Flexible power distribution system fast voltage recovery method based on on-line feedback of measurements and related apparatus

Abstract

The application provides a flexible power distribution system fast voltage recovery method based on measurement online feedback and related devices, the method obtains the basic parameters of the selected power distribution network and the measurement data of the voltage and current of the fault area in the power distribution network, and calculates the voltage and current pseudo-Jacobian matrix of the fault area; determines the power distribution network fast voltage recovery model of the initial optimization time according to the basic parameters; solves the power distribution network fast voltage recovery model of the initial optimization time based on the initial value of the voltage and current pseudo-Jacobian matrix and issues the voltage recovery strategy; within the fault duration of the fault area, the optimization time and the corresponding power distribution network fast voltage recovery model are updated constantly, and the voltage recovery is carried out based on the updated model. The application comprehensively considers that the accurate line parameters are difficult to obtain and the output of the distributed power supply is strong volatility, establishes the voltage recovery model based on measurement online feedback, and realizes the flexible power distribution system fast voltage recovery.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of voltage recovery of power distribution system, and particularly relates to a flexible power distribution system fast voltage recovery method based on measurement online feedback and related devices. BACKGROUND

[0002] In recent years, the access of large-scale distributed power sources aggravates the operation volatility of distribution networks, and brings a series of problems such as power reverse sending and voltage out-of-limit, which seriously impacts the safe operation of distribution networks. Especially under fault conditions, the operation characteristics of distribution networks are further complicated. Fast voltage recovery after power sudden failure is an important development goal of distribution networks. Based on the rich controllable resources of distribution networks, such as intelligent soft open points (SOP), how to quickly develop a voltage recovery strategy is an important problem to improve the fault self-healing ability of the system.

[0003] The traditional voltage recovery method is mainly based on accurate line parameters and relies on detailed or approximate physical models to solve the voltage recovery strategy. However, the model-based voltage recovery method has certain limitations. When the line parameters of the distribution network are incomplete or inaccurate, especially when the parameters need to be maintained during the fault process, the voltage recovery method based on accurate physical parameters cannot guarantee the effectiveness of the real-time voltage recovery strategy. And due to the access of a large number of controllable devices to the distribution network, the calculation time of the voltage recovery optimization method based on accurate physical models increases rapidly, and the online calculation capacity is usually limited. SUMMARY

[0004] Therefore, the application aims to provide a flexible power distribution system voltage recovery method based on measurement online feedback, which can quickly obtain a voltage recovery strategy in the absence of accurate line parameters and related devices

[0005] In order to achieve the above-mentioned purpose, the technical scheme provided by the application is as follows:

[0006] In the first aspect, the application provides a flexible power distribution system fast voltage recovery method based on measurement online feedback, comprising the following steps:

[0007] Obtaining the basic parameters of the selected distribution network and the measurement data of the voltage and current of the fault area in the distribution network;

[0008] Calculating the initial value of the pseudo-Jacobian matrix of the voltage and current of the fault area according to the measurement data;

[0009] The power distribution network fast voltage recovery model for determining the initial optimization time according to the basic parameters is based on measurement data, and at least includes a model with the minimum voltage deviation and the minimum network loss as optimization objectives, wherein a voltage and current pseudo-Jacobian matrix calculated from the measurement data is used for participating in voltage deviation and network loss calculation respectively;

[0010] Based on the initial value of the voltage and current pseudo-Jacobian matrix, the power distribution network fast voltage recovery model for the initial optimization time is solved and the voltage recovery strategy is issued, and the voltage and current pseudo-Jacobian matrix is updated based on the optimized voltage and current measurement data.

[0011] In the fault duration of the fault area, the optimization time and the corresponding power distribution network fast voltage recovery model are updated constantly, and the voltage recovery is carried out based on the updated model.

