Alternating current and direct current hybrid multi-infeed system power grid strength calculation method and system

Abstract

The invention relates to the technical field of power system calculation control, in particular to a power grid strength calculation method and system for an alternating-current and direct-current hybrid multi-infeed system, and aims at constructing a current balance equation of the alternating-current and direct-current hybrid multi-infeed system and constructing a power grid characteristic vector value function according to the current balance equation. Power grid strength calculation is converted into a nonlinear optimization problem, and an objective function and constraint conditions are set by using the function. And solving by adopting an improved interior point method to obtain an extreme value of a power grid characteristic vector value, calculating the power grid strength of each feed-in node according to the extreme value, and taking the minimum value as the system power grid strength. And the voltage supporting capability and the stability margin of the system are accurately quantified.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution system calculation and control, and in particular to a method and system for calculating the power grid strength of an AC / DC hybrid multi-feed system. Background Art

[0002] With the large-scale integration and long-distance transmission of renewable energy, the penetration of power electronic interface devices in modern power systems has increased significantly, leading to a shift from a synchronous-dominated grid to a heterogeneous one. However, the lack of reactive power support capabilities in power electronic converters reduces the voltage support capability of AC / DC hybrid systems and increases the risk of voltage instability for newly connected equipment. Power electronic equipment is highly dependent on and sensitive to the voltage at the grid-connected node, especially PLL-based converters, which have limited overcurrent tolerance. When the voltage deviates from the normal operating range, the converter may disconnect from the grid. Similarly, LCC-HVDC systems will enter low-voltage current limiting control mode when the bus voltage is too low. Therefore, quantifying the voltage support strength of AC / DC hybrid systems is crucial to ensuring their safe operation.

[0003] Existing technologies primarily focus on the short circuit ratio (SCR) metric and its improved methods. These metrics are widely used to assess grid strength, and their main implementation solutions can be summarized as follows. First, node metrics modify traditional SCR calculation methods using power ratios and interaction factors, deriving critical values ​​for single-infeed systems. Typical interaction factors include the multi-infeed voltage interaction factor (MVIF) and the hybrid power sensitivity factor (HPSF). Related improved metrics include MIESCR, HIESCR, and QESCR. Second, modal metrics are constructed based on eigenvalue analysis of the system Jacobian matrix, such as the generalized short circuit ratio (GSCR). These metrics reflect the critical voltage stability of the system through the minimum eigenvalue and have been gradually extended to heterogeneous systems and real-time assessment applications. Third, other matrix analysis methods include grid strength indices based on matrix norms and impedance indices based on system eigentrajectory.

[0004] However, current research on AC / DC hybrid multi-infeed systems still has the following shortcomings: (1) Lack of equilibrium point existence conditions: Due to the commutation requirements of the DC converter and the deep coupling of AC and DC devices, the existence of the equilibrium point of the AC / DC hybrid multi-infeed system is affected by more factors. Existing methods mostly propose local analysis for independent AC / DC systems, but lack a systematic equilibrium point existence theory. In particular, in the AC / DC deeply coupled multi-infeed scenario, the specific conditions for the existence of the equilibrium point are not clearly defined.

[0005] (2) Limitations of the short-circuit ratio indicator: The short-circuit ratio (SCR) is a traditional indicator for evaluating grid strength and has been widely used in power electronics penetration systems in recent years. However, the traditional SCR and its improved versions are mostly targeted at single AC / DC systems and are difficult to capture the complexity brought about by AC / DC coupling. At the same time, the critical values ​​of different SCR indicators lack uniformity, which greatly reduces their applicability in AC / DC hybrid systems.

[0006] (3) Lack of calculation methods for grid strength indicators: In recent years, the definition of grid strength has been based on mathematical theories (such as Brouwer's fixed point theorem). However, these theoretical indicators often remain at the conceptual level and lack specific calculation methods, which limits their practical application in AC / DC hybrid multi-infeed systems. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to address the deficiencies in the above-mentioned prior art and provide a method and system for calculating the grid strength of an AC / DC hybrid multi-infeed system, so as to solve the technical problem that the application of multi-infeed systems is limited due to the lack of existing grid strength calculation methods.

[0008] The purpose of the present invention is achieved by the following technical solutions: In a first aspect, the present invention provides a method for calculating the grid strength of a DC-AC hybrid multi-infeed system, comprising: constructing a current balance equation of the system according to the topology, device parameters and control strategy of the DC-AC hybrid multi-feed system; and constructing a grid characteristic vector value function according to the current balance equation; The grid strength calculation problem is transformed into a nonlinear optimization problem, and the objective function and constraints are set according to the grid characteristic vector value function; The improved interior point method is used to solve the nonlinear optimization problem and obtain the extreme value of the grid characteristic vector value. The grid strength of each feeding node is calculated based on the extreme value of the grid characteristic vector value, and the minimum grid strength in each feeding node is taken as the grid strength of the DC-AC hybrid multi-feed system.

