Method and device for adjusting power flow of power grid and processor

Abstract

The invention discloses a power grid power flow adjusting method, a power grid power flow adjusting device and a processor. The power grid comprises an alternating current network and a multi-terminal flexible direct current converter station, the method comprises the steps that first attribute information of the alternating current network and second attribute information of the multi-terminal flexible direct current converter station are acquired, the first attribute information is used for representing the operation state of a bus, the operation state of a branch and the operation state of a generator in the alternating current network, and the second attribute information is used for representing the operation state of the generator in the multi-terminal flexible direct current converter station; the second attribute information is used for representing a modulation ratio and a phase shift angle of the multi-terminal flexible DC converter station; analyzing the first attribute information and the second attribute information by utilizing a power flow model to obtain a constraint condition and a target function of the power flow model; and adjusting the first attribute information and the second attribute information based on the constraint condition and the target function to obtain an adjustment result, and determining the power flow adjustment direction of the power grid based on the adjustment result. The technical problem of low accuracy of power flow adjustment of the power grid is solved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and more specifically, to a method, apparatus, and processor for adjusting the power flow of a power grid. Background Technology

[0002] Currently, power flow control methods in power grids are relatively limited, mainly relying on adjusting generator output, transformer tap positions, or switching reactive power compensation equipment. These methods are often inefficient in handling the complex power flow problems of large urban power grids, making it difficult to achieve flexible and precise power flow regulation. Furthermore, although flexible DC transmission technology has shown great potential in improving the controllability and adaptability of power grids, its practical application and research in large urban power grids are still in their early stages.

[0003] In related technologies, for urban power grids with multi-terminal flexible DC transmission, power flow adjustment is often based on local optimization strategies. This can lead to situations where the power flow adjustment may not achieve a suitable state, affecting the grid's operational efficiency and security. Therefore, the technical problem of low accuracy in power flow adjustment still exists. Summary of the Invention

[0004] This invention provides a method, apparatus, and processor for adjusting power flow in a power grid, thereby addressing at least the technical problem of low accuracy in adjusting power flow in a power grid.

[0005] According to one aspect of the present invention, a method for adjusting the power flow of a power grid is provided. The power grid includes an AC network and a multi-terminal flexible DC converter station. The method includes: acquiring first attribute information of the AC network and second attribute information of the multi-terminal flexible DC converter station, wherein the first attribute information is used to represent the operating state of the bus, the operating state of the branch, and the operating state of the generator in the AC network, respectively, and the second attribute information is used to represent the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station; analyzing the first and second attribute information using a power flow model to obtain the constraints and objective function of the power flow model, wherein the power flow model is used to determine the power flow distribution state of the power grid under the constraints, the constraints are used to represent the upper and lower limits of the first and second attribute information, and the objective function is used to represent the adjustment target of the power grid operation; adjusting the first and second attribute information based on the constraints and the objective function to obtain the adjustment result, and determining the power flow adjustment direction of the power grid based on the adjustment result.

[0006] Optionally, the power flow model includes an AC network constrained power flow model and a flexible DC converter valve mathematical model. Using the power flow model, the first attribute information and the second attribute information are analyzed to obtain the constraints and objective function of the power flow model. This includes: using the AC network constrained power flow model to analyze the first attribute information to obtain the constraints corresponding to the first attribute information and the objective function corresponding to the first attribute information, wherein the AC network constrained power flow model is a nonlinear programming model. The method further includes: transforming the AC network constrained power flow model based on the constraints and objective function to obtain a transformed AC network constrained power flow model, wherein the solution difficulty of the transformed AC network constrained power flow model is lower than that of the original AC network constrained power flow model.

[0007] Optionally, the method further includes: using a mathematical model of a flexible DC converter valve to analyze the first attribute information and the second attribute information to obtain the power exchanged between the multi-terminal flexible DC converter station and the AC grid, wherein the power includes active power and / or reactive power.

[0008] Optionally, the constraints include equality constraints and inequality constraints. Using a power flow model, the first and second attribute information are analyzed to determine the constraints of the power flow model. This includes: using a mathematical model of a flexible DC converter valve to analyze the first and second attribute information to obtain the operational constraints of the multi-terminal flexible DC converter station and the DC line, as well as the upper and lower limit constraints of the generator's active and reactive power output. Here, the DC line represents the high-voltage DC transmission line connecting the multi-terminal converter stations; active power output represents the actual electrical power output by the generator to the grid; and reactive power output represents the electrical power required to maintain the operation of the grid and the multi-terminal converter station. Based on the operational constraints and the upper and lower limit constraints, equality constraints and inequality constraints are determined. Equality constraints represent the physical relationships and power conservation principles satisfied between the components within the grid, while inequality constraints represent the information ranges of the first and second attribute information.

[0009] Optionally, after obtaining the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station, the method further includes: converting the first attribute information and the second attribute information to obtain per-unit values, wherein the per-unit values ​​are used to unify the first attribute information and the second attribute information to the same scale.

[0010] Optionally, based on constraints and an objective function, the first attribute information and the second attribute information are adjusted to obtain an adjustment result, and based on the adjustment result, the power flow adjustment direction of the power grid is determined, including: taking the constraints as the root node, deleting the integer constraints of the constraints to obtain a subset of constraints, wherein the root node is used to represent the initial operating state of the power grid; a first determination step, based on the subset of constraints, determining the upper and lower bounds of the initial objective function of the current node, wherein the current node is used to represent the subset of constraints from the root node to the current node; a second determination step, in response to the existence of a next node for the current node, determining the next node as the current node, returning to execute the first determination step, until the current node has no next node, performing branch operations on the subset of constraints and the upper and lower bounds of the initial objective function of the current node respectively to obtain the upper and lower bounds of the objective function of the current node; based on the determined upper and lower bounds of the objective function, adjusting the first attribute information and the second attribute information to obtain the power flow adjustment direction of the power grid.

[0011] According to another aspect of the present invention, a power flow adjustment device for a power grid is also provided. The power grid includes an AC network and a multi-terminal flexible DC converter station. The device includes: an acquisition unit, configured to acquire first attribute information of the AC network and second attribute information of the multi-terminal flexible DC converter station, wherein the first attribute information represents the operating state of the bus, the operating state of the branch, and the operating state of the generator in the AC network, respectively, and the second attribute information represents at least the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station; an analysis unit, configured to analyze the first and second attribute information using a power flow model to obtain the constraints and objective function of the power flow model, wherein the power flow model determines the power flow distribution state of the power grid under constraints, the constraints represent the upper and lower limits of the first and second attribute information, and the objective function represents the adjustment target of the power grid operation; and an adjustment unit, configured to adjust the first and second attribute information based on the constraints and objective function to obtain an adjustment result, and determine the power flow adjustment direction of the power grid based on the adjustment result.

[0012] According to another aspect of the present invention, a computer-readable storage medium is also provided, which stores a plurality of instructions adapted for loading by a processor and executing any of the methods described above.

[0013] According to another aspect of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform any of the methods described above.

[0014] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements any of the methods described above.

