Distribution network voltage cooperative control method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of distributed power distribution network voltage control, in particular to a power distribution network voltage cooperative control method and device, electronic equipment and a storage medium. Then, if the current moment meets the condition of first-layer control of the time scale, taking a control model of the traditional voltage regulation equipment as a target control model; if the current moment does not meet the condition of the first-layer control of the time scale, taking the control model of the photovoltaic inverter as a target control model; and finally, according to the optimization constraint condition, solving the target control model by adopting a particle swarm algorithm, and regulating and controlling a traditional voltage regulation device or a photovoltaic inverter according to a solving result. According to the embodiment of the invention, different time scales are distributed for the traditional voltage regulation equipment and the photovoltaic inverter, and the advantages of large regulation amplitude of the traditional voltage regulation equipment and high response speed of the photovoltaic inverter are combined.

Description

Technical Field

[0001] The present invention relates to the technical field of voltage control of distributed power distribution networks, and in particular to a method, device, electronic equipment and storage medium for coordinated voltage control of a power distribution network. Background Art

[0002] At present, the number of household photovoltaic grid-connected to my country's medium and low voltage distribution networks is growing rapidly, and the grid-connected capacity is also increasing. Although the increase in photovoltaic penetration can alleviate the rapid depletion of fossil fuels and reduce carbon emissions from traditional power plants, it has created major technical challenges for the operation and control of distribution networks. A high proportion of photovoltaic access to the grid will cause power flow reverse transmission and voltage over-limit; at the same time, due to the strong uncertainty and volatility of photovoltaic output, node voltage fluctuations are frequent.

[0003] Traditional voltage regulation equipment, such as on-load tap changers (OLTCs) and smart capacitors, can greatly adjust the voltage, but cannot suppress rapid voltage fluctuations. The voltage regulation process is slow, usually taking several hours or even days. Photovoltaic inverters are power electronic devices with high response speed and flexible reactive injection range. The response time is usually a few minutes or even seconds, which can effectively solve the problem of voltage fluctuations. Since photovoltaic inverters generally use maximum power point tracking to connect to the grid, their reactive voltage regulation capabilities are limited. When the grid has a large voltage limit, they no longer have a significant regulation effect. Therefore, there is a big difference in the time scale of regulation between photovoltaic inverters and traditional voltage regulation equipment. How to coordinate photovoltaic inverters with traditional voltage regulation equipment to control the voltage of the distribution network is a problem that needs to be solved urgently.

[0004] Based on this, it is necessary to develop and design a distribution network voltage coordinated control method. Summary of the invention

[0005] The embodiments of the present invention provide a distribution network voltage coordinated control method, device, electronic device and storage medium, which are used to solve the problem in the prior art that photovoltaic inverters and traditional voltage regulation equipment have great differences in the time scale of regulation and are difficult to coordinate and control.

[0006] In a first aspect, an embodiment of the present invention provides a distribution network voltage coordinated control method, comprising:

[0007] Obtaining time scales and optimization constraints;

[0008] If the first-level control condition of the time scale is met at the current moment, the control model of the traditional voltage regulation device is used as the target control model, wherein the control model of the traditional voltage regulation device includes: the control target of the traditional voltage regulation device and the constraint condition of the traditional voltage regulation device;

[0009] Otherwise, the control model of the photovoltaic inverter is used as the target control model, wherein the control model of the photovoltaic inverter includes: a control target of the photovoltaic inverter and constraints of the photovoltaic inverter;

[0010] According to the optimization constraints, the target control model is solved by using a particle swarm algorithm, and the traditional voltage regulation device or the photovoltaic inverter is regulated according to the solution result.

[0011] In a possible implementation, the control target of the conventional voltage regulation device is constructed according to the distribution network loss target and the node voltage deviation value target, including:

[0012] A first network loss target and a first node voltage deviation value target are respectively constructed, wherein the first network loss target is:

[0013]

[0014] The first node voltage deviation value target is:

[0015]

[0016] In the formula, i and j represent the starting and ending nodes of the line respectively, N represents the number of system nodes, and U i and U j Respectively represent the voltage at the beginning and end of the line; cosθ ij represents the node voltage phase angle cosine, g ij Indicates line conductance; U N Indicates the node voltage rating; U max and U min Respectively represent the maximum and minimum values ​​of node voltage;

[0017] According to the first network loss target and the first node voltage deviation value target, a control target of the traditional voltage regulation device is constructed, wherein the control target of the traditional voltage regulation device is:

[0018]

[0019] Wherein, α1 and α2 are the first weight coefficient and the second weight coefficient respectively, and minf is the control target of the traditional voltage regulation device.

