Method and system for evaluating static voltage stability margin of power system

Abstract

The invention provides an electric power system static voltage stability margin evaluation method and system. The method comprises the following steps: acquiring active outputs of all power supply nodes in a target voltage node area; performing reactive power optimization on the target voltage node area to obtain reactive power output of the power system; adjusting active power output of all power supply nodes in the target voltage node area through a search algorithm; updating the reactive power output of the electric power system and the active power output of all power supply nodes in the target voltage node area until a preset iteration requirement is met, and obtaining static voltage stability limit power; and evaluating the static voltage stability margin of the corresponding target node channel. The method solves the problem that in the prior art, reactive power optimization is not fully considered to deviate from actual operation of a power system, the real operation state and potential risks of the system cannot be comprehensively reflected, and an evaluation result is inaccurate. The accuracy of the evaluation result is improved through the evaluation method comprehensively considering the active increase proportion and the reactive optimization.

Description

Technical Field

[0001] The present invention relates to the field of power system analysis, and in particular to a method and system for evaluating static voltage stability margin of a power system. Background Art

[0002] In the power system, voltage stability is one of the key factors to ensure the safe and stable operation of the system. The static voltage stability margin is an important indicator to measure the system's ability to resist voltage collapse under the current operating state. It has important guiding significance for the planning, design, operation and dispatching of the power system.

[0003] Traditional static voltage stability margin assessment methods mainly rely on detailed power flow calculations and limit power searches based on the continuous power flow method. Although these methods are accurate, they are computationally intensive and time-consuming, and are difficult to meet the needs of real-time analysis and rapid decision-making in power systems. For example, commonly used methods in the prior art include sensitivity method, singular value analysis method, continuous power flow method and indirect method. The basic principle of the sensitivity method is to calculate the power flow equation to obtain the sensitivity of the system variables to the disturbance under small disturbances, thereby analyzing the system voltage stability. This method has the characteristics of simple solution and easy calculation in the voltage stability analysis of simple systems. However, in more complex power systems, it cannot keep the various criteria consistent, and the results obtained by each criterion cannot accurately judge the limit state of the system, and cannot reflect the distance between the normal operating state and the collapse state of the system; the principle of the singular value analysis method is to calculate the singular values ​​of the Jacobian matrix, using the minimum singular value. Outliers characterize the degree of stability of the operating state of the power system relative to the critical state of the system. This method cannot fully characterize the changing state of the system voltage from stability to collapse, and will affect the accuracy of the calculated value when the system exceeds the limit. The indirect rule quickly evaluates the system stability by constructing voltage stability indicators (such as L indicators, sensitivity indicators, etc.), but the accuracy is relatively low. The continuous power flow method (CPF) is currently a very widely used method for analyzing static voltage stability. This method overcomes the singularity problem of the Jacobian matrix at the critical point of voltage by introducing continuous parameters, and estimates the stability margin by gradually increasing the load through the prediction and correction method until the system approaches the voltage collapse point, but its calculation complexity is high.

[0004] In addition, with the widespread application of reactive power compensation equipment in power systems, such as static VAR compensators (SVCs) and static synchronous compensators (STATCOMs), these devices play an important role in improving system voltage stability and power factor. However, traditional evaluation methods often ignore the impact of reactive power optimization on voltage stability margin, and fail to fully consider the deviation from the actual operation of the power system caused by reactive power optimization, which cannot fully reflect the actual operation status and potential risks of the system, resulting in conservative or inaccurate evaluation results. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a method and system for evaluating the static voltage stability margin of a power system, which take reactive power optimization into consideration and improve the accuracy of the evaluation result of the static voltage stability margin of the power system.

[0006] To achieve the above object, an embodiment of the present invention provides a method for evaluating a static voltage stability margin of a power system, comprising:

[0007] Based on the initial state of the power system and the preset random proportional growth rule, the active output of all power nodes in the target voltage node area is obtained;

[0008] Based on the preset optimization algorithm, the reactive power optimization is performed on the target voltage node area to obtain the reactive power output of the power system;

[0009] Based on the reactive output of the power system, adjusting the active output of all power supply nodes in the target voltage node area by executing a preset search algorithm;

[0010] Updating the reactive output of the power system and the active output of all power supply nodes in the target voltage node area until the preset iteration requirements are met to obtain the static voltage stability limit power;

[0011] Based on the static voltage stability limit power and the active output of the target node in the initial state of the power system, the static voltage stability margin of the corresponding target node channel is evaluated.