[0009] As a further improvement of the present invention, a grid characteristic vector value function is constructed according to the current balance equation, specifically including: The constraints determine the feed-in nodes of the DC-AC hybrid multi-feed system and the voltage and current values ​​of each feed-in node, and the current balance equation is determined based on the voltage and current values ​​of each feed-in node; Define the grid characteristic vector value function from the current balance equation according to the implicit function theorem; The grid characteristic vector value function is:

[0010]

[0011] Where, is a vector-valued function; is the characteristic component of the vector-valued function corresponding to the kth feed-in node; is the d-axis component of the system active current in the dq coordinate system; is the q-axis component of the system reactive current in the dq coordinate system; is the d-axis component of the active current at the m-th feeding point in the dq coordinate system; is the q-axis component of the reactive current at the m-th feeding point in the dq coordinate system.

[0012] As a further improvement of the present invention, setting the objective function and constraint conditions according to the grid characteristic vector value function specifically includes: The objective function is the extreme value of the grid characteristic vector value function; The constraints are the current and voltage constraints of the devices corresponding to each feeding node; the constraint expressions are:

[0013]

[0014] Where, is the square of the d-axis component of the characteristic component function of the k-th feeding node, is the square of the q-axis component of the characteristic component function of the k-th feeding node; is the square of the maximum value of the current fed into the kth node; is the minimum voltage amplitude of the kth feeding node; is the maximum voltage amplitude of the kth feeding node; is the d-axis current injection value of the device connected to the mth feeding node; is the q-axis current injection value of the device connected to the mth feeding node.

[0015] As a further improvement of the present invention, the grid strength calculation problem is transformed into a nonlinear optimization problem, which is:

[0016] Where, is the objective function; is the equality constraint; is an inequality constraint; is the upper limit of the constraint; is the lower bound constraint, is a constraint condition.

[0017] As a further improvement of the present invention, the improved interior point method specifically includes: Introducing non-negative slack variables to convert constraints in the nonlinear optimization problem into equality constraints; converting the equality constraints into logarithmic barrier functions, introducing the logarithmic barrier function and logarithmic parameters into the objective function, and updating the objective function in the nonlinear optimization problem; Construct the Lagrangian function based on the updated objective function and nonlinear optimization problem, and establish the KKT condition; The Newton method is used to iteratively calculate the Lagrangian function under KKT conditions to obtain the extreme value of the grid characteristic vector value component function, and the extreme value of the grid characteristic vector value function is obtained according to the extreme value of the grid characteristic vector value component function.

[0018] As a further improvement of the present invention, the Newton method is used to iteratively calculate the Lagrangian function under the KKT condition, specifically including: In each iteration, the Newton method is used to linearize the KKT conditions, solve the modified equations under the linearized KKT conditions, and determine the update direction; The primary and dual variables are dynamically adjusted along the update direction based on the step size, and the barrier parameters are updated at the same time to ensure the non-negativity of the slack variables until the calculation is terminated when the convergence conditions are met.

[0019] As a further improvement of the present invention, the grid strength corresponding to the feed-in node is:

[0020] Where, is the grid strength corresponding to the kth feeding node; is the open-circuit voltage of the kth feed point, and are the maximum and minimum operating voltages allowed for the kth feed node, and These are the upper and lower bounds of the grid characteristic function of the kth feeding node.

[0021] In a second aspect, the present invention provides a system for calculating the grid strength of a DC-AC hybrid multi-infeed system, which is used to implement the above-mentioned method for calculating the grid strength of a DC-AC hybrid multi-infeed system, comprising: A system model building module constructs the current balance equation of the system based on the topology, device parameters and control strategy of the DC-AC hybrid multi-infeed system; and constructs a grid characteristic vector value function based on the current balance equation; The grid strength objective function module converts the grid strength calculation problem into a nonlinear optimization problem and sets the objective function and constraints based on the grid characteristic vector value function; The grid strength calculation module uses an improved interior point method to solve the nonlinear optimization problem and obtain the extreme value of the grid characteristic vector value. The grid strength of each feeding node is calculated based on the extreme value of the grid characteristic vector value, and the minimum grid strength value of each feeding node is used as the grid strength of the DC-AC hybrid multi-feed system.

[0022] In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, enable the computing device to perform the above-mentioned method for calculating the grid strength of the DC-AC hybrid multi-feed system.

[0023] In a fourth aspect, the present invention provides a computing device, comprising: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the above-mentioned method for calculating the grid strength of the DC-AC hybrid multi-feed system.

