As a preferred embodiment of the robust control method for preventing cascading overload of transmission sections in new energy power according to the present invention, the method includes: selecting adjustment node pairs based on node sequences and in conjunction with the reverse equal-quantity pairing principle, including:

[0031] Select the first node from the output node sequence and the output node sequence respectively to form an adjustment node pair, and satisfy the condition that the output increase at the upper adjustment point is equal to the output decrease at the lower adjustment point;

[0032] If any node is unadjustable, select the next adjustable point of priority from the corresponding sequence and re-form the node pair.

[0033] As a preferred embodiment of the robust control method for preventing cascading overload of new energy power transmission sections according to the present invention, the method includes: taking into account the dynamic margin constraint of the adjustment amount due to the uncertainty of new energy output, and calculating the adjustment amount of node output, including:

[0034] The potential impact of renewable energy unit output on branch power flow under the scenario of maximum fluctuation is quantified as a dynamic margin, specifically expressed as the change in active power flow of the branch due to renewable energy fluctuations.

[0035]

[0036] Set adjustment constraints, including: node output constraints, overload branch constraints, normal branch power flow constraints, and power flow reversal constraints;

[0037] The output adjustment amount of the adjustment node pair is determined according to the adjustment amount constraint conditions. The minimum adjustment amount that satisfies all constraints is selected, and the adjustment amount is ensured to reserve sufficient dynamic margin for all branches in the section.

[0038] The final adjustment is generated and used to update the node output scheme.

[0039] As a preferred embodiment of the robust control method for preventing cascading overload of new energy power transmission sections as described in this invention, the method includes: determining whether the power flow and margin of the transmission section meet the termination conditions; if not, iterative adjustment or load shedding is performed; if the conditions are met, iteration is stopped to achieve optimized control, including:

[0040] The first termination condition is that the power flow of all branches within the transmission section does not exceed the limit and does not reverse;

[0041] The second termination condition is that the margin reserved for each branch meets the robustness preset value under extreme fluctuation scenarios of new energy power output.

[0042] If both convergence conditions are met, the adjustment process ends and the final solution is output.

[0043] If branch overload still exists within the transmission section after the set maximum number of iterations, an emergency load shedding operation will be initiated according to the importance of the load and the sensitivity of the load node to the overloaded branch, until the termination condition is met.

[0044] Secondly, the present invention provides a robust control system for new energy power to prevent cascading overloads of transmission sections, comprising:

[0045] The acquisition module is used to acquire the active power flow magnitude and operating status of each branch within the transmission section and to identify overloaded branches.

[0046] The first calculation module is used to calculate the comprehensive sensitivity of all controllable nodes to each branch within the transmission section. Based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk, a composite priority index is generated.

[0047] The classification and sorting module is used to prioritize generator nodes according to composite priority indicators and generate a node sequence.

[0048] The second calculation module is used to select and adjust node pairs based on the node sequence and the reverse equal-quantity pairing principle, adjust the sensitivity and output requirements of the node pairs, and take into account the dynamic margin constraint of the adjustment amount due to the uncertainty of the new energy output, and calculate the adjustment amount of the node output.

[0049] The third calculation module is used to recalculate the active power flow and operating status of each branch within the cross section based on the adjustment of node output.

[0050] The judgment module is used to determine whether the cross-sectional power flow and margin meet the termination conditions. If not, it iterates and adjusts or cuts off the load; if they meet, it stops iterating to achieve optimized control.

[0051] Thirdly, the present invention provides a computer device, comprising:

[0052] Memory and processor;

[0053] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of a robust control method for new energy power to prevent cascading overload of transmission sections.

[0054] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the robust control method for preventing cascading overload of transmission sections in new energy power.

[0055] Compared with existing technologies, the beneficial effects of this invention are as follows: By introducing a composite priority index that couples integrated sensitivity with renewable energy fluctuation risk, this invention addresses the problem of traditional methods neglecting the uncertainty of renewable energy output, enabling node selection and sequencing to proactively suppress fluctuation risk. Simultaneously, it proposes dynamic margin constraints for adjustment, quantifying the worst-case impact of renewable energy fluctuations into margin thresholds to ensure cross-sectional safety in extreme scenarios and avoid secondary overload. Through risk suppression coefficient adjustment, a balance is achieved between proactive suppression and passive margin reservation, enhancing system robustness. The optimized node sequencing strategy can accurately identify nodes with significant power flow control effects, improving adjustment efficiency. A reverse equal-quantity pairing principle is adopted to maintain system power balance, avoiding frequency fluctuations or node overruns. The comprehensive multi-constraint approach ensures accurate and feasible adjustment calculations, improving the robustness of renewable energy power system operation. Attached Figure Description

[0056] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a schematic diagram of the overall process of a robust control method for preventing cascading overload of transmission sections in new energy power, as described in one embodiment of the present invention.