[0015] In this embodiment of the invention, if it is necessary to adjust the power flow direction of the power grid, the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station can be obtained. The first attribute information is used to represent the operating status of the bus, the operating status of the branch, and the operating status of the generator in the AC network, respectively. The second attribute information is used to represent the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. The power flow model can be used to analyze the first and second attribute information to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under the constraints. The constraints represent the upper and lower limits of the first and second attribute information, and the objective function represents the adjustment target of the power grid operation. The first and second attribute information can be adjusted based on the constraints and objective function to obtain the adjustment result, and the power flow adjustment direction of the power grid can be determined based on the adjustment result. In this embodiment, the operating states of buses, branches, and generators in the AC network, as well as the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station, are analyzed using a power flow model. The constraints and objective function of the power flow model are determined, and the first and second attribute information are adjusted according to the constraints and objective function to obtain the required power flow adjustment direction. This overcomes the limitations of existing technologies where power flow adjustment lacks global optimization and fast solution methods when the power grid is embedded with a multi-terminal flexible DC converter station. It solves the technical problem of low accuracy in power flow adjustment and achieves the technical effect of improving the accuracy of power flow adjustment in the power grid. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1 This is a flowchart of a power flow adjustment method for a power grid according to an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of a flexible DC transmission system according to an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of a steady-state model of a flexible DC converter station according to an embodiment of the present invention;

[0020] Figure 4This is a flowchart of a branch and bound algorithm according to an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of an improved power system test model node system according to an embodiment of the present invention;

[0022] Figure 6 This is a schematic diagram of the voltage amplitude at each node according to an embodiment of the present invention;

[0023] Figure 7 This is a schematic diagram of another node voltage amplitude according to an embodiment of the present invention;

[0024] Figure 8 This is a schematic diagram of the structure of a power flow adjustment device for a power grid according to an embodiment of the present invention;

[0025] Figure 9 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] According to an embodiment of the present invention, a method for adjusting the power flow of a power grid is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] Figure 1 This is a flowchart of a power flow adjustment method for a power grid according to an embodiment of the present invention. The power grid includes an AC network and multi-terminal flexible DC converter stations, such as... Figure 1 As shown, the method includes the following steps:

[0031] Step S102: Obtain the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station.

[0032] In the technical solution provided in step S102 of this embodiment of the invention, the power grid can be an urban power grid. The AC network consists of a series of interconnected buses, branches, and generators, used for the transmission and distribution of electrical energy. A multi-terminal flexible DC converter station is a key device in modern power systems used to connect AC and DC power grids, achieving the conversion between AC and DC power through fully controlled semiconductor devices. The first attribute information is used to represent the operating status of the buses, branches, and generators in the AC network, respectively. The second attribute information is used to represent the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. Buses are connection points in the power grid, each carrying electrical energy input and output from multiple branches. Branches are lines used to connect different buses for transmitting electrical energy. Generators are one of the energy sources of the power grid, providing active and reactive power support.

[0033] In this embodiment, the first attribute information (parameters) of the AC network can be obtained, such as the parameters of each bus (including bus type, bus active load, bus reactive load, and the highest and lowest voltage amplitudes of the bus during operation); the parameters of each branch (including the start and end nodes, resistance, reactance, susceptance, and turns ratio of each branch); and the parameters of the generator (including the number of the connected bus, the upper and lower limits of active power output, and the upper and lower limits of reactive power output). The second attribute information (control parameters) of the multi-terminal flexible DC converter station can also be obtained, such as the modulation ratio and phase shift angle. The modulation ratio (M) is a key factor determining the output voltage amplitude of the multi-terminal flexible DC converter station, affecting the output capacity of active and reactive power; the phase shift angle (δ) determines the direction and magnitude of power exchange between the multi-terminal flexible DC converter station and the AC network, directly affecting the adjustment of power flow in the grid.

[0034] Optionally, a Supervisory Control and Data Acquisition (SCADA) system can capture real-time voltage, current, and power data for each bus. Simultaneously, it can confirm the bus type and upper / lower limits of voltage amplitude by referring to power grid design documents, reflecting the safety boundaries and control strategies of the power grid operation. Using an online data monitoring system, the resistance, reactance, and susceptance of each branch can be obtained; alternatively, relevant parameters for branches can be obtained by consulting power line technical data manuals. The real-time operating status of generators can also be obtained through the SCADA system, or by consulting the generator's technical specifications or design documents.

[0035] Optionally, by utilizing sensors and data acquisition systems installed within the multi-terminal flexible DC converter station, such as voltage sensors, current sensors, and phase detection devices, the voltage, current amplitude, and phase on both the DC and AC sides can be monitored in real time, thereby calculating secondary attribute information (e.g., modulation ratio and phase shift angle). The modulation ratio and phase shift angle, as control parameters of the multi-terminal flexible DC converter station, can be directly set on the station's control panel. These settings can be remotely adjusted through a central control strategy based on grid operation objectives, such as power transmission optimization, voltage stability control, and frequency response.

[0036] It should be noted that the content and acquisition method of the first and second attribute information mentioned above are merely illustrative examples and are not specifically limited here. Any information that can be used to reflect the operating status and characteristics of the AC network and the multi-terminal flexible DC converter station, as well as information that can be obtained through effective means such as real-time monitoring and setting, is within the protection scope of this invention.

[0037] Step S104: Using the power flow model, analyze the first attribute information and the second attribute information to obtain the constraints and objective function of the power flow model.

[0038] In the technical solution provided in step S104 of this embodiment of the invention, after obtaining the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station, a power flow model can be used to analyze the first and second attribute information to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under constraints. The constraints represent the upper and lower limits of the first and second attribute information, and the objective function represents the adjustment target of the power grid operation. The power flow model can be a constrained power flow model for an AC network embedded with a multi-terminal flexible DC converter station.

[0039] In this embodiment, the AC network constrained power flow model embedded with multi-terminal flexible DC can be used to predict the power flow distribution of the power grid under different operating conditions. The AC network constrained power flow model includes an AC network constrained power flow model and a flexible DC converter valve mathematical model. The AC network constrained power flow model, based on the node admittance matrix, expresses the operating characteristics of the AC network as a set of equality and inequality constraints, including but not limited to the active and reactive power balance of each node, voltage amplitude limits, and generator output upper and lower limits. The flexible DC converter valve mathematical model mathematically abstracts the working principle and operating parameters of each multi-terminal flexible DC converter station, establishing a dynamic equivalent model within the AC network. This includes the power relationship between the multi-terminal flexible DC converter station and both the AC and DC sides, as well as the influence of modulation ratio and phase shift angle on active and reactive power output.

[0040] Optionally, the constraints define the physical limits and safety standards for grid operation, including but not limited to: bus voltage constraints: ensuring that the voltage of each bus remains within a predetermined range to avoid overvoltage or undervoltage conditions; generator output constraints: setting upper and lower limits for active and reactive power output based on the physical and economic characteristics of the generators; branch power constraints: ensuring that the power transmission of AC and DC branches does not exceed capacity limits to prevent overload and thermal stability problems; and converter station control parameter constraints: limiting the upper and lower limits of the modulation ratio and phase shift angle to ensure that the converter station operates within a safe and efficient range.

[0041] Optionally, the objective function serves as a compass for optimization calculations, clarifying the ultimate goal of power flow adjustment. The objective function can be to minimize the sum of squares of the power flow adjustment amounts. By adjusting the parameters of generators and converter stations, the goal is to bring the power grid from a load level with no solution to a solvable state through the minimum adjustment of adjustable parameters, while minimizing interference with the original operating state. Alternatively, it can be to minimize operating costs by optimizing the operating state and power output of generators, thereby reducing fuel consumption and other maintenance expenses.

