Photovoltaic output control method and device and power distribution network distributed photovoltaic cluster system

Abstract

The invention relates to a photovoltaic output control method and device and a power distribution network distributed photovoltaic cluster system, an edge calculation controller is deployed on the edge side of a power distribution network, voltage and distributed photovoltaic output conditions are monitored in real time, a voltage and power mathematical model is replaced with measurement data, the calculation amount is reduced, and the requirement for model precision is reduced. Through the combination of the edge calculation controller and the photovoltaic local controller, the control process can be adjusted according to the real-time change condition of each distributed photovoltaic in the distributed photovoltaic cluster system, the control effect is more accurate, and the accurate control of the distributed photovoltaic output can be realized. According to the method, the response speed of voltage regulation in the distributed photovoltaic cluster system of the power distribution network can be improved, the power transmission of the head end of the feeder line can be ensured to be within an allowable range, higher control precision is realized, and the method is of great significance in improving the operation efficiency of the power grid, improving the utilization rate of new energy and guaranteeing the safe and stable operation of the power grid.

Description

Technical Field

[0001] The present application relates to the technical field of distribution network cluster control, and in particular to a photovoltaic output control method and device and a distributed photovoltaic cluster system of a distribution network. Background Art

[0002] With the rapid development of renewable energy, photovoltaic power generation, as an important form of clean energy, is being widely used around the world. Photovoltaic power generation systems use smart inverters to achieve precise control of reactive power and active power, effectively supporting the stable operation of the power grid.

[0003] Traditional photovoltaic power generation systems are mostly centralized control modes. Although this mode simplifies the design and management of the system to a certain extent, it also faces many challenges. The centralized control mode relies on the global scheduling of a single control center. Once the system scale is expanded, the computing and communication burden of the control center will increase sharply, resulting in a decrease in the system response speed and difficulty in adapting to the needs of large-scale distributed photovoltaic clusters. Secondly, the randomness and intermittent characteristics of photovoltaic power generation make real-time control more complicated, and the centralized control mode is difficult to cope with the dynamic changes of each node in the distributed photovoltaic system. Summary of the invention

[0004] Based on this, it is necessary to provide a photovoltaic output control method, device and distribution network distributed photovoltaic cluster system that can effectively cope with the dynamic changes of multiple nodes in a large-scale photovoltaic power generation system in response to the above technical problems.

[0005] In a first aspect, the present application provides a photovoltaic output control method, which is applied to a photovoltaic local controller of a distributed photovoltaic cluster system of a distribution network, wherein the distributed photovoltaic cluster system of the distribution network includes an edge computing controller and at least one photovoltaic local controller, and the photovoltaic local controller is connected to the edge computing controller, and the method includes:

[0006] Obtaining the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, various dual variable update values ​​and the linearization sensitivity parameter matrix; wherein the various dual variable update values ​​and the linearization sensitivity parameter matrix are calculated and sent by the edge computing controller;

[0007] According to the current photovoltaic actual reactive power measurement value, the current photovoltaic actual active power measurement value, the dual variable update value and the linearized sensitivity parameter matrix, the photovoltaic actual active power and the photovoltaic actual reactive power offset analysis are performed to obtain the target active power offset and the target reactive power offset;

[0008] Adjusting the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain a target active power setting value and a target reactive power setting value;

[0009] The distributed photovoltaic output is controlled according to the target active power setting value and the target reactive power setting value.

[0010] In one embodiment, the step of calculating the linearized sensitivity parameter matrix includes:

[0011] The edge computing controller performs initialization processing to obtain the distribution network topology connection relationship, line parameters, voltage control range parameters, feeder head end active power control range parameters and initial values ​​of various dual variables;

[0012] The edge computing controller calculates the linearized sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node, and the linearized sensitivity parameter matrix of the active power at the head end of the feeder with respect to the active power and reactive power injected into each node according to the topological connection relationship of the distribution network and the line parameters;

[0013] The linearized sensitivity parameter matrix is ​​transmitted to the photovoltaic local controller.

