A power system optimal reactive power flow calculation method and system

Abstract

The present application relates to the technical field of power system, in order to solve the problem that the current reactive power flow calculation result cannot be applied to the actual operation system, provide a kind of power system optimal reactive power flow calculation method and system.Power system optimal reactive power flow calculation method includes with the active power network loss in power system as minimum to construct objective function, then combine linearized power flow equation, the reactive power output limit value corresponding to synchronous generator in power system and the linearization approximation constraint converted by the constraint of the internal potential and output current of inverter, construct optimal reactive power flow model and solve to obtain the new operation mode of power system;After obtaining the new operation mode of power system, recalculate the power flow distribution of power system, obtain the active power network loss of power system under new operation mode, in the process of successive linear approximation, the active power network loss is continuously reduced.It can obtain the optimal reactive power flow calculation result, guarantee the stability of power system.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method and system for calculating optimal reactive power flow in a power system. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Reactive power-voltage control is a key technology for ensuring the safe and economical operation of power systems. Based on the completion of unit combination and economic dispatch, the optimal operating scheme for reactive power regulation equipment in the system is accurately determined by establishing a reactive power optimization power flow model. Accurate modeling of reactive power regulation equipment in the power system is a prerequisite for establishing a correct reactive power-voltage control strategy, which requires that the established reactive power optimization model be consistent with the operating characteristics of modern power systems. Currently, most renewable energy sources are connected to the grid through inverters rather than synchronous motors. Correctly modeling the operating characteristics of inverters and incorporating them into the optimal power flow solution model is of great significance for stabilizing node voltages, optimizing system network losses, and improving operating efficiency.

[0004] Most existing technologies focus on the impact of inverters on power system stability. In power flow calculation and optimization, traditional synchronous generators are usually modeled as PV or PQ nodes. Their feasible operating region on the QV plane is represented as a rectangle composed of upper and lower limits of reactive power output and node voltage amplitude constraints. There is a lack of accurate methods to characterize the feasible operating region of inverters in steady state, which makes it impossible to apply the reactive power flow calculation results to the actual operating system and to ensure the stability of the power system. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and system for calculating optimal reactive power flow in power systems. It uses a linearized approximation model of the optimal reactive power flow model that considers inverter operating constraints, and can obtain optimal reactive power flow calculation results. This method can be applied to actual operating systems to ensure the stability of the power system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of this invention provides a method for calculating the optimal reactive power flow in a power system.

[0008] In one or more embodiments, a method for calculating the optimal reactive power flow of a power system is provided, comprising:

[0009] Based on the current operating parameters of the power system, the objective function is constructed with the minimum active power network loss in the power system as the objective function. Then, combined with the linearized power flow equation, the reactive power output limit corresponding to the synchronous generator in the power system, and the linearized approximate constraint converted from the constraint of the internal potential and output current of the inverter, the optimal reactive power flow model is constructed and the new operating mode of the power system is obtained by solving it.

[0010] After obtaining the new operating mode of the power system, the power flow distribution of the power system is recalculated to obtain the active power network loss of the power system under the new operating mode. When the active power network loss is higher than the recorded historical value, the power flow optimization process stops, and the power flow optimization result will be rolled back to the previous power flow solution, which is the optimal operating mode of the power system. Otherwise, the optimal reactive power flow model is reconstructed and solved. In the process of successive linear approximations, the active power network loss is continuously reduced until the optimal operating mode of the power system is obtained.

[0011] As one implementation method, by analyzing the steady-state characteristics of the inverter, the constraints of the inverter's internal potential and output current are obtained, and then transformed into a linear form through a first-order Taylor series expansion, thus obtaining the linearized approximate constraints of the inverter's internal potential and output current.

[0012] As one implementation method, the internal potential of the inverter is constrained as follows:

[0013] ;

[0014] in, This represents the internal electromotive force of the inverter. This represents the maximum value of the corresponding internal potential; This represents the bus node for new energy sources to connect to the power grid, and also serves as a generator node in power flow calculation; This indicates the common connection point, which is the AC side node of the inverter; This indicates the amount of reactive power injected. AC power grid bus Voltage amplitude at the location; Represents a node and nodes The phase angle difference between them; and Representing nodes respectively The equivalent resistance and equivalent reactance of the inverter at the location are, and the equivalent impedance is... The corresponding impedance angle is ; This represents the AC filter reactance of the inverter.