[0042] In this embodiment of the invention, constraints ensure that the power grid operation does not exceed safety boundaries, preventing risks such as overvoltage, overcurrent, and equipment overheating, and guaranteeing the stability and reliability of the power grid. The objective function, such as minimizing operating costs, can guide the power grid to achieve economical operation while meeting load demand, thereby reducing overall operating costs. The comprehensive determination of constraints and the objective function can simultaneously consider the operating requirements of both the AC and DC sides. By adjusting the control parameters of the multi-terminal flexible DC converter station, coordinated operation of the entire power system can be achieved, improving the flexibility and response speed of the power grid.

[0043] Step S106: Based on the constraints and objective function, adjust the first attribute information and the second attribute information to obtain the adjustment result, and determine the power flow adjustment direction of the power grid based on the adjustment result.

[0044] In the technical solution provided by step S106 of the present invention, after analyzing the first attribute information and the second attribute information using the power flow model to obtain the constraints and objective function of the power flow model, the first attribute information and the second attribute information can be adjusted based on the constraints and objective function to obtain the adjustment result, and the power flow adjustment direction of the power grid can be determined based on the adjustment result.

[0045] In this embodiment, a suitable objective function can be selected based on the economic, safety, or other strategic objectives of power grid operation. For example, the objective function can be set to minimize generator fuel costs, optimize power allocation, or reduce line losses. Considering the necessary conditions for safe power grid operation, such as voltage amplitude limits, generator output limits, and branch capacity limits, as well as the operational constraints of multi-terminal flexible DC converter stations, such as the range of DC voltage and active and reactive power output limits, the previously acquired attribute information (first attribute information and second attribute information) of the AC network and multi-terminal flexible DC converter stations can be used as initial power flow model parameters. These parameters can be adjusted by an algorithm to meet the optimization objective. Branch-and-bound algorithms or other global optimization strategies can be used to traverse all possible combinations of parameters (first attribute information and second attribute information) to find a solution that maximizes or minimizes the objective function while satisfying all constraints.

[0046] Optionally, the optimization algorithm gradually approaches the optimal solution through multiple iterations, updating the first and second attribute information after each iteration until the convergence condition is met (such as the objective function reaching a preset threshold or the number of iterations reaching an upper limit). After each iteration, it is necessary to check whether the adjusted parameters still satisfy all constraints to ensure the feasibility of the adjustment results in engineering practice.

[0047] Optionally, after the optimization process is complete, the adjusted first and second attribute information is output, resulting in the optimized generator active and reactive power output, bus voltage, branch current, and modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. Based on the adjusted parameters, their impact on power flow distribution in the grid is analyzed. This includes power redistribution, voltage level adjustment, and line load optimization to ensure safer, more efficient, and more economical grid operation. Based on the optimization results, it can be determined which buses, branches, and generators in the grid need adjustment, and the specific adjustment methods and extent. Simultaneously, the direction of control parameter adjustment for the multi-terminal flexible DC converter station is clarified, such as adjusting the modulation ratio to increase active power output or adjusting the phase shift angle to improve the power factor.

[0048] In steps S102 to S106 of this embodiment of the invention, if it is necessary to adjust the power flow direction of the power grid, the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station can be obtained. The first attribute information is used to represent the operating status of the bus, the operating status of the branch, and the operating status of the generator in the AC network, respectively. The second attribute information is used to represent the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. The power flow model can be used to analyze the first and second attribute information to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under the constraints. The constraints are used to represent the upper and lower limits of the first and second attribute information, and the objective function is used to represent the adjustment target of the power grid operation. The first and second attribute information can be adjusted based on the constraints and objective function to obtain the adjustment result, and the power flow adjustment direction of the power grid can be determined based on the adjustment result. In this embodiment, the operating states of buses, branches, and generators in the AC network, as well as the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station, are analyzed using a power flow model. The constraints and objective function of the power flow model are determined, and the first and second attribute information are adjusted according to the constraints and objective function to obtain the required power flow adjustment direction. This overcomes the limitations of existing technologies where power flow adjustment lacks global optimization and fast solution methods when the power grid is embedded with a multi-terminal flexible DC converter station. It solves the technical problem of low accuracy in power flow adjustment and achieves the technical effect of improving the accuracy of power flow adjustment in the power grid.

[0049] The embodiments of the present invention will now be described in detail with reference to the steps described above.

[0050] As an optional embodiment, the power flow model includes an AC network constrained power flow model and a flexible DC converter valve mathematical model. Step S104 involves using the power flow model to analyze the first attribute information and the second attribute information to obtain the constraints and objective function of the power flow model. This includes: using the AC network constrained power flow model to analyze the first attribute information to obtain the constraints and objective function corresponding to the first attribute information, wherein the AC network constrained power flow model is a nonlinear programming model. The method further includes: transforming the AC network constrained power flow model based on the constraints and objective function to obtain a transformed AC network constrained power flow model, wherein the solution difficulty of the transformed AC network constrained power flow model is lower than that of the original AC network constrained power flow model.

[0051] In this embodiment, the AC network constrained power flow model is a complex nonlinear programming model, including node parameters such as active load, reactive load, and voltage amplitude limits; branch parameters such as resistance, reactance, and turns ratio; and generator parameters such as active and reactive power output and output limits. Through the aforementioned series of equality and inequality constraints, the power flow distribution under the conditions of satisfying the power system's operating requirements is described. However, it is essentially a nonlinear problem, making it relatively difficult to solve.

[0052] Alternatively, to reduce the difficulty of solving the problem, the Second-Order Cone Relaxation (SOCR) technique can be used to transform the AC network constrained power flow model, converting the nonlinear constraints into more manageable linear or convex optimization forms. Linear or convex optimization problems are easier to solve than the original nonlinear problems, significantly reducing computation time. The transformed AC network constrained power flow model is more suitable for using advanced optimization algorithms, such as branch and bound algorithms, to ensure that the global optimum is found.

[0053] As an optional embodiment, the method further includes: using a mathematical model of a flexible DC converter valve to analyze the first attribute information and the second attribute information to obtain the power exchanged between the multi-terminal flexible DC converter station and the AC grid, wherein the power includes active power and / or reactive power.

[0054] In this embodiment, a mathematical model of the flexible DC converter valve is constructed based on the electrical characteristics of the flexible DC converter station, including the modulation ratio M and the phase shift angle δ. This mathematical model describes the dynamic process of power exchange between the multi-terminal flexible DC converter station and the AC grid, focusing on how to regulate the output power by controlling the converter valve. Through this mathematical model, it is possible to understand how the modulation ratio and phase shift angle affect the output power of the flexible DC converter valve, and how this output power affects the overall grid operation. The active and reactive power exchanged between the multi-terminal flexible DC converter station and the AC grid can be calculated. Therefore, based on the analysis results of the flexible DC converter valve mathematical model, the actual values ​​of the active and reactive power exchanged between the multi-terminal flexible DC converter station and the AC grid, as well as the variation patterns of these powers under different operating modes, are clarified.

[0055] Optionally, by utilizing the control modes of multi-terminal flexible DC converter stations (such as constant DC voltage, constant AC active power, constant AC reactive power, or constant AC voltage), the control of active and reactive power can be made independent, facilitating individual adjustment and optimization, and achieving decoupling of active and reactive power. Power exchange calculation: Combining the AC network constrained power flow model and the mathematical model of the flexible DC converter valve, as well as the control parameters of the multi-terminal flexible DC converter station, the actual power exchange between the multi-terminal flexible DC converter station and the power grid can be calculated based on the node admittance matrix and the electrical parameters of each branch, ensuring the accuracy and reliability of the results.