[0058] Figure 2 This is a schematic diagram illustrating the specific process of robust safety control of transmission sections in a robust control method for preventing cascading overload of transmission sections in a new energy power system according to an embodiment of the present invention.

[0059] Figure 3 This is a schematic diagram of the IEEE 39-node system in a robust control method for preventing cascading overloads of transmission sections in new energy power, as described in an embodiment of the present invention.

[0060] Figure 4 This is a diagram showing the change in load rate of each branch within a transmission section before and after adjustment in a robust control method for preventing cascading overload of a transmission section, as described in an embodiment of the present invention. Detailed Implementation

[0061] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0062] Example 1, referring to Figure 1 As an embodiment of the present invention, a robust control method for new energy power to prevent cascading overload of transmission sections is provided, comprising:

[0063] S100: Obtain the active power flow magnitude and operating status of each branch within the transmission section, and identify overloaded branches;

[0064] S200: Calculate the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, and generate a composite priority index based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk.

[0065] S300: Prioritize generator nodes according to composite priority indicators to generate a node sequence;

[0066] S400: Based on the node sequence and combined with the reverse equal-quantity pairing principle, select adjustment node pairs, adjust the sensitivity and output requirements of the adjustment node pairs, and take into account the dynamic margin constraint of the adjustment amount due to the uncertainty of the new energy output, and calculate the adjustment amount of the node output.

[0067] S500: Based on the adjustment of node output, recalculate the active power flow and operating status of each branch within the cross section;

[0068] S600: Determine whether the cross-sectional power flow and margin meet the termination conditions. If not, iterate and adjust or cut off the load. If they meet, stop the iteration to achieve optimized control.

[0069] It should be noted that the above scheme proposes a composite priority index that couples comprehensive sensitivity with the risk of new energy fluctuations, in order to improve the traditional comprehensive sensitivity algorithm so that it can simultaneously consider the comprehensive impact of nodes on the transmission section and the risk of new energy output fluctuations when adjusting the classification and ranking of nodes. This solves the problem that the traditional node ranking method ignores the uncertainty of new energy output.

[0070] The above scheme addresses how to improve the adjustment constraints, quantifies the worst-case impact of renewable energy fluctuations on branch power flow as a margin threshold, and embeds it into the adjustment calculation. By reserving margin, the robustness of the adjustment scheme is ensured, thereby eliminating overload while effectively defending against the risk of secondary overload caused by the uncertainty of renewable energy output.

[0071] The above scheme integrates key aspects such as sensitivity analysis, reverse equal-quantity pairing principle, and dynamic margin reservation to construct a complete robust and fast control strategy for transmission sections that takes into account the uncertainty of new energy output. This strategy can ensure the safety of the transmission section under the scenario of fluctuating new energy output while maintaining system power balance and quickly eliminating section overload, effectively preventing the occurrence of cascading trips.

[0072] Example 2, refer to Figures 1-2 As an embodiment of the present invention, based on the above embodiment, a robust control method for new energy power to prevent cascading overload of transmission sections is provided.

[0073] In this embodiment of the application, step S100 obtains the active power flow magnitude and operating status of each branch within the transmission section and identifies overloaded branches.

[0074] In an alternative implementation, S100 can utilize power system analysis software, such as Matlab, PSASP, or DIgSILENT, to construct an AC power flow model based on the power grid topology, node parameters (e.g., generator output, load demand), and branch parameters (e.g., impedance, transmission limits), and calculate the active power flow value of each branch within the transmission section to obtain the operating status.

[0075] In another optional implementation, S100 can also use the SCADA of the power system to collect information such as active power flow data, voltage amplitude and phase angle of each branch in the transmission section in real time, compare the collected real-time power flow data with the rated transmission limit of the branch, determine the operating status of the branch, and automatically mark the branch whose power flow value exceeds the transmission limit as an overload branch based on the real-time data.