[0014] In one embodiment, the step of calculating the updated values ​​of each dual variable includes:

[0015] The edge computing controller collects the current voltage measurement value of each voltage control node, the current active power measurement value of the feeder head end, and the values ​​of various dual variables at the previous moment, and calculates the upper and lower limit offset values ​​of the voltage control range, the voltage balance offset value, the upper and lower limit offset values ​​of the active power control range of the feeder head end, and the updated values ​​of various dual variables according to the current voltage measurement value, the current active power measurement value of the feeder head end, the voltage control range parameter, the active power control range parameter of the feeder head end, and the values ​​of various dual variables at the previous moment; wherein, if the current moment is the first collection moment, the values ​​of various dual variables at the previous moment are the corresponding initial values ​​of various dual variables.

[0016] In one embodiment, the voltage control range upper and lower limit offset values, voltage balance offset value, feeder head end active power control range upper and lower limit offset values, and various dual variable update values ​​are calculated based on the voltage measurement value at the current moment, the active power measurement value at the feeder head end at the current moment, the voltage control range parameter, the active power control range parameter at the feeder head end, and various dual variable values ​​at the previous moment, respectively, including:

[0017] Calculate the upper and lower limit offset values ​​of the voltage control range and the voltage balance offset value according to the upper and lower limit values ​​of the voltage control range parameter and the voltage measurement value at the current moment;

[0018] According to the upper and lower limit values ​​of the active power control range parameter of the feeder head end and the current measured active power value of the feeder head end, the upper and lower limit offset values ​​of the active power control range of the feeder head end are calculated;

[0019] According to the dual variable values ​​related to the upper and lower bounds of the voltage at the previous moment, the dual variable values ​​related to the upper and lower bounds of the active power at the head end of the feeder at the previous moment, the dual variable change step size, and the regularization parameter of the edge computing controller, the dual variable update values ​​related to the upper and lower bounds of the voltage at the current moment and the dual variable update values ​​related to the upper and lower bounds of the active power at the head end of the feeder at the current moment are calculated respectively.

[0020] In one embodiment, the method further comprises:

[0021] Initializing the photovoltaic local controller to obtain voltage variable step adaptive module coefficients, active weight adaptive adjustment model parameters, and reactive weight adaptive adjustment model parameters;

[0022] After the distributed photovoltaic local controller obtains the actual photovoltaic reactive power measurement value and the actual photovoltaic active power measurement value at the current moment, the method further includes:

[0023] The voltage adaptive adjustment coefficient is calculated according to the voltage balance offset value and the voltage variable step adaptive model coefficient;

[0024] The active weight adaptive adjustment coefficient is calculated based on the active weight adaptive adjustment model parameters, the actual photovoltaic reactive power measurement value, and the distributed photovoltaic maximum reactive power output parameters;

[0025] The reactive weight adaptive adjustment coefficient is calculated according to the reactive weight adaptive adjustment model parameters, the actual reactive power measurement value of photovoltaics, and the maximum reactive power output parameters of distributed photovoltaics.

[0026] In one embodiment, the offset analysis of the actual photovoltaic active power and the actual photovoltaic reactive power is performed according to the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, the dual variable update values ​​and the linearized sensitivity parameter matrix to obtain the target active power offset and the target reactive power offset, including:

[0027] The first part of the offset is calculated based on the actual photovoltaic reactive power measurement value, the actual photovoltaic active power measurement value and the photovoltaic local controller regularization parameter;

[0028] The second part of the offset is calculated according to the linearized sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node, the voltage adaptive adjustment coefficient, the active weight adaptive adjustment coefficient, the reactive weight adaptive adjustment coefficient, and the dual variable update value related to the upper and lower bounds of the voltage at the current moment;

[0029] The third part offset is calculated according to the linearized sensitivity parameter matrix of the active power at the head end of the feeder with respect to the active power and reactive power injected into each node, the active weight adaptive adjustment coefficient, the reactive weight adaptive adjustment coefficient, and the dual variable update value related to the upper and lower bounds of the active power at the head end of the feeder at the current moment;

[0030] The target active power offset and the target reactive power offset are calculated according to the first offset, the second offset and the third offset.