[0056] As an optional embodiment, the constraints include equality constraints and inequality constraints. Using a power flow model, the first attribute information and the second attribute information are analyzed to determine the constraints of the power flow model. This includes: using a mathematical model of a flexible DC converter valve to analyze the first and second attribute information to obtain the operational constraints of the multi-terminal flexible DC converter station and the DC line, as well as the upper and lower limit constraints of the generator's active and reactive power output. Here, the DC line represents the high-voltage DC transmission line connecting the multi-terminal converter stations; active power output represents the actual electrical power output by the generator to the grid; and reactive power output represents the electrical power required to maintain the operation of the grid and the multi-terminal converter station. Based on the operational constraints and the upper and lower limit constraints, equality constraints and inequality constraints are determined. The equality constraints represent the physical relationships and power conservation principles satisfied between the components within the grid, while the inequality constraints represent the information ranges of the first and second attribute information.

[0057] In this embodiment, the DC line is a key component connecting the multi-terminal flexible DC converter station. By analyzing the electrical characteristics of the DC line, including DC current, voltage, and line impedance, the upper and lower limits of these parameters constitute inequality constraints, ensuring that the DC line operates within a safe range and avoiding overload or voltage anomalies. Through the mathematical model of the flexible DC converter valve, the operating range of the control parameters of the multi-terminal flexible DC converter station can be determined, such as the upper and lower limits of the modulation ratio M and phase shift angle δ. These constraints ensure that the multi-terminal flexible DC converter station does not exceed the safe operating range during power conversion, and also consider the active and reactive power control modes of the multi-terminal flexible DC converter station, ensuring the stability and controllability of the power grid operation.

[0058] Optionally, the upper and lower limits of the generator's active power output (Pmax and Pmin) can be set to define the range of actual electrical power that the generator can output. These limits are mainly determined by the generator's physical performance and the grid's operational requirements, ensuring the reliability of power supply. The upper and lower limits of the generator's reactive power output (Qmax and Qmin) define the range of reactive power that the generator can provide while maintaining the operation of the grid and multi-terminal converter stations. Reactive power is crucial to the grid's voltage stability and power factor. Therefore, these constraints ensure the quality of grid operation.

[0059] Optionally, equality constraints reflect the physical relationships and power conservation principles among the components of the power grid, such as nodal power balance equations and branch voltage-current relationship equations. These constraints ensure the continuity and conservation of power in the power grid during power transmission. Inequality constraints reflect the operating range of primary and secondary attribute information, such as upper and lower voltage limits and upper and lower power limits. These constraints guarantee that the power grid operates safely, stably, and economically, avoiding overload or abnormal operation.

[0060] As an optional embodiment, after obtaining the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station, the method further includes: converting the first attribute information and the second attribute information to obtain per-unit values, wherein the per-unit values ​​are used to unify the first attribute information and the second attribute information to the same scale.

[0061] In this embodiment, after obtaining the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station, the first attribute information and the second attribute information can be normalized. Normalization can eliminate the influence of physical units and enable electrical parameters (first attribute information and second attribute information) of different orders of magnitude to be compared and calculated on the same scale.

[0062] Optionally, a set of reference values ​​can be selected, such as reference voltage (Vbase), reference current (Ibase), reference power (Sbase), and reference frequency (fbase). Although frequency is not directly involved in the calculation during per-unit scaling, it is relevant to the design and analysis of the electrical system. For AC systems, rated voltage and rated power can be selected as reference values; for DC systems, the reference values ​​can be based on DC voltage and DC power. For the first and second attribute information, the original parameter values ​​are converted into per-unit values ​​relative to the reference values.

[0063] For example, if the original parameter is voltage V, its per-unit value Vpu can be calculated using the formula Vpu = V / Vbase. For power information (active and reactive power), per-unit scaling follows the formulas Ppu = P / Sbase and Qpu = Q / Sbase, converting power into per-unit values ​​relative to a reference power. Per-unit scaling unifies information to the same scale, facilitating comparison and calculation in power flow models, while eliminating the complexity and errors caused by different physical units.

[0064] As an optional embodiment, step S106, based on constraints and objective function, adjusts the first attribute information and the second attribute information to obtain an adjustment result, and determines the power flow adjustment direction of the power grid based on the adjustment result, including: taking the constraints as the root node, deleting the integer constraints of the constraints to obtain a subset of constraints, wherein the root node is used to represent the initial operating state of the power grid; a first determination step, based on the subset of constraints, determining the upper and lower bounds of the initial objective function of the current node, wherein the current node is used to represent the subset of constraints from the root node to the current node; a second determination step, in response to the existence of a next node for the current node, determining the next node as the current node, returning to execute the first determination step, until the current node has no next node, performing branch operations on the subset of constraints and the upper and lower bounds of the initial objective function of the current node respectively to obtain the upper and lower bounds of the objective function of the current node; based on the determined upper and lower bounds of the objective function, adjusting the first attribute information and the second attribute information to obtain the power flow adjustment direction of the power grid.

[0065] In this embodiment, the branch and bound algorithm (B&B) can be used to adjust the first attribute information and the second attribute information based on the constraints and the objective function in order to determine the power flow adjustment direction of the power grid.

[0066] Optionally, the initial operating state of the power grid is taken as the root node. Then, to simplify calculations, starting from the root node, all integer constraints are temporarily ignored, such as discrete variations in generator output and limitations on the control parameters of the multi-terminal flexible DC converter station, resulting in a subset of constraints. This subset includes all continuous constraints, such as voltage upper and lower limits, power transmission upper and lower limits, etc. Subsequently, based on this subset of constraints, a preliminary relaxation solution is performed on the objective function to estimate the possible range of the optimal solution, thereby determining the upper and lower bounds of the objective function for the current node (initially the root node).

[0067] Optionally, by relaxing integer constraints and using linear or convex optimization methods, the objective function can be solved to obtain a lower value, which serves as the lower bound of the objective function. This represents the optimal solution without integer constraints. Upper bound of the objective function: Simultaneously, based on known feasible solutions, such as the current operating state of the power grid or solutions obtained from previous iterations, a higher value is estimated as the upper bound of the objective function.

[0068] Optionally, after obtaining the upper and lower bounds of the objective function, the iterative branching process begins. If a next node exists, it can be designated as the new current node, and the first determining step is executed again to re-evaluate the upper and lower bounds of the objective function. This process continues until no next node exists, meaning all possible branches have been explored. During this process, whenever a branch point is encountered, a new subproblem can be created based on the type of constraint (e.g., generator output, converter station control mode, voltage limits, etc.). Each subproblem represents a more specific constraint scenario. For each subproblem, the upper and lower bounds of the objective function are established once. Through this series of branching operations, the solution space of the objective function is gradually narrowed, improving the accuracy and efficiency of the solution.

[0069] Optionally, during the branch and bound algorithm, the upper and lower bounds of the objective function are repeatedly updated. After each branch operation, it can be checked whether the new upper and lower bounds are tangent or close, i.e., whether there is a solution that satisfies all constraints. Once it is determined that the upper and lower bounds of the objective function of a certain subproblem are sufficiently close, it means that a possible optimal solution or a solution in its neighborhood has been found. At this point, the first and second attribute information can be adjusted based on the solution, such as by fine-tuning the active and reactive power output of the generator, adjusting the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station, etc., to obtain a specific power flow adjustment direction.