[0024] The beneficial effect of the present invention is that the calculation method of the power grid strength of the DC-AC hybrid multi-feed system of the present invention can realize fast, efficient and accurate power grid strength assessment. By constructing the current balance equation and the power grid characteristic vector value function, and converting the power grid strength calculation into a nonlinear optimization problem solution, the present invention can accurately obtain the power grid strength of each feed node and the overall power grid strength of the system, providing a reliable quantitative basis for system operation and planning. For example, when planning a new transmission line, based on accurate power grid strength data, the line capacity can be reasonably determined to avoid waste or shortage of resources. By using the improved interior point method to solve the nonlinear optimization problem, the extreme value of the power grid characteristic vector value can be quickly obtained, and then the power grid strength can be efficiently calculated, the calculation efficiency and accuracy can be improved, and it can be compared with the critical power grid strength to accurately quantify the voltage support capability and stability margin of the system. Compared with traditional methods, the present invention greatly reduces the calculation time, does not rely on linearization assumptions, and is suitable for complex AC-DC hybrid systems. This method provides reliable technical support for the safe grid connection of new energy equipment, system planning and operation optimization, and is particularly suitable for modern power systems with a high proportion of power electronic equipment penetration.

[0025] Furthermore, addressing the nonlinear characteristics of AC / DC hybrid systems and the complex coupling between devices, a condition for the existence of equilibrium points in multi-infeed systems was proposed to ensure that the system maintains static voltage stability when connected to a variety of devices. This provides a more comprehensive means of evaluating the voltage support capability of the system, effectively reducing the risk of voltage instability and significantly improving the safety and reliability of grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 It is a flow chart of a method for calculating the grid strength of a DC-AC hybrid multi-feed system according to the present invention.

[0028] Figure 2 It is a structural diagram of the IEEE118-node AC / DC hybrid system of the present invention.

[0029] FIG3 shows the voltage changes at the feed point in different scenarios using the method of the present invention; (a) shows the voltage changes in scenario 2; (b) shows the voltage changes in scenario 3; (c) shows the voltage changes in scenario 4; and (d) shows the voltage changes in scenario 5.

[0030] Figure 4 This is a curve diagram of the voltage change at the feed-in point when the LCC-HVDC of the present invention is connected.

[0031] Figure 5 This is a curve diagram of the voltage change at the feed-in point when new energy is connected to the present invention.

[0032] Figure 6 It is a schematic diagram of the voltage change at the feed-in point when the ZIP load of the present invention is connected.

[0033] Figure 7 It is a schematic structural diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose and technical solution of the present invention clearer and easier to understand, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] The technical solutions of the present invention will be described clearly and completely below with reference to the accompanying drawings and specific embodiments. The described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0036] Example 1 like Figure 1As shown, this embodiment provides a method for calculating the grid strength of a DC / AC hybrid multi-infeed system. This method fully considers the interaction between power electronic devices, proposes conditions for the existence of equilibrium points in AC / DC hybrid multi-infeed systems, and proposes a fast calculation method for grid strength based on the interior point method to accurately quantify the voltage support capability and stability margin of the grid.

[0037] First, this embodiment considers the voltage-sensitive characteristics of renewable energy and DC devices. It constructs the system's current balance equation based on the topology, device parameters, and control strategy of the DC-AC hybrid multi-infeed system. This fully captures the nonlinear interactions between power electronic devices. A vector-valued function of the grid characteristics is then constructed based on the current balance equation.

[0038] The AC / DC hybrid multi-feedback system in this embodiment has n nodes, including multiple high-voltage direct current transmission lines (LCC-HVDC and VSC-HVDC), multiple new energy power generation equipment (such as photovoltaic power generation, wind power generation), synchronous generators, loads and other equipment. These devices are connected to the system through multiple grid-connected nodes, and the AC / DC devices are deeply coupled through the power grid. In the AC / DC hybrid multi-feedback system, due to the differences in the operating characteristics of the AC / DC devices and the complexity of their mutual interactions, the system must provide sufficient voltage support capabilities to ensure that all connected devices can operate within their stable operating range. In particular, for multi-feedback scenarios, assuming that the first m nodes are feed-in nodes, the system is required to have a balance point for all grid-connected bus voltages within the specified operating range after multiple devices are connected. Then, the current balance equation is: (1) (2) (3) (4) in and are the network admittance matrix and node voltage amplitude, Indicates local Coordinate system and global The angular difference between the coordinate systems, Returns an n×n diagonal matrix whose diagonal elements are , is a unit vector of length n, and Connect to the Node devices Axis and Axis current injection values, which depend on the voltage amplitudes at the corresponding nodes and device characteristic functions and . is the active current component fed into the device, usually determined by the power demand of the device, It is the reactive current component fed into the device and is relevant to voltage regulation and device control strategies.

[0039] This embodiment applies the Brouwer fixed point theorem to an AC / DC hybrid multi-infeed system, and can transform the voltage stability problem of the system into a fixed point problem.