[0031] In one embodiment, the method further comprises:

[0032] After controlling the preset time of distributed photovoltaic output according to the target active power setting value and the target reactive power setting value, jump to execute the step of obtaining the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, the updated values ​​of each dual variable and the linearized sensitivity parameter matrix.

[0033] In one embodiment,

[0034] The distributed photovoltaic output setting value includes the distributed photovoltaic active power output setting value and reactive power output setting value at the previous moment;

[0035] The step of adjusting the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain the target active power setting value and the target reactive power setting value includes:

[0036] Calculate the target active power setting value according to the target active power offset and the active power output setting value of the distributed photovoltaic at the previous moment;

[0037] The target reactive power setting value is calculated based on the target reactive power offset and the reactive power output setting value of the distributed photovoltaic system at the previous moment.

[0038] In a second aspect, the present application further provides a photovoltaic output control device, which is applied to a photovoltaic local controller of a distributed photovoltaic cluster system of a distribution network, wherein the distributed photovoltaic cluster system of the distribution network includes an edge computing controller and at least one photovoltaic local controller, wherein the photovoltaic local controller is connected to the edge computing controller, and the device includes:

[0039] An acquisition module is used to acquire the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, various dual variable update values ​​and the linearization sensitivity parameter matrix; wherein the various dual variable update values ​​and the linearization sensitivity parameter matrix are calculated and sent by the edge computing controller;

[0040] An analysis module is used to perform an offset analysis of the actual photovoltaic active power and the actual photovoltaic reactive power according to the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, the updated values ​​of each dual variable and the linearized sensitivity parameter matrix, so as to obtain a target active power offset and a target reactive power offset;

[0041] An adjustment module, used to adjust the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain a target active power setting value and a target reactive power setting value;

[0042] A control module is used to control the distributed photovoltaic output according to the target active power setting value and the target reactive power setting value.

[0043] In a third aspect, the present application further provides a distributed photovoltaic cluster system for a power distribution network, including an edge computing controller and at least one photovoltaic local controller, wherein the photovoltaic local controller is connected to the edge computing controller;

[0044] The edge computing controller is connected to the voltage control node, the photovoltaic on-site controller is connected to the distributed photovoltaic, and the edge computing controller and the photovoltaic on-site controller are used to execute the steps of the photovoltaic output control method described in the first aspect.

[0045] In a fourth aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the photovoltaic output control method described in the first aspect when executing the computer program.

[0046] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the photovoltaic output control method described in the first aspect are implemented.

[0047] In a sixth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the photovoltaic output control method described in the first aspect are implemented.

[0048] In summary, the present application proposes a photovoltaic output control method, device and a distributed photovoltaic cluster system for a distribution network, which deploys an edge computing controller at the edge of the distribution network to monitor the voltage and distributed photovoltaic output in real time, and replaces the mathematical model of voltage and power with measurement data, thereby reducing the amount of calculation and the demand for model accuracy. The combination of the edge computing controller and the photovoltaic on-site controller allows the control process to be adjusted according to the real-time changes of each distributed photovoltaic in the distributed photovoltaic cluster system, and the control effect is more accurate, which can achieve precise control of the distributed photovoltaic output. The present invention can not only improve the response speed of voltage regulation in the distributed photovoltaic cluster system of the distribution network, but also ensure that the power transmission at the head end of the feeder is within the allowable range, and achieve higher control accuracy, which is of great significance for improving the operation efficiency of the power grid, improving the utilization rate of new energy, and ensuring the safe and stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of a topological structure of a power distribution network in an embodiment;