[0012] The embodiment of the present invention proposes a method for evaluating the static voltage stability margin of a power system. The active output of all power supply nodes in a target node area is obtained through the initial state of the power system. The active output of all power supply nodes in the target node area that increases in a random proportion is simulated to improve the load level. The reactive output of the power system is obtained through an optimization algorithm for subsequent consideration, thereby improving the voltage stability and operation efficiency of the system. The active output of all power supply nodes in the target voltage node area is adjusted through a search algorithm. The power system output is then iterated to obtain a static voltage stability limit power. Reactive optimization and search adjustment are performed on the system state in the step-by-step iterations to improve the reliability and accuracy of subsequent evaluations. Finally, the static voltage stability margin is evaluated by comparing the iteratively obtained static voltage stability limit power with the active output of the power system in the initial state. The evaluation method that comprehensively considers the active growth ratio and reactive optimization can fully reflect the real operation state and potential risks of the system, and can more accurately reflect the voltage stability performance of the system under different operation states, thereby improving the accuracy of the evaluation result.

[0013] Furthermore, based on the initial state of the power system and the preset random proportional growth rule, the active output of all power supply nodes in the target voltage node area is obtained, specifically:

[0014] Obtain the operation section of the power system and construct the initial operation state of the power system;

[0015] Based on the initial operating state of the power system, obtaining a target voltage node area;

[0016] Based on a preset random proportional growth rule and a preset initial active output growth step, the active output of all power nodes in the target voltage node area is calculated.

[0017] Furthermore, based on the preset optimization algorithm, reactive power optimization is performed on the target voltage node area to obtain the reactive power output of the power system, specifically:

[0018] Calculate the minimum network loss based on the preset power system reactive power optimization model;

[0019] Based on minimum network loss and genetic algorithm, the reactive power optimization objective function model and fitness function model are constructed;

[0020] Based on the reactive power optimization objective function model and the fitness function model, reactive power optimization is performed on the target voltage node area to obtain the reactive power output of the power system.

[0021] Furthermore, based on the reactive power output of the power system, the active power output of all power supply nodes in the target voltage node region is adjusted by executing a preset search algorithm, specifically:

[0022] Based on the reactive power output of the power system, a power flow calculation is performed on the active power output of all power supply nodes under the target voltage node area to obtain a power flow convergence result;

[0023] Based on the power flow convergence result, the step length of the active output increase of all power nodes in the next iteration step is determined by a preset binary search method to obtain a search result;

[0024] Based on the search result, the active output of all power supply nodes in the target voltage node region is adjusted.

[0025] An embodiment of the present invention proposes a method for evaluating the static voltage stability margin of an electric power system. By introducing a rapid evaluation method for the static voltage stability margin based on an improved binary search, compared with the original binary search, the number of calculations and the calculation time can be effectively reduced, thereby achieving rapid evaluation of the static voltage stability margin and improving evaluation efficiency.

[0026] Further, based on the power flow convergence result, the step length of the active output growth of all power nodes in the next iteration step is determined by a preset binary search method, and the search results are obtained, specifically:

[0027] Based on the active output of all power nodes in the target voltage node area under the initial state of the power system, the lower limit of the search interval is obtained;

[0028] Constructing a search interval based on the search interval lower limit and a preset search interval upper limit;

[0029] Based on the search interval, obtain the search point;

[0030] Performing power flow calculation on the active power output of the search point to obtain a power flow convergence result;

[0031] Based on the power flow convergence result, the search interval is updated until the search interval width meets the preset accuracy requirement, and the search result is obtained.

[0032] Furthermore, the step of obtaining the search point based on the search interval is as follows:

[0033] Obtaining a search interval, dividing the search interval into a number of equal parts according to a preset division ratio, and obtaining a number of division points;

[0034] Further, based on the power flow convergence result, the search interval is updated until the search interval width meets the preset accuracy requirement, and the search results are obtained, specifically:

[0035] When the power flow convergence result is convergence, the search interval is updated with the search point as the lower limit of the search interval;

[0036] When the power flow convergence result is non-convergence, updating the search interval with the search point as the upper limit of the search interval;

[0037] The search interval is updated until the width of the search interval meets the preset accuracy requirement to obtain the search result.

[0038] Further, the reactive output of the power system and the active output of all power supply nodes in the target voltage node area are updated until the preset iteration requirements are met, and the static voltage stability limit power is obtained, which is specifically:

[0039] By updating the reactive output of the power system and the active output of all power supply nodes in the target voltage node area, the active output growth step of all power supply nodes in the target voltage node area is obtained;

[0040] The active output growth step size of all power supply nodes in the target voltage node region is updated until the preset iteration requirement is met, and all power supply nodes in the target voltage node region that meet the preset iteration requirement are read to obtain the static voltage stability limit power.

[0041] The embodiment of the present invention proposes a method for evaluating the static voltage stability margin of an electric power system. In the process of step-by-step searching and iterative process of the static stability limit power, reactive power optimization is performed in combination with the current system state. By adjusting the reactive output and active output of nodes with reactive power compensation capability, the voltage stability and power factor of the system are effectively improved.

[0042] Furthermore, based on the static voltage stability limit power and the active output of the target node in the initial state of the power system, the static voltage stability margin of the corresponding target node channel is evaluated, specifically:

[0043] Calculating a static voltage stability margin index based on the static voltage stability limit power and the active output of the target node in the initial state of the power system;

[0044] Based on the static voltage stability margin indicator, the static voltage stability margin of the corresponding target node channel is evaluated.