[0012] Further, the objective function of the power distribution network fast voltage recovery model is as follows:

[0013] f = min (C1f1+C2f2+C3f3+C4f4)

[0014] f1 = ∑ i∈Ω α i (1-λ i [t])P i [t]

[0015]

[0016] In the formula, C1 represents the outage cost of the fault area, C2 represents the fluctuation cost of the load recovery rate of the outage node, C3 represents the voltage deviation cost, C4 represents the network loss cost, f1 represents the active power of the load outage in the fault area, f2 represents the load recovery rate fluctuation, f3 represents the voltage deviation of the node in the fault area, and f4 represents the estimated network loss of the fault area. α i represents the i-node load importance coefficient, λ i [t] represents the i-node load recovery rate at t time, P i [t] represents the i-node load active power at t time, Ω represents the set of nodes to be recovered, X λ [t] represents the load recovery rate vector, U ref represents the voltage reference value, represents the voltage measurement of the node in the fault area at t time, represents the voltage pseudo-Jacobian matrix, ΔX λ [t] represents the i-node load recovery rate change at t time, represents the line resistance weight vector, represents the line current measurement horizontal direction of the fault area, represents the current pseudo-Jacobian matrix.

[0017] Further, the constraints of the distribution network fast voltage recovery model include distribution system voltage recovery constraints, as follows:

[0018] 0≤λ i [t]≤1,i∈Ω

[0019]

[0020] where λ i [t-Δt] represents the i-node load recovery rate at t-Δt, Ω * represents the set of important load nodes, Ω PV represents the set of photovoltaic nodes in the fault area, P α [t] represents the active power output of the α-node photovoltaic at t, P α [t-Δt] represents the active power output of the α-node photovoltaic at t-Δt, P i [t] represents the i-node active load at t, P α [t-Δt] represents the i-node active load at t-Δt, P Δ1 represents the net growth of active power of the photovoltaic in the fault area, P Δ2 represents the available active power growth margin, U represents the lower limit of the safe voltage, represents the upper limit of the safe voltage, represents the upper limit of the safe current square value.

[0021] Further, the constraints of the distribution network fast voltage recovery model also include SOP operation constraints, as follows:

[0022]

[0023] where, and represent the active power and reactive power output of the SOP at t, Q i [t] represents the i-node reactive load, S SOP represents the SOP capacity, and P SOP represent the upper and lower limits of the active power output of the SOP port, and Q SOP represent the upper and lower limits of the reactive power output of the SOP port.

[0024] Further, the SOP operation constraints are linearized, as follows:

[0025]

[0026] wherein k represents a linearization constraint index, a k , β k and γ k represent linearization constraint coefficients.

[0027] Further, the voltage and current pseudo-Jacobian matrix initial values are as follows:

[0028]

[0029] wherein X[t0] represents a load recovery rate vector of the faulted node at t0; represents a faulted area node voltage measurement vector at t0, represents a faulted area line current measurement vector at t0.

[0030] Further, the updated voltage and current pseudo-Jacobian matrix are as follows:

[0031]

[0032] wherein, represents a voltage pseudo-Jacobian matrix at t-Δt, ρ1 and μ1 represent weight coefficients, represents a faulted area node voltage measurement change vector at t, represents a current pseudo-Jacobian matrix at t-Δt, represents a faulted area line current measurement change vector at t, ρ2 and μ2 represent weight coefficients.

[0033] In a second aspect, the present application provides a flexible power distribution system fast voltage recovery device based on measurement online feedback, comprising:

[0034] a data acquisition module, configured to acquire basic parameters of a selected power distribution network and measurement data of voltage and current of a faulted area in the power distribution network;

[0035] a first calculation module, configured to calculate voltage and current pseudo-Jacobian matrix initial values of the faulted area according to the measurement data;

[0036] a model determination module, configured to determine a power distribution network fast voltage recovery model at an initial optimization time according to the basic parameters, wherein the power distribution network fast voltage recovery model is a model established based on the measurement data and at least includes an optimization objective of minimizing voltage deviation and network loss, and wherein the voltage and current pseudo-Jacobian matrix calculated from the measurement data are respectively used to participate in voltage deviation and network loss calculation;

[0037] The model solving module is configured to solve the power distribution network fast voltage recovery model at the initial optimization time based on the voltage and current pseudo-Jacobian matrix initial value and issue a voltage recovery strategy, and update the voltage and current pseudo-Jacobian matrix based on the optimized voltage and current measurement data.

[0038] The voltage recovery module is configured to update the optimization time and the corresponding power distribution network fast voltage recovery model constantly within the fault duration of the fault area, and perform voltage recovery based on the updated model.

[0039] Correspondingly, the present application provides a computer device, which comprises a processor and a memory:

[0040] The memory is configured to store a computer program and send instructions of the computer program to the processor.

[0041] The processor is configured to execute the instructions of the computer program to perform the method for fast voltage recovery of a flexible power distribution system based on measurement online feedback according to the first aspect.