[0050] Figure 2 A schematic diagram of controller deployment of a distributed photovoltaic cluster system in a power distribution network in an embodiment;

[0051] Figure 3 One of the flow charts of a photovoltaic output control method in one embodiment;

[0052] Figure 4 The second flowchart of a photovoltaic output control method in one embodiment;

[0053] Figure 5 The third flowchart of a photovoltaic output control method in one embodiment;

[0054] Figure 6 The fourth flowchart of a photovoltaic output control method in one embodiment;

[0055] Figure 7 FIG5 is a fifth flow chart of a photovoltaic output control method in an embodiment;

[0056] Figure 8 is a schematic diagram of a prediction curve of distributed photovoltaic output and load changes in an embodiment;

[0057] Fig. 9 is a schematic diagram of the power variation of the feeder head end under the control of different schemes in an embodiment;

[0058] Fig.10 is a schematic diagram of the upper and lower limits of voltages at all voltage measurement points under control of different schemes in one embodiment;

[0059] Fig.11The diagram is a schematic diagram of distributed photovoltaic active output at nodes 8, 11, and 16 under the action of scheme 2 in an embodiment;

[0060] Fig.12 is a schematic diagram of distributed photovoltaic reactive power output at nodes 8, 11, and 16 under scheme 2 in an embodiment;

[0061] Fig.13 is a structural block diagram of a photovoltaic power output device in one embodiment;

[0062] Fig.14 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0064] As described in the above background technology, photovoltaic power generation systems in power grids have become an indispensable clean energy system. In terms of reactive power control, photovoltaic power generation systems can provide static and dynamic reactive power compensation, stabilize voltage and adjust power factor by adjusting reactive power. In terms of active power control, photovoltaic power generation systems can optimize active power output through maximum power point tracking, and limit power output and frequency response according to grid demand. Photovoltaic power generation systems also have reduction control capabilities in active power control, that is, when there is sufficient sunlight, they can actively reduce active power output to avoid grid overload or meet grid operation requirements.

[0065] The distributed control mode of the photovoltaic power generation system decomposes the global control task into multiple local control tasks, so that each node can make control decisions independently, thereby reducing the system's dependence on the central controller and improving the system's flexibility and robustness.

[0066] Primitive-dual theory is an effective solution to optimization problems. Its core idea is to decompose the global optimization problem into multiple local sub-problems, each of which involves only a single or a few control variables and constraints. By introducing dual variables, the coupling relationship between sub-problems can be weakened, making it possible to solve each sub-problem independently in distributed photovoltaics. Through the primal-dual update mechanism, each distributed photovoltaic gradually approaches the global optimal solution through limited information exchange, realizing the overall coordinated control of the photovoltaic cluster.

[0067] like Figure 1 and Figure 2As shown, this embodiment provides a distributed photovoltaic cluster system for a distribution network, the system includes a distributed photovoltaic cluster edge computing controller and at least one distributed photovoltaic local controller, wherein the photovoltaic local controller is connected to the edge computing controller. Figure 2 The photovoltaic local controller in this embodiment is connected to a single distributed photovoltaic in the distributed photovoltaic cluster of the distribution network. It should be noted that each distributed photovoltaic in the distributed photovoltaic cluster of the distribution network is connected to a corresponding photovoltaic local controller.

[0068] In this embodiment, the edge computing controller is connected to the voltage measurement points in the distribution network, wherein each voltage measurement point is a voltage control node in the distribution network.

[0069] It should be noted that this embodiment does not limit the specific topological structure of the distribution network and the number of photovoltaic local controllers, and the topological structure of the distribution network and the number of photovoltaic local controllers can be configured according to the needs of actual application scenarios.

