Multi-inverter coordinated reactive power compensation method and device, electronic equipment and storage medium

Abstract

The application relates to the technical field of power systems, and discloses a multi-inverter coordinated reactive power compensation method and device, an electronic device and a storage medium, the method comprising the following steps: collecting voltage data of a plurality of treatment nodes and reactive power capacity information of inverters; based on the voltage data, the reactive power capacity information and pre-stored power system network parameters, a target function is established, the target function is used to make the voltage of the plurality of treatment nodes approach a target voltage under the condition of satisfying the reactive power capacity constraints of the inverters, and the target function is solved to obtain optimal reactive power injection amounts of the inverters; and the corresponding inverters are controlled to perform reactive power compensation according to the optimal reactive power injection amounts. The application realizes real-time optimization control of multi-inverter coordinated compensation, stabilizes the voltage of the treatment nodes around a target value under the premise of satisfying the capacity constraints of the inverters, and significantly improves the voltage stability of a distribution network and the utilization efficiency of reactive power resources.

Description

Technical Field

[0001] This application relates to the field of power system technology, specifically to a method, device, electronic equipment, and storage medium for multi-inverter coordinated reactive power compensation. Background Technology

[0002] In the field of reactive power compensation technology for power systems, the improvement of voltage stability and power factor in distribution networks mainly relies on traditional dedicated compensation equipment, such as static var generators (SVG) and static synchronous compensators (STATCOM). Although these devices are technologically mature, their inherently high investment costs limit their large-scale deployment in distribution networks, resulting in limited reactive power compensation coverage and difficulty in coping with the global and dynamic reactive power demands brought about by the widespread integration of distributed power sources.

[0003] At the same time, with the high penetration rate of distributed photovoltaic power, there are a large number of grid-connected inverters in the distribution network. These inverters have considerable spare capacity when operating under light load, which could have been used as a decentralized reactive power compensation resource.

[0004] However, while some related technologies attempt to achieve multi-inverter coordination, they generally employ numerical iterative solutions, which inherently suffer from high computational complexity and long processing times, failing to meet the stringent requirements of real-time control in distribution networks for computational speed and efficiency. Therefore, the current technological landscape faces a prominent contradiction: on the one hand, expensive dedicated compensation equipment is insufficiently deployed due to economic constraints; on the other hand, the reactive power potential of numerous dispersed inverter resources remains untapped due to the lack of efficient and rapid collaborative optimization algorithms. This contradiction makes it difficult for distribution networks to achieve economical, efficient, and rapid voltage-reactive power coordinated control. Summary of the Invention

[0005] This application provides a method, device, electronic equipment, and storage medium for multi-inverter coordinated reactive power compensation to solve the problem of difficult-to-achieve economical, efficient, and fast voltage and reactive power coordinated control in power distribution networks.

[0006] In a first aspect, this application provides a multi-inverter coordinated reactive power compensation method, comprising: collecting voltage data of multiple governance nodes and reactive power capacity information of each inverter; establishing an objective function based on the voltage data, the reactive power capacity information, and pre-stored power system network parameters, wherein the objective function is used to make the voltage of the multiple governance nodes approach a target voltage under the condition of satisfying the reactive power capacity constraints of each inverter, and solving the objective function to obtain the optimal reactive power injection amount of each inverter; and controlling the corresponding inverter to perform reactive power compensation according to the optimal reactive power injection amount.

[0007] Beneficial Effects: This application collects voltage data from multiple governance nodes and capacity information of each inverter, establishes and solves an objective function based on power system network parameters, and finally controls the inverters for compensation according to the optimal reactive power injection. This effectively solves the problem of limited coverage of dedicated compensation equipment in related technologies. By utilizing the remaining capacity of existing distributed inverters, the investment cost of reactive power compensation equipment is significantly reduced. Simultaneously, it overcomes the high computational complexity of related coordination algorithms. By establishing an objective function model suitable for rapid solution, real-time optimized control of multi-inverter collaborative compensation is achieved. This enables the system to quickly stabilize the voltage of governance nodes near the target value while meeting the capacity constraints of each inverter, significantly improving the voltage stability and reactive power resource utilization efficiency of the distribution network.

[0008] In one optional implementation, establishing the objective function includes: calculating a voltage-reactive power sensitivity matrix based on the power system network parameters, wherein the sensitivity matrix is ​​used to characterize the linear relationship between the reactive power injection change and the node voltage change; constructing a voltage deviation term based on the voltage-reactive power sensitivity matrix, the target voltage, and the voltage data; constructing a capacity penalty term based on the optimal reactive power injection amount and the maximum reactive power capacity of each inverter; and defining the combination of the voltage deviation term and the capacity penalty term as the objective function.