[0042] Correspondingly, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for fast voltage recovery of a flexible power distribution system based on measurement online feedback according to the first aspect.

[0043] In summary, the present application provides a method for fast voltage recovery of a flexible power distribution system based on measurement online feedback and related devices, which comprises the following steps: obtaining basic parameters of a selected power distribution network and measurement data of voltage and current of a fault area in the power distribution network; calculating voltage and current pseudo-Jacobian matrix initial value of the fault area according to the measurement data; determining a power distribution network fast voltage recovery model at an initial optimization time according to the basic parameters; solving the power distribution network fast voltage recovery model at the initial optimization time based on the voltage and current pseudo-Jacobian matrix initial value and issuing a voltage recovery strategy, and updating the voltage and current pseudo-Jacobian matrix based on the optimized voltage and current measurement data; constantly updating the optimization time and the corresponding power distribution network fast voltage recovery model within the fault duration of the fault area, and performing voltage recovery based on the updated model. The present application comprehensively considers that accurate line parameters are difficult to obtain and distributed power output is strongly fluctuant, and realizes fast voltage recovery of a flexible power distribution system by establishing a voltage recovery model based on measurement online feedback. The present application provides a new idea for voltage recovery of a power distribution system, and is helpful to improve the self-healing level of a power distribution system. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0045] Figure 1 The flow chart of the flexible power distribution system fast voltage recovery method based on measurement online feedback provided by the embodiments of the present application;

[0046] Figure 2 The power distribution system topology structure adopted by the embodiments of the present application;

[0047] Figure 3 The fluctuation curve of photovoltaic output and load change provided by the embodiments of the present application;

[0048] Figure 4 The active power output curve of the fault period SOP provided by the embodiments of the present application;

[0049] Figure 5 The reactive power output curve of the fault period SOP provided by the embodiments of the present application;

[0050] Figure 6 The capacity utilization rate of the fault period SOP provided by the embodiments of the present application;

[0051] Figure 7 The comparison of the fault line load recovery ratio of scenario two and scenario three provided by the embodiments of the present application;

[0052] Figure 8 The comparison of the terminal 18 node voltage of the fault line of scenario two and scenario three provided by the embodiments of the present application;

[0053] Figure 9 The composition block diagram of the flexible power distribution system fast voltage recovery device based on measurement online feedback provided by the embodiments of the present application;

[0054] Figure 10 The composition block diagram of a computer device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0055] In order to make the purposes, characteristics and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings of the embodiments of the present application. Obviously, the following described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0056] The embodiment provides a flexible power distribution system fast voltage recovery method based on measurement online feedback, and comprises the following steps:

[0057] Step 1: Obtain the basic parameters of the selected power distribution network and the voltage and current measurement data of the fault area in the power distribution network.

[0058] It should be noted that the basic information of the selected power distribution network is collected in this step, such as system topological connection relationship, fault position, type, access position, capacity and parameters of load and distributed power, SOP capacity and access position, power distribution network operation voltage constraint and branch current limit, etc. These are the basis for building the recovery model. At the same time, the voltage and current measurement data of the fault area are collected in real time, which is the direct basis for subsequent analysis and adjustment. At the same time, the starting time of executing the voltage recovery method is set as t0, the total fault time is T, and the optimization step is Δt.

[0059] Step 2: Calculate the initial value of the voltage and current pseudo-Jacobian matrix of the fault area according to the measurement data.

[0060] It should be noted that the initial value of the voltage and current pseudo-Jacobian matrix is calculated by using the voltage and current measurement data collected from the fault area. The pseudo-Jacobian matrix plays a role of sensitivity analysis in this context, helping to understand the reaction of system state (such as voltage and current) to input changes (such as control action).

[0061] Step 3: Determine the power distribution network fast voltage recovery model at the initial optimization time according to the basic parameters. The power distribution network fast voltage recovery model is established based on the measurement data, and at least includes a model with the optimization objectives of minimizing voltage deviation and network loss, wherein the voltage and current pseudo-Jacobian matrices calculated from the measurement data are used to participate in the calculation of voltage deviation and network loss respectively.

[0062] It should be noted that a fast voltage recovery optimization model with the objectives of minimizing voltage deviation and network loss is constructed based on the basic parameters and the measurement data. The model uses the previously calculated pseudo-Jacobian matrix to refine the calculation process, ensuring that the realization of the optimization objectives is more efficient and accurate.