[0045] Based on the plurality of division points, one of the division points is used as a search point.

[0046] The embodiment of the present invention also provides a static voltage stability margin assessment system for a power system, comprising: an active output acquisition module, a reactive power optimization module, a search module, a limit power acquisition module and a stability margin assessment module;

[0047] The active output acquisition module is used to acquire the active output of all power supply nodes in the target voltage node area based on the initial state of the power system;

[0048] The reactive power optimization module is used to perform reactive power optimization on the target voltage node area based on a preset optimization algorithm to obtain reactive power output of the power system;

[0049] The search module is used to adjust the active output of all power supply nodes in the target voltage node area by executing a preset search algorithm based on the reactive output of the power system;

[0050] The limit power acquisition module is used to update the reactive output of the power system and the active output of all power supply nodes in the target voltage node area until the preset iteration requirements are met to obtain the static voltage stability limit power;

[0051] The stability margin evaluation module is used to evaluate the static voltage stability margin of the corresponding target node channel based on the static voltage stability limit power and the active output of the target node in the initial state of the power system.

[0052] The embodiment of the present invention proposes a static voltage stability margin assessment system for a power system, wherein an active output acquisition module acquires the active output of all power supply nodes in a target node area through an initial state of the power system, simulates the active output of all power supply nodes in the target node area that increases in a random proportion, and improves the load level; and a reactive power optimization module acquires the reactive output of the power system through an optimization algorithm for subsequent consideration, thereby improving the voltage stability and operation efficiency of the system; and a search module adjusts the active output of all power supply nodes in the target voltage node area through a search algorithm, and then the power system output is iteratively acquired through a limit power acquisition module to acquire a static voltage stability limit power, and reactive power optimization and search adjustment are performed on the system state in the stepwise iterations, thereby improving the reliability and accuracy of subsequent assessments; and finally, the static voltage stability limit power iteratively obtained through the stability margin assessment module and the active output of the power system in the initial state are used to implement the assessment of the static voltage stability margin; and through an assessment method that comprehensively considers the active growth ratio and reactive power optimization, the real operation state and potential risks of the system are fully reflected, and the voltage stability performance of the system under different operation states can be more accurately reflected. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a process flow of a method for evaluating a static voltage stability margin of a power system provided by an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of the principle flow of a method for evaluating static voltage stability margin of a power system provided by a certain embodiment of the present invention;

[0055] Figure 3 A schematic diagram of the principle of static voltage stability analysis based on a power flow algorithm of a prior art method for evaluating a static voltage stability margin of a power system provided by an embodiment of the present invention;

[0056] Figure 4 A schematic diagram of an improved dichotomy principle of a method for evaluating a static voltage stability margin of a power system provided by a certain embodiment of the present invention;

[0057] Figure 5 A schematic diagram of an improved binary search process of a method for evaluating a static voltage stability margin of a power system provided by a certain embodiment of the present invention;

[0058] Figure 6 A schematic diagram of the module structure of a power system static voltage stability margin assessment system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] In the field of power system analysis, a variety of methods have been developed for static voltage stability margin assessment, including sensitivity method, singular value analysis method, continuous power flow method and indirect method. 1. The basic principle of the sensitivity method is to calculate the power flow equation to obtain the sensitivity of the system variables to the disturbance under small disturbances, so as to analyze the system voltage stability. The more frequently used criteria are: dVL / dQL, dVL / dEG, dQG / dQL and dDQ / dVL, etc., where VL and QL are the voltage and reactive power of the load node, EG and QG represent the voltage and reactive power of the reactive source node respectively, and DQ represents the difference between the total reactive power injected by the load node and the reactive power demanded by the load. This method is easy to solve and calculate in the voltage stability analysis of simple systems, but in more complex power systems, it cannot keep the various criteria consistent, and the results of each criterion cannot accurately judge the limit state of the system, and cannot reflect the distance between the normal operation state and the collapse state of the system; 2. The principle of the singular value analysis method is to calculate the singular values ​​of the Jacobian matrix, and use the minimum singular value to characterize the stability of the power system operation state relative to the critical state of the system. This method is feasible for analyzing voltage stability in ACDC systems, but the singular value analysis method cannot fully characterize the change state of system voltage from stability to collapse, and when the system exceeds the limit, it will affect the accuracy of the calculated value; 3. The indirect rule quickly evaluates system stability by constructing voltage stability indicators (such as L indicators, sensitivity indicators, etc.), but the accuracy is relatively low. The optimization-based method attempts to introduce optimization algorithms into the evaluation process to improve the accuracy and efficiency of the evaluation; 4. The continuous power flow method (CPF) is currently a widely used method for analyzing static voltage stability. This method overcomes the singularity of the Jacobian matrix at the voltage critical point by introducing continuous parameters, and estimates the stability margin by gradually increasing the load through the prediction and correction method until the system approaches the voltage collapse point, but its calculation complexity is high. It can be seen that traditional evaluation methods often ignore the impact of reactive power optimization on the voltage stability margin, resulting in conservative or inaccurate evaluation results.