[0009] Beneficial effects: By constructing an objective function that includes voltage deviation and capacity penalty terms, the optimization process simultaneously considers voltage regulation accuracy and safe equipment operation. The voltage deviation term directly corresponds to the voltage stability target, ensuring that the system voltage quickly approaches the target value; the capacity penalty term effectively prevents equipment overload risk by limiting the inverter's reactive power output to its maximum capacity, enabling the optimal solution to achieve the best balance between voltage quality and equipment safety.

[0010] In one optional implementation, the values ​​of the elements in the voltage-reactive power sensitivity matrix are determined by the ratio of the reactance component between the governance node and the compensation source access point to the voltage amplitude of the governance node.

[0011] Beneficial effects: By explicitly defining the mathematical relationships between the elements of the sensitivity matrix and the reactance components and node voltages, an accurate reactive power-voltage quantification model was established. This sensitivity calculation method based on physical parameters has higher accuracy than empirical estimation or simplified models, ensuring the reliability of the basic data for optimization calculations and improving the accuracy of the model and the effectiveness of the entire control strategy from the source.

[0012] In one optional implementation, the capacity penalty term is defined by a capacity constraint matrix, which is a diagonal matrix, and the values ​​of the diagonal elements of the diagonal matrix are determined by the maximum reactive power capacity of the corresponding inverter.

[0013] Beneficial effects: The diagonal matrix form of the capacity constraint matrix allows the capacity limit of each inverter to be independently and precisely incorporated into the optimization objective. The design that the diagonal elements are related to the maximum capacity of the corresponding inverter ensures the relevance and fairness of the capacity constraints. This avoids the overuse of inverters with smaller capacities while ensuring that inverters with larger capacities can fully play their role, achieving a reasonable allocation of inverter resources and avoiding the problem of coarse capacity constraint processing.

[0014] In one optional implementation, solving the objective function to obtain the optimal reactive power injection amount for each inverter includes: solving the objective function using the least squares method to obtain an analytical solution for the optimal reactive power injection amount.

[0015] Beneficial effects: Using the least squares method to solve the objective function fully leverages the algorithm's computational efficiency advantage in solving linearly constrained optimization problems. Compared to numerical iterative algorithms in related technologies, the least squares method can directly obtain analytical solutions, avoiding the time consumption of iterative calculations, significantly improving computational speed, meeting the stringent requirements of real-time control for computational efficiency, and enhancing the real-time performance of control.

[0016] In one optional implementation, the analytical solution is obtained through the following calculation process: calculating the product of the transpose of the voltage-reactive power sensitivity matrix and the voltage-reactive power sensitivity matrix, adding it to the capacity constraint matrix and then inverting it to obtain a first intermediate matrix; calculating the product of the transpose of the voltage-reactive power sensitivity matrix and a voltage deviation vector to obtain a second intermediate vector, wherein the voltage deviation vector is the difference between the target voltage and the voltage data; and multiplying the first intermediate matrix and the second intermediate vector to obtain the optimal reactive power injection amount.

[0017] Beneficial effects: By decomposing the analytical solution into three explicit matrix operation steps, the controllability and stability of the computation process are achieved. First, intermediate matrices and vectors are obtained through matrix operations, and finally, the optimal solution is obtained through matrix multiplication. This step-by-step computation method not only improves computational efficiency but also enhances the numerical stability of the algorithm, avoids the computational divergence problem common in complex optimization problems, and ensures the reliability of the control system.

[0018] In one optional implementation, controlling the corresponding inverter to perform reactive power compensation based on the optimal reactive power injection amount includes: converting the optimal reactive power injection amount into a corresponding reactive current command; and sending the reactive current command to each inverter to drive the corresponding inverter to perform reactive power compensation.

[0019] Beneficial effects: By converting the optimal reactive power into reactive current commands and sending them to the inverter, the final link from optimization calculation to actual control is completed, ensuring that the optimization results can be accurately and timely converted into equipment control actions.

[0020] In one optional implementation, after controlling the corresponding inverter to perform reactive power compensation, the method further includes: monitoring the voltage status of the plurality of governance nodes; determining whether the parameter update conditions are met based on the monitoring results; when the parameter update conditions are met, updating the optimization parameters, and re-executing the establishment and solution of the objective function based on the updated parameters, and controlling the corresponding inverter to perform reactive power compensation again based on the solution results.

[0021] Beneficial effects: By adding closed-loop control links for monitoring, judgment and parameter updating, the system's adaptive optimization capability enables the system to dynamically adjust and optimize parameters according to the actual operating state, overcoming the problem of decreased control effect when fixed parameters change system operating conditions, achieving continuous optimization of control effect and improving the adaptability of control strategy.

[0022] Secondly, this application provides a multi-inverter collaborative reactive power compensation device, comprising: a data acquisition module for acquiring voltage data of multiple governance nodes and reactive power capacity information of each inverter; a processing module connected to the data acquisition module for establishing an objective function based on the voltage data, the reactive power capacity information, and pre-stored power system network parameters, wherein the objective function is used to make the voltage of the multiple governance nodes approach a target voltage under the condition of satisfying the reactive power capacity constraints of each inverter, and solving the objective function to obtain the optimal reactive power injection amount of each inverter; and a control module connected to the processing module for generating control commands according to the optimal reactive power injection amount to drive the corresponding inverter to perform reactive power compensation.