[0063] Step four: based on the initial value of the voltage and current pseudo-Jacobian matrix, the initial optimization time point of the distribution network fast voltage recovery model is solved and the voltage recovery strategy is issued, and the voltage and current pseudo-Jacobian matrix is updated based on the optimized voltage and current measurement data.

[0064] It should be noted that this step uses the initial pseudo-Jacobian matrix to solve the model to obtain the voltage recovery strategy, and the strategies are issued to the corresponding control equipment for execution. At the same time, according to the new measurement data after execution, the pseudo-Jacobian matrix is dynamically updated to maintain the timeliness and accuracy of the model.

[0065] Step five: within the fault duration of the fault area, the optimization time point and the corresponding distribution network fast voltage recovery model are constantly updated, and the voltage recovery is carried out based on the updated model.

[0066] It should be noted that during the fault duration, the optimization time point and the corresponding recovery model are constantly updated to ensure that the model always reflects the current system condition. Based on the latest model, the voltage recovery operation is continuously carried out until the system returns to normal operation state.

[0067] The embodiment provides a flexible distribution system fast voltage recovery method based on measurement online feedback. The method establishes a data model based on system measurement data, constructs the correlation between system input and output variables, and does not depend on accurate line parameters. The method has the advantages of fast solving speed and strong adaptability in complex scenes. With the improvement of the informatization and digitization level of the distribution network, the system accumulates a large amount of multi-source heterogeneous operation data and historical information. In the case of lack of accurate line parameters, the measurement online feedback method is used to solve the problem of fast construction of the distribution network fault operation model, to support the system resilience operation, to support the fast and reliable decision of the load transfer scheme, to ensure the uninterrupted and safe operation of important loads under extreme faults, and to improve the fault self-healing level of the distribution network.

[0068] In a preferred embodiment of the present application, a method for calculating the initial value of the voltage and current pseudo-Jacobian matrix is provided. First, the load recovery rate vector X λ [t0] of the fault area is initialized SOP [t0] and the initial active and reactive power output P SOP [t0] of the SOP are initialized, and the initial value of the voltage pseudo-Jacobian matrix of the fault area is calculated based on the inaccurate physical model according to the basic parameter information of step one The initial value of the current pseudo-Jacobian matrix is calculated as follows:

[0069]

[0070] In the formula, X[t0] represents the load recovery rate vector of the power failure node at t0.​ represents the fault area node voltage measurement vector at t0, represents the fault area line current measurement vector at t0.

[0071] In a preferred embodiment of the present application, a flexible power distribution system fast voltage recovery model is provided, which takes the minimum loss of fault area load, the minimum fluctuation of load recovery rate, the minimum voltage deviation and the minimum network loss as the objective function. The flexible power distribution system fast voltage recovery objective function f based on measurement online feedback is represented as:

[0072] f = min (C1f1 + C2f2 + C3f3 + C4f4) (3)

[0073] f1 = ∑ i∈Ω α i (1 - λ i [t])P i [t] (4)

[0074]

[0075] In the formula, C1 represents the fault area loss cost, C2 represents the loss of node load recovery rate fluctuation cost, C3 represents the voltage deviation cost, C4 represents the network loss cost, f1 represents the fault area loss of active power, f2 represents the load recovery rate fluctuation, f3 represents the fault area node voltage deviation, f4 represents the estimated fault area network loss, α i represents the i node load importance coefficient, λ i [t] represents the i node load recovery rate at t, P i [t] represents the i node load active power at t, Ω represents the set of nodes to be recovered, X λ [t] represents the load recovery rate vector, U ref represents the voltage reference value, represents the fault area node voltage measurement at t, represents the voltage pseudo-Jacobian matrix, ΔX λ [t] represents the change of i node load recovery rate at t, represents the line resistance weight vector, represents the fault area line current measurement vector, represents the current pseudo-Jacobian matrix.