[0020] In a possible implementation, when the conventional voltage regulating device is an on-load tap-changing transformer, the constraint condition of the conventional voltage regulating device is:

[0021]

[0022] In the formula, is the number of gears of the on-load tap-changing transformer at time t; and They are the minimum and maximum values ​​of the on-load tap-changing transformer gear positions respectively; is the adjustable times of the on-load tap-changing transformer at node i; The maximum number of times the on-load tap-changing transformer can be adjusted; is the number of gears of the on-load tap-changing transformer at time t+Δt;

[0023] When the conventional voltage regulating device is a smart capacitor, the constraint conditions of the conventional voltage regulating device are:

[0024]

[0025] In the formula, It is the reactive power output by the smart capacitor; is the reactive power of a single group of smart capacitors; is the number of smart capacitor groups in operation; and The minimum and maximum values ​​of reactive power output by the smart capacitor; It is the maximum number of groups of smart capacitors that can be put into operation.

[0026] In a possible implementation, the control target of the photovoltaic inverter is constructed according to the standard voltage value and the reactive power corresponding to the standard voltage value, including:

[0027] A reactive power control model is constructed according to the standard voltage value and the reactive power corresponding to the standard voltage value, wherein the reactive power control model is:

[0028] Q obj =Q0+K qv (U ref -U meas ) meas L or U meas >U H

[0029] Where: Q obj is the reactive power target value of distributed photovoltaic, Q0 is the reactive power when the voltage of distributed photovoltaic grid connection point is the standard voltage value, K qv is the reactive voltage droop control coefficient, U ref is the measured value of the grid connection point voltage, U h is the upper limit of the dead zone voltage, U L is the lower limit of the dead zone voltage, U meas It is the standard voltage value.

[0030] ​In a possible implementation, when the reactive power of the photovoltaic inverter adopts a variable coefficient droop control strategy, the reactive voltage droop control coefficient is determined according to a first formula, which is:

[0031]

[0032] In the formula, α3 is the third coefficient, is the maximum reactive power that can be provided by the i-th PV inverter at time t, and n is the number of PV inverters in the region.

[0033] In a possible implementation, the optimization constraint condition includes an AC power flow equation constraint, and the AC power flow equation constraint is:

[0034]

[0035] Where P Gi and Q Gi are the active power and reactive power injected by node i respectively; P Li and Q Li are the active power and reactive power of the load at node i respectively; δ ij is the phase difference between the voltage vectors at node i and node j; G ij and B ij are the conductance and susceptance of the line between node i and node j respectively, and N is the total number of nodes in the power grid.

[0036] In a possible implementation, the adopting of a particle swarm algorithm to solve the target control model includes:

[0037] Acquire and initialize a particle swarm of a preset population size, wherein the position information of each particle in the particle swarm includes: grid parameters, distributed photovoltaic parameters, load parameters, and parameters of traditional voltage regulation equipment;

[0038] Fitness value calculation steps: Calculate the voltage deviation and network loss of the distribution network as the fitness value of the particle, evaluate the fitness values ​​of all particles, select the global optimal position of the particle and the individual extreme point and save them separately;

[0039] Determine the maximum number of iterations or convergence accuracy;

[0040] If the network loss target and the node voltage deviation value target are met, the process ends;

[0041] If the requirement is not met, the position and velocity information of the particle is updated and the fitness value calculation step is repeated.