[0023] Thirdly, this application provides an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the multi-inverter coordinated reactive power compensation method described in the first aspect or any corresponding embodiment.

[0024] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing a computer to execute the multi-inverter coordinated reactive power compensation method described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram illustrating an application scenario according to an embodiment of this application;

[0027] Figure 2 This is a schematic diagram of the first type of multi-inverter collaborative reactive power compensation method according to an embodiment of this application; Figure 3 This is a schematic diagram of the second process of the multi-inverter collaborative reactive power compensation method according to the embodiments of this application; Figure 4 This is a schematic diagram of the third process of the multi-inverter collaborative reactive power compensation method according to the embodiments of this application; Figure 5 This is a schematic diagram of the algorithm flow of the multi-inverter collaborative reactive power compensation method according to an embodiment of this application; Figure 6 This is a structural block diagram of a multi-inverter collaborative reactive power compensation device according to an embodiment of this application; Figure 7 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] It is understood that before using the technical solutions disclosed in the various embodiments of this application, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this application in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0030] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0031] In related technologies, reactive power compensation devices such as Static Var Generators (SVG), Static Var Compensators (SVC), and Static Synchronous Compensators (STATCOM) have high investment costs, low equipment utilization rates, and limited installation numbers in distribution networks, which cannot fully meet the growing reactive power demand.

[0032] Meanwhile, with the large-scale integration of renewable energy sources such as distributed photovoltaics, there are a large number of grid-connected inverters in the system. These inverters have spare capacity when operating at non-full power. However, existing multi-inverter coordinated control methods mostly use numerical iterative algorithms, which have problems such as high computational complexity and poor real-time performance, and cannot fully explore and coordinate the reactive power compensation potential of these dispersed resources.

[0033] This invention provides a multi-inverter collaborative reactive power compensation method. By effectively tapping and coordinating the reactive power compensation potential of distributed inverters in the system, it reduces the dependence on traditional reactive power compensation equipment, thereby achieving an economical, efficient, and rapid voltage and reactive power collaborative control effect.

[0034] As one optional application scenario in the embodiments of this application, such as Figure 1 As shown, the system for implementing this multi-inverter collaborative reactive power compensation method may include a central reactive power compensation control center 101, a communication network 102, and multiple distributed multifunctional grid-connected inverters 103 (MFGCI). Figure 1 The example illustrates that the system connects the central reactive power compensation control center 101 with multiple MFGCIs and power measurement devices via a communication network.

[0035] Specifically, the central reactive power compensation control center 101 can be a cloud server, edge computing server, or power plant monitoring system with optimized control algorithms deployed; MFGCI refers to a grid-connected inverter with active and reactive power four-quadrant operation capabilities, deployed in scenarios such as distributed photovoltaic power generation systems and energy storage systems; the communication network 102 can be a wired network or a wireless network, such as a power fiber optic private network, a wireless private network, or a mobile communication network, used to realize data interaction between the control center and various MFGCIs and measurement devices in the plant.

[0036] Power measurement devices 104 (such as voltage transformers, current transformers, and smart meters) are deployed at key governance nodes in the distribution network or microgrid to collect real-time electrical quantity data such as node voltage and current. The access points of each MFGCI constitute the compensation source access points. The central reactive power compensation control center 101 receives real-time monitoring data from the power measurement devices and reactive power capacity information reported by each MFGCI via a communication network. Based on the method described in this application, it generates optimal reactive power injection commands and distributes them to each MFGCI via the communication network. The MFGCI executes the commands, injecting or absorbing corresponding reactive power into the grid, achieving coordinated, rapid, and accurate compensation of the governance node voltage.

[0037] It should be noted that, Figure 1 This is merely an example of an application scenario, and the scope of protection of this application is not limited to this specific architecture. For example, the functions of the control center can also be performed collaboratively by distributed controllers, or integrated into a main inverter.

[0038] According to an embodiment of this application, a method for multi-inverter coordinated reactive power compensation 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.

[0039] This embodiment provides a multi-inverter collaborative reactive power compensation method, which can be used in the aforementioned central reactive power compensation control center 101, such as a cloud server, edge computing server, or power plant monitoring system. Figure 2 This is a flowchart of a multi-inverter coordinated reactive power compensation method according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps: Step S201: Collect voltage data from multiple governance nodes and reactive power capacity information from each inverter.

[0040] It should be noted that "management nodes" refer to key locations in the distribution network that require focused voltage monitoring and management. These nodes are typically located at voltage-sensitive locations such as feeder ends, important load connection points, or distributed generation common connection points. The voltage data collected in this embodiment refers to the voltage before compensation.