[0076] In a preferred embodiment of the present application, the flexible power distribution system fast voltage recovery model considers the power distribution system operation constraints, as follows:

[0077] 0 ≤ λ i [t] ≤ 1, i ∈ Ω (8)

[0078]

[0079] where λ i [t-Δt] represents the i-node load restoration rate at t-Δt, Ω * represents the set of important load nodes, Ω PV represents the set of fault area photovoltaic nodes, P α [t] represents the active power output of the α-node photovoltaic at t, P α [t-Δt] represents the active power output of the α-node photovoltaic at t-Δt, P i [t] represents the active load of the i-node at t, P α [t-Δt] represents the active load of the i-node at t-Δt, P Δ1 represents the net active power growth of the fault area photovoltaic, P Δ2 represents the available active power growth margin, U represents the lower limit of the safety voltage, represents the upper limit of the safety voltage, represents the upper limit of the safety current square value.

[0080] In a preferred embodiment of the present application, the flexible power distribution system rapid voltage recovery model considers the SOP operation constraints as follows:

[0081]

[0082] wherein, and represent the active power and reactive power output of the SOP connected to the fault line port at t, Q i [t] represents the reactive load of the i-node, S SOP represents the SOP capacity, and P SOP represent the upper and lower limits of the active power output of the SOP port, and Q SOP represent the upper and lower limits of the reactive power output of the SOP port.

[0083] In a preferred embodiment of the present application, the SOP operation constraints of the foregoing embodiment are linearized as follows:

[0084]

[0085] wherein k represents the linearization constraint index, α k , β k , and γ k represent the linearization constraint coefficients.

[0086] In a preferred embodiment of the present application, the voltage pseudo-Jacobian matrix of the fault area at t and the current pseudo-Jacobian matrix [t] as follows:

[0087]

[0088] wherein, denotes the voltage pseudo-Jacobian matrix at t-Δt, and ρ1 and μ1 denote weight coefficients, denotes the fault region node voltage measurement change vector at t, denotes the current pseudo-Jacobian matrix at t-Δt, denotes the fault region line current measurement change vector at t, and ρ2 and μ2 denote weight coefficients.

[0089] Referring to Figure 1 , Figure 1 is a flow chart of the flexible power distribution system fast voltage recovery method based on measurement online feedback proposed in one specific embodiment in combination with the above-mentioned embodiments.

[0090] The flexible power distribution system fast voltage recovery method based on measurement online feedback of the present application realizes fast solution of the voltage recovery strategy without relying on accurate line parameters.

[0091] For the example of the present application, the power distribution network includes 44 nodes, and the topology connection condition is as shown in Figure 2 The SOP four terminals are connected to nodes 5, 14, 38 and 43, and the port capacity is 2000 kVA. The photovoltaic system with a capacity of 500 kWp is connected at nodes 9, 13, 16, 18, 19, 24, 30, 38 and 42. The line between node 10 and node 11 is set to be faulty at 8:00. Nodes 11, 12 and 13 are set to be important load nodes, and the important coefficient of the important load nodes is 5 times that of the ordinary load nodes. The distributed power output and load fluctuation curve are as shown in Figure 3 The system voltage is 12.66 kV, the reference power is 1 MVA, the active power load and the reactive power load of the faulty line are 3700 kW and 2000 kVar respectively. The optimization step Δt is 1 s, the fault duration T is 3 h, and the voltage reference value of the power distribution network is set to be 1.0 p.u. The linearization constraint coefficient values are as shown in Table 1.

[0092] Table 1 Linearization constraint coefficient values

[0093]

[0094] The weight coefficients ρ1, μ1, ρ2, μ2 all take 1.0, and the voltage safety range is set as [0.95 p.u., 1.05 p.u.]. The flexible power distribution system fast voltage recovery method based on measurement online feedback is used for optimization, and the voltage recovery strategy can be obtained through the above steps. In order to verify the effectiveness of the method, the following three voltage recovery scenarios are used for comparison in the power distribution system:

[0095] Scenario one: without SOP control, the initial state of the fault area is obtained;

[0096] Scenario two: using the flexible power distribution system fast voltage recovery method based on measurement online feedback;

[0097] Scenario three: the theoretical optimal flexible power distribution system voltage recovery method based on accurate line parameters.

[0098] The computer hardware environment for performing optimization calculation is Intel(R) Core(TM) CPU i5-10210U, the main frequency is 1.6 GHz, and the memory is 16 GB; the software environment is Windows 11 operating system.

[0099] The example topology adopted by the embodiment of the application is shown in Figure 2 The load recovery effect comparison under the three scenarios is shown in Table 2.