[0076] In this embodiment of the application, step S200, calculating the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, includes calculating the sensitivity of nodes to branch power flow, specifically the following steps A1-A3:

[0077] A1: Based on the AC power flow model, obtain the relationship between node injection power and branch power flow;

[0078] A2: Using the inverse of the Jacobian matrix, the changes in node injection power are mapped to the changes in branch power flow;

[0079] A3: For each controllable node, calculate the impact of its injected power change on the active power flow of a specific branch, and obtain the sensitivity data of each node to the branch power flow.

[0080] For example, in steps A1-A3:

[0081] For branch l (from node m to node n), its active power flow equation can be written as:

[0082]

[0083] In the formula, G mn and B mn These are the conductance and susceptance of the branch circuit, respectively.

[0084] By linearizing the power flow equations and using the inverse of the Jacobian matrix, the influence of the active power variation injected at node k on the active power flow variation of branch l can be obtained, i.e., the active power sensitivity S of node k to branch l. l,k :

[0085]

[0086] In the formula, e k It is a unit vector that is 1 only at the position corresponding to node k.

[0087] It should be noted that the sensitivity S l,k The magnitude of the value reveals the efficiency of different nodes in controlling the power flow of a specific branch, while the sign reflects the impact of changes in output on the direction of the power flow. A positive sign indicates that an increase in output leads to an increase in power flow, while a negative sign indicates that an increase in output leads to a decrease in power flow.

[0088] In this embodiment of the application, step S200, which calculates the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, further includes calculating the comprehensive sensitivity of the nodes to the transmission section, specifically the following steps A4-A6:

[0089] A4: Identify branches within the transmission section, classifying them into overloaded branches and normal branches with high load rates;

[0090] A5: Based on the sensitivity data of each node to the branch power flow, assign weights to each branch. The weight of overloaded branches is based on their overload level, and the weight of normal branches with high load rate is based on their remaining margin.

[0091] A6: Calculate the overall sensitivity of each node to the entire transmission section.

[0092] For example, in steps A4-A6:

[0093] Assume that section T contains L overloaded branches and M normal branches with a load factor greater than a set value β (e.g., 0.8). The overall sensitivity S of node k to section T is... T,k The result, obtained through weighted conventional sensitivity, taking into account both the overload degree of the overloaded branch and the redundancy degree of the normal branch, is expressed as:

[0094]

[0095] Where, α l and α m The weights for overloaded branches and normal branches are respectively, and their calculation formulas are as follows:

[0096]

[0097] in:

[0098] In the formula, λ is the overall index weight of the overloaded branch (usually taken as 2); ΔP l ΔP represents the overload of branch l. m This represents the redundancy of the normal branch m.

[0099] In an alternative implementation, in step S200, based on the above implementation scheme, the classification of nodes can be achieved through a comprehensive sensitivity S. T,k The symbols categorize generator nodes into two types, including:

[0100] A negative overall sensitivity value indicates an upward adjustment of the output node; a positive overall sensitivity value indicates a downward adjustment of the output node.

[0101] Specifically, it can be:

[0102] 1) Lower the output node: S T,k >0 indicates that increasing the output of a node will lead to an increase in the overall power flow of the cross section, and the output of that node should be adjusted downward.

[0103] 2) Adjust the output node: S T,k <0 indicates that increasing the output of a node will lead to a decrease in the overall power flow of the cross section, and the output of that node should be adjusted upward.

[0104] If S T,k =0 indicates that the change in node output has no effect on the overall power flow of the cross section. In other words, it is meaningless to adjust the output of the node when the cross section is overloaded, so it is excluded from the pairing adjustment calculation.

[0105] Furthermore, to address the issue of traditional methods neglecting the uncertainty of new energy output, a composite priority index is proposed.

[0106] In this embodiment of the application, step S200 generates a composite priority index based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk, including:

[0107] Considering the risks posed by the efficiency of adjusting node output to eliminate cross-sectional overload and the uncertainty of new energy output, a risk suppression coefficient is introduced to balance the proportion of comprehensive sensitivity and fluctuation risk in the index.

[0108] Composite Priority Index R T,i Represented as:

[0109]

[0110] In the formula, α∈[0,1] is the risk suppression coefficient, used to adjust the proportion of comprehensive sensitivity and volatility risk in the composite priority calculation; B T,i Let be the fluctuation risk of node i relative to section T, representing the maximum potential impact of node output fluctuations on the power flow of the section.

[0111] Specifically, B T,i It can be represented as:

[0112]

[0113] In the formula, δ i The maximum fluctuation range of the output of generator node i after adjustment (0 for traditional units); The predicted output after adjustment for generator node i; S′ T,i =∑ l∈T S l,i Let be the sum of the sensitivities of node i to all branches within section T.