[0070] In this embodiment of the invention, if it is necessary to adjust the power flow direction of the power grid, the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station can be obtained. The first attribute information is used to represent the operating status of the bus, the operating status of the branch, and the operating status of the generator in the AC network, respectively. The second attribute information is used to represent the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. The power flow model can be used to analyze the first and second attribute information to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under the constraints. The constraints represent the upper and lower limits of the first and second attribute information, and the objective function represents the adjustment target of the power grid operation. The first and second attribute information can be adjusted based on the constraints and objective function to obtain the adjustment result, and the power flow adjustment direction of the power grid can be determined based on the adjustment result. In this embodiment, the operating states of buses, branches, and generators in the AC network, as well as the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station, are analyzed using a power flow model. The constraints and objective function of the power flow model are determined, and the first and second attribute information are adjusted according to the constraints and objective function to obtain the required power flow adjustment direction. This overcomes the limitations of existing technologies where power flow adjustment lacks global optimization and fast solution methods when the power grid is embedded with a multi-terminal flexible DC converter station. It solves the technical problem of low accuracy in power flow adjustment and achieves the technical effect of improving the accuracy of power flow adjustment in the power grid.

[0071] Example 2

[0072] The following describes in detail another optional implementation method.

[0073] Currently, urban power grids are characterized by large electricity consumption, high load density, high safety and reliability, and high requirements for power quality. They are the main load centers of today's power systems and a crucial infrastructure for promoting urban modernization. In recent years, with the continuous advancement of urbanization and rapid socio-economic development, the load on urban power grids has not only continued to grow rapidly with urbanization, but the requirements for the reliability and quality of power supply have also become increasingly stringent. Therefore, supplying large amounts of high-quality and reliable electricity to urban load centers will face increasingly severe difficulties and challenges.

[0074] In related technologies, the main drawbacks of AC distribution networks are as follows: First, with the increasing maturity of urban development and construction, environmental protection and land resource constraints not only restrict the construction of large-capacity power sources but also cause increasingly congested power line corridors, even leading to power supply bottlenecks and a lack of necessary power line corridors when supplying power to cities. Second, as urban power supply capacity increases and investment costs rise, so do the requirements for sanitation and living environment. Therefore, to save money and reduce the impact of power grid construction and operation on the urban living environment, a more suitable power supply method is needed. Third, the increase in urban power supply capacity greatly threatens the safe operation of network components such as switching equipment, thereby increasing the short-circuit current of the power system. Fourth, urban loads have increasingly higher requirements for power supply reliability and power quality. This requires urban load centers to have flexible, controllable power supply that adapts to various operational needs, ensuring both operational flexibility and power supply reliability. Therefore, the technical problem of low accuracy in power flow adjustment still exists.

[0075] This invention proposes a power flow adjustment method for urban power grids with multi-terminal flexible DC converters. Specifically, it studies power flow adjustment techniques under operational constraints for AC power grids embedded with multi-terminal flexible DC converters. By solving for the optimal objective and employing a branch-and-bound algorithm to achieve global optimization, it effectively overcomes the shortcomings of traditional methods, such as sensitivity to initial conditions and narrow convergence domains. This method achieves the goal of solving power flow problems for multiple relaxed generators in AC systems while also adjusting the parameters of flexible DC converter stations, thus addressing the technical problem of low accuracy in power flow adjustment and improving the accuracy of power flow adjustment in the power grid.

[0076] The method will be further described below.

[0077] In this embodiment, in the AC network constrained power flow model, for an AC power system with n nodes, N can represent the set of all nodes, and E can represent the set of all branches. Active power constraint equations, reactive power constraint equations, and voltage magnitude constraint equations are established. Solving the constrained power flow model means finding a feasible solution while satisfying all constraints. The active power constraint equations, reactive power constraint equations, and voltage magnitude constraint equations can be determined by the following formulas:

[0078]

[0079]

[0080] In this context, a branch is denoted as the positive direction of power flow from node i to node j,p. j It can be used to represent the active power injected into node j; q jIt can be used to represent the reactive power injected at node j; k can be used to represent a node; P jk It can be used to represent the active power on branch jk; P ij It can be used to represent the active power on branch ij; r ij It can be used to represent the resistance of branch ij; g j It can be used to represent the conductance of node j; It can be used to represent the square of the voltage at node j; q j It can be used to represent the reactive power injected at node j; Q jk It can be used to represent the reactive power on branch jk; Q ij It can be used to represent the reactive power on branch ij; x ij It can be used to represent the reactance of branch ij; b j It can be used to represent the susceptance of node j; ij can be used to represent the node number; I ij , These can be used to represent the upper and lower bounds of the current in branch ij, respectively. V j , These can be used to represent the upper and lower bounds of the voltage at node j, respectively; V j δ(j) can be used to represent the voltage magnitude at node j; δ(j) can be used to represent the set of terminal nodes of a branch with node j as the starting node; β(j) can be used to represent the set of starting nodes of a branch with node j as the ending node; p i It can be used to represent the active power injected at node i, q i It can be used to represent the reactive power injected at node i; P loadi It can be used to represent the active load at node i, Q loadi It can be used to represent the reactive load at node i; V i It can be used to represent the voltage magnitude at node i; I ij It can be used to represent the AC branch current with node i as the starting point and node j as the ending point.

[0081] The original AC network constrained power flow model is a nonlinear programming model, which can make By performing SOCR transformation on equation (3), we can obtain:

[0082]

[0083] Among them, V i =V i 2 , These can be used to represent the squares of the node voltages at nodes i and j, respectively; V j These can be used to represent the variables resulting from squaring the original DC current and node voltage, respectively.

[0084] Optionally, equations (6)-(10) above constitute the basic form of the relaxed static constraint power flow. Under the premise that the objective function is strictly increasing and is a convex function, a technique is introduced to approximate the non-convex optimization problem by introducing convex second-order cone constraints. Its core is to transform complex non-convex constraints (such as quadratic terms, bilinear terms, or nonlinear parts in mixed integer programming) into convex optimization forms that are easier to solve. In implementation, it is necessary to first identify the non-convex structure (such as quadratic equations or bilinear relationships), use mathematical techniques (such as McCormick envelope, auxiliary variables, or geometric transformations) to embed it into the second-order cone constraints, and then use a solver to calculate the relaxed convex problem.

[0085] Optionally, if the relaxed feasible region closely matches the original problem (such as in some quadratic programming or special scenarios), the solution may be accurate (called "tight relaxation"); however, in most cases there will be relaxation gaps, which need to be combined with branch and bound, cutting planes or heuristic repair to improve the quality of the solution.

[0086] Figure 2 This is a schematic diagram of a flexible DC transmission system according to an embodiment of the present invention, as shown below. Figure 2 As shown, the core of the flexible DC transmission system lies in the use of a voltage source converter based on fully controllable semiconductor devices. These fully controllable semiconductor devices possess autonomous switching capabilities, enabling the flexible DC transmission system to perform high-frequency commutation operations in each cycle. Precise triggering control of the converter valves can be achieved through pulse width modulation (PWM) technology, generating output voltage and current waveforms with sinusoidal characteristics and enabling flexible adjustment of the power factor. This allows for real-time dynamic control of the AC output voltage amplitude and phase, enabling independent and rapid adjustment of active and reactive power, significantly improving the controllability and response speed of the power system.

[0087] Optionally, a voltage source converter (VSC) employing pulse width modulation technology has two control variables: the modulation ratio M (i.e., the ratio of the fundamental frequency phase voltage amplitude of the output voltage to the DC voltage) and the phase shift angle δ relative to the VSC AC bus voltage Us, which determines the fundamental component of its output AC bus voltage. This can be expressed by the following formula:

[0088]

[0089] Among them, u d μ can be used to represent the DC-side voltage of the converter, and δ can be used to represent the DC voltage utilization rate associated with PWM modulation. s It can be used to represent AC bus voltage U s The phase angle, M can be used to represent the modulation ratio, and δ can be used to represent the phase shift angle.