[0100] Table 2 Load recovery effect comparison

[0101]

[0102] The prediction curve changes of distributed power output and load information are shown in Figure 3 The active power output strategy of the SOP fault area port is shown in Figure 4 The reactive power output strategy of the SOP fault area port is shown in Figure 5 The SOP capacity utilization rate is shown in Figure 6 The load recovery effect comparison of scenario two and scenario three is shown in Figure 7 The voltage comparison of scenario two and scenario three at the end node 18 of the fault area is shown in Figure 8

[0103] Scenario one cannot perform load recovery because there is no source node in the fault area without SOP control, and the total amount of lost load during the fault period is 6704 kWh. Combined with Table 2 and Figures 3 to 10 ​It can be seen that the flexible power distribution system fast voltage recovery method based on measurement online feedback in scenario two effectively realizes the voltage recovery of the power distribution system in the embodiment without relying on accurate line parameters, ensures zero power outage of important loads, and the load recovery effect is close to the theoretical optimal voltage recovery method based on accurate parameters in scenario three. Due to the fluctuation of photovoltaic output and the capacity limitation of SOP, the load recovery ratio decreases in some moments. For example, near 10:35, photovoltaic power appears a sharp fluctuation, and the active power output decreases, Figure 6 It can be seen that the flexible power distribution system fast voltage recovery method based on measurement online feedback in scenario two effectively realizes the voltage recovery of the power distribution system in the embodiment without relying on accurate line parameters, ensures zero power outage of important loads, and the load recovery effect is close to the theoretical optimal voltage recovery method based on accurate parameters in scenario three. Due to the fluctuation of photovoltaic output and the capacity limitation of SOP, the load recovery ratio decreases in some moments. For example, near 10:35, photovoltaic power appears a sharp fluctuation, and the active power output decreases, Figure 3 It can be seen that the flexible power distribution system fast voltage recovery method based on measurement online feedback in scenario two effectively realizes the voltage recovery of the power distribution system in the embodiment without relying on accurate line parameters, ensures zero power outage of important loads, and the load recovery effect is close to the theoretical optimal voltage recovery method based on accurate parameters in scenario three. Due to the fluctuation of photovoltaic output and the capacity limitation of SOP, the load recovery ratio decreases in some moments. For example, near 10:35, photovoltaic power appears a sharp fluctuation, and the active power output decreases,

[0104] Based on the same inventive concept, the embodiment of the present application also provides a flexible power distribution system fast voltage recovery device based on measurement online feedback for implementing the above-mentioned flexible power distribution system fast voltage recovery method based on measurement online feedback. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme described in the above method, so the specific limitations in the following embodiment of the flexible power distribution system fast voltage recovery device based on measurement online feedback can be referred to the limitations of the flexible power distribution system fast voltage recovery method based on measurement online feedback described above, which will not be repeated here.

[0105] Please refer to Figure 9 The embodiment provides a flexible power distribution system fast voltage recovery device based on measurement online feedback, which comprises:

[0106] A data acquisition module is configured to acquire basic parameters of a selected power distribution network and measurement data of voltage and current in a fault area of the power distribution network.

[0107] A first calculation module is configured to calculate voltage and current pseudo-Jacobian matrix initial values of the fault area according to the measurement data.

[0108] A model determination module is configured to determine a power distribution network fast voltage recovery model at an initial optimization moment according to the basic parameters, wherein the power distribution network fast voltage recovery model is a model established based on the measurement data and at least includes optimization objectives of minimizing voltage deviation and minimizing network loss, and wherein the voltage and current pseudo-Jacobian matrices calculated from the measurement data are respectively used to participate in voltage deviation and network loss calculation.

[0109] The model solving module is configured to solve the power distribution network fast voltage recovery model at the initial optimization time based on the initial value of the voltage and current pseudo-Jacobian matrix, and to issue a voltage recovery strategy, and to update the voltage and current pseudo-Jacobian matrix based on the optimized voltage and current measurement data.

[0110] The voltage recovery module is configured to update the optimization time and the corresponding power distribution network fast voltage recovery model within the fault duration of the fault area, and to perform voltage recovery based on the updated model.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the system is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of the functional units and modules are only for easy distinction, and do not limit the protection scope of the application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0112] Reference Figure 10 The embodiment of the application further provides a computer device 1, which comprises a memory 12, a processor 11 and a computer program 13 stored in the memory 12, and when the computer program 13 is executed on the processor 11, the online feedback-based flexible power distribution system fast voltage recovery method is realized.