[0015] As one implementation method, the constraint of the inverter's internal electromotive force can be expressed in the form of a first-order Taylor series expansion as follows:

[0016] ;

[0017] ;

[0018] ;

[0019] in, , The first Taylor coefficient of internal potential in the next optimization iteration; For the first AC power grid bus in the second optimization iteration The voltage amplitude at that location.

[0020] As one implementation method, the output current of the inverter is constrained as follows:

[0021] ;

[0022] in, This is the output current value of the inverter. This represents the maximum value of the output current. This represents the bus node for new energy sources to connect to the power grid, and also serves as a generator node in power flow calculation; This indicates the common connection point, which is the AC side node of the inverter; This indicates the amount of active power injected. This indicates the amount of reactive power injected. AC power grid bus Voltage amplitude at the location; This represents the AC filter reactance of the inverter.

[0023] As one implementation method, the constraint on the inverter's output current, expressed as a first-order Taylor series expansion, is as follows:

[0024] ;

[0025] ;

[0026] ;

[0027] in, For the first Taylor coefficient of output current in the next optimization iteration; For the first The amount of reactive power injected in the next optimization iteration; These are slack variables.

[0028] As one implementation method, the power flow equation is linearized based on the linearized approximation constraints of the inverter's internal potential and output current. The voltage magnitude constraints of the nodes in the linearized power flow equation are represented by a quadratic form.

[0029] A second aspect of the present invention provides an optimal reactive power flow calculation system for a power system.

[0030] In one or more embodiments, a power system optimal reactive power flow calculation system includes:

[0031] The optimal reactive power flow model construction module is used to construct an objective function based on the current operating parameters of the power system, with the active power network loss in the power system as the minimum. Then, it combines the linearized power flow equation, the reactive power output limit corresponding to the synchronous generator in the power system, and the linearized approximate constraints converted from the internal potential and output current constraints of the inverter to construct the optimal reactive power flow model and solve it to obtain the new operating mode of the power system.

[0032] The optimal operating mode solution module is used to recalculate the power flow distribution of the power system after obtaining the new operating mode, and obtain the active power network loss of the power system under the new operating mode. When the active power network loss is higher than the recorded historical value, the power flow solution optimization process stops, and the power flow solution optimization result will be rolled back to the previous power flow solution, which is the optimal operating mode of the power system. Otherwise, the optimal reactive power flow model is reconstructed and solved, and the active power network loss is continuously reduced in the process of successive linear approximation until the optimal operating mode of the power system is obtained.

[0033] A third aspect of the present invention provides a computer-readable storage medium.

[0034] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method for calculating optimal reactive power flow in a power system.

[0035] A fourth aspect of the present invention provides an electronic device.

[0036] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the above-described method for calculating optimal reactive power flow in a power system.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] (1) The optimal reactive power flow calculation method of the present invention analyzes the steady-state characteristics of the inverter, expresses the constraints of the inverter's internal potential and output current, and transforms them into a linear form through a first-order Taylor series expansion. These two types of constraints can be embedded into the linearized power flow equation for solution. The corresponding optimal reactive power flow model is established and solved by successive linearization approximation. The internal constraints of the inverter are considered. By establishing a corresponding model for the steady-state operation of the inverter, the constructed model is aligned with the characteristics of the actual operating system, thus avoiding unusable power flow solutions.