[0040] Determine the feed-in node of the DC / AC hybrid multi-feed system and the voltage and current values ​​of each feed-in node according to the constraint conditions, and determine the current balance equation according to the voltage and current values ​​of each feed-in node; Define the grid characteristic vector value function from the current balance equation according to the implicit function theorem; Among them, the grid characteristic vector value function is: (5) (6) Where, is a vector-valued function; is the characteristic component of the vector-valued function corresponding to the kth feed-in node; is the d-axis component of the system active current in the dq coordinate system; is the q-axis component of the system reactive current in the dq coordinate system; is the d-axis component of the active current at the m-th feeding point in the dq coordinate system; is the q-axis component of the reactive current at the m-th feeding point in the dq coordinate system. It is a comprehensive reflection of the nonlinear behavior of the system, combining the admittance characteristics of the network, the current distribution of the feeding device and the interaction of the load. In actual engineering, the current injection capability of the feeding device is limited by its rated power and control strategy. The maximum allowable current of each feeding device is is known, and its constraints can be expressed as: (7) The grid characteristic vector value function describes the nonlinear mapping relationship between the voltage amplitude at the feed point and the injected current at the feed point. At this time, the solution to the equilibrium point is converted into an existence proof of the fixed point problem. This method has the following advantages: First, it does not need to rely on linearization assumptions, so it can more accurately reflect the nonlinear characteristics of the system; second, the mathematical rigor of Brouwer's fixed point theorem makes its analysis results more reliable; finally, this method can directly give the sufficient conditions for the existence of the system's equilibrium point within the static voltage stability range, thereby providing a theoretical basis for judging the operating status of the system after the multi-feed device is connected. Specifically, if the grid characteristic function It is a continuous mapping from the feed current constraint set to itself, and the range of the mapping is completely within the constraint set. According to Brouwer's fixed point theorem, the equilibrium equation must have at least one equilibrium point, which corresponds to the following conclusion: Assume that the device is at the feed point The voltage amplitude Under this condition, the injected current satisfies a set of functional characteristics, and each component of the vector valued function Value range , then there must be a voltage balance point in the multi-infeed system.

[0041] For each feed point , component function It represents the injection current characteristic associated with the node, and its specific expression is: (8) Secondly, the grid strength calculation problem is transformed into a nonlinear optimization problem, and the objective function and constraints are set according to the grid characteristic vector-valued function.

[0042] The grid strength calculation problem is transformed into a nonlinear optimization problem. The nonlinear optimization problem is: (9) Where, is the objective function; is the equality constraint; is an inequality constraint; is the upper limit of the constraint; is the lower bound constraint, is a constraint condition.

[0043] The injection current amplitude of each feed point device is limited by physical characteristics, and its limiting relationship is: (10) That is, the amplitude of the injected current does not exceed the maximum value specified by a certain device. According to the current injection constraint and the node voltage amplitude constraint, the component function of the feed point device is The value range of is: (11) Where, is the square of the d-axis component of the characteristic component function of the k-th feeding node, is the square of the q-axis component of the characteristic component function of the k-th feeding node; is the square of the maximum value of the current fed into the kth node; is the minimum voltage amplitude of the kth feeding node; is the maximum voltage amplitude of the kth feeding node; is the d-axis current injection value of the device connected to the mth feeding node; is the q-axis current injection value of the device connected to the mth feeding node.

[0044] Furthermore, the component functions of all feeding points are extended to the whole system, which can be expressed as a multivariable function: (12) in The range of the value is , that is, the voltage amplitude of all feeding points is limited to and .

[0045] Component Function is the injected current and is a continuous function, and and Node voltage again is a continuous function of . Therefore, It's about Therefore, the continuous function Will Mapped onto itself, according to Brouwer's fixed point theorem, There must be at least one fixed point, that is, satisfy: (13) (14) The voltage amplitude at the feed point satisfies And under the premise that the vector-valued function meets the continuity conditions, the system must have at least one equilibrium point.

[0046] The improved interior point method is used to solve the nonlinear optimization problem and obtain the extreme value of the grid characteristic vector value. The grid strength of each feeding node is calculated based on the extreme value of the grid characteristic vector value, and the minimum grid strength in each feeding node is taken as the grid strength of the DC-AC hybrid multi-feed system.

[0047] Specifically, the improved interior point method includes: Introducing non-negative slack variables to convert constraints in the nonlinear optimization problem into equality constraints; converting the equality constraints into logarithmic barrier functions, introducing the logarithmic barrier function and logarithmic parameters into the objective function, and updating the objective function in the nonlinear optimization problem; Construct the Lagrangian function based on the updated objective function and nonlinear optimization problem, and establish the KKT condition; The Newton method is used to iteratively calculate the Lagrangian function under KKT conditions to obtain the extreme value of the grid characteristic vector value component function, and the extreme value of the grid characteristic vector value function is obtained according to the extreme value of the grid characteristic vector value component function.