[0113] The computer device 1 can be a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The computer device 1 can include, but is not limited to, a processor 11 and a memory 12. Those skilled in the art can understand that, Figure 10 The computer device 1 is only an example and does not limit the computer device 1, which can include more or fewer components than shown, or combine certain components, or different components, for example, can also include input and output devices, network access devices and the like.

[0114] The processor 11 can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0115] The memory 12 can be an internal storage unit of the computer device 1 in some embodiments, for example, a hard disk or a memory of the computer device 1. The memory 12 can also be an external storage device of the computer device 1 in other embodiments, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 12 can include both the internal storage unit and the external storage device of the computer device 1. The memory 12 is used to store an operating system, an application program, a boot loader, data, and other programs, for example, program codes of the computer program, etc. The memory 12 can also be used to temporarily store data that has been output or is to be output.

[0116] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is run by a processor to implement the method for fast voltage recovery of a flexible power distribution system based on online feedback of measurement.

[0117] In this embodiment, the integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the computer program for instructing the relevant hardware to complete all or part of the processes in the above-described embodiment methods can be stored in a computer readable storage medium. The computer program can be executed by a processor to implement the steps of the above-mentioned various method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer readable medium at least includes any entity or device capable of carrying the computer program code to the photographing device / terminal equipment, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. For example, U disk, mobile hard disk, magnetic disk or optical disk, etc. In some jurisdictions, according to legislation and patent practice, the computer readable medium can not be an electrical carrier signal and a telecommunication signal.

[0118] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0119] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solutions. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0120] In the embodiments disclosed in the present application, it should be understood that the disclosed apparatus / terminal equipment and methods can be implemented in other ways. For example, the apparatus / terminal equipment embodiments described above are only schematic, for example, the division of the modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual units can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0121] The above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can be modified, or some technical features can be replaced by equivalent features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for fast voltage recovery of a flexible power distribution system based on metrology online feedback, characterized in that, The method comprises the following steps: obtaining the basic parameters of the selected power distribution network and the measured data of the voltage and current of the fault area in the power distribution network; calculating the initial value of the voltage pseudo-Jacobian matrix and the initial value of the current pseudo-Jacobian matrix of the fault area according to the measured data; determining the power distribution network fast voltage recovery model at the initial optimization time according to the basic parameters, wherein the power distribution network fast voltage recovery model is a model established based on the measured data and at least including the optimization objectives of minimizing the voltage deviation and minimizing the network loss, wherein the voltage pseudo-Jacobian matrix and the current pseudo-Jacobian matrix calculated from the measured data are respectively applied to participate in the calculation of the voltage deviation and the network loss; solving the power distribution network fast voltage recovery model at the initial optimization time based on the initial value of the voltage pseudo-Jacobian matrix and the initial value of the current pseudo-Jacobian matrix, and issuing the voltage recovery strategy, and updating the voltage pseudo-Jacobian matrix and the current pseudo-Jacobian matrix based on the optimized voltage and current measured data; updating the optimization time and the corresponding power distribution network fast voltage recovery model within the fault duration of the fault area, and performing voltage recovery based on the updated model; the objective function of the power distribution network fast voltage recovery model is as follows: ； ； ； ； ； wherein, represents the outage cost of the fault area, represents the load restoration rate fluctuation cost of the outage node, represents the voltage deviation cost, represents the network loss cost, represents the active power of the fault area, represents the load restoration rate fluctuation, represents the voltage deviation of the fault area node, represents the estimated network loss of the fault area, represents the node load importance coefficient, represents the time the node load restoration rate, represents the time the node load active power, represents the set of nodes to be restored, represents the load restoration rate vector, represents the voltage reference value, represents the time the fault area node voltage measurement, represents the voltage pseudo-Jacobian matrix, represents the time the node load restoration rate change, represents the line resistance weight vector, represents the fault area line current measurement horizontal direction vector, represents the current pseudo-Jacobian matrix.

2. The method of claim 1, wherein, the constraints of the power distribution network fast voltage recovery model include power distribution system voltage recovery constraints, as follows: ； ； ； ； ； ； In the formula, represents the node load recovery rate at time i, represents the important load node set, represents the fault area photovoltaic node set, represents the node photovoltaic at the active power at time i, represents the node photovoltaic at the active power at time i, represents the node active load at time i, represents the active load at time i, represents the node active load at time i, represents the active load at time i, represents the fault area photovoltaic net growth active power, represents the available growth active power margin, represents the lower limit of the safety voltage, represents the upper limit of the safety voltage, represents the upper limit of the safety current square value; represents the upper limit of the SOP port active power output.