[0041] Reactive power capacity information refers to the maximum reactive power capacity that each inverter can provide under the current operating conditions, which is usually determined by the inverter's rated capacity, current active power output, and environmental conditions.

[0042] This step S201 collects grid state variables and inverter state variables to form the initial conditions for the optimization problem, thereby spatially associating the discretely distributed inverter resources with grid voltage monitoring points, which can establish a data mapping relationship for subsequent collaborative optimization.

[0043] Step S202: Based on the voltage data, the reactive power capacity information, and the pre-stored power system network parameters, establish an objective function. The objective function is used to make the voltage of the multiple governance nodes approach the target voltage while satisfying the reactive power capacity constraints of each inverter. Solve the objective function to obtain the optimal reactive power injection amount of each inverter.

[0044] It should be noted that power system network parameters mainly refer to the reactance parameters in the node admittance matrix, which are calculated based on the power grid topology. The optimal reactive power injection amount refers to the reactive power value that each inverter should output to minimize the objective function.

[0045] In step S202, model initialization is first performed, including reading network parameters and initializing optimization variables. Then, the iterative solution process begins, calculating gradients and updating optimization variables. Finally, the converged optimal solution is output. This method can transform the complex power grid coordination and control problem into a convex optimization problem with clear mathematical meaning, ensuring the reliability and efficiency of the solution.

[0046] Step S203: Control the corresponding inverter to perform reactive power compensation according to the optimal reactive power injection amount.

[0047] It should be noted that the optimal reactive power injection amount represents the optimal reactive power output setting value for each inverter based on the aforementioned calculations. Reactive power compensation refers to the inverter outputting a specific amount of capacitive or inductive reactive power according to instructions, thereby affecting the grid node voltage.

[0048] In step S203, the central reactive power compensation control center acts as the decision-making hub, establishing control loops with each inverter through the communication network to form a complete "sensing-decision-execution" closed-loop system, enabling the distributed inverter resources to participate in grid voltage regulation in a coordinated manner.

[0049] The multi-inverter collaborative reactive power compensation method provided in this embodiment collects voltage data from multiple governance nodes and capacity information of each inverter, establishes and solves an objective function based on power system network parameters, and finally controls the inverters to perform compensation according to the optimal reactive power injection amount. This effectively solves the problem of limited coverage of dedicated compensation equipment in related technologies. By utilizing the remaining capacity of existing distributed inverters, the investment cost of reactive power compensation equipment is significantly reduced. Simultaneously, it overcomes the high computational complexity of related coordination algorithms by establishing an objective function model suitable for rapid solution, achieving real-time optimized control of multi-inverter collaborative compensation. This enables the system to quickly stabilize the voltage of governance nodes near the target value while meeting the capacity constraints of each inverter, significantly improving the voltage stability and reactive power resource utilization efficiency of the distribution network.

[0050] This embodiment provides a multi-inverter collaborative reactive power compensation method, which can be used in the aforementioned central reactive power compensation control center 101, such as a cloud server, edge computing server, or power plant monitoring system. Figure 3 This is a flowchart of a multi-inverter coordinated reactive power compensation method according to an embodiment of this application, such as... Figure 3 As shown, the process includes the following steps: Step S301: Collect voltage data from multiple governance nodes and reactive power capacity information from each inverter. For details, please refer to [link to relevant documentation]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0051] Step S302: Based on the voltage data, the reactive power capacity information, and the pre-stored power system network parameters, establish an objective function. The objective function is used to make the voltage of the multiple governance nodes approach the target voltage while satisfying the reactive power capacity constraints of each inverter. Solve the objective function to obtain the optimal reactive power injection amount of each inverter.

[0052] Specifically, in step S302 above, the step of establishing the objective function includes: Step S3021: Calculate the voltage-reactive power sensitivity matrix based on the power system network parameters. The sensitivity matrix is ​​used to characterize the linear relationship between the reactive power injection change and the node voltage change.

[0053] It should be noted that the values ​​of the elements in the voltage-reactive power sensitivity matrix are determined by the ratio of the reactance component between the governance node and the compensation source access point to the voltage amplitude of the governance node.

[0054] Specifically, the voltage-reactive power sensitivity matrix, i.e., the voltage-reactive power sensitivity model, is based on power system theory. The linearized relationship between node voltage and reactive power injection is as follows: ΔV=S QV ΔQ In the formula, ΔV=[Δ V 1, Δ V 2, ..., Δ V n ] T The voltage change vector for each governance node; ΔQ=[Δ Q 1, Δ Q 2, ..., Δ Q m ] T Injection vector of reactive power for each compensation source; S QV This is the voltage-reactive power sensitivity matrix; n This refers to the number of voltage management nodes; m This represents the number of inverter compensation sources.