[0042] In a second aspect, an embodiment of the present invention provides a distribution network voltage collaborative control device, which is used to implement the distribution network voltage collaborative control method described in the first aspect or any possible implementation of the first aspect, and the distribution network voltage collaborative control device includes:

[0043] Model condition acquisition module, used to obtain time scale and optimization constraints;

[0044] a first model building module, configured to use a control model of a traditional voltage regulation device as a target control model if a condition of the first layer control of the time scale is satisfied at a current moment, wherein the control model of the traditional voltage regulation device includes: a control target of the traditional voltage regulation device and a constraint condition of the traditional voltage regulation device;

[0045] A second model building module is used to use the control model of the photovoltaic inverter as the target control model if the condition of the first layer control of the time scale is not met at the current moment, wherein the control model of the photovoltaic inverter includes: a control target of the photovoltaic inverter and a constraint condition of the photovoltaic inverter;

[0046] as well as,

[0047] The model solving module is used to solve the target control model according to the optimization constraints using a particle swarm algorithm, and to regulate the traditional voltage regulating device or the photovoltaic inverter according to the solution result.

[0048] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the steps of the method described in the first aspect or any possible implementation method of the first aspect.

[0049] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation of the first aspect are implemented.

[0050] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0051] The embodiment of the present invention discloses a distribution network voltage coordinated control method, which first obtains a time scale and optimization constraints; then, if the first-level control conditions of the time scale are met at the current moment, a control model of a traditional voltage regulation device is used as a target control model, wherein the control model of the traditional voltage regulation device includes: a control target of the traditional voltage regulation device and constraints of the traditional voltage regulation device; if the first-level control conditions of the time scale are not met at the current moment, a control model of a photovoltaic inverter is used as a target control model, wherein the control model of the photovoltaic inverter includes: a control target of the photovoltaic inverter and constraints of the photovoltaic inverter; finally, according to the optimization constraints, a particle swarm algorithm is used to solve the target control model, and the traditional voltage regulation device or the photovoltaic inverter is regulated according to the solution result. The implementation mode of the present invention allocates different time scales to traditional voltage regulation equipment and photovoltaic inverters. At different time scales, traditional voltage regulation equipment is used to regulate the grid voltage at a large time scale, and inverter is used to regulate the grid voltage at a small time scale. The traditional voltage regulation equipment and photovoltaic inverter are coordinated and controlled, combining the advantages of large regulation range of traditional voltage regulation equipment and fast response speed of photovoltaic inverter. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0053] Figure 1 is a flow chart of a distribution network voltage coordinated control method provided by an embodiment of the present invention;

[0054] Figure 2 It is a functional block diagram of a distribution network voltage cooperative control device provided in an embodiment of the present invention;

[0055] Figure 3 It is a functional block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary details.

[0057] In order to make the purpose, technical solutions and advantages of the present invention more clear, a specific implementation method will be described below in conjunction with the accompanying drawings.

[0058] The following is a detailed description of an embodiment of the present invention. This example is implemented based on the technical solution of the present invention, and provides a detailed implementation method and a specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0059] Figure 1 A flow chart of a distribution network voltage coordinated control method provided in an embodiment of the present invention.

[0060] like Figure 1 As shown, it shows a flow chart of the implementation of the distribution network voltage coordinated control method provided by an embodiment of the present invention, which is described in detail as follows:

[0061] In step 101, a time scale and optimization constraints are obtained.

[0062] In some embodiments, the optimization constraint condition includes an AC power flow equation constraint, and the AC power flow equation constraint is:

[0063]

[0064] Where P Gi and Q Gi are the active power and reactive power injected by node i respectively; P Li and Q Li are the active power and reactive power of the load at node i respectively; δ ij is the phase difference between the voltage vectors at node i and node j; G ij and B ij are the conductance and susceptance of the line between node i and node j respectively, and N is the total number of nodes in the power grid.

[0065] For example, the time scale is the basis for double-layer control and the basis for dividing whether to use traditional voltage regulation or photovoltaic inverter voltage regulation. For example, in some application scenarios, the first layer of control is to control the traditional voltage regulation equipment before the day, once every 4 hours, and the control target is to minimize network loss and voltage deviation; the second layer of control is to control the photovoltaic inverter during the day, which is real-time control of voltage deviation, and the control target is to minimize voltage deviation.