[0048] In each iteration, the Newton method is used to linearize the KKT conditions, solve the modified equations under the linearized KKT conditions, and determine the update direction; The primary and dual variables are dynamically adjusted along the update direction based on the step size, and the barrier parameters are updated at the same time to ensure the non-negativity of the slack variables until the calculation is terminated when the convergence conditions are met.

[0049] Specifically, we first introduce a non-negative slack variable and , transforming the inequality constraints into equality constraints. Then, the non-negative constraints of the slack variables are replaced by logarithmic barrier functions and combined with the barrier parameters By introducing the Lagrange multiplier 、 and , the Lagrangian function expression for the equality constraint barrier problem for: (15) For the Lagrangian function, the KKT (Karush-Kuhn-Tucker) condition is: (16) in is a vector of all 1s of appropriate size. The Newton method is usually used to solve the nonlinear KKT optimal conditions. By linearizing the KKT conditions, the Newton direction can be obtained by solving the following correction equation in each iteration : (17) in , , , represents the identity matrix of appropriate dimensions. Subsequently, the principal and dual variables are and Updates are performed along the Newton direction. To ensure that the slack variables and Strictly positive, and It is calculated as follows: (18) After the KKT condition is met, the barrier parameters are updated through the following adaptive strategy, and the calculation expression is: (19) The iterative process will terminate after the required convergence conditions are met. After the extreme value of the vector-valued component function of the grid characteristic is solved by the interior point method, the grid strength of each feeding node is calculated.

[0050] In a multi-infeed system, grid strength is a key indicator for measuring the system's voltage support capability. It comprehensively reflects the support provided by each infeed point to the grid under different voltage conditions. Compared to a single-infeed system, a multi-infeed system is more complex because the voltages at each infeed point have an interrelated impact on the overall stability of the system. Therefore, grid strength is not determined by just one infeed point, but by the minimum support capability of all infeed points. Grid strength (GS) is defined by the minimum grid strength of all infeed points: (20) Where m is the number of feed-in points in the system. The grid strength at each feed-in point is Determined by its voltage support capability.

[0051] The grid strength of the kth feed-in point is quantified by comparing the maximum and minimum voltage support capabilities of the feed-in point. The grid strength corresponding to the feed-in node is: (twenty one) Where, is the grid strength corresponding to the kth feeding node; is the open-circuit voltage of the kth feed point, and are the maximum and minimum operating voltages allowed for the kth feed node, and These are the upper and lower bounds of the grid characteristic function of the kth feeding node.

[0052] Boundary value under the condition of maximum current injected into a given feeding point and They are: (twenty two) (twenty three) The grid strength of a multi-infeed system not only considers the voltage support capability of each feed-in point but also reflects the relative importance of each feed-in point in the grid. The minimum grid strength determines the voltage support capability of the entire system; that is, the weakest feed-in point limits the stability of the entire system. Therefore, it can comprehensively assess the system's voltage support capability. When the system's grid strength is low, it means that the system's voltage support capability is weak, which may cause the system to be unable to maintain voltage stability when disturbed. Higher grid strength indicates that the system has stronger support capabilities and a larger stability margin, thereby improving system reliability and stability, especially in the event of load fluctuations or external disturbances.

[0053] The calculation method of the DC-AC hybrid multi-feed system power grid strength provided by the present invention is further explained below with reference to application examples: For example, Figure 2 As shown, the revised IEEE 118-node receiving system verifies the accuracy of the grid strength calculation based on the interior point method. This system, based on the original IEEE 118-node system, has been modified to incorporate a high proportion of renewable energy generation and DC feed-in lines to better reflect the complex scenarios of high penetration of power electronic equipment in modern power systems. The system consists of 186 lines, 13 synchronous generators, 3 phase-converting units, 18 renewable energy generation units, and 77 ZIP loads. To simulate a high proportion of renewable energy integration, the system's renewable energy output accounts for over 70%. Furthermore, the system includes three DC feed-in lines, whose inverter sides are connected to busbars 89, 100, and 111, respectively. These busbars are located in area C of the receiving system. Constant power is used on the rectifier side of the inverter and constant arc-off angle control is used on the inverter side. The base power of the entire system is 100 MW and can be roughly divided into three areas: areas A, B, and C. The rated voltages of areas A and B are 500 kV, and area C is 750 kV. As a high-voltage area, Area C not only hosts the inverter-side connection points of three DC lines but also plays an important voltage support role in the overall system. Its complex AC / DC hybrid system structure enables it to truly reflect the characteristics of the deep coupling of AC and DC equipment in modern power systems.