[0055] Sensitivity matrix elements S QV，ij Indicates the first j The unit reactive power injected by the compensation source affects the first... i The impact of node voltage:

[0056] In the formula, X ij For nodes i and j The reactance components between; V i For nodes i The voltage amplitude.

[0057] The compensated node voltage is: V=V0+ S QV ΔQ In the formula, V0 is the voltage vector of each governance node before compensation.

[0058] Step S3021 establishes an accurate reactive power-voltage quantification model by explicitly defining the mathematical relationships between the elements of the sensitivity matrix, the reactance components, and the node voltages. This sensitivity calculation method based on physical parameters has higher accuracy than empirical estimation or simplified models, ensuring the reliability of the basic data for optimization calculations and improving the accuracy of the model and the effectiveness of the entire control strategy from the source.

[0059] Step S3022: Based on the voltage-reactive power sensitivity matrix, the target voltage, and the voltage data, construct a voltage deviation term.

[0060] It should be noted that the objective function in this embodiment includes two core components: a voltage deviation term and a capacity penalty term. In other words, an objective function that simultaneously considers voltage stability and capacity constraints needs to be established. J = J 1+ βJ 2 Specifically, voltage stability is used to characterize the degree to which the voltage at each node approaches the target value; that is, the voltage deviation term can be expressed as:

[0061] In the formula, V target The target voltage vector (usually set to the rated voltage). β Here, V is the capacity penalty coefficient, and V0 is the voltage vector before compensation. This term quantifies the deviation between the current voltage and the target voltage by minimizing... J 1. To enable the voltage at the control node to quickly approach the rated value. The design of the voltage deviation term can transform the complex voltage stability problem into an optimizable quadratic objective, avoiding the limitations of traditional methods that rely on trial and error or iterative adjustments, and directly linking the system control objective with the optimization process.

[0062] Step S3023: Based on the optimal reactive power injection amount and the maximum reactive power capacity of each inverter, construct a capacity penalty term.

[0063] It should be noted that the capacity penalty term is defined by a capacity constraint matrix, which is a diagonal matrix. The values ​​of the diagonal elements of the diagonal matrix are determined by the maximum reactive power capacity of the corresponding inverter.

[0064] Specifically, capacity constraints are used to limit the capacity of compensation sources from exceeding limits; that is, the capacity penalty term can be expressed as:

[0065] In the formula, Q max，j For the first j The maximum reactive power capacity of a compensation source; ||·|| denotes the Euclidean norm of a vector.

[0066] Based on this, the capacity constraint matrix is ​​defined as:

[0067] In the formula, R Q It is a capacity-constrained diagonal matrix.

[0068] It should be noted that the capacity penalty term is used to apply a secondary penalty when the inverter's reactive power output exceeds its capacity. βThe penalty coefficient is adjustable. This design transforms discrete capacity constraints into continuously optimizable objectives, preventing inverter overload risks and simplifying calculations through matrix diagonalization. This ensures that the optimization process balances equipment safety and system performance.

[0069] Step S3023 employs a diagonal matrix form for the capacity constraint matrix, ensuring that the capacity limit of each inverter can be independently and precisely incorporated into the optimization objective. The design, where diagonal elements are related to the maximum capacity of the corresponding inverter, guarantees the targeted and fair nature of the capacity constraints. This avoids overuse of smaller capacity inverters while ensuring that larger capacity inverters are fully utilized, achieving a rational allocation of inverter resources and avoiding the problem of coarse capacity constraint processing.

[0070] Step S3024: Define the combination of the voltage deviation term and the capacity penalty term as the objective function.

[0071] Specifically, based on the above formula, the objective function can be written in matrix form:

[0072] In the formula, superscript T This indicates the matrix transpose.

[0073] This objective function achieves multi-objective optimization by weighting and combining voltage deviation and capacity penalty terms. The voltage deviation term governs voltage regulation accuracy, while the capacity penalty term constrains safe equipment operation. This design resolves the contradiction between voltage quality and equipment limitations that traditional single-objective optimization cannot reconcile, providing a mathematical foundation for real-time collaborative control.

[0074] In steps S3021 to S3024 above, by constructing an objective function that includes a voltage deviation term and a capacity penalty term, the optimization process simultaneously considers voltage regulation accuracy and safe equipment operation. The voltage deviation term directly corresponds to the voltage stability target, ensuring that the system voltage quickly approaches the target value; the capacity penalty term, by limiting the inverter's reactive power output to not exceed its maximum capacity, effectively prevents the risk of equipment overload, enabling the optimized solution to achieve the best balance between voltage quality and equipment safety.

[0075] Specifically, in step S302 above, solving the objective function to obtain the optimal reactive power injection amount for each inverter includes: Step S3025: Solve the objective function using the least squares method to obtain the analytical solution for the optimal reactive power injection amount.