[0066] In terms of grid voltage adjustment optimization, the AC power flow equation constraints need to be met:

[0067]

[0068] Where P Gi and Q Gi are the active power and reactive power injected by node i respectively; PLi and Q Li are the active power and reactive power of the load at node i respectively; δ ij is the phase difference between the voltage vectors at node i and node j; G ij and B ij are the conductance and susceptance of the line between node i and node j respectively, and N is the total number of nodes in the power grid.

[0069] In addition, in some scenarios, voltage and current constraints need to be met:

[0070]

[0071] Where: U i,max , U i,min Respectively represent the upper and lower limits of the voltage of the grid node i; I i,max ,I i,min They represent the upper and lower limits of the current at the grid node i respectively.

[0072] In step 102, if the first-level control conditions of the time scale are met at the current moment, the control model of the traditional voltage regulation device is used as the target control model, wherein the control model of the traditional voltage regulation device includes: the control target of the traditional voltage regulation device and the constraints of the traditional voltage regulation device.

[0073] In some implementations, the control target of the conventional voltage regulation device is constructed according to the distribution network loss target and the node voltage deviation value target, including:

[0074] A first network loss target and a first node voltage deviation value target are respectively constructed, wherein the first network loss target is:

[0075]

[0076] The first node voltage deviation value target is:

[0077]

[0078] In the formula, i and j represent the starting and ending nodes of the line respectively, N represents the number of system nodes, and U i and U j Respectively represent the voltage at the beginning and end of the line; cosθ ij represents the node voltage phase angle cosine, g ij Indicates line conductance; U N Indicates the node voltage rating; U max and U min Respectively represent the maximum and minimum values ​​of node voltage;

[0079] According to the first network loss target and the first node voltage deviation value target, a control target of the traditional voltage regulation device is constructed, wherein the control target of the traditional voltage regulation device is:

[0080]

[0081] Wherein, α1 and α2 are the first weight coefficient and the second weight coefficient respectively, and min f is the control target of the traditional voltage regulation device.

[0082] In some embodiments, when the conventional voltage regulating device is an on-load tap-changing transformer, the constraint condition of the conventional voltage regulating device is:

[0083]

[0084] In the formula, is the number of gears of the on-load tap-changing transformer at time t; and They are the minimum and maximum values ​​of the on-load tap-changing transformer gear positions respectively; is the adjustable times of the on-load tap-changing transformer at node i; The maximum number of times the on-load tap-changing transformer can be adjusted; is the number of gears of the on-load tap-changing transformer at time t+Δt;

[0085] When the conventional voltage regulating device is a smart capacitor, the constraint conditions of the conventional voltage regulating device are:

[0086]

[0087] In the formula, It is the reactive power output by the smart capacitor; is the reactive power of a single group of smart capacitors; is the number of smart capacitors in operation; and The minimum and maximum values ​​of reactive power output by the smart capacitor; It is the maximum number of groups of smart capacitors that can be put into operation.

[0088] Exemplarily, as mentioned above, when the conditions of the first-level control of the time scale are met, for example, the time interval between the voltage regulation of the previous traditional voltage regulation device and that of the previous traditional voltage regulation device is 4 hours, the control model of the traditional voltage regulation device is used as the target control model, and the control model of the traditional voltage regulation device includes the control target of the traditional voltage regulation device and the constraint conditions of the traditional voltage regulation device. In the implementation manner of the present invention, the control target of the traditional voltage regulation device is constructed according to the distribution network loss target and the node voltage deviation value target, including:

[0089] A first network loss target and a first node voltage deviation value target are respectively constructed, wherein the first network loss target is:

[0090]

[0091] The target voltage deviation value of the first node is:

[0092]

[0093] In the formula, i and j represent the starting and ending nodes of the line respectively, N represents the number of system nodes, and U i and U j Respectively represent the voltage at the beginning and end of the line; cosθ ij represents the node voltage phase angle cosine, g ij Indicates line conductance; U N Indicates the node voltage rating; U max and U min Respectively represent the maximum and minimum values ​​of node voltage;

[0094] In some application scenarios, in order to facilitate subsequent solution analysis, the above two objective functions are weighted respectively to form a comprehensive objective function:

[0095]

[0096] Wherein, α1 and α2 are the first weight coefficient and the second weight coefficient respectively, and min f is the control target of the traditional voltage regulation device.