[0090] Optionally, the voltage amplitude of the voltage source converter (VSC) output is directly determined by the modulation ratio M, while the frequency and phase of the output voltage completely follow the given parameters of the sinusoidal modulation wave. Since the active power exchanged between the VSC and the grid is mainly affected by the output voltage phase difference, while the reactive power is related to the output voltage amplitude difference, decoupling control of active and reactive power can be achieved by adjusting the phase of the modulation wave and setting the modulation ratio. This pulse-width modulation-based dual-degree-of-freedom regulation mechanism enables the flexible DC transmission system to independently and precisely regulate the active power P. s and reactive power Q s The magnitude and direction of transmission. The active power P can be expressed by the following formula. s and reactive power Q s To regulate:

[0091]

[0092] Among them, U c X can be used to represent the AC voltage at the converter terminal; X can be used to represent the equivalent reactance of the reactor connected to the converter station.

[0093] Figure 3 This is a schematic diagram of a steady-state model of a flexible DC converter station according to an embodiment of the present invention, as shown below. Figure 3 As shown, the two-level voltage source converter topology consists of a fully controlled converter bridge, a converter reactor, a DC capacitor, and an AC filter. si and Q si It can be used to represent the active and reactive power transmitted between the converter and the AC grid; U s It can be used to represent the voltage of the AC bus connected to a flexible DC converter station; R c and X c These can be used to represent the equivalent resistance and equivalent reactance of a transformer, respectively; X f It can be used to represent the equivalent reactance of a filter.

[0094] Optionally, the flexible DC converter station decouples active and reactive power, allowing them to be controlled independently. The active power control method is a constant DC voltage U. d Or a fixed AC active power P s The reactive power control method is constant AC reactive power Q. s Or constant AC voltage U s Therefore, VSC has four control modes, as shown in Table 1.

[0095] Table 1 Control methods of DC converter stations

[0096]

[0097] Optionally, the equivalent model of a flexible DC converter station is closely related to its control strategy. In voltage control mode (modes 1 / 3), the grid-connected AC bus voltage remains constant, and the converter station can be characterized as a pressure-voltage (PV) node with a fixed voltage amplitude. In power control mode (modes 2 / 4), the converter station maintains a constant active-reactive power output, and its electrical characteristics are equivalent to a pressure-quantity (PQ) node. These operating characteristics correspond to the PV node (controllable voltage amplitude) and PQ node (constant power) models in power system flow calculations, respectively. The former reflects voltage support capability, while the latter characterizes power transmission function.

[0098] Alternatively, during steady-state operation, the power relationship between the flexible DC converter station and the AC network can be expressed by the following formula:

[0099]

[0100] Among them, X li It can be used to represent the equivalent reactance of the i-th converter; M i It can be used to represent the modulation index of the i-th converter; U dci It can be used to represent the DC-side voltage of the i-th converter; N VSC It can be used to represent the set of bus node numbers connected to the converter; U ci It can be used to represent the AC voltage at the i-th converter terminal; U si It can be used to represent the voltage transmitted between the i-th converter and the AC grid.

[0101] In this embodiment, when the converter reactor resistance and system harmonic components are ignored, the power S on the AC bus side connected to the converter is... si Converter-side power S ci and the DC side power S of the converter dci The relationship can be expressed by the following formula:

[0102]

[0103] The relationship between the DC network-side converter station and the AC network-side transmission power can be obtained through formula (15), which can be expressed by the following formula:

[0104]

[0105] The operational constraints of converter stations and DC lines can be expressed by the following formula:

[0106]

[0107] In the formula, It can be used to represent the DC current in a DC network with i as the starting point and j as the ending point; It can be used to represent the impedance of each branch in a DC network; It can be used to represent the DC side voltage of a converter station.

[0108] For an AC system with embedded multi-terminal flexible DC, the algebraic sum of the active and reactive power of each node's input and output is zero, which can be expressed by the following formula:

[0109]

[0110] Among them, P load It can be used to represent the active power load of a node; P gj It can be used to represent the active power feed into the generator at node j; P sj It can be used to represent the active power exchange between DC transfer stations at node j; Q load It can be used to represent nodal reactive load; Q gj It can be used to represent the reactive power feed into the generator at node j; Q sj It can be used to represent reactive power exchange between DC transfer stations at node j.

[0111] The active and reactive power outputs of each generator must meet the upper and lower limits of generator output constraints, which can be expressed by the following formula:

[0112]

[0113] in, and It can be used to represent the maximum and minimum active power output of generator set i. and These can be used to represent the maximum and minimum reactive power output of a generator set, respectively.

[0114] By integrating the constraints of both the AC and DC systems, the following constraint power flow model can be established:

[0115] Equality constraints:

[0116] Inequality constraints:

[0117] Optionally, different objective functions can be defined for different optimization scenarios, such as minimizing generator fuel costs, minimizing the sum of generator active power output, and minimizing the sum of generator reactive power output. Taking the minimization of the sum of squares of generator output adjustments as an example, the objective function can be expressed by the following formula:

[0118] minf(γ)=∑γ 2(26)

[0119] Here, γ can be used to represent the active and reactive power adjustment amounts of each node. When the objective function is 0, the optimization problem has a solution; otherwise, the power flow equation itself does not have a real solution, and the parameters in the model need to be corrected so that each parameter in the equation enters the feasible region. That is, the focus is on how to make the power flow equation have a solution by adjusting an unsolvable load level with the fewest adjustable parameters, and finally give the direction of power flow adjustment.

[0120] Figure 4 This is a flowchart of a branch and bound algorithm according to an embodiment of the present invention, such as... Figure 4 As shown, it includes the following steps:

[0121] Step S401: Input the parameters for the integer programming problem.

[0122] In this embodiment, all necessary parameters of the integer programming problem can be input, such as the active and reactive power output of the generator, the bus voltage amplitude, the converter station control parameters, etc. All these parameters must meet the safety constraints and control objectives of the power grid operation.

[0123] Step S402: Find the optimal solution to the relaxation problem.

[0124] In this embodiment, the relaxation problem refers to removing the integer restriction on the variables, transforming the problem into a continuous optimization problem. This process involves finding the optimal solution to the objective function without considering the integer property of the variables. For example, solvers such as Gurobi can be used to find the optimal solution to the relaxation problem.

[0125] Step S403: Let the optimal solution be x, and the optimal value be f.

[0126] In this embodiment, an optimal solution x, which may not be an integer, and the corresponding optimal value f are obtained by solving the problem.

[0127] Step S404: Determine whether each component of x is an integer.

[0128] In this embodiment, it is checked whether each component of the solution x satisfies the integer property requirement of the integer programming problem. If all components are integers, then the algorithm may have found a feasible integer solution, and step S405 is executed; if there are non-integer components, a branch operation is required, and step S406 is executed.

[0129] Step S405, let F = f, x * =x, thus obtaining the optimal integer solution.

[0130] In this embodiment, if all components of the solution x are integers, then the solution is a solution to an integer programming problem with an objective function value of F and a solution x*. If F is better than the currently known optimal integer value, then the optimal integer value F and the optimal integer solution x* are updated. At this point, the solution x* is the currently known optimal integer solution, and the algorithm may continue to check other branches to ensure global optimum.