[0061] For further information, see Figure 3 , Figure 3 A schematic diagram of the principle of static voltage stability analysis based on a power flow algorithm is provided as a prior art of a method for evaluating static voltage stability margin of a power system according to an embodiment of the present invention; Figure 3As shown in the figure, in order to improve the evaluation efficiency, some scholars have proposed a fast evaluation technology based on approximate methods. These methods reduce the amount of calculation by simplifying the calculation model or using approximate algorithms, and need to make a compromise between evaluation accuracy and calculation efficiency. Commonly used methods include the dichotomy method and the equidistant halving method. The core idea of ​​this type of method is to continuously determine the load growth ratio through the above algorithm, and to find the system collapse point by continuously increasing the load level until it approaches the system collapse point, until the system collapse flow does not converge. It is worth mentioning that there are also static voltage stability assessments that consider combining reactive power optimization in the existing technology: However, most of the current research on combining voltage stability margin assessment and reactive power optimization focuses on the reactive power optimization algorithm itself, such as genetic algorithm, particle swarm optimization algorithm, etc., and the evaluation efficiency still needs to be improved; or more consideration is given to incorporating the static voltage stability margin index into the system reactive power optimization penalty item to improve the reactive power optimization benefit; In general, few studies have focused on the impact of reactive power optimization on the static voltage stability margin during the successive iterations of voltage stability margin assessment.

[0062] In the embodiment of the present invention, the static stability limit power P max It refers to the maximum active power transmission capacity of the system that can maintain stable operation without voltage collapse under given power system operating conditions. This parameter reflects the degree of proximity of the system to the voltage stability boundary under the combined effect of multiple factors such as network structure, generator output and load level. When the active power transmission in the system approaches or exceeds this limit, the system may enter an abnormal operating state due to voltage instability, resulting in voltage collapse and large-scale power outages. The embodiment of the present invention simulates the continuous growth of active output step by step through simulation experiments, and observes whether the system collapses to continuously approach this value, that is, the active output near the collapse point represents the corresponding static stability limit power.

[0063] Example 1

[0064] See also Figure 1 and Figure 2 , Figure 1 A schematic diagram of a process flow of a method for evaluating a static voltage stability margin of a power system provided by an embodiment of the present invention; Figure 2 The following is a schematic diagram of the principle flow of a method for evaluating the static voltage stability margin of a power system provided by a certain embodiment of the present invention. Figure 1 and Figure 2 As shown, the embodiment of the present invention proposes a method for evaluating the static voltage stability margin of a power system, including steps 101 to 105, each of which is specifically as follows:

[0065] Step 101, based on the initial state of the power system and a preset random proportional growth rule, the active output of all power supply nodes in the target voltage node area is obtained;

[0066] As an example of this embodiment, the operation section of the power system is obtained to construct the initial operation state of the power system; based on the initial operation state of the power system, the target voltage node area is obtained; based on the preset random proportional growth rule and the preset initial active output growth step, the active output of all power nodes under the target voltage node area is calculated. A specific implementation method is to use a certain operation section of the power system as the initial operation state, clearly select the power system area containing the target 220KV node, and set a random proportional growth rule a=[a1, a2,…, a n ], ensure that all power nodes increase their active output according to the random ratio, set the initial active output growth step k1, and calculate the active increase of all power nodes under the target 220KV node ΔP=[k1·a1,k1·a2,…,k1·a n ], adjust the system power node output accordingly based on the current system status; more specifically, the data source and 220KV node selection include the following steps: select the power flow file (dat file) under a certain section of the power system as the basic operating state, select the node that needs to be evaluated for static voltage stability margin as the target 220KV node according to the static voltage stability assessment requirements of the node channel (mainly for some 220KV nodes here), and screen all the power nodes in the area that are sent to the 220KV node. If there are n power nodes in total, then the active output of these n power nodes is simulated to increase continuously at a random ratio until the target 220KV node reaches the static stability limit power P max ; For the active power increase of n power nodes, ΔP = [k·a1, k·a2,…, k·a n ] specific explanation: where a i is the active power output growth ratio corresponding to the power node i, which does not change with the number of iterations after determination; k is the growth step of the active power output of all power nodes in this iteration, which changes with the number of iterations. As the number of iterations increases, the cumulative active power growth of n power nodes ΣΔP=∑k·[a1,a2,…,a n ] is also increasing, causing the corresponding 220KV node channel active power to increase continuously until it reaches the static stability limit power P of the 220KV node. max .