[0097] In terms of the constraints of traditional voltage regulation equipment, when the traditional voltage regulation equipment is an on-load tap-changing transformer, the constraints are:

[0098]

[0099] In the formula, is the number of gears of the on-load tap-changing transformer at time y; and They are the minimum and maximum values ​​of the on-load tap-changing transformer gear positions respectively; is the adjustable times of the on-load tap-changing transformer at node i; The maximum number of times the on-load tap-changing transformer can be adjusted; is the number of gears of the on-load tap-changing transformer at time t+Δt.

[0100] When the conventional voltage regulating device is a smart capacitor, the constraint conditions of the conventional voltage regulating device are:

[0101]

[0102] In the formula, It is the reactive power output by the smart capacitor; is the reactive power of a single group of smart capacitors; is the number of smart capacitors in operation; and The minimum and maximum values ​​of reactive power output by the smart capacitor; It is the maximum number of groups of smart capacitors that can be put into operation.

[0103] In step 103, if the first-level control condition of the time scale is not met at the current moment, the control model of the photovoltaic inverter is used as the target control model, wherein the control model of the photovoltaic inverter includes: the control target of the photovoltaic inverter and the constraint conditions of the photovoltaic inverter.

[0104] In some implementations, the control target of the photovoltaic inverter is constructed according to the standard voltage value and the reactive power corresponding to the standard voltage value, including:

[0105] A reactive power control model is constructed according to the standard voltage value and the reactive power corresponding to the standard voltage value, wherein the reactive power control model is:

[0106] Q obj =Q0+K qv (U ref -U meas ) meas L or U meas >U H

[0107] Where: Q obj is the reactive power target value of distributed photovoltaic, Q0 is the reactive power when the voltage of distributed photovoltaic grid connection point is the standard voltage value, K qv is the reactive voltage droop control coefficient, U ref is the measured value of the grid connection point voltage, U H is the upper limit of the dead zone voltage, U L is the lower limit of the dead zone voltage, U meas It is the standard voltage value.

[0108] In some embodiments, when the reactive power of the photovoltaic inverter adopts a variable coefficient droop control strategy, the reactive voltage droop control coefficient is determined according to a first formula, which is:

[0109]

[0110] In the formula, α3 is the third coefficient, is the maximum reactive power that can be provided by the i-th PV inverter at time t, and n is the number of PV inverters in the region.

[0111] ​For example, between two time slots when the traditional voltage regulating device regulates the voltage, the photovoltaic inverter is used for control, and the regulation target is the same as the voltage deviation value target of the traditional voltage regulating device:

[0112]

[0113] In the formula, i and j represent the starting and ending nodes of the line respectively, N represents the number of system nodes, and U i and U j Respectively represent the voltage at the beginning and end of the line; cosθ ij represents the node voltage phase angle cosine, g ij Indicates line conductance; U N Indicates the node voltage rating; U max and U min Represent the maximum and minimum values ​​of the node voltage respectively.

[0114] The relationship between the active and reactive power output of the photovoltaic inverter can be expressed as:

[0115]

[0116] Where: Q PV is the reactive power output by the photovoltaic inverter; S PV is the apparent power of the photovoltaic inverter; P PV is the active power of the PV inverter.

[0117] In the traditional fixed coefficient voltage-VAR Droop Control (VVDC) mode, the reactive power target value of the photovoltaic power station is calculated according to the following formula:

[0118] Q obj =Q0+K qv (U ref -U meas ) meas L or U meas >U H

[0119] Where: Q obj is the reactive power target value of distributed photovoltaic, in unit of per unit (pu), Q0 is the reactive power when the voltage of distributed photovoltaic grid connection point is the standard voltage value, in unit of per unit (pu), K qv is the reactive voltage droop control coefficient, U ref is the measured value of the grid connection point voltage (the rated voltage can be taken), the unit is per unit value (pu), U H is the upper limit of the dead zone voltage, U L is the lower limit of the dead zone voltage, U meas ​It is the standard voltage value.

[0120] In the variable coefficient VVDC mode, the droop coefficient should be proportional to its reactive power capacity.

[0121]

[0122] In the formula, α3 is the third coefficient, which is set according to the reactive power demand. is the maximum reactive power that can be provided by the i-th PV inverter at time t, and n is the number of PV inverters in the region.