[0114] It should be noted that R T,i The larger the value, the greater the overall contribution of the node to the system's stability and resistance to fluctuations, and the more priority it should be for adjustment.

[0115] In this embodiment of the application, in step S300, the generator nodes are prioritized according to the composite priority index to generate a node sequence;

[0116] In an alternative implementation, S300 can adjust the composite priority index R. T,i The power output nodes are sorted in descending order based on their relative importance, resulting in sequences for both upward and downward power output nodes. This method, which directly sorts nodes in descending order based on a composite priority index, is a simple, direct, and computationally efficient preferred approach.

[0117] In another optional implementation, S300 can also perform dynamic sorting based on a weighted composite priority index. Compared with the previous implementation, it is necessary to dynamically adjust the weights of comprehensive sensitivity and volatility risk in the composite priority index according to the current cross-section overload level and the severity of new energy fluctuation risk. This can adapt to different cross-section overload and new energy fluctuation scenarios, and improve the flexibility and pertinence of sorting.

[0118] In this embodiment of the application, step S400, based on the node sequence and combined with the reverse equal-quantity pairing principle, selects and adjusts node pairs, including the following steps B1-B2:

[0119] B1: Select the first node from the upward output node sequence and the downward output node sequence to form an adjustment node pair, and satisfy the condition that the output increase of the upward adjustment point is equal to the output decrease of the downward adjustment point;

[0120] B2: If any node is not adjustable, select the next adjustable point of priority from the corresponding sequence and re-form the node pair.

[0121] It should be noted that, in order to ensure that the total power generation of the system remains unchanged and to avoid power imbalance, the adjustment node pairs are selected using the principle of reverse equal-quantity pairing.

[0122] For example, the first node is selected from the sequence of increasing output nodes and the sequence of decreasing output nodes to form an adjustment node pair (e.g., node a increases output ΔP). a Node b reduces output force ΔP b ), and satisfy ΔP a =-ΔP b If the selected node is not adjustable, continue searching for the next adjustable node to pair with.

[0123] In this embodiment of the application, step S400 involves adjusting the sensitivity and output requirements of the node pair;

[0124] Among them, adjusting the sensitivity of node pairs, for example:

[0125] Adjust the active power flow sensitivity S of node to α and b to branch l l,ab for:

[0126] S l,ab =S l,a -S l,b (9)

[0127] Adjusting the combined sensitivity S of node pairs α and b to transmission section T T,ab for:

[0128] S T,ab =S T,a ′-S T,b ′ (10)

[0129] Among them, the output requirements of the adjustment node pair are exemplified as follows: the output of the selected adjustment node pair should meet the following requirements to ensure that the overall power flow of the transmission section is reduced after adjustment and there are no overloaded branches.

[0130] 1) The overall power flow of the transmission section is less than the maximum transmission capacity of the section, that is:

[0131] S T,ab =S T,a ′-S T,b ′<0 (11)

[0132] 2) There are no overloaded branches within the cross-section; that is, for all overloaded branches l, the following condition must be met:

[0133] S l,ab =S l,a -S l,b <0 (12)

[0134] 3) For a normal branch n whose active power flow is close to the limit, it should be ensured that its power flow will not exceed the limit in the positive direction, i.e., S n,ab <0.

[0135] In this embodiment of the application, step S400, which takes into account the dynamic margin constraint of the adjustment amount for the uncertainty of the new energy output, calculates the adjustment amount of the node output, including the following steps C1-C3:

[0136] C1: The potential impact of renewable energy unit output on branch power flow under the scenario of maximum fluctuation is quantified as a dynamic margin, specifically expressed as the change in active power flow of the branch due to renewable energy fluctuations.

[0137]

[0138] C2: Set adjustment constraints, including: node output constraints, overload branch constraints, normal branch power flow constraints, and power flow reversal constraints;

[0139] Specifically, the adjustment amount ΔP of a pair of adjustment nodes α and b a and ΔP b (where ΔP) a =-ΔP b The value is determined by the minimum value of the following constraints:

[0140]

[0141] 1) Generator node output constraints The maximum upscaling amount of node a is The maximum adjustable amount of node b is

[0142] The maximum adjustable amount for new energy nodes is set to 30% of the initial output.