[0067] Step 102, based on a preset optimization algorithm, reactive power optimization is performed on the target voltage node area to obtain reactive power output of the power system;

[0068] As an example of this embodiment, based on the preset reactive power optimization model of the power system, the minimum network loss is calculated; based on the minimum network loss and the genetic algorithm, a reactive power optimization objective function model and a fitness function model are constructed; based on the reactive power optimization objective function model and the fitness function model, the target voltage node area is reactively optimized to obtain the reactive power output of the power system. A specific explanation is that based on the state determined in step 101, the target 220KV node area is reactively optimized based on the genetic algorithm, and the system state is adjusted accordingly according to the reactive power optimization result, that is, by adjusting the reactive output of the node with reactive power compensation capability, the system voltage stability and power factor are improved; the reference mathematical model of reactive power optimization of the power system is as follows:

[0069]

[0070] V i,min ≤V i ≤V i,max (i∈S B )

[0071] Q Gi,min ≤Q Gi ≤Q Gi ,max (i∈S G )

[0072] Q Ci,min ≤Q Ci ≤Q Ci ,max (i∈S C )

[0073] In equality and inequality constraints, S B , S G and S C Represent the system node set, the generator node number set and the compensation capacitor node set respectively. The equality constraint is the power balance constraint, P Gi , Q Gi represents the active and reactive output of the i-th generator, P Di , Q Di represents the active and reactive loads of the ith node, G ij , B ij represents the real and imaginary parts of the elements in the i-th row and j-th column of the node admittance matrix. The inequality constraints are the upper and lower limits of the node voltage, reactive power generation and compensation capacitor capacity. The first two are state variable constraints, and the latter is a control variable constraint. Ci is the reactive power output of compensation capacitor i, the subscript min represents the lower threshold, the subscript max represents the upper threshold, f Q is the network loss, represents the active power loss of branch ij, g ijis the conductance of branch ij, V i 、V j represents the voltage amplitude of nodes i and j, θ ij is the voltage phase angle difference between node i and node j.

[0074] Reactive power optimization based on genetic algorithm: When using genetic algorithm for optimization, select reactive power compensation value Q C As a control variable, we construct a Q A reactive power optimization model with minimum as the goal, power balance as the equality constraint, and node voltage, reactive power generation and the upper and lower limits of the capacity of the compensation capacitor as the inequality constraints. In the iterative process, by evaluating the fitness of each individual in the population according to the fitness function, high fitness solutions are continuously selected, thus gradually approaching the optimal solution of the problem.

[0075] Based on the genetic algorithm for reactive power optimization, the fitness function is constructed as follows:

[0076]

[0077] in,

[0078]

[0079] In the formula, the equality and inequality constraints are written into the original objective function f as penalty functions. Q To construct a new objective function F Q , where the penalty factor of the equality constraint penalty term is 10 5 , which means that once the power balance constraint is not satisfied, the objective function will be too large and the solution will be eliminated immediately, which is equivalent to a hard constraint; λ Vi , is the penalty factor of the corresponding inequality penalty term, which is equivalent to a soft constraint. The fitness function F of the genetic algorithm is fit With the objective function F Q The smaller the value of the objective function, the larger the value of the fitness function, and the better the solution, the closer it is to the optimal solution. Gi represents the reactive power output of the ith generator, V i Represents the voltage amplitude of node i, flag PQ is the indicator of whether the power balance constraint is satisfied, S B and S G They represent the system node set and the generator node number set respectively, and const is a constant, which takes a value of 1 in the embodiment of the present invention.

[0080] Step 103, based on the reactive power output of the power system, adjusting the active power output of all power supply nodes in the target voltage node region by executing a preset search algorithm;

[0081] As an example of this embodiment, based on the reactive output of the power system, the active output of all power supply nodes in the target voltage node area is calculated to obtain a power flow convergence result; based on the power flow convergence result, the step size of the active output increase of all power supply nodes in the next iteration step is determined by a preset binary search method to obtain a search result; based on the search result, the active output of all power supply nodes in the target voltage node area is adjusted. For a specific explanation, see Figure 5 , Figure 5 A schematic diagram of an improved binary search process of a method for evaluating a static voltage stability margin of a power system provided by a certain embodiment of the present invention; Figure 5 As shown, based on the system state after reactive power optimization in step 102, power flow calculation is performed, and based on the power flow convergence result, the step size of the active output growth of all power nodes in the next iteration step is determined by using an improved binary search method, and the system power node output is adjusted accordingly according to the search result.