[0076] It should be noted that, to solve the objective function using the least squares method, the voltage deviation vector must first be defined:

[0077] This vector is the core input driving the entire optimization process, quantifying the difference between the current system voltage and the target voltage. Therefore, the objective function can be expressed as:

[0078] Further expansion yields:

[0079] This formula clearly shows the objective function. J It is a quadratic function of the optimization variable ΔQ. Based on this, [the following is discussed]... J Find the partial derivative with respect to ΔQ and set it to zero:

[0080] Finally, solving this linear equation yields the analytical solution for the optimal reactive power injection:

[0081] In step S3025, the least squares method is used to solve the objective function, fully leveraging the computational efficiency advantage of this algorithm in solving linear constrained optimization problems. Compared to numerical iterative algorithms in related technologies, the least squares method can directly obtain analytical solutions, avoiding the time consumption of iterative calculations, significantly improving the calculation speed, meeting the stringent requirements of real-time control for computational efficiency, and enhancing the real-time performance of control.

[0082] In some optional implementations, in step S3025 above, the analytical solution is obtained through the following calculation process: Step a1: Calculate the product of the transpose of the voltage-reactive power sensitivity matrix and the voltage-reactive power sensitivity matrix, add it to the capacity constraint matrix and then invert it to obtain the first intermediate matrix.

[0083] It should be noted that the first intermediate matrix can be obtained through the analytical solution formula (S) T QV S QV +R Q ) -1 Partial computational implementation. Because the first intermediate matrix incorporates the grid topology sensitivity (S... QV ) and inverter capacity constraints (R Q The inverse matrix is ​​strictly positive definite, guaranteeing its existence and uniqueness, thus mathematically laying the foundation for the existence and uniqueness of analytical solutions. This step transforms the physical constraints of the system into a stable and invertible mathematical operator.

[0084] Step a2: Calculate the product of the transpose of the voltage-reactive power sensitivity matrix and a voltage deviation vector to obtain a second intermediate vector, where the voltage deviation vector is the difference between the target voltage and the voltage data.

[0085] It should be noted that the second intermediate vector can be obtained from the analytical solution formula S. T QV The calculation of part e is implemented, and the result of this calculation is the voltage deviation e, which is then expressed as the transpose of the sensitivity matrix S. T QV Projecting the vector onto the reactive power space yields a gradient vector representing the direction of reactive power adjustment required to eliminate the current voltage deviation. This vector is the driving force behind the optimization solution.

[0086] Step a3: Multiply the first intermediate matrix by the second intermediate vector to obtain the optimal reactive power injection amount.

[0087] It should be noted that step a3 completes the final calculation of the analytical solution formula: ΔQ =[First intermediate matrix] × [Second intermediate vector]. This matrix, calculated in step a1 and representing the system's inherent "gain," is applied to the vector calculated in step a2, reflecting the system's real-time "demand," directly outputting the unique optimal solution ΔQ that minimizes the objective function J. .

[0088] In steps a1 to a3 above, the controllability and stability of the computation process are achieved by decomposing the analytical solution into three explicit matrix operation steps. First, intermediate matrices and vectors are obtained through matrix operations, and finally, the optimal solution is obtained through matrix multiplication. This step-by-step computation method not only improves computational efficiency but also enhances the numerical stability of the algorithm, avoids the computational divergence problem common in complex optimization problems, and ensures the reliability of the control system.

[0089] Step S303: Control the corresponding inverter to perform reactive power compensation according to the optimal reactive power injection amount. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0090] This embodiment provides a multi-inverter collaborative reactive power compensation method, which can be used in the aforementioned central reactive power compensation control center 101, such as a cloud server, edge computing server, or power plant monitoring system. Figure 4 This is a flowchart of a multi-inverter coordinated reactive power compensation method according to an embodiment of this application, such as... Figure 4 As shown, the process includes the following steps: Step S401: Collect voltage data from multiple governance nodes and reactive power capacity information from each inverter. For details, please refer to [link to relevant documentation]. Figure 2Step S201 of the illustrated embodiment will not be described again here.

[0091] Step S402: Based on the voltage data, the reactive power capacity information, and the pre-stored power system network parameters, an objective function is established. This objective function aims to make the voltage of the multiple governance nodes approach the target voltage while satisfying the reactive power capacity constraints of each inverter. The objective function is then solved to obtain the optimal reactive power injection amount for each inverter. For details, please refer to [link to details]. Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0092] Step S403: Control the corresponding inverter to perform reactive power compensation according to the optimal reactive power injection amount.

[0093] Specifically, step S403 includes: Step S4031: Convert the optimal reactive power injection amount into the corresponding reactive current command.