[0054] Will Figure 2Busbars 75, 82, 102, and 106 in the multi-infeed system are used as feed-in points to verify the effectiveness of grid strength indicators in characterizing the balance point of the multi-infeed system. Considering the complex interactions between feed-in points, different maximum allowable current combination scenarios for feed-in points 75, 82, 102, and 106 are set: [0.5, 0.5, 0.5, 0.5], [1.5, 0.5, 0.5, 0.5], [0.5, 1.5, 0.5, 0.5], [0.5, 0.5, 1.5, 0.5], and [0.5, 0.5, 0.5, 1.5], and are named Scenarios 1 to 5. The boundary values ​​of the feed-in point grid characteristic functions under different scenarios are shown in Table 1. At the same time, it is known that the voltage allowable operating range of buses 75, 82, 102 and 106 is [0.9, 1.1], and the initial voltages are 0.9898, 0.9836, 0.9977 and 1.0031, respectively. The calculated grid strength of the multi-infeed system is shown in Table 1.

[0055] Table 1 System grid strength under different scenarios

[0056] Table 1 shows that the grid strength of scenarios 1 to 3 and 5 is greater than 1. According to the existence conditions of the multi-feed system balance point, any device that meets the node current requirements will have an operating balance point after being connected to the grid at the same time. However, the grid strength of scenario 4 is less than 1, and it cannot be guaranteed that there will be an operating balance point after multiple devices are connected to the grid at the same time. By comparing the results of scenarios 2 to 5, it can be seen that the voltage support capacity of bus 101 is the weakest, which is the key factor affecting the existence of the system balance point. In addition, it can be found from Table 1 that the interaction between feeding bus 101 and 102 is greater than that between other feeding busbars, which is the same as the Figure 1 The electrical distance results between the feeding busbars shown in are consistent, indicating that the grid characteristic function proposed in this embodiment can accurately characterize the interaction between the feeding devices.

[0057] To analyze the validity of these results, this experiment connected DC power to node 75, renewable energy to node 82, and ZIP loads to node 102 and 106 in scenarios 2 through 5. The infeed bus voltages obtained using Simulink simulation are shown in Figure 3. After the devices in scenarios 2, 3, and 5 in Figure 3 were connected, the system transitioned smoothly to a balance point within the permitted voltage range. However, in scenario 4, bus 101's voltage support capacity was insufficient, preventing the connected loads from operating within the permitted voltage range, posing a risk to system safety and stability. This validated the validity of the conditions for the existence of a balance point in a multi-infeed distribution network and the correctness of the grid strength indicator calculations.

[0058] In order to make the grid strength index effectively applied to engineering planning research, it has accurate and objective critical values ​​and good robustness. For this purpose, the grid strength proposed in this embodiment is compared with the accuracy of MESCR, MIESCR, EESCR, gSCR and IESCR indicators in different scenarios. Figure 2 The four feeding points in the system are connected to devices of the same type and capacity at the same time. Figures 4 to 6 The figure plots the changes in the feed-in point voltage and each indicator value with the equipment injection current when LCC-HVDC, new energy and load are connected to the system.

[0059] from Figure 4-Figure 6 As can be seen in the figure, all indicators show a downward trend as the device injection current increases, verifying the rationality of the above indicators in representing the system voltage support strength. However, when the feed-point voltage exceeds the allowable node voltage range, only the grid indicator proposed in this embodiment is less than the corresponding critical value, while the actual values ​​of the other indicators are still greater than the recommended critical values. Therefore, the grid strength indicator proposed in this embodiment can more accurately characterize the existence of the system's equilibrium point within the allowable voltage range than other indicators.

[0060] To verify the efficiency advantage of the interior point method in grid strength calculation, this example compares the calculation time of the grid strength calculation method based on the continuous power flow method, the simulation method, and the interior point method in a modified 118-node system. The time comparison results are summarized in Table 2 below: Table 2 Grid strength calculation time based on different methods

[0061] It can be seen from Table 2 that the calculation time of the interior point method is significantly lower than that of the continuous power flow method and the simulation-based calculation method. This is because the continuous power flow method finds the voltage stability limit point of the power grid by gradually adjusting the load and power. Although it can accurately evaluate the static stability, it is less efficient when dealing with large-scale systems due to the need for multiple power flow iterations; and the simulation-based method simulates the power grid operation characteristics through dynamic modeling. Although it can better characterize the dynamic characteristics of power electronic equipment, it consumes more time due to the complexity of the model and high computational cost. The interior point method adopted in the present invention converts the calculation of power grid strength into an optimization problem, and combines it with the efficient solution of the Karush-Kuhn-Tucker (KKT) condition to achieve rapid convergence, significantly improve the computational efficiency, and verify the effectiveness of the AC / DC hybrid system power grid strength calculation based on the interior point method proposed in this embodiment.