[0123] The constraint condition of the photovoltaic inverter voltage control model is the reactive power output of the photovoltaic inverter, that is:

[0124] Q PV,min ≤Q PV ≤Q PV,max

[0125] In step 104, the target control model is solved using a particle swarm algorithm according to the optimization constraints, and the traditional voltage regulation device or the photovoltaic inverter is regulated according to the solution result.

[0126] In some implementations, step 104 includes:

[0127] Acquire and initialize a particle swarm of a preset population size, wherein the position information of each particle in the particle swarm includes: grid parameters, distributed photovoltaic parameters, load parameters, and parameters of traditional voltage regulation equipment;

[0128] Fitness value calculation steps: Calculate the voltage deviation and network loss of the distribution network as the fitness value of the particle, evaluate the fitness values ​​of all particles, select the global optimal position of the particle and the individual extreme point and save them separately;

[0129] Determine the maximum number of iterations or convergence accuracy;

[0130] If the network loss target and the node voltage deviation value target are met, the process ends;

[0131] If the requirement is not met, the position and velocity information of the particle is updated and the fitness value calculation step is repeated.

[0132] Exemplarily, the embodiment of the present invention adopts a particle swarm algorithm to solve the optimal strategy for double-layer voltage control:

[0133] 1) The population size of the multi-time scale two-layer optimization model is set. At the same time, the position information of the mth particle is composed of grid parameters, distributed photovoltaic parameters, OLTC and CB parameters, and load parameters, and the particle position and speed are initialized.

[0134] 2) Calculate the voltage deviation and network loss of the distribution network as the fitness value of the particle. Evaluate the fitness values ​​of all particles, select the global optimal position of the particle and the individual extreme point and save them separately.

[0135] 3) Determine the maximum number of iterations or convergence accuracy. If the first network loss target and the first node voltage deviation value target are met, end; if the requirements are not met, update the particle position and velocity information and repeat steps 2) and 3).

[0136] The implementation method of the distribution network voltage cooperative control method of the present invention first obtains the time scale and the optimization constraint conditions; then if the current moment meets the conditions of the first-level control of the time scale, the control model of the traditional voltage regulation device is used as the target control model, wherein the control model of the traditional voltage regulation device includes: the control target of the traditional voltage regulation device and the constraint conditions of the traditional voltage regulation device; if the current moment does not meet the conditions of the first-level control of the time scale, the control model of the photovoltaic inverter is used as the target control model, wherein the control model of the photovoltaic inverter includes: the control target of the photovoltaic inverter and the constraint conditions of the photovoltaic inverter; finally, according to the optimization constraint conditions, the particle swarm algorithm is used to solve the target control model, and the traditional voltage regulation device or the photovoltaic inverter is regulated according to the solution results. The implementation method of the present invention allocates different time scales to the traditional voltage regulation device and the photovoltaic inverter. At different time scales, the traditional voltage regulation device is used to regulate the grid voltage at a large time scale, and the inverter is used to regulate the grid voltage at a small time scale. The traditional voltage regulation device and the photovoltaic inverter are controlled in a coordinated manner, combining the advantages of the large regulation amplitude of the traditional voltage regulation device and the fast response speed of the photovoltaic inverter.

[0137] In the implementation mode of the present invention, control objectives and constraints are constructed according to traditional voltage regulation equipment, and a reactive power control model is constructed according to the characteristics of photovoltaic inverters. Under the constraints of optimization constraints, a particle swarm algorithm is used to solve the optimal control scheme. Since the constraints of the equipment are taken into consideration, the optimized control scheme is more reliable.

[0138] It should be understood that the size of the serial numbers of the steps in the above implementation does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation method of the present invention.

[0139] The following is an implementation of the device of the present invention. For details not described in detail, reference may be made to the corresponding method implementation described above.