[0131] Step S406, select any non-integer component x. j Create a branch.

[0132] In this embodiment, if there are non-integer components in the solution x, the algorithm will select one of the non-integer components x. j Perform a branch. A branching process refers to processing a non-integer variable x. j Create two new subproblems, one assuming x j ≤l j Another hypothesis x j ≥l j , where l j This indicates rounding down. This breaks the original problem down into two smaller subproblems for further exploration.

[0133] In this embodiment of the invention, the branch and bound algorithm is a global optimization method for solving discrete optimization problems (such as integer programming and combinatorial optimization) and complex non-convex continuous optimization problems. Its core idea is to decompose the original problem into smaller subproblems (branches) and gradually narrow the search space by combining upper and lower bound estimations (bounding), ultimately finding the global optimum. The original problem is taken as the root node, and the lower bound of the objective function of the current node is calculated by relaxing the problem (such as ignoring integer constraints or simplifying nonlinear conditions). Then, the problem is branched according to variable values ​​or constraints, generating several subproblems and adding them to the search queue. In each iteration, by comparing the quality of the relaxed solutions of the subproblems with known feasible solutions, branches that cannot possibly contain better solutions are eliminated (pruning), thereby avoiding invalid computation. This combination of divide-and-conquer strategy and intelligent pruning allows the algorithm to significantly reduce computational complexity while ensuring global optimum.

[0134] The following analysis will take the improved power system test model (IEEE39) node example as an example for further analysis.

[0135] Figure 5 This is a schematic diagram of an improved power system test model node system according to an embodiment of the present invention, such as... Figure 5As shown, the reference value for both the AC and DC systems is 100MW. The transmission lines from node 3 to node 18 and from node 4 to node 14 in the original system are deleted. DC converter stations are connected at nodes 4, 14, and 18, and the DC converter stations are interconnected in pairs. Nodes 19-39 also represent nodes. Converter station 1 operates in rectification mode, while converter stations 2 and 3 operate in inverter mode. Converter station 1 uses a constant DC side voltage control method, while converter stations 2 and 3 use a constant active power control method. The DC voltage utilization rate of the converter stations is set to 0.9.

[0136] The relevant parameters of each node in the AC section of the simulation system are shown in Tables 2, 3, and 4. The parameters and control methods of the DC converter station are shown in Tables 5 and 6. In the bus parameters, Type is the node type, 1 is the PQ node, 2 is the PV node, and 3 is the slack node. Qd is the load size connected to the node, Vmax is the upper limit of the node voltage amplitude, and Vmin is the lower limit of the node voltage amplitude. In the branch parameters, fbus is the branch starting node, tbus is the branch ending node, r is the branch resistance, x is the branch reactance, and b is the branch susceptance to ground. In the generator parameters, Pg and Qg are the initial active and reactive power outputs of the generator, Pmax and Pmin are the upper and lower limits of the generator active power output, and Qmax and Qmin are the upper and lower limits of the generator reactive power output.

[0137] Table 2 IEEE 39-bus system bus parameters

[0138]

[0139]

[0140] Table 3. Modified parameters of each branch of the IEEE 39-node system

[0141]

[0142]

[0143] Table 4. Modified generator parameters for the IEEE 39-bus system

[0144]

[0145] Table 5 Control parameters for DC converter stations (Case 1: Power direction is positive when flowing into the AC network)

[0146]

[0147] Table 6 Control parameters for DC converter stations (Case 2, power direction is positive when flowing into the AC network)

[0148]

[0149]

[0150] Optionally, in Case 1, the active power control method of the converter station is as follows: Converter station 1 adopts constant DC voltage control, and the control parameter value is set to 1.41 per unit value. Other converter stations adopt constant active power control, and the reactive power control method is constant AC reactive power control. The optimized parameters of the converter station are shown in Table 7, and the optimized generator active and reactive power outputs are shown in Table 8. Figure 6 This is a schematic diagram of the voltage amplitude at each node according to an embodiment of the present invention, where the voltage amplitude at each node is as follows: Figure 6 As shown.

[0151] Table 7 Parameters of the DC Converter Station in Case 1

[0152]

[0153] Table 8. Active and Reactive Power Output of Generator in Case 1

[0154]

[0155] Optionally, in Case 2, the active power control method for the converter stations is as follows: Converter station 1 adopts constant DC voltage control, with the control parameter value set to 1.41 per unit; the other converter stations adopt constant active power control, with the output active power set to 1.08 per unit and 0.01 per unit, respectively. The reactive power control method is set to constant AC bus voltage control. The optimized parameters of the converter stations are shown in Table 9, and the generator active and reactive power outputs are shown in Table 10. Figure 7 This is a schematic diagram of the voltage amplitude at each node according to another embodiment of the present invention, where the voltage amplitude at each node is as follows: Figure 7 As shown.

[0156] Table 9 Parameters of the DC Converter Station in Case 2

[0157]

[0158] Table 10. Active and Reactive Power Output of Generator in Case 2

[0159]

[0160]

[0161] In this embodiment of the invention, parameters of each bus in the AC system (including bus type, bus active load, bus reactive load, and the highest and lowest voltage amplitudes of the bus during operation), parameters of each branch (including the start and end nodes, resistance, reactance, susceptance, and turns ratio of each branch), and parameters of the generators (including the bus connection number, upper and lower limits of active and reactive power output) are read in and converted into per-unit values. Control parameters for the multi-terminal flexible DC converter station are set; a node admittance matrix is ​​constructed, and system safety constraints and objective functions are set; a solver is called to solve the optimization problem, obtaining the optimal solution under constraints, and outputting the parameter values ​​under the optimal solution (including the active and reactive power outputs of each generator, the voltage status of each bus, the power exchange between the flexible DC converter station and the AC grid, and the power status of the DC lines); the various operating control parameters of the converter station under the optimal solution are calculated, thus providing the power flow adjustment direction. This solves the technical problem of low accuracy in power flow adjustment of the power grid and achieves the technical effect of improving the accuracy of power flow adjustment in the power grid.

[0162] Example 3

[0163] This invention provides a power flow adjustment device for a power grid. It should be noted that the power flow adjustment device of this invention can be used to perform... Figure 1 The present invention provides a method for adjusting power flow in a power grid. The following describes a power flow adjustment device for a power grid provided in an embodiment of the present invention.

[0164] Figure 8 This is a schematic diagram of the structure of a power flow adjustment device for a power grid according to an embodiment of the present invention, as shown below. Figure 8 As shown, the power flow adjustment device 800 of the power grid may include: an acquisition unit 802, an analysis unit 804, and an adjustment unit 806.

[0165] The acquisition unit 802 is used to acquire first attribute information of the AC network and second attribute information of the multi-terminal flexible DC converter station. The first attribute information is used to represent the operating status of the bus, the operating status of the branch, and the operating status of the generator in the AC network, respectively. The second attribute information is used to represent at least the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station.

[0166] Analysis unit 804 is used to analyze the first attribute information and the second attribute information using the power flow model to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under the constraints. The constraints are used to represent the upper and lower limits of the first attribute information and the upper and lower limits of the second attribute information. The objective function is used to represent the adjustment target of the power grid operation.

[0167] The adjustment unit 806 is used to adjust the first attribute information and the second attribute information based on the constraints and the objective function, obtain the adjustment result, and determine the power flow adjustment direction of the power grid based on the adjustment result.