[0094] Specifically, in the synchronous coordinate system, the relationship between the reactive power and the q-axis current of an inverter (or compensation source) based on active-reactive (PQ) control is as follows: Q ≈- VI q Therefore, the optimal reactive power injection amount ΔQ The reactive current command that can be directly executed by the inverter, i.e., the reactive compensation current, can be expressed as:

[0095] In the formula, V comp This represents the voltage vector at each compensation source connection point. It should be noted that this conversion relationship is based on the power control principle of the inverter in a synchronous rotating coordinate system. The negative sign is due to the convention that injected inductive reactive power (positive Q) corresponds to a negative q-axis current (-Q / Q). I q ).

[0096] Step S4032: The reactive current command is sent to each inverter to drive the corresponding inverter to perform reactive compensation.

[0097] This step S4032 will generate the reactive current command I from step S4031. Q The command is transmitted via the communication network to the corresponding multi-functional grid-connected inverters (MFGCI). Upon receiving the command, the inverter's internal dual-loop controller (typically an outer loop voltage control and an inner loop current control) will adjust the I... QAs a given value for the q-axis current, the switching action of power semiconductor devices (such as IGBTs) is driven by a pulse width modulation (PWM) signal, ultimately outputting the required reactive current on the AC side of the inverter to achieve reactive power compensation to the power grid. This step completes the closed loop from "signal" to "action," enabling the optimization calculation results based on the least squares method to be transformed into reactive power injection that actually affects the grid voltage. It is an indispensable final link in the entire coordinated control chain.

[0098] In steps S4031 to S4032 above, by converting the optimal reactive power into reactive current command and sending it to the inverter, the final link from optimization calculation to actual control is completed, ensuring that the optimization result can be accurately and timely converted into equipment control actions.

[0099] Based on the above embodiments, in some embodiments of this application, after the corresponding inverter performs reactive power compensation, the multi-inverter coordinated reactive power compensation method further includes: Step b1: Monitor the voltage status of the multiple governance nodes; Step b2: Determine whether the parameter update conditions are met based on the monitoring results; Step b3: When the parameter update condition is met, update the optimization parameters, and re-execute the establishment and solution of the objective function based on the updated parameters, and control the corresponding inverter again to perform reactive power compensation based on the solution result.

[0100] In steps b1 to b2, by adding a closed-loop control loop of monitoring, judgment and parameter updating, the system's adaptive optimization capability enables the system to dynamically adjust the optimization parameters according to the actual operating state, overcoming the problem of the control effect of fixed parameters decreasing when the system operating conditions change, realizing the control effect of continuous optimization, and improving the adaptability of the control strategy.

[0101] Reference Figure 5 As shown, in conjunction with the above embodiments, the algorithm flow of the multi-inverter coordinated reactive power compensation method of this application is as follows: (1) Collect voltage data V0 of each governance node and capacity information of each inverter; (2) Calculate the voltage-reactive power sensitivity matrix S based on the system network parameters. QV ; (3) Set the target voltage V target and capacity penalty coefficient β ; (4) Construct the capacity constraint matrix R Q ; (5) Calculate the optimal reactive power injection ΔQ using the analytical solution formula (13). ; (6) Converted into reactive power compensation current I Q And issue control commands; (7) Monitor the system status in real time and dynamically adjust and optimize parameters.

[0102] This embodiment also provides a multi-inverter collaborative reactive power compensation device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0103] This embodiment provides a multi-inverter collaborative reactive power compensation device, such as... Figure 6 As shown, it includes: The data acquisition module 501 is used to collect voltage data from multiple governance nodes and reactive power capacity information from each inverter.

[0104] The processing module 502, connected to the data acquisition module, is used to establish an objective function based on the voltage data, the reactive power capacity information, and the pre-stored power system network parameters. The objective function is used to make the voltage of the multiple governance nodes approach the target voltage while satisfying the reactive power capacity constraints of each inverter, and to solve the objective function to obtain the optimal reactive power injection amount of each inverter.

[0105] The control module 503 is connected to the processing module and is used to generate control commands based on the optimal reactive power injection amount to drive the corresponding inverter to perform reactive power compensation.

[0106] In some alternative implementations, the processing module 502 includes: A sensitivity calculation unit is used to calculate a voltage-reactive power sensitivity matrix based on the power system network parameters, wherein the values ​​of the elements in the sensitivity matrix are determined by the ratio of the reactance component between the control node and the compensation source access point to the voltage amplitude of the control node. The function construction unit is used to construct a voltage deviation term based on the sensitivity matrix, target voltage, and voltage data, and to construct a capacity penalty term based on the optimal reactive power injection and the maximum capacity of the inverter, so as to form the objective function; The analytical solution unit is used to solve the objective function using the least squares method. It calculates the product of the sensitivity matrix transpose and itself, adds the capacity constraint matrix, inverts it, and then multiplies it by the product of the sensitivity matrix transpose and the voltage deviation vector to obtain the analytical solution of the optimal reactive power injection amount.

[0107] In some alternative embodiments, the apparatus further includes: The status monitoring module is used to monitor the voltage status of the governance node after the inverter performs reactive power compensation; The parameter update module is used to determine whether the parameter update conditions are met based on the monitoring results, and update the optimization parameters when the conditions are met, triggering the processing module to recalculate the optimal reactive power injection amount.