[0140] Figure 2 is a functional block diagram of a distribution network voltage cooperative control device provided in an embodiment of the present invention, referring to Figure 2The distribution network voltage cooperative control device includes: a model condition acquisition module 201, a first model construction module 202, a second model construction module 203 and a model solution module 204, wherein:

[0141] Model condition acquisition module 201, used to acquire time scale and optimization constraint conditions;

[0142] A first model building module 202 is used to use the control model of the traditional voltage regulation device as the target control model if the condition of the first layer control of the time scale is met at the current moment, wherein the control model of the traditional voltage regulation device includes: the control target of the traditional voltage regulation device and the constraint condition of the traditional voltage regulation device;

[0143] The second model building module 203 is used to use the control model of the photovoltaic inverter as the target control model if the condition of the first layer control of the time scale is not met at the current moment, wherein the control model of the photovoltaic inverter includes: the control target of the photovoltaic inverter and the constraint conditions of the photovoltaic inverter;

[0144] The model solving module 204 is used to solve the target control model according to the optimization constraints using a particle swarm algorithm, and regulate the traditional voltage regulating device or the photovoltaic inverter according to the solution result.

[0145] Figure 3 is a functional block diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, the electronic device 3 of this embodiment includes: a processor 300 and a memory 301, wherein the memory 301 stores a computer program 302 that can be run on the processor 300. When the processor 300 executes the computer program 302, the steps in the above-mentioned distribution network voltage coordinated control method and the embodiment are implemented, for example Figure 1 Steps 101 to 104 are shown.

[0146] Exemplarily, the computer program 302 may be divided into one or more modules / units, and the one or more modules / units are stored in the memory 301 and executed by the processor 300 to implement the present invention.

[0147] The electronic device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 3 may include, but is not limited to, a processor 300 and a memory 301. Those skilled in the art will appreciate that Figure 3It is only an example of the electronic device 3 and does not constitute a limitation of the electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 3 may also include input and output devices, network access devices, buses, etc.

[0148] The processor 300 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0149] The memory 301 may be an internal storage unit of the electronic device 3, such as a hard disk or memory of the electronic device 3. The memory 301 may also be an external storage device of the electronic device 3, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 3. Further, the memory 301 may also include both an internal storage unit of the electronic device 3 and an external storage device. The memory 301 is used to store the computer program 302 and other programs and data required by the electronic device 3. The memory 301 may also be used to temporarily store data that has been output or is to be output.

[0150] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the implementation method can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method implementation method, which will not be repeated here.

[0151] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0152] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0153] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0154] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0155] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0156] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned implementation method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various methods and device implementation methods. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0157] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A distribution network voltage coordinated control method, characterized in that: include: Obtaining time scales and optimization constraints; If the first-level control condition of the time scale is met at the current moment, the control model of the traditional voltage regulation device is used as the target control model, wherein the control model of the traditional voltage regulation device includes: the control target of the traditional voltage regulation device and the constraint condition of the traditional voltage regulation device; Otherwise, the control model of the photovoltaic inverter is used as the target control model, wherein the control model of the photovoltaic inverter includes: a control target of the photovoltaic inverter and constraints of the photovoltaic inverter; According to the optimization constraints, the target control model is solved by using a particle swarm algorithm, and the traditional voltage regulation device or the photovoltaic inverter is regulated according to the solution result.

2. The distribution network voltage coordinated control method according to claim 1, characterized in that: The control target of the conventional voltage regulation device is constructed according to the distribution network loss target and the node voltage deviation value target, including: A first network loss target and a first node voltage deviation value target are respectively constructed, wherein the first network loss target is: The first node voltage deviation value target is: In the formula, i and j represent the starting and ending nodes of the line respectively, N represents the number of system nodes, and U i and U j Respectively represent the voltage at the beginning and end of the line; cosθ ij represents the node voltage phase angle cosine, g ij Indicates line conductance; U N Indicates the node voltage rating; U max and U min Respectively represent the maximum and minimum values ​​of node voltage; According to the first network loss target and the first node voltage deviation value target, a control target of the traditional voltage regulation device is constructed, wherein the control target of the traditional voltage regulation device is: Wherein, α1 and α2 are the first weight coefficient and the second weight coefficient respectively, and min f is the control target of the traditional voltage regulation device.