[0062] Example 2 This embodiment further provides a system for calculating the grid strength of a DC-AC hybrid multi-infeed system, including the following modules: A system model building module constructs the current balance equation of the system based on the topology, device parameters and control strategy of the DC-AC hybrid multi-infeed system; and constructs a grid characteristic vector value function based on the current balance equation; The grid strength objective function module converts the grid strength calculation problem into a nonlinear optimization problem and sets the objective function and constraints based on the grid characteristic vector value function; The grid strength calculation module uses an improved interior point method to solve the nonlinear optimization problem and obtain the extreme value of the grid characteristic vector value. The grid strength of each feeding node is calculated based on the extreme value of the grid characteristic vector value, and the minimum grid strength value of each feeding node is used as the grid strength of the DC-AC hybrid multi-feed system.

[0063] The system in this embodiment is mainly used to implement the calculation method of the DC-AC hybrid multi-feed system grid strength in Example 1.

[0064] Example 3 In another embodiment of the present invention, a computer-readable storage medium is provided as a storage component within a terminal device, the function of which is to store programs and data. It should be noted that the computer-readable storage medium herein encompasses not only the built-in storage component of the terminal device, but also the extended storage component supported by the device. Essentially, it is a tangible medium that can contain or store programs that can be called by, or run in conjunction with, an instruction execution system, device, or component. This storage medium provides a storage area for the terminal's operating system and stores one or more instructions suitable for loading and executing by the processor. These instructions can constitute one or more computer programs containing program code.

[0065] In particular, examples (a non-exclusive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable magnetic disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, optical fiber, a portable optical disc read-only memory, an optical storage device, a magnetic storage device, or any reasonable combination of the foregoing.

[0066] The storage medium may also include a data signal transmitted as part of a baseband portion or carrier wave, which carries readable program code. Such a transmitted data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any reasonable combination of the two. In addition, computer-readable storage media may also refer to other readable media other than traditional readable storage media, which are capable of sending, transmitting, or transmitting programs for use by or in conjunction with an instruction execution system, device, or device. The program code on the storage medium may be transmitted via any suitable medium, including but not limited to wireless, wired, optical cable, or any reasonable combination thereof.

[0067] The program code used to implement the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as "C." The program code can be executed entirely on the user's computing device, partially on the user's device as a standalone software package, partially distributed across the user's device and a remote computing device, or entirely on a remote computing device or server. When a remote computing device is involved, the device may be connected to the user's computing device via any type of network, such as a local area network or wide area network, or connected to an external computing device via the Internet through an Internet service provider.

[0068] The processor is capable of loading and executing one or more instructions stored in a computer-readable storage medium to implement corresponding steps of the method for calculating the grid strength of the DC-AC hybrid multi-feed system described in Example 1.

[0069] Example 4 Reference Figure 7 Another embodiment of the present invention provides a terminal device, which is specifically a computer device 60. This computer device 60 is mainly composed of three parts, namely a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and capable of running on the processor 61. Among them, the processor 61 is responsible for executing the computer program to implement the method for calculating the grid strength of the DC-AC hybrid multi-feed system described in Example 1. The memory 62 is used to store computer programs and other programs and data required for the operation of the device. When the computer program 63 runs on the processor 61, it can implement the method for calculating the grid strength of the DC-AC hybrid multi-feed system. In order to avoid repetition of content, the relevant details will not be described in detail here.

[0070] The computer device 60 has many different forms. It can be a desktop computer, a notebook computer, a handheld computer, or a computing device such as a cloud server.

[0071] The processor 60 may be a central processing unit, or other types of general-purpose processors, central processing units, graphics processing units, digital signal processors, application-specific integrated circuits, field programmable gate arrays, or other programmable logic devices, discrete gate or transistor logic devices, quantum computing-based data processing logic, discrete hardware components, etc. The general-purpose processor referred to herein refers to a microprocessor or any conventional processor.

[0072] Memory 62 can be an internal storage unit of computer device 60, such as its hard drive or memory, or an external storage device, such as a plug-in hard drive, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard. Memory 62 not only stores computer programs but also other programs and data required for device operation, and temporarily stores data that has been or is about to be output.

[0073] In the various embodiments provided herein, references to memory, databases, or other media will encompass at least one of non-volatile memory and volatile memory. There are many types of non-volatile memory, including read-only memory, magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory, magnetic random access memory, ferroelectric memory, phase change memory, graphene memory, and the like. Volatile memory may include random access memory (RAM) or external cache memory. It should be noted that RAM has various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

Claims

1. A method for calculating the grid strength of a DC / AC hybrid multi-feed system, characterized in that: include: Constructing the current balance equation of the system based on the topology, device parameters and control strategy of the DC-AC hybrid multi-feed system; Construct a vector-valued function of the grid characteristics based on the current balance equation; The grid strength calculation problem is transformed into a nonlinear optimization problem, and the objective function and constraints are set according to the grid characteristic vector value function; The improved interior point method is used to solve the nonlinear optimization problem and obtain the extreme value of the grid characteristic vector value. The grid strength of each feeding node is calculated based on the extreme value of the grid characteristic vector value, and the minimum grid strength in each feeding node is taken as the grid strength of the DC-AC hybrid multi-feed system.