[0039] (2) The optimal reactive power flow calculation method of the power system of the present invention linearizes the internal potential constraint and output current constraint of the inverter by first-order Taylor series expansion in the model construction, and incorporates the relevant constraints into the linearized power flow equation, so that the established model can be solved quickly by linear programming, thereby improving the solution speed. Attached Figure Description

[0040] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0041] Figure 1 This is the equivalent circuit of renewable energy connected to the grid via the inverter grid connection interface in an embodiment of the present invention;

[0042] Figure 2 This is a modified IEEE-39 node system topology diagram according to an embodiment of the present invention;

[0043] Figure 3 This is a flowchart of the optimal reactive power flow calculation method for a power system according to an embodiment of the present invention;

[0044] Figure 4 This is a comparison of the inverter's internal electromotive force under different power flow solutions in embodiments of the present invention;

[0045] Figure 5 This is a schematic diagram of the optimal reactive power flow calculation system structure of the power system according to an embodiment of the present invention;

[0046] Figure 6 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0047] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0048] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0049] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0050] The proportion of traditional synchronous generators powered by fossil fuels in the power system is declining, while the proportion of renewable energy generation (such as wind and solar power) using inverters as grid-connected interfaces is continuously increasing. This is not only reducing carbon emissions in the power industry but also fundamentally changing the operating characteristics of the power system, thereby altering the decision-making basis and models of power system operators. The output power of an inverter is limited by its internal potential and output current, requiring the establishment of its specific constraints in the optimal power flow model to accurately reflect the inverter's operating range. Currently, many methods, such as linear programming, interior-point methods, and artificial intelligence methods, have been applied to solve the optimal power flow problem in power systems. Among them, linear programming has been widely used in engineering practice due to its good convergence performance and the availability of excellent solution software such as CPLEX and GUROBI. Furthermore, compared with conventional optimal power flow models, the appropriate selection of variable forms can significantly reduce the errors caused by linearization, providing a theoretical basis for the linearization method of inverter operating constraints. Therefore, this invention mainly focuses on the linearization approximation problem of inverter operating constraints.

[0051] This invention proposes a linearized approximation model for the optimal reactive power flow model considering inverter operating constraints. Based on the steady-state characteristics of the inverter and the linearized power flow equations, a linearization method for the inverter's internal potential constraints and output current constraints based on first-order Taylor series expansion is derived. These constraints are then incorporated into the optimal power flow model, establishing a successive linear approximation iterative solution algorithm for the optimal reactive power flow considering inverter operating constraints. Finally, the effectiveness of the proposed method is verified using a modified IEEE-39 node as a case study.

[0052] Figure 3 A schematic diagram of the optimal reactive power flow calculation method for power systems according to an embodiment of the present invention is provided. Figure 3 The optimal reactive power flow calculation method for the power system in this embodiment may include the following steps S301 to S302.

[0053] The specific implementation process of steps S301 to S302 is as follows:

[0054] Step S301: Based on the current operating parameters of the power system, construct the objective function with the minimum active power network loss in the power system as the objective function. Then, combine the linearized power flow equation, the reactive power output limit corresponding to the synchronous generator in the power system, and the linearized approximate constraint converted from the constraint of the internal potential and output current of the inverter, construct the optimal reactive power flow model, and solve it to obtain the new operating mode of the power system.

[0055] The equivalent circuit of renewable energy connected to the grid through the inverter grid interface is as follows: Figure 1 As shown, this indicates that renewable energy generation processes the active and reactive power of the power grid through an inverter. Figure 1 middle, This represents the bus node where new energy sources are connected to the power grid, and it also serves as a generator node in power flow calculation. This refers to the point of common coupling, which is the AC side node of the inverter. To protect the internal semiconductor devices of the inverter from damage, upper limits are set for both the output voltage and output current at the point of common coupling. The inverter then... (The sentence is incomplete and requires further context to translate accurately.) The active and reactive power injections into the AC power grid are respectively:

[0056] (1);

[0057] (2);

[0058] in, This indicates the amount of active power injected. This indicates the amount of reactive power injected. and These represent the inverter at the node. The active and reactive power outputs; AC power grid bus Voltage amplitude at that point Inverter-side node The amplitude of the internal potential at that point, Represents a node and nodes The phase angle difference between them; and Representing nodes respectively The equivalent resistance and equivalent reactance of the inverter at the location are, and the equivalent impedance is... The corresponding impedance angle is ; This represents the AC filter reactance of the inverter.