3. The distribution network voltage coordinated control method according to claim 1, characterized in that: When the conventional voltage regulating device is an on-load tap-changing transformer, the constraint conditions of the conventional voltage regulating device are: In the formula, is the number of gears of the on-load tap-changing transformer at time t; and They are the minimum and maximum values ​​of the on-load tap-changing transformer gear positions respectively; is the adjustable times of the on-load tap-changing transformer at node i; The maximum number of times the on-load tap-changing transformer can be adjusted; is the number of gears of the on-load tap-changing transformer at time t+Δt; When the conventional voltage regulating device is a smart capacitor, the constraint conditions of the conventional voltage regulating device are: In the formula, It is the reactive power output by the smart capacitor; is the reactive power of a single group of smart capacitors; is the number of smart capacitor groups in operation; and The minimum and maximum values ​​of reactive power output by the smart capacitor; It is the maximum number of groups of smart capacitors that can be put into operation.

4. The distribution network voltage coordinated control method according to claim 1, characterized in that: The control target of the photovoltaic inverter is constructed according to the standard voltage value and the reactive power corresponding to the standard voltage value, including: A reactive power control model is constructed according to the standard voltage value and the reactive power corresponding to the standard voltage value, wherein the reactive power control model is: Q obj = Q0 + K qv (U ref - U meas )U meas <U L or U meas >U H Where: Q obj is the reactive power target value of distributed photovoltaic, Q0 is the reactive power when the voltage of distributed photovoltaic grid connection point is the standard voltage value, K qv is the reactive voltage droop control coefficient, U ref is the measured value of the grid connection point voltage, U H is the upper limit of the dead zone voltage, U L is the lower limit of the dead zone voltage, U meas It is the standard voltage value.

5. The distribution network voltage coordinated control method according to claim 4, characterized in that: When the reactive power of the photovoltaic inverter adopts a variable coefficient droop control strategy, the reactive voltage droop control coefficient is determined according to a first formula, which is: In the formula, α3 is the third coefficient, is the maximum reactive power that can be provided by the i-th PV inverter at time t, and n is the number of PV inverters in the region.

6. The distribution network voltage coordinated control method according to claim 1, characterized in that: The optimization constraint condition includes an AC power flow equation constraint, and the AC power flow equation constraint is: Where P Gi and Q Gi are the active power and reactive power injected by node i respectively; P Li and Q Li are the active power and reactive power of the load at node i respectively; δ ij is the phase difference between the voltage vectors at node i and node j; G ij and B ij are the conductance and susceptance of the line between node i and node j respectively, and N is the total number of nodes in the power grid.

7. The distribution network voltage coordinated control method according to any one of claims 1 to 6, characterized in that: The adopting of a particle swarm algorithm to solve the target control model comprises: Acquire and initialize a particle swarm of a preset population size, wherein the position information of each particle in the particle swarm includes: grid parameters, distributed photovoltaic parameters, load parameters, and parameters of traditional voltage regulation equipment; Fitness value calculation steps: Calculate the voltage deviation and network loss of the distribution network as the fitness value of the particle, evaluate the fitness values ​​of all particles, select the global optimal position of the particle and the individual extreme point and save them separately; Determine the maximum number of iterations or convergence accuracy; If the network loss target and the node voltage deviation value target are met, the process ends; If the requirement is not met, the position and velocity information of the particle is updated and the fitness value calculation step is repeated.

8. A distribution network voltage coordinated control device, characterized in that: Used to implement the distribution network voltage coordinated control method according to any one of claims 1 to 7, the distribution network voltage coordinated control device comprises: Model condition acquisition module, used to obtain time scale and optimization constraints; a first model building module, configured to use a control model of a traditional voltage regulation device as a target control model if a condition of the first layer control of the time scale is satisfied at a current moment, wherein the control model of the traditional voltage regulation device includes: a control target of the traditional voltage regulation device and a constraint condition of the traditional voltage regulation device; A second model building module is used to use the control model of the photovoltaic inverter as the target control model if the condition of the first layer control of the time scale is not met at the current moment, wherein the control model of the photovoltaic inverter includes: a control target of the photovoltaic inverter and a constraint condition of the photovoltaic inverter; as well as, The model solving module is used to solve the target control model according to the optimization constraints using a particle swarm algorithm, and to regulate the traditional voltage regulating device or the photovoltaic inverter according to the solution result.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

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