[0143] 2) Overload constraint of overload branch (ΔP) xtl For a specific overloaded branch l within the cross section, the required adjustment amount for the adjustment node is:

[0144]

[0145] When multiple overloaded branches exist within the cross-section, the adjustment should be taken as the maximum value:

[0146] ΔP xtl =max{ΔP xtl1 ′,ΔP xtl2 ′,…} (16)

[0147] 3) Normal branch power flow exceeding limits constraint For a normal branch n within the cross section, to prevent its power flow from exceeding the limit, the constraint is as follows:

[0148]

[0149] To ensure that the power flow of all normal branches does not exceed the limit, the minimum value of the constraint value of all branches is taken:

[0150]

[0151] 4) Branch flow reverse constraint For any branch m within the cross section, to avoid reverse power flow, the maximum adjustable amount is:

[0152]

[0153] Among them, K l >1 represents the margin coefficient.

[0154] C3: Determine the output adjustment amount of the adjustment node pair according to the adjustment amount constraint conditions, select the minimum adjustment amount that satisfies all constraints, and ensure that the adjustment amount reserves sufficient dynamic margin for all branches in the section.

[0155] For example, the minimum of the maximum adjustable values ​​of all branches can be expressed as:

[0156]

[0157] The final adjustment is generated and used to update the node output scheme.

[0158] In this embodiment of the application, in step S500, the active power flow and operating status of each branch within the cross section are recalculated based on the adjustment amount of the node output.

[0159] It should be noted that the parameter calculations involved in S500 are basically the same as those involved in S100, and the Newton-Raphson method is usually used to solve the nonlinear power flow equations.

[0160] In this embodiment of the application, step S600 determines whether the cross-sectional power flow and margin meet the termination conditions. If not, iterative adjustment or load shedding is performed; if they are met, iteration stops, thus achieving optimized control. This includes:

[0161] The first termination condition is that the power flow of all branches within the transmission section does not exceed the limit and does not reverse;

[0162] The second termination condition is that the margin reserved for each branch meets the robustness preset value under extreme fluctuation scenarios of new energy power output.

[0163] If both convergence conditions are met, the adjustment process ends and the final solution is output.

[0164] If branch overload still exists within the transmission section after the set maximum number of iterations, an emergency load shedding operation will be initiated according to the importance of the load and the sensitivity of the load node to the overloaded branch, until the termination condition is met.

[0165] In summary, this invention can significantly improve the robustness of new energy power system operation.

[0166] By taking into account the uncertainty of new energy output, the traditional node ranking method can overcome the limitation of ignoring the uncertainty of new energy output. By introducing a composite priority index that couples comprehensive sensitivity with the risk of new energy fluctuations, the selection and ranking of adjustment nodes can proactively consider and suppress the risk of new energy fluctuations.

[0167] By reserving dynamic margins and taking into account the dynamic margin constraints of adjustments for uncertainties in renewable energy output, the worst-case impact of renewable energy fluctuations on branch power flow is quantified into a margin threshold and embedded in the calculation of adjustments. This ensures that the adjustment scheme can maintain section safety even under extreme fluctuation scenarios and effectively avoid secondary overload.

[0168] By adjusting the risk suppression coefficient, that is, by prioritizing the adjustment of new energy nodes with high volatility risk, an effective balance is achieved between proactive suppression of new energy volatility risk and passive reservation of safety margin, thereby improving the robustness of the overall control strategy.

[0169] This invention can also achieve rapid and efficient elimination of overload in power transmission sections.

[0170] By improving the traditional comprehensive sensitivity algorithm and optimizing the node sorting strategy, it is possible to more accurately identify nodes that have a significant effect on power flow control of the transmission section and improve adjustment efficiency.

[0171] By adopting the principle of reverse equal-quantity pairing adjustment, the total power balance of the system is maintained throughout the adjustment process, thus avoiding frequency fluctuations or overstepping of balance nodes caused by power imbalance.

[0172] By comprehensively considering multiple constraints such as node output constraints, overload elimination requirements, prevention of normal branch power flow exceeding limits, and prevention of branch power flow reversal, the adjustment calculation is more accurate and comprehensive, ensuring the physical feasibility of the adjustment scheme.

[0173] Example 3, referring to Figures 3-4 Based on the above embodiments, as shown in Tables 1-5, this implementation proposes a simulation implementation of a robust control method for preventing cascading overload of transmission sections in new energy power, verifying the effectiveness and applicability of the proposed method.

[0174] like Figure 3As shown, a simulation test was conducted using an improved IEEE 39-bus system. Using Matlab R2024b software, the traditional thermal power units connected to the 30th and 34th busbars were changed to new energy units. It was set that the output of the adjusted new energy units might fluctuate within ±30% of their predicted value. To enhance the system's regulation capability, the maximum output of all units was increased to 1.05 times the original maximum output, and the risk suppression coefficient was set to 0.6.