3. The method of claim 2, wherein the method further comprises: the constraints of the power distribution network fast voltage recovery model also include SOP operation constraints, as follows: ； ； ； ； ； wherein and represent the active power and the reactive power output of the SOP at the time instant when the faulty line port is connected, represent the reactive load at the node, represent the SOP capacity, and represent the upper and lower limits of the active power output of the SOP port, and represent the upper and lower limits of the reactive power output of the SOP port.​​ 4. The method of claim 3, wherein, further comprising: linearizing the SOP operation constraints, as follows: ； wherein denotes the linearized constraint index, , and denotes the linearized constraint coefficient.

5. The method of claim 1, wherein, the initial value of the voltage pseudo-Jacobian matrix and the initial value of the current pseudo-Jacobian matrix are as follows: ； ； wherein represents the initial value of the voltage pseudo-Jacobian matrix, represents the initial value of the current pseudo-Jacobian matrix, represents the load restoration rate vector of the de-energized nodes at the time instant; represents the measured voltage vector of the faulted area nodes at the time instant, represents the measured current vector of the faulted area lines at the time instant.

6. The method of claim 5, wherein the method further comprises: the updated voltage and current pseudo-Jacobian matrices are as follows: ； ； wherein and respectively represent a voltage pseudo-Jacobian matrix and a current pseudo-Jacobian matrix of the fault area at the time point, represent a voltage pseudo-Jacobian matrix at the time point, and represent a weight coefficient, represent a node voltage measurement change vector of the fault area at the time point, represent a current pseudo-Jacobian matrix at the time point, represent a line current measurement change vector of the fault area at the time point, and represent a weight coefficient, represent a load recovery rate change at the time point.

7. A flexible power distribution system fast voltage recovery device based on metrology online feedback, characterized in that, comprising: a data acquisition module for obtaining the basic parameters of the selected power distribution network and the measured data of the voltage and current of the fault area in the power distribution network; a first calculation module for calculating the initial value of the voltage pseudo-Jacobian matrix and the initial value of the current pseudo-Jacobian matrix of the fault area according to the measured data; a model determination module for determining the power distribution network fast voltage recovery model at the initial optimization time according to the basic parameters, wherein the power distribution network fast voltage recovery model is a model established based on the measured data and at least including the optimization objectives of minimizing the voltage deviation and minimizing the network loss, wherein the voltage pseudo-Jacobian matrix and the current pseudo-Jacobian matrix calculated from the measured data are respectively applied to participate in the calculation of the voltage deviation and the network loss; a model solving module for solving the power distribution network fast voltage recovery model at the initial optimization time based on the initial value of the voltage pseudo-Jacobian matrix and the initial value of the current pseudo-Jacobian matrix, and issuing the voltage recovery strategy, and updating the voltage pseudo-Jacobian matrix and the current pseudo-Jacobian matrix based on the optimized voltage and current measured data; a voltage recovery module for updating the optimization time and the corresponding power distribution network fast voltage recovery model within the fault duration of the fault area, and performing voltage recovery based on the updated model; the objective function of the power distribution network fast voltage recovery model is as follows: ； ； ； ； ； In the formula, represents the power loss cost of the fault area, represents the load recovery rate fluctuation cost of the outage node, represents the voltage deviation cost, represents the network loss cost, represents the active power of the load loss in the fault area, represents the load recovery rate fluctuation, represents the node voltage deviation in the fault area, represents the estimated network loss in the fault area, represents the node load importance coefficient, represents the time the node load recovery rate, represents the time the active power of the node load, represents the set of nodes to be recovered, represents the load recovery rate vector, represents the voltage reference value, represents the node voltage measurement in the fault area at the time, represents the voltage pseudo-Jacobian matrix, represents the time the load recovery rate change of the node, represents the line resistance weight vector, represents the line current measurement flat direction vector in the fault area, represents the current pseudo-Jacobian matrix.

8. A computer device, comprising: the device comprises a processor and a memory: the memory is used to store computer programs and send instructions of the computer programs to the processor; The processor executes the instructions of the computer program to perform the method of claim 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to perform the method of claim 1-6.

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