[0082] As another example of this embodiment, a search interval is obtained, and the search interval is divided into several equal parts according to a preset division ratio to obtain several division points; based on the several division points, one of the division points is used as the search point. Based on the active output of all power supply nodes under the target voltage node area in the initial state of the power system, the lower limit of the search interval is obtained; based on the lower limit of the search interval and the preset upper limit of the search interval, a search interval is constructed; based on the search interval, a search point is obtained; a flow calculation is performed on the active output of the search point to obtain a flow convergence result; based on the flow convergence result, the search interval is updated until the width of the search interval meets the preset accuracy requirement, and the search result is obtained. When the flow convergence result is convergence, the search interval is updated with the search point as the lower limit of the search interval; when the flow convergence result is non-convergence, the search interval is updated with the search point as the upper limit of the search interval; the search interval is updated until the width of the search interval meets the preset accuracy requirement, and the search result is obtained. A specific explanation, in the embodiment of the present invention, the improved binary search method for static stability limit power P max Basic process: Determine the search interval: First, you need to determine a region that contains the static stability limit power P maxThe search interval is set. The initial active power level is set as the lower limit a of the interval, and a relatively high active power level is set as the upper limit b of the interval. The bisection method is applied for searching: After determining the search interval [a, b], the bisection method is used to search for the static stability limit power. The specific steps are as follows: Calculate the system state at the midpoint c = (a + b) / 2 of the interval. Conduct a power flow calculation to determine whether the power flow converges at the active power level of the midpoint c of the system; if the power flow converges at the midpoint c level of the system, it means that the static stability limit power > c, then update the search interval to [c, b]; if the power flow does not converge at the midpoint c level of the system, it means that the static stability limit power < c, then update the search interval to [a, c]; Repeat the above steps until the width of the search interval is less than the preset accuracy requirement or the maximum number of iterations is reached; Refer to Figure 4 , Figure 4 is a schematic diagram of the improved bisection method principle for a method for evaluating the static voltage stability margin of a power system provided by an embodiment of the present invention; As Figure 4 shown, the improvement of the bisection method is specifically explained as follows: When setting the bisection search interval, the initially set bisection search upper limit should be high enough to conservatively estimate the maximum stable power limit that any node in the system may reach. However, this strategy will result in low efficiency in the initial stage of the search for those nodes with relatively small stability margins themselves, because the algorithm will first explore power values far higher than their actual stability limits. Therefore, make appropriate improvements to the initial iteration of the bisection method. In the initial stage of the bisection method, instead of directly using the midpoint of the search interval as the starting trial point, the trial point in the initial stage is set at 1 / 4 of the search interval to more quickly approach the stability limits of those nodes with relatively small stability margins themselves and reduce unnecessary traversal of the search range. Until the first power flow converges, then retreat to 1 / 2 of the search interval. Specifically: The first search: Search at 1 / 4 of the original interval, that is, at S2. Conduct a power flow calculation. If the power flow does not converge, then update the search interval to [0, S2]; The second search: Search at 1 / 4 of the new interval [0, S2], that is, at S4. Conduct a power flow calculation. If the power flow converges, then update the search interval to [S4, S2]; The third search: Since the power flow converges for the first time at the previous search point, retreat to 1 / 2 of the new search interval, that is, search at 1 / 2 of the new interval [S4, S2], which is 15.625%; and so on. Update the search interval until the width of the search interval meets the preset accuracy requirement to obtain the search result. It is worth mentioning that the improved bisection method adopted in the embodiment of the present invention sets the trial point in the initial stage at 1 / 4 of the search interval. It is not only 1 / 4, but also other values less than 1 / 2, such as 1 / 5, 1 / 8, 1 / 10, etc.

[0083] Step 104, update the reactive power output of the power system and the active power outputs of all power source nodes in the target voltage node area until the preset iteration requirement is met to obtain the static voltage stability limit power;

[0084] As an example of this embodiment, by updating the reactive output of the power system and the active output of all power supply nodes in the target voltage node area, the active output growth step of all power supply nodes in the target voltage node area is obtained; the active output growth step of all power supply nodes in the target voltage node area is updated until the preset iteration requirement is met, and all power supply nodes in the target voltage node area that meet the preset iteration requirement are read to obtain the static voltage stability limit power. A specific explanation is to repeat steps 102 and 103 until the active output growth step of the power supply node in the current iteration step is less than the preset threshold or the maximum number of iterations is reached, and the active output of the target 220KV node channel at this time is read as the static voltage stability limit power P of the node. max ;

[0085] Step 105 , based on the static voltage stability limit power and the active output of the target node in the initial state of the power system, the static voltage stability margin of the corresponding target node channel is evaluated.

[0086] As an example of this embodiment, based on the static voltage stability limit power and the active output of the target node in the initial state of the power system, the static voltage stability margin index is calculated; based on the static voltage stability margin index, the static voltage stability margin of the corresponding target node channel is evaluated. A specific explanation is that according to the static voltage stability limit power P max The static voltage stability margin of the corresponding channel is calculated based on the active output P0 of the target node in the initial state of the system, and the static voltage stability margin of the power system considering reactive power optimization is quickly evaluated; for a certain 220KV node, the corresponding static voltage stability margin index is:

[0087]

[0088] Among them, P max is the static stability limit power of the node obtained according to the above steps, and P0 is the operating power of the node under the initial section.