[0059] It can be calculated by the following expression:

[0060] (3);

[0061] Before establishing the power flow and corresponding optimization model, the impact of the inverter's internal limitations on its output must be considered and quantified. For traditional synchronous generators, the reactive power output must be set... and voltage amplitude Determining the upper and lower bounds is a common method. However, inverters have a completely different structure from synchronous motors, and their operating constraints are determined by their internal parameters. For power flow analysis, the steady-state output limit conditions of the inverter are determined by its internal potential and output current, expressed as:

[0062] (4);

[0063] (5);

[0064] in, This represents the internal electromotive force of the inverter. This represents the maximum value of the corresponding internal potential; This is the output current value of the inverter. This represents the maximum output current.

[0065] Based on the linearized approximation constraints of the inverter's internal potential and output current, the power flow equations are linearized. The voltage magnitude constraints of the nodes in the linearized power flow equations are expressed in quadratic form. Based on the inverter operating constraints proposed above, the linearized approximation method of the power flow equations is given by formulas (6)-(8), and formulas (9)-(18) represent the specific expressions of some parameters, where the selected parameters are... , , and As an independent variable:

[0066] (6);

[0067] (7);

[0068] (8);

[0069] (9);

[0070] (10);

[0071] (11);

[0072] (12);

[0073] (13);

[0074] (14);

[0075] (15);

[0076] (16);

[0077] (17);

[0078] (18);

[0079] in, , Representing nodes respectively Active and reactive power generation at the location (and the inverter) , (equivalent) , Representing nodes respectively Active and reactive loads at the location; For nodes Voltage amplitude at that point For nodes Voltage amplitude at the location; For nodes and nodes The phase angle difference. and They are nodes Self-conductivity and self-susceptivity; and They are nodes With nodes Mutual conductance and mutual susceptance between them; The total number of nodes; superscript Indicates the first This is the second optimization iteration. , , and All of these are intermediate parameters of phase angle difference; and These are all intermediate parameters of the voltage amplitude at the nodes; to improve the robustness of the model, this invention introduces slack variables into the model, represented as... ; and They represent the first In the next optimization iteration and The value of will be saved and updated during the iteration process. and Indicates the first In this optimization iteration, the node With nodes Intermediate parameters of mutual conductance between them; and Indicates the first In this optimization iteration, the node With nodes Intermediate parameters of mutual susceptance.

[0080] For new energy grid-connected nodes with inverters as grid-connection interfaces, it is necessary to formulate regulations for... Additional constraints to avoid internal electromotive force of the inverter With output current Exceeding the limits. Therefore, the linearization method for the constraints on the internal electromotive force and output current of the inverter's steady-state output is as follows:

[0081] Linearization method for internal potential constraint in inverter:

[0082] First, reconstructing formula (4), we have:

[0083] (19);

[0084] Among them, the one on the right for:

[0085] (20);

[0086] right Expanding the series by a first-order Taylor series, we have:

[0087] (twenty one);

[0088] in, , The first Taylor coefficient of internal potential in the next optimization iteration;

[0089] (twenty two);

[0090] (twenty three);

[0091] Substituting equation (21) into equation (19), we obtain the linearized approximate expression for the internal potential constraint, which is:

[0092] (twenty four);

[0093] Linearization approximation method for inverter output current constraint:

[0094] Reconstructing formula (5), we have the following expression:

[0095] (25);

[0096] For the formula Expanding the series by a first-order Taylor series, we have:

[0097] (26);

[0098] in, For the first Taylor coefficient of output current in the next optimization iteration:

[0099] (27);

[0100] Therefore, the linearized approximate expression for formula (25) is obtained as follows:

[0101] (28);

[0102] because Since it is non-negative, formula (29) is added as a constraint in this invention to avoid negative values. The relevant expression is as follows:

[0103] (29);

[0104] In the above formula, analogous to the treatment of formula (8), the present invention adds slack variables to the formula. To enhance robustness during the iteration process.