[0175] The transmission limit of the branch is changed to simulate the situation of overloaded branch under high load. It is assumed that the transmission section where the overloaded branch l3 is located has been found. This section contains a total of 4 branches. The power flow situation of each branch in the section is shown in Table 1.

[0176] Table 1. Power flow conditions of each branch within the cross section.

[0177]

[0178] Directly disconnecting branch L3 could lead to a system facing the risk of cascading overload tripping. The system diagram in this case is as follows: Figure 3 As shown in the figure, the red dashed line represents branch l3 that was disconnected due to overload, and the red solid lines represent branches l1 and l2 that experienced overload after disconnecting l3. 42 The solid blue line represents branch l9, where the load rate rose to 93.2% after l3 was disconnected. If overload is not controlled in its early stages and branch l3 is allowed to be disconnected due to a delay in the overload protection, the resulting power flow shift will lead to branch l1 and l 42 An overload and subsequent disconnection will trigger a new round of large-scale power flow shifts, ultimately leading to a cascading overload and tripping of the system. Therefore, immediate emergency measures must be taken to eliminate branch overloads and prevent the cascading effect.

[0179] The calculated sensitivity of each generator node to the branch within the cross section is shown in Table 2.

[0180] Table 2. Sensitivity of each generator node to branches within the cross section.

[0181]

[0182] During the first round of pairing adjustments, the calculation results of the comprehensive sensitivity of each generator node to the cross section, the fluctuation risk of the new energy node to the cross section, and the composite priority index of each node are shown in Table 3.

[0183] Table 3 Calculation results of the first round of pairing adjustment

[0184]

[0185] Nodes are classified according to the sign of their comprehensive sensitivity to the cross-section in Table 3, and ranked according to the magnitude of their composite priority index. In the first round of pairing adjustment calculations, the sequence of nodes with increased output is 35, 36, 33, and 32, and the sequence of nodes with decreased output is 30, 39, 34, 37, and 38. The first node in each sequence is selected to form an adjustment node pair, the adjustment amount is calculated, and the adjustment is performed. When node 35 reaches its output limit, the adjustment ends. Since the overload has not yet been eliminated, the output of each node and the operating status of the branch are updated, and the next round of pairing adjustment is performed. Meanwhile, as shown in Table 3, in this round of adjustment, the comprehensive sensitivity value of new energy node 30 to the cross-section is lower than that of nodes 37 and 39. However, considering the risk that its output uncertainty brings to the cross-section power flow, its composite priority is higher, and its output is preferentially reduced to actively suppress the fluctuation risk. Although node 34 has a higher fluctuation risk, it is not assigned a higher node ranking due to its lowest comprehensive sensitivity and lowest adjustment efficiency.

[0186] In each round of adjustment calculations, the nodes need to be reclassified and reordered. This is because the overall sensitivity of each node and the fluctuation risk of new energy nodes will change in each round of adjustment, which may result in different sequences of adjusted nodes in each round of adjustment, so this calculation step needs to be repeated.

[0187] Table 4. Calculation results of the second round of pairing adjustments

[0188]

[0189]

[0190] Table 4 shows the calculation results of the second round of paired adjustments. The calculation process is the same as the first round. In the second round, the output node sequence was increased to 32, 35, 36, and 33, and the output node sequence was decreased to 30, 37, 34, 39, and 38. Nodes 32 and 30 were paired to form an adjustment node pair, and the adjustment amount was calculated and implemented. In this round of adjustments, the fluctuation risk of node 30 has decreased compared to the previous adjustment. However, due to the risk suppression coefficient of 0.6, its high overall sensitivity still contributes a significant amount to the composite priority calculation, keeping it at the top of the adjustment sequence. When node 30 reaches its lower output limit, this round of adjustments ends, and the same calculation is repeated until the termination condition is met.

[0191] Table 5 Final Control Adjustment Scheme

[0192]

[0193] Table 5 shows the final control adjustment scheme. As can be seen from Table 5, the final control adjustment scheme in this case involved three rounds of paired adjustment calculations, adjusting the output of four nodes. New energy node 30 participated in the first two rounds of adjustment, actively suppressing fluctuation risks by reducing its own output; while new energy node 34 did not participate in the adjustment, passively defending against fluctuation risks entirely through the margin reserved in the adjustment scheme. The changes in load rates of each branch within the cross-section before and after adjustment are shown below. Figure 4 As shown.