[0089] The embodiment of the present invention proposes a method for evaluating the static voltage stability margin of an electric power system, which obtains the active output of all power supply nodes in a target node area through the initial state of the electric power system, simulates the active output of all power supply nodes in the target node area that increases in random proportion, improves the load level, and obtains the reactive output of the electric power system through an optimization algorithm for subsequent consideration, thereby improving the voltage stability and operation efficiency of the system, and further adjusts the active output of all power supply nodes in the target voltage node area through a search algorithm, and then iterates the output of the electric power system to obtain the static voltage stability limit power, and performs reactive optimization and search adjustment on the system state in the step-by-step iterations, thereby improving the reliability and accuracy of subsequent evaluations, and finally evaluates the static voltage stability margin through the iteratively obtained static voltage stability limit power and the active output of the electric power system in the initial state; through an evaluation method that comprehensively considers the active growth ratio and reactive optimization, the real operating state and potential risks of the system are fully reflected, and the system can be more accurately reflected in different The voltage stability performance under the operating state improves the accuracy of the evaluation results; by introducing a fast evaluation method for static voltage stability margin based on improved binary search, compared with the original binary search, it can effectively reduce the number of calculations and calculation time, realize the fast evaluation of static voltage stability margin, and improve the evaluation efficiency; in the step-by-step search and iteration process of the static stability limit power, reactive power optimization is performed in combination with the current system state, and the reactive output and active output of nodes with reactive compensation capability are adjusted to effectively improve the system voltage stability and power factor; in summary, the embodiment of the present invention innovatively integrates the reactive power optimization strategy in the successive iterative solution process of the static stability limit power, and improves the system voltage stability and power factor by adjusting the output of nodes with reactive compensation capability at each iteration, thereby improving the reliability and accuracy of the evaluation. In addition, in order to improve the calculation efficiency, the embodiment of the present invention also introduces an algorithm based on improved binary search, which effectively reduces the number of calculations and calculation time by optimizing the search strategy.

[0090] Example 2

[0091] See also Figure 6 , Figure 6 A schematic diagram of the module structure of a power system static voltage stability margin assessment system provided by an embodiment of the present invention. Figure 6 As shown, an embodiment of the present invention provides a static voltage stability margin assessment system for a power system, comprising:

[0092] Active power acquisition module 601, reactive power optimization module 602, search module 603, limit power acquisition module 604 and stability margin evaluation module 605;

[0093] The active output acquisition module 601 is used to acquire the active output of all power supply nodes in the target voltage node area based on the initial state of the power system;

[0094] The reactive power optimization module 602 is used to perform reactive power optimization on the target voltage node area based on a preset optimization algorithm to obtain reactive power output of the power system;

[0095] The search module 603 is used to adjust the active output of all power supply nodes in the target voltage node area by executing a preset search algorithm based on the reactive output of the power system;

[0096] The limit power acquisition module 604 is used to update the reactive output of the power system and the active output of all power supply nodes in the target voltage node area until the preset iteration requirements are met to obtain the static voltage stability limit power;

[0097] The stability margin evaluation module 605 is used to evaluate the static voltage stability margin of the corresponding target node channel based on the static voltage stability limit power and the active output of the target node in the initial state of the power system.

[0098] The embodiment of the present invention proposes a static voltage stability margin assessment system for a power system, wherein an active output acquisition module acquires the active output of all power supply nodes in a target node area through an initial state of the power system, simulates the active output of all power supply nodes in the target node area that increases in a random proportion, and improves the load level; and a reactive power optimization module acquires the reactive output of the power system through an optimization algorithm for subsequent consideration, thereby improving the voltage stability and operation efficiency of the system; and a search module adjusts the active output of all power supply nodes in the target voltage node area through a search algorithm, and then the power system output is iteratively acquired through a limit power acquisition module to acquire a static voltage stability limit power, and reactive power optimization and search adjustment are performed on the system state in the stepwise iterations, thereby improving the reliability and accuracy of subsequent assessments; and finally, the static voltage stability limit power iteratively obtained through the stability margin assessment module and the active output of the power system in the initial state are used to implement the assessment of the static voltage stability margin; and through an assessment method that comprehensively considers the active growth ratio and reactive power optimization, the real operation state and potential risks of the system are fully reflected, and the voltage stability performance of the system under different operation states can be more accurately reflected.

[0099] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0100] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0101] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

Claims

1. A method for evaluating static voltage stability margin of power system. It is characterized in that include: Based on the initial state of the power system and the preset random proportional growth rule, the active output of all power nodes in the target voltage node area is obtained; Based on the preset optimization algorithm, the reactive power optimization is performed on the target voltage node area to obtain the reactive power output of the power system; Based on the reactive output of the power system, adjusting the active output of all power supply nodes in the target voltage node area by executing a preset search algorithm; Updating the reactive output of the power system and the active output of all power supply nodes in the target voltage node area until the preset iteration requirements are met to obtain the static voltage stability limit power; Based on the static voltage stability limit power and the active output of the target node in the initial state of the power system, the static voltage stability margin of the corresponding target node channel is evaluated.