2. The method for calculating the grid strength of a DC-AC hybrid multi-feed system according to claim 1, characterized in that: The grid characteristic vector value function is constructed based on the current balance equation, including: The constraints determine the feed-in nodes of the DC-AC hybrid multi-feed system and the voltage and current values ​​of each feed-in node, and the current balance equation is determined based on the voltage and current values ​​of each feed-in node; Define the grid characteristic vector value function from the current balance equation according to the implicit function theorem; The grid characteristic vector value function is: Where, is a vector-valued function; is the characteristic component of the vector-valued function corresponding to the kth feed-in node; is the d-axis component of the system active current in the dq coordinate system; is the q-axis component of the system reactive current in the dq coordinate system; is the d-axis component of the active current at the m-th feeding point in the dq coordinate system; is the q-axis component of the reactive current at the m-th feeding point in the dq coordinate system.

3. The method for calculating the grid strength of a DC-AC hybrid multi-feed system according to claim 2, characterized in that: The objective function and constraint conditions are set according to the grid characteristic vector value function, specifically including: The objective function is the extreme value of the grid characteristic vector value function; The constraints are the current and voltage constraints of the devices corresponding to each feeding node; the constraint expressions are: Where, is the square of the d-axis component of the characteristic component function of the k-th feeding node, is the square of the q-axis component of the characteristic component function of the k-th feeding node; is the square of the maximum value of the current fed into the kth node; is the minimum voltage amplitude of the kth feeding node; is the maximum voltage amplitude of the kth feeding node; is the d-axis current injection value of the device connected to the mth feeding node; is the q-axis current injection value of the device connected to the mth feeding node.

4. The method for calculating the grid strength of a DC-AC hybrid multi-feed system according to claim 1, characterized in that: The grid strength calculation problem is transformed into a nonlinear optimization problem, which is: Where, is the objective function; is the equality constraint; is an inequality constraint; is the upper limit of the constraint; is the lower bound constraint, is a constraint condition.

5. The method for calculating the grid strength of a DC-AC hybrid multi-feed system according to claim 1, characterized in that: The improved interior point method specifically includes: Introducing non-negative slack variables to convert constraints in the nonlinear optimization problem into equality constraints; converting the equality constraints into logarithmic barrier functions, introducing the logarithmic barrier function and logarithmic parameters into the objective function, and updating the objective function in the nonlinear optimization problem; Construct the Lagrangian function based on the updated objective function and nonlinear optimization problem, and establish the KKT condition; The Newton method is used to iteratively calculate the Lagrangian function under KKT conditions to obtain the extreme value of the grid characteristic vector value component function, and the extreme value of the grid characteristic vector value function is obtained according to the extreme value of the grid characteristic vector value component function.

6. The method for calculating the grid strength of a DC-AC hybrid multi-feed system according to claim 5, characterized in that: The Newton method is used to iteratively calculate the Lagrangian function under KKT conditions, including: In each iteration, the Newton method is used to linearize the KKT conditions, solve the modified equations under the linearized KKT conditions, and determine the update direction; The primary and dual variables are dynamically adjusted along the update direction based on the step size, and the barrier parameters are updated at the same time to ensure the non-negativity of the slack variables until the calculation is terminated when the convergence conditions are met.

7. The method for calculating the grid strength of a DC-AC hybrid multi-feed system according to claim 1, characterized in that: The grid strength corresponding to the feed-in node is: Where, is the grid strength corresponding to the kth feeding node; is the open-circuit voltage of the kth feed point, and are the maximum and minimum operating voltages allowed for the kth feed node, and These are the upper and lower bounds of the grid characteristic function of the kth feeding node.

8. A system for calculating the grid strength of a DC-AC hybrid multi-infeed system, for implementing the method for calculating the grid strength of a DC-AC hybrid multi-infeed system according to any one of claims 1 to 7, characterized in that: include: A system model building module constructs the current balance equation of the DC-AC hybrid multi-infeed system based on its topology, device parameters, and control strategy; Construct a vector-valued function of the grid characteristics based on the current balance equation; The grid strength objective function module converts the grid strength calculation problem into a nonlinear optimization problem and sets the objective function and constraints based on the grid characteristic vector value function; The grid strength calculation module uses an improved interior point method to solve the nonlinear optimization problem and obtain the extreme value of the grid characteristic vector value. The grid strength of each feeding node is calculated based on the extreme value of the grid characteristic vector value, and the minimum grid strength value of each feeding node is used as the grid strength of the DC-AC hybrid multi-feed system.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions, which, when executed by a computing device, enable the computing device to execute the method for calculating the grid strength of a DC-AC hybrid multi-feed system according to any one of claims 1 to 7.

10. A computing device, characterized in that include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the method for calculating the grid strength of the DC-AC hybrid multi-feed system according to any one of claims 1 to 7.

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