[0105] The optimal reactive power flow model can be expressed in the following form:

[0106] The objective function is:

[0107] (30);

[0108] The constraints are:

[0109] (31);

[0110] (32);

[0111] (33);

[0112] Formula (30) represents the network loss of active power in the system. The objective function of the model is to minimize the total active power generation of the power generation equipment. For nodes The maximum voltage amplitude at that location; For nodes Minimum voltage amplitude at that location; For nodes The maximum reactive power generation at the location; For nodes The minimum reactive power generation at that location.

[0113] In the constraints, the linearized power flow equations are represented by formulas (6)-(8), and the voltage magnitude constraints of the nodes are represented by quadratic forms. For the synchronous generator in the system, the corresponding reactive power output limit is represented by formula (33), while the linearized approximate constraints of the internal potential and output current of the inverter are represented by formulas (24), (28) and (29).

[0114] Step S302: After obtaining the new operating mode of the power system, recalculate the power flow distribution of the power system to obtain the active power network loss of the power system under the new operating mode; when the active power network loss is higher than the recorded historical value, the power flow optimization process stops, and the power flow optimization result will be rolled back to the previous power flow solution, which is the optimal operating mode of the power system; otherwise, reconstruct the optimal reactive power flow model and solve it, continuously reducing the active power network loss in the process of successive linear approximation until the optimal operating mode of the power system is obtained.

[0115] To verify the effectiveness of the proposed method, the IEEE-39 Node system is used as a case study. The system topology is as follows: Figure 2 As shown in Table 1. The relevant example data comes from MATPOWER 8.0, and CPLEX was selected as the linear programming solver for this model. Except for nodes 31 and 39, the synchronous generators connected to the remaining nodes were replaced with renewable energy generation equipment using inverters as the grid connection interface. The relevant parameters are shown in Table 1. In the improved system, the penetration rate of renewable energy reached 73%.

[0116] Table 1. Parameters of the inverter equipment;

[0117]

[0118] It should be noted that all parameters in Table 1 are per-unit values.

[0119] During the successive linearization approximation process, the active power loss decreased from 0.4365 (pu) in the initial power flow state to 0.4132 (pu), and rebounded to 0.4287 (pu) in the last iteration. In comparison, applying the method proposed in this invention to the unmodified system resulted in a slight decrease in power loss to 0.4325 (pu); this indicates that the initial operating mode is an excellent operating scheme with little room for improvement, and the proposed optimal reactive power flow model can effectively utilize the inverter's regulation capability.

[0120] This example also compares the impact of considering inverter operating constraints. For example... Figure 4 As shown, for renewable energy grid-connected nodes with inverters as grid-connected interfaces, three power flow states are calculated for these renewable energy grid-connected nodes: initial power flow operation mode, power flow operation mode based on the optimal reactive power flow model proposed for the modified system application, and power flow operation mode based on the optimal reactive power flow model proposed for the original system application. Under the above three power flow operation modes, the internal potential of each renewable energy grid-connected node is denoted as UC_init, UC_opt(IBG), and UC_opt(SG), respectively, and the maximum internal potential of each node is denoted as UC_max. In this embodiment of the invention, the nodes equipped with renewable energy grid-connected inverters are eight nodes, including BUS-30, BUS-32, and BUS-33.

[0121] according to Figure 4 The comparison shows that the method proposed in this invention can ensure that the internal potential amplitude of the inverter will not exceed the internal potential constraint condition. In contrast, if the grid-connected nodes of renewable energy with inverters as the grid interface are still modeled according to the traditional synchronous machine model, the internal potentials of nodes 32 (i.e., BUS-32) and 33 (i.e., BUS-33) will exceed their maximum values, and the power system operator may obtain an infeasible power flow operation mode. At this time, in order to protect the semiconductor devices inside the inverter, the inverter will reduce its own reactive power output to prevent serious inverter failure, forcing the power system to operate under insufficient reactive power support.

[0122] like Figure 5 As shown, the optimal reactive power flow calculation system for power systems provided in this embodiment of the invention can be implemented in software. The optimal reactive power flow calculation system for power systems includes the following software modules: optimal reactive power flow model construction module 501 and optimal operation mode solution module 502.