2. A method for evaluating static voltage stability margin of a power system according to claim 1, It is characterized in that The active output of all power supply nodes in the target voltage node area is obtained based on the initial state of the power system and the preset random proportional growth rule, specifically: Obtain the operation section of the power system and construct the initial operation state of the power system; Based on the initial operating state of the power system, obtaining a target voltage node area; Based on a preset random proportional growth rule and a preset initial active output growth step, the active output of all power nodes in the target voltage node area is calculated.

3. A method for evaluating static voltage stability margin of a power system according to claim 1, It is characterized in that Based on the preset optimization algorithm, reactive power optimization is performed on the target voltage node area to obtain the reactive power output of the power system, specifically: Calculate the minimum network loss based on the preset power system reactive power optimization model; Based on minimum network loss and genetic algorithm, the reactive power optimization objective function model and fitness function model are constructed; Based on the reactive power optimization objective function model and the fitness function model, reactive power optimization is performed on the target voltage node area to obtain the reactive power output of the power system.

4. A method for evaluating static voltage stability margin of a power system according to claim 1, It is characterized in that Based on the reactive power output of the power system, the active power output of all power supply nodes in the target voltage node area is adjusted by executing a preset search algorithm, specifically: Based on the reactive power output of the power system, a power flow calculation is performed on the active power output of all power supply nodes under the target voltage node area to obtain a power flow convergence result; Based on the power flow convergence result, the step length of the active output increase of all power nodes in the next iteration step is determined by a preset binary search method to obtain a search result; Based on the search result, the active output of all power supply nodes in the target voltage node region is adjusted.

5. A method for evaluating static voltage stability margin of a power system according to claim 4, It is characterized in that Based on the power flow convergence result, the step size of the active output growth of all power nodes in the next iteration step is determined by a preset binary search method, and the search results are obtained, specifically: Based on the active output of all power nodes in the target voltage node area under the initial state of the power system, the lower limit of the search interval is obtained; Constructing a search interval based on the search interval lower limit and a preset search interval upper limit; Based on the search interval, obtain the search point; Performing power flow calculation on the active power output of the search point to obtain a power flow convergence result; Based on the power flow convergence result, the search interval is updated until the search interval width meets the preset accuracy requirement, and the search result is obtained.

6. A method for evaluating static voltage stability margin of a power system according to claim 5, It is characterized in that The step of obtaining the search point based on the search interval is specifically as follows: Obtaining a search interval, dividing the search interval into a number of equal parts according to a preset division ratio, and obtaining a number of division points; Based on the plurality of division points, one of the division points is used as a search point.

7. A method for evaluating static voltage stability margin of a power system according to claim 5 or 6, It is characterized in that Based on the power flow convergence result, the search interval is updated until the search interval width meets the preset accuracy requirement, and the search results are obtained, specifically: When the power flow convergence result is convergence, the search interval is updated with the search point as the lower limit of the search interval; When the power flow convergence result is non-convergence, updating the search interval with the search point as the upper limit of the search interval; The search interval is updated until the width of the search interval meets the preset accuracy requirement to obtain the search result.

8. A method for evaluating static voltage stability margin of a power system according to claim 1, It is characterized in that Update the reactive output of the power system and the active output of all power supply nodes in the target voltage node area until the preset iteration requirements are met, and obtain the static voltage stability limit power, which is specifically: By updating the reactive output of the power system and the active output of all power supply nodes in the target voltage node area, the active output growth step of all power supply nodes in the target voltage node area is obtained; The active output growth step size of all power supply nodes in the target voltage node region is updated until the preset iteration requirement is met, and all power supply nodes in the target voltage node region that meet the preset iteration requirement are read to obtain the static voltage stability limit power.

9. A method for evaluating static voltage stability margin of a power system according to claim 1, It is characterized in that Based on the static voltage stability limit power and the active output of the target node in the initial state of the power system, the static voltage stability margin of the corresponding target node channel is evaluated, specifically: Calculating a static voltage stability margin index based on the static voltage stability limit power and the active output of the target node in the initial state of the power system; Based on the static voltage stability margin indicator, the static voltage stability margin of the corresponding target node channel is evaluated.

10. A static voltage stability margin assessment system for a power system, It is characterized in that include: Active power acquisition module, reactive power optimization module, search module, limit power acquisition module and stability margin assessment module; The active output acquisition module is used to acquire the active output of all power supply nodes in the target voltage node area based on the initial state of the power system; The reactive power optimization module is used to perform reactive power optimization on the target voltage node area based on a preset optimization algorithm to obtain reactive power output of the power system; The search module is used to adjust the active output of all power supply nodes in the target voltage node area by executing a preset search algorithm based on the reactive output of the power system; The limit power acquisition module is used to update the reactive output of the power system and the active output of all power supply nodes in the target voltage node area until the preset iteration requirements are met to obtain the static voltage stability limit power; The stability margin evaluation module is used to evaluate the static voltage stability margin of the corresponding target node channel based on the static voltage stability limit power and the active output of the target node in the initial state of the power system.

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