[0194] This case study completed the generation of the final adjustment scheme in 0.09 seconds, which is a fast calculation speed and can meet the speed requirements of transmission section protection, thus having certain reference value.

[0195] The sensitivity analysis-based method has a short computation time. For example, the simulation verification in the IEEE 39-bus system in this embodiment shows that the final adjustment scheme is generated in only 0.09 seconds, which meets the stringent requirements of speed for the safety protection of transmission sections.

[0196] Example 4 illustrates a schematic scheme for a robust control method for preventing cascading overloads of transmission sections in new energy power. It should be noted that the technical solution of this robust control system for preventing cascading overloads of transmission sections in new energy power is based on the same concept as the aforementioned robust control method for preventing cascading overloads of transmission sections in new energy power. Details not described in detail in this embodiment can be found in the description of the aforementioned robust control method for preventing cascading overloads of transmission sections in new energy power.

[0197] This embodiment also provides another robust control system for new energy power to prevent cascading overload of transmission sections, including:

[0198] The acquisition module is used to acquire the active power flow magnitude and operating status of each branch within the transmission section and to identify overloaded branches.

[0199] The first calculation module is used to calculate the comprehensive sensitivity of all controllable nodes to each branch within the transmission section. Based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk, a composite priority index is generated.

[0200] The classification and sorting module is used to prioritize generator nodes according to composite priority indicators and generate a node sequence.

[0201] The second calculation module is used to select and adjust node pairs based on the node sequence and the reverse equal-quantity pairing principle, adjust the sensitivity and output requirements of the node pairs, and take into account the dynamic margin constraint of the adjustment amount due to the uncertainty of the new energy output, and calculate the adjustment amount of the node output.

[0202] The third calculation module is used to recalculate the active power flow and operating status of each branch within the cross section based on the adjustment of node output.

[0203] The judgment module is used to determine whether the cross-sectional power flow and margin meet the termination conditions. If not, it iterates and adjusts or cuts off the load; if they meet, it stops iterating to achieve optimized control.

[0204] This embodiment also provides a computer device applicable to a robust control method for preventing cascading overloads of transmission sections in new energy power, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement a robust control method for preventing cascading overloads of transmission sections in new energy power as proposed in the above embodiment.

[0205] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a robust control method for preventing cascading overloads of transmission sections in new energy power, as proposed in the above embodiments.

[0206] The storage medium proposed in this embodiment and the robust control method for preventing cascading overload of transmission sections in new energy power proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0207] Based on the above description of the implementation methods, those skilled in the art will clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0208] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A robust control method for new energy power to prevent cascading overload of transmission sections, characterized in that, include: Obtain the active power flow magnitude and operating status of each branch within the transmission section, and identify overloaded branches; Calculate the comprehensive sensitivity of all controllable nodes to each branch within the transmission section, and generate a composite priority index based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk. The generator nodes are prioritized according to the composite priority index to generate a node sequence; Based on the node sequence and combined with the reverse equal-quantity pairing principle, adjustment node pairs are selected, and the sensitivity and output requirements of the adjustment node pairs are considered. The dynamic margin constraint of the adjustment amount due to the uncertainty of the new energy output is also taken into account, and the adjustment amount of the node output is calculated. Based on the adjustment of node output, the active power flow and operating status of each branch within the cross section are recalculated. Determine whether the cross-sectional power flow and margin meet the termination conditions. If not, iterate and adjust or cut off the load. If they meet, stop the iteration to achieve optimized control.

2. The robust control method for preventing cascading overload of transmission sections in new energy power as described in claim 1, characterized in that, Calculate the overall sensitivity of all controllable nodes to each branch within the transmission section, including calculating the sensitivity of nodes to branch power flow, specifically: Based on the AC power flow model, the relationship between node injection power and branch power flow is obtained; By using the inverse of the Jacobian matrix, the changes in node injection power are mapped to the changes in branch power flow; For each controllable node, the impact of its injected power change on the active power flow of a specific branch is calculated, and the sensitivity data of each node to the branch power flow is obtained.

3. The robust control method for preventing cascading overload of transmission sections in new energy power as described in claim 2, characterized in that, Calculating the overall sensitivity of all controllable nodes to each branch within the transmission section also includes calculating the overall sensitivity of the nodes to the transmission section, specifically: Identify branches within the transmission section, classifying them into overloaded branches and normal branches with high load rates; Based on the sensitivity data of each node to the branch power flow, a weight is assigned to each branch. The weight of an overloaded branch is based on its overload level, and the weight of a normal branch with a high load rate is based on its remaining margin. Calculate the overall sensitivity of each node to the entire transmission section.