[0108] The multi-inverter coordinated reactive power compensation device provided in this application can execute the multi-inverter coordinated reactive power compensation method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0109] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0110] The following is a detailed reference. Figure 7 This diagram illustrates a suitable structural schematic for implementing the electronic device described in the embodiments of this application. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0111] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0112] 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 non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the multi-inverter coordinated reactive power compensation method of this application.

[0113] Figure 7 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0114] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the multi-inverter coordinated reactive power compensation method shown in the above embodiments is implemented.

[0115] A portion of this application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0116] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A multi-inverter coordinated reactive power compensation method, characterized in that, include: Collect voltage data from multiple governance nodes and reactive power capacity information from each inverter; Based on the voltage data, the reactive power capacity information, and the pre-stored power system network parameters, an objective function is established. The objective function is used to make the voltage of the multiple governance nodes approach the target voltage while satisfying the reactive power capacity constraints of each inverter. The objective function is then solved to obtain the optimal reactive power injection amount for each inverter. The inverter is controlled to perform reactive power compensation based on the optimal reactive power injection amount.

2. The multi-inverter coordinated reactive power compensation method according to claim 1, characterized in that, The objective function includes: The voltage-reactive power sensitivity matrix is ​​calculated based on the power system network parameters. The sensitivity matrix is ​​used to characterize the linear relationship between the reactive power injection change and the node voltage change. Based on the voltage-reactive power sensitivity matrix, the target voltage, and the voltage data, a voltage deviation term is constructed; Based on the optimal reactive power injection amount and the maximum reactive power capacity of each inverter, a capacity penalty term is constructed. The combination of the voltage deviation term and the capacity penalty term is defined as the objective function.

3. The multi-inverter coordinated reactive power compensation method according to claim 2, characterized in that, The values ​​of the elements in the voltage-reactive power sensitivity matrix are determined by the ratio of the reactance component between the governance node and the compensation source access point to the voltage amplitude of the governance node.

4. The multi-inverter coordinated reactive power compensation method according to claim 2, characterized in that, The capacity penalty term is defined by a capacity constraint matrix, which is a diagonal matrix. The values ​​of the diagonal elements of the diagonal matrix are determined by the maximum reactive power capacity of the corresponding inverter.

5. The multi-inverter coordinated reactive power compensation method according to claim 1, characterized in that, Solving the objective function to obtain the optimal reactive power injection for each inverter includes: The objective function is solved using the least squares method to obtain the analytical solution for the optimal reactive power injection.

6. The multi-inverter coordinated reactive power compensation method according to claim 5, characterized in that, The analytical solution is obtained through the following calculation process: Calculate the product of the transpose of the voltage-reactive power sensitivity matrix and the voltage-reactive power sensitivity matrix, add it to the capacity constraint matrix and then invert it to obtain the first intermediate matrix; The product of the transpose of the voltage-reactive power sensitivity matrix and a voltage deviation vector is calculated to obtain a second intermediate vector, wherein the voltage deviation vector is the difference between the target voltage and the voltage data. Multiply the first intermediate matrix by the second intermediate vector to obtain the optimal reactive power injection amount.

7. The multi-inverter coordinated reactive power compensation method according to claim 1, characterized in that, The step of controlling the corresponding inverter to perform reactive power compensation based on the optimal reactive power injection amount includes: The optimal reactive power injection amount is converted into a corresponding reactive current command. The reactive current command is sent to each inverter to drive the corresponding inverter to perform reactive power compensation.

8. The multi-inverter coordinated reactive power compensation method according to claim 1, characterized in that, After the inverter corresponding to the control performs reactive power compensation, the method further includes: Monitor the voltage status of the multiple governance nodes; Determine whether the parameter update conditions are met based on the monitoring results; When the parameter update conditions are met, the optimization parameters are updated, and the objective function is re-established and solved based on the updated parameters. The corresponding inverter is then controlled again to perform reactive power compensation based on the solution results.

9. A multi-inverter collaborative reactive power compensation device, characterized in that, include: The data acquisition module is used to collect voltage data from multiple governance nodes and reactive power capacity information from each inverter. The processing module, connected to the data acquisition module, is used to establish an objective function based on the voltage data, the reactive power capacity information, and the pre-stored power system network parameters. The objective function is used to make the voltage of the multiple governance nodes approach the target voltage while satisfying the reactive power capacity constraints of each inverter, and to solve the objective function to obtain the optimal reactive power injection amount of each inverter. A control module, connected to the processing module, is used to generate control commands based on the optimal reactive power injection amount to drive the corresponding inverter to perform reactive power compensation.

10. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the multi-inverter coordinated reactive power compensation method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the multi-inverter coordinated reactive power compensation method according to any one of claims 1 to 8.

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