[0123] The functions of each software module in the optimal reactive power flow calculation system for power systems are described below:

[0124] The optimal reactive power flow model construction module 501 is used to construct an objective function based on the current operating parameters of the power system, with the active power network loss in the power system as the minimum. Then, it combines the linearized power flow equation, the reactive power output limit corresponding to the synchronous generator in the power system, and the linearized approximate constraint converted from the constraint of the internal potential and output current of the inverter to construct the optimal reactive power flow model and solve it to obtain the new operating mode of the power system.

[0125] The optimal operating mode solution module 502 is used to recalculate the power flow distribution of the power system after obtaining the new operating mode of the power system, and obtain the active power network loss of the power system under the new operating mode. When the active power network loss is higher than the recorded historical value, the power flow solution optimization process stops, and the power flow solution optimization result will be rolled back to the previous power flow solution, which is the optimal operating mode of the power system. Otherwise, the optimal reactive power flow model is reconstructed and solved, and the active power network loss is continuously reduced in the process of successive linear approximation until the optimal operating mode of the power system is obtained.

[0126] It should be noted that each module in the power system optimal reactive power flow calculation system of the present invention corresponds one-to-one with each step in the power system optimal reactive power flow calculation method in the above embodiments, and their specific implementation processes are the same, so they will not be repeated here.

[0127] The structure of the electronic device according to an embodiment of the present invention will be described in detail below. Figure 6 This is a schematic diagram of the composition structure of an electronic device provided in an embodiment of the present invention. It can be understood that... Figure 6 The diagram shows only an exemplary structure of the electronic device, not the entire structure. Some or all of the structures shown may be implemented as needed.

[0128] The electronic device provided in this embodiment of the invention includes: at least one processor 601, a memory 602, a user interface 603, and at least one network interface 604. The various components in the optimal reactive power flow calculation system of the power system are coupled together through a bus system 605. It can be understood that the bus system 605 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 605 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 6 The general designated all buses as Bus System 605.

[0129] The user interface 603 may include a monitor, keyboard, mouse, trackball, click wheel, buttons, touchpad, or touch screen.

[0130] It is understood that memory 602 can be volatile memory or non-volatile memory, or both. In this embodiment of the invention, memory 602 is capable of storing data to support the operation of the terminal. Examples of this data include any computer programs used to operate on the terminal, such as operating systems and applications. The operating system includes various system programs, such as framework layers, core library layers, driver layers, etc., used to implement various basic services and handle hardware-based tasks. Applications can include various applications.

[0131] In some embodiments, the optimal reactive power flow calculation system for power systems provided in this invention can be implemented using a combination of hardware and software. For example, the optimal reactive power flow calculation system for power systems provided in this invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the optimal reactive power flow calculation method for power systems provided in this invention. For instance, the processor in the form of a hardware decoding processor can employ one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0132] As an example, processor 601 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., wherein the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0133] As an example of the hardware implementation of the optimal reactive power flow calculation system for power systems provided in this embodiment of the invention, the device provided in this embodiment of the invention can be directly executed by a processor 601 in the form of a hardware decoding processor. For example, it can be executed by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components to implement the optimal reactive power flow calculation method for power systems provided in this embodiment of the invention.

[0134] The memory 602 in this embodiment of the invention is used to store various types of data to support the operation of the optimal reactive power flow calculation system for the power system, or to store data for execution. Figure 3 The program code for the method shown. Examples of this data include: any executable instructions for operation on a power system optimal reactive power flow calculation system, such as executable instructions, and programs implementing the power system optimal reactive power flow calculation method of this embodiment of the invention may be contained in executable instructions.

[0135] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including functions for executing... Figure 3 The program code for the method shown. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by the central processing unit, it performs the various functions defined in the apparatus of this application.

[0136] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as 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 1A device that provides the functions specified in one or more boxes.