4. A robust control method for preventing cascading overload of transmission sections in new energy power as described in claim 3, characterized in that, Based on the calculated comprehensive sensitivity, node classification, and new energy volatility risk, a composite priority index is generated, including: Considering the risks posed by the efficiency of adjusting node output to eliminate cross-sectional overload and the uncertainty of new energy output, a risk suppression coefficient is introduced to balance the proportion of comprehensive sensitivity and fluctuation risk in the index. Composite Priority Index R T,i Represented as: In the formula, α∈[0,1] is the risk suppression coefficient, used to adjust the proportion of comprehensive sensitivity and volatility risk in the composite priority calculation; B T,i Let be the fluctuation risk of node i relative to section T, representing the maximum potential impact of node output fluctuations on the power flow of the section.

5. A robust control method for preventing cascading overload of transmission sections in new energy power as described in claim 4, characterized in that, Based on the node sequence and combined with the reverse equal-quantity pairing principle, select and adjust node pairs, including: Select the first node from the output node sequence and the output node sequence respectively to form an adjustment node pair, and satisfy the condition that the output increase at the upper adjustment point is equal to the output decrease at the lower adjustment point; If any node is unadjustable, select the next adjustable point of priority from the corresponding sequence and re-form the node pair.

6. A robust control method for preventing cascading overload of transmission sections in new energy power as described in claim 5, characterized in that, Taking into account the dynamic margin constraint of the adjustment amount for the uncertainty of new energy output, the adjustment amount of the node output is calculated, including: The potential impact of renewable energy unit output on branch power flow under the scenario of maximum fluctuation is quantified as a dynamic margin, specifically expressed as the change in active power flow of the branch due to renewable energy fluctuations. Set adjustment constraints, including: node output constraints, overload branch constraints, normal branch power flow constraints, and power flow reversal constraints; The output adjustment amount of the adjustment node pair is determined according to the adjustment amount constraint conditions. The minimum adjustment amount that satisfies all constraints is selected, and the adjustment amount is ensured to reserve sufficient dynamic margin for all branches in the section. The final adjustment is generated and used to update the node output scheme.

7. A robust control method for preventing cascading overload of transmission sections in new energy power as described in claim 6, characterized in that, Determine if the cross-sectional power flow and margin meet the termination conditions. If not, iterate and adjust or cut off the load. If they meet, stop the iteration to achieve optimized control, including: The first termination condition is that the power flow of all branches within the transmission section does not exceed the limit and does not reverse; The second termination condition is that the margin reserved for each branch meets the robustness preset value under extreme fluctuation scenarios of new energy power output. If both convergence conditions are met, the adjustment process ends and the final solution is output. If branch overload still exists within the transmission section after the set maximum number of iterations, an emergency load shedding operation will be initiated according to the importance of the load and the sensitivity of the load node to the overloaded branch, until the termination condition is met.

8. A robust control system for preventing cascading overloads in new energy power transmission sections, comprising the method described in any one of claims 1-7, characterized in that, include: The acquisition module is used to acquire the active power flow magnitude and operating status of each branch within the transmission section and to identify overloaded branches. The first calculation module is used to calculate the comprehensive sensitivity of all controllable nodes to each branch within the transmission section. Based on the calculated comprehensive sensitivity, node classification, and new energy fluctuation risk, a composite priority index is generated. The classification and sorting module is used to prioritize generator nodes according to composite priority indicators and generate a node sequence. The second calculation module is used to select and adjust node pairs based on the node sequence and the reverse equal-quantity pairing principle, adjust the sensitivity and output requirements of the node pairs, and take into account the dynamic margin constraint of the adjustment amount due to the uncertainty of the new energy output, and calculate the adjustment amount of the node output. The third calculation module is used to recalculate the active power flow and operating status of each branch within the cross section based on the adjustment of node output. The judgment module is used to determine whether the cross-sectional power flow and margin meet the termination conditions. If not, it iterates and adjusts or cuts off the load; if they meet, it stops iterating to achieve optimized control.

9. A computer device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the robust control method for preventing cascading overload of transmission sections for new energy power as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions, which, when executed by a processor, implement the steps of the robust control method for preventing cascading overload of transmission sections for new energy power as described in any one of claims 1 to 7.

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