[0168] The power flow adjustment device for a power grid provided in this embodiment of the invention acquires first attribute information of an AC network and second attribute information of a multi-terminal flexible DC converter station through an acquisition unit 802. The first attribute information represents the operating status of the bus, branch, and generator in the AC network, respectively, while the second attribute information represents at least the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. An analysis unit 804 analyzes the first and second attribute information using a power flow model to obtain the constraints and objective function of the power flow model. The power flow model determines the power flow distribution state of the power grid under constraints, the constraints represent the upper and lower limits of the first and second attribute information, and the objective function represents the adjustment target of the power grid operation. An adjustment unit 806 adjusts the first and second attribute information based on the constraints and objective function to obtain the adjustment result. Based on the adjustment result, the direction of power flow adjustment for the power grid is determined, thereby solving the technical problem of low accuracy in power flow adjustment and achieving the technical effect of improving the accuracy of power flow adjustment.

[0169] Example 4

[0170] According to an embodiment of the present invention, a computer-readable storage medium is also provided, on which a program is stored, which, when executed by a processor, implements the method of the embodiments of the present invention.

[0171] Example 5

[0172] According to an embodiment of the present invention, a processor is also provided, which is used to run a program, wherein the program executes the method of the embodiment of the present invention during runtime.

[0173] Example 6

[0174] Figure 9 This is a schematic diagram of an electronic device according to an embodiment of the present invention, such as... Figure 9 As shown in the embodiment of the present invention, an electronic device 900 is also provided. The device includes a processor 901, a memory 902, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the above steps.

[0175] The devices mentioned in this article can be servers, PCs, tablets (Portable Automated Devices, or PADs for short), mobile phones, etc.

[0176] The present invention also provides a computer program product that, when executed on a data processing device, is adapted to execute a program that initializes the above-described method steps.

[0177] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, compact disc read-only memory (CD-ROM), optical storage, etc.) containing computer-usable program code.

[0178] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0179] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0180] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0181] In a typical configuration, a computing device includes one or more central processing units (CPUs), input / output interfaces, network interfaces, and memory.

[0182] Memory may include non-persistent memory in computer-readable media, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0183] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. As defined in this article, computer-readable media do not include transient computer-readable media, such as modulated data signals and carrier waves.

[0184] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0185] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0186] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for adjusting the power flow of a power grid, characterized in that, The power grid includes an AC network and multi-terminal flexible DC converter stations, and the method includes: The first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station are obtained. The first attribute information is used to represent the operating status of the bus, the operating status of the branch, and the operating status of the generator in the AC network, respectively. The second attribute information is used to represent the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. Using a power flow model, the first attribute information and the second attribute information are analyzed to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under the constraints. The constraints are used to represent the upper and lower limits of the first attribute information and the upper and lower limits of the second attribute information. The objective function is used to represent the adjustment target of the power grid operation. Based on the constraints and the objective function, the first attribute information and the second attribute information are adjusted to obtain the adjustment result, and based on the adjustment result, the power flow adjustment direction of the power grid is determined.

2. The power flow adjustment method for a power grid according to claim 1, characterized in that, The power flow model includes an AC network constrained power flow model and a flexible DC converter valve mathematical model. Using the power flow model, the first attribute information and the second attribute information are analyzed to obtain the constraints and objective function of the power flow model, including: Using the AC network constrained power flow model, the first attribute information is analyzed to obtain the constraint conditions corresponding to the first attribute information and the objective function corresponding to the first attribute information, wherein the AC network constrained power flow model is a nonlinear programming model; The method further includes: transforming the AC network constrained power flow model based on the constraints and the objective function to obtain the transformed AC network constrained power flow model, wherein the solution difficulty of the transformed AC network constrained power flow model is lower than that of the original AC network constrained power flow model.

3. The power flow adjustment method for a power grid according to claim 2, characterized in that, The method further includes: Using the mathematical model of the flexible DC converter valve, the first attribute information and the second attribute information are analyzed to obtain the power exchanged between the multi-terminal flexible DC converter station and the AC power grid, wherein the power includes active power and / or reactive power.

4. The power flow adjustment method for a power grid according to claim 3, characterized in that, The constraints include equality constraints and inequality constraints. Using a power flow model, the first attribute information and the second attribute information are analyzed to determine the constraint conditions of the power flow model, including: Using the mathematical model of the flexible DC converter valve, the first attribute information and the second attribute information are analyzed to obtain the operating constraints of the multi-terminal flexible DC converter station and the DC line, as well as the upper and lower limit constraints of the generator's active and reactive power output. The DC line is used to represent the high-voltage DC transmission line connecting the multi-terminal converter stations, the active power output is used to represent the actual electrical power output by the generator to the power grid, and the reactive power output is used to represent the electrical power required to maintain the operation of the power grid and the multi-terminal converter station. Based on the operational constraints and the upper and lower limit constraints, the equality constraints and the inequality constraints are determined, wherein the equality constraints are used to represent the physical relationships and power conservation principles satisfied between the various components within the power grid, and the inequality constraints are used to represent the information range to which the first attribute information belongs and the information range to which the second attribute information belongs.

5. The power flow adjustment method for a power grid according to claim 1, characterized in that, After acquiring the first attribute information of the AC network and the second attribute information of the multi-terminal flexible DC converter station, the method further includes: The first attribute information and the second attribute information are converted to obtain per-unit values, wherein the per-unit values ​​are used to unify the first attribute information and the second attribute information to the same scale.

6. The power flow adjustment method for a power grid according to claim 1, characterized in that, Based on the constraints and the objective function, the first attribute information and the second attribute information are adjusted to obtain an adjustment result, and based on the adjustment result, the power flow adjustment direction of the power grid is determined, including: Using the constraints as the root node, the integer constraints of the constraints are deleted to obtain a subset of constraints, wherein the root node is used to represent the initial operating state of the power grid; The first determining step is to determine the upper and lower bounds of the initial objective function of the current node based on the subset of constraints, wherein the current node is used to represent the subset of constraints from the root node to the current node; The second determination step involves, in response to the existence of a next node for the current node, determining the next node as the current node, returning to execute the first determination step, until the current node does not have a next node, and performing branch operations on the constraint subset and the upper and lower bounds of the initial objective function of the current node respectively to obtain the upper and lower bounds of the objective function of the current node; Based on the determined upper and lower bounds of the objective function, the first attribute information and the second attribute information are adjusted to obtain the power flow adjustment direction of the power grid.

7. A power flow adjustment device for a power grid, characterized in that, The power grid includes an AC network and multi-terminal flexible DC converter stations, and the device includes: The acquisition unit is used to acquire first attribute information of the AC network and second attribute information of the multi-terminal flexible DC converter station, wherein the first attribute information is used to represent the operating status of the bus, the operating status of the branch, and the operating status of the generator in the AC network, respectively, and the second attribute information is used to represent at least the modulation ratio and phase shift angle of the multi-terminal flexible DC converter station. The analysis unit is used to analyze the first attribute information and the second attribute information using a power flow model to obtain the constraints and objective function of the power flow model. The power flow model is used to determine the power flow distribution state of the power grid under the constraints. The constraints are used to represent the upper and lower limits of the first attribute information and the upper and lower limits of the second attribute information. The objective function is used to represent the adjustment target of the power grid operation. The adjustment unit is used to adjust the first attribute information and the second attribute information based on the constraints and the objective function to obtain the adjustment result, and to determine the power flow adjustment direction of the power grid based on the adjustment result.

8. A processor, characterized in that, The processor is used to run a program, wherein the program is executed by the processor to perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 6.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 6.

11. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 6.

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