[0137] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimal reactive power flow calculation of a power system, characterized in that, include: Based on the current operating parameters of the power system, the objective function is constructed with the minimum active power network loss in the power system as the objective function. Then, combined with the linearized power flow equation, the reactive power output limit corresponding to the synchronous generator in the power system, and the linearized approximate constraint converted from the constraint of the internal potential and output current of the inverter, the optimal reactive power flow model is constructed and the new operating mode of the power system is obtained by solving it. After obtaining the new operating mode of the power system, the power flow distribution of the power system is recalculated to obtain the active power network loss of the power system under the new operating mode. When the active power network loss is higher than the recorded historical value, the power flow optimization process stops, and the power flow optimization result will be rolled back to the previous power flow solution, which is the optimal operating mode of the power system. Otherwise, the optimal reactive power flow model is reconstructed and solved. In the process of successive linear approximations, the active power network loss is continuously reduced until the optimal operating mode of the power system is obtained. By analyzing the steady-state characteristics of the inverter, the constraints of the inverter's internal potential and output current are obtained, and they are transformed into a linear form through a first-order Taylor series expansion, thus obtaining the linearized approximate constraints of the inverter's internal potential and output current. The internal potential constraint of the inverter is: ； wherein, represents the internal voltage of the inverter, is the maximum value of the corresponding internal voltage; represents the bus node of the grid connected with the new energy, and also serves as a generator node in the power flow calculation; represents the point of common coupling, i.e. the AC side node of the inverter; represents the injection amount of reactive power; is the voltage amplitude at the AC grid bus ; represents the phase angle difference between the node and the node ; and respectively represent the equivalent resistance and the equivalent reactance of the inverter at the node , the equivalent impedance is , and the corresponding impedance angle is ; represents the AC filter reactance of the inverter; The constraint on the internal electromotive force of the inverter, expressed as a first-order Taylor series expansion, is as follows: ； ； ； in, , The first Taylor coefficient of internal potential in the next optimization iteration; For the first AC power grid bus in the second optimization iteration Voltage amplitude at the location; This indicates the amount of active power injected.

2. The optimal reactive power flow calculation method for a power system as described in claim 1, characterized in that, The output current of the inverter is constrained as follows: ； in, This is the output current value of the inverter. This represents the maximum output current.

3. The optimal reactive power flow calculation method for a power system as described in claim 2, characterized in that, The constraint on the inverter's output current, expressed as a first-order Taylor series expansion, is as follows: ； ； ； in, For the first Taylor coefficient of output current in the next optimization iteration; For the first The amount of reactive power injected in the next optimization iteration; These are slack variables.

4. The optimal reactive power flow calculation method for a power system as described in claim 1, characterized in that, Based on the linearized approximation constraints of the inverter's internal potential and output current, the power flow equation is linearized and approximated. The voltage magnitude constraints of the nodes in the linearized power flow equation are expressed in quadratic form. The quadratic form is represented as follows: in, For nodes Voltage amplitude at the location; For nodes The maximum voltage amplitude at that location; For nodes The minimum voltage amplitude at that location.

5. A power system optimal reactive power flow calculation system, characterized in that, The optimal reactive power flow calculation method for a power system based on any one of claims 1-4 includes: The optimal reactive power flow model construction module is used to construct an objective function based on the current operating parameters of the power system, with the active power network loss in the power system as the minimum. Then, it combines the linearized power flow equation, the reactive power output limit corresponding to the synchronous generator in the power system, and the linearized approximate constraints converted from the internal potential and output current constraints of the inverter to construct the optimal reactive power flow model and solve it to obtain the new operating mode of the power system. The optimal operating mode solution module is used to recalculate the power flow distribution of the power system after obtaining the new operating mode, and obtain the active power network loss of the power system under the new operating mode. When the active power network loss is higher than the recorded historical value, the power flow solution optimization process stops, and the power flow solution optimization result will be rolled back to the previous power flow solution, which is the optimal operating mode of the power system. Otherwise, the optimal reactive power flow model is reconstructed and solved, and the active power network loss is continuously reduced in the process of successive linear approximation until the optimal operating mode of the power system is obtained.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the optimal reactive power flow calculation method for power systems as described in any one of claims 1-4.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the power system optimal reactive power flow calculation method as described in any one of claims 1-4.

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