[0070] This embodiment provides a photovoltaic output control method applied to a distributed photovoltaic cluster system of a distribution network, which can realize photovoltaic distributed control while making flexible decisions for each voltage control node, reducing the system's dependence on a central controller and greatly improving the efficiency of photovoltaic output control.

[0071] In one embodiment, Figure 3 As shown, a photovoltaic output control method is provided, which is applied to Figure 2 The distributed photovoltaic cluster system in the distribution network is used as an example to illustrate, including the following steps:

[0072] S301, the edge computing controller performs initialization processing to obtain the distribution network topology connection relationship, line parameters, voltage control range parameters, feeder head end active power control range parameters and initial values ​​of various dual variables.

[0073] In this embodiment, before implementing the coordinated control step of the voltage and power of distributed photovoltaics in the distributed photovoltaic cluster of the distribution network, it is first necessary to initialize the distributed photovoltaic cluster edge computing controller and the distributed photovoltaic on-site controller respectively.

[0074] The specific contents of the initialization processing of the edge computing controller include inputting the topological connection relationship and line parameters of the distribution network to which the distributed photovoltaic cluster is connected, and inputting the voltage control range parameters of each voltage control node in each distribution network. , Input feeder head end active power control range parameters , initial value of the dual variable related to the voltage lower bound , initial value of the dual variable related to the voltage upper bound , initial value of the dual variable related to the lower bound of active power at the feeder head end , initial value of the dual variable related to the upper bound of active power at the feeder head end , dual variable change step and the edge computing controller regularization parameter Wait for the initial data.

[0075] In one embodiment, the specific content of initializing the distributed photovoltaic local controller includes: inputting the photovoltaic local controller regularization parameter , voltage variable step adaptive model coefficient , active weights adaptively adjust model parameters and , reactive weight adaptively adjusts model parameters and .

[0076] It should be noted that in this embodiment and subsequent embodiments, Figure 2 As shown, the number of each voltage control node is set to , the node number of the distributed photovoltaic is set to , the current time is set to , the preset time interval society is .

[0077] S302, the edge computing controller calculates the linearized sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node, and the linearized sensitivity parameter matrix of the active power at the head end of the feeder with respect to the active power and reactive power injected into each node according to the topological connection relationship of the distribution network and the line parameters, and transmits the linearized sensitivity parameter matrix to the photovoltaic local controller;

[0078] In this embodiment, after the edge computing controller obtains the topological connection relationship and line parameters of the distribution network, it can further calculate the linear sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node according to the topological connection relationship and line parameters of the distribution network. and , Linearized sensitivity parameter matrix of active power at the feeder head end with respect to active power and reactive power injected into each node and , and and Transmitted to each distributed photovoltaic local controller.

[0079] In this embodiment, the linearized sensitivity parameter matrix Include elements , linearized sensitivity parameter matrix Include elements ,element and elements The solution is as follows:

[0080]

[0081]

[0082] in, The voltage control node The node where the distributed photovoltaic The set of branches between represents the total number of nodes in the distribution network, Indicates the branch number. For line The resistance, For line The reactance, For branch At the voltage control node The node where the distributed photovoltaic The branch-node correlation coefficient between them. The solution is as follows:

[0083]

[0084] In this embodiment, the linearized sensitivity parameter matrix Include elements , linearized sensitivity parameter matrix Include elements , ignoring the influence of network loss, element and elements The solution is, , .

[0085] S303, the edge computing controller collects the current voltage measurement value of each voltage control node, the current active power measurement value of the feeder head end, and the values ​​of each dual variable at the previous moment, and calculates the upper and lower limit offset values ​​of the voltage control range, the voltage balance offset value, the upper and lower limit offset values ​​of the active power control range of the feeder head end, and the updated values ​​of each dual variable according to the current voltage measurement value, the current active power measurement value of the feeder head end, the voltage control range parameter, the feeder head end active power control range parameter, and the values ​​of each dual variable at the previous moment; wherein, if the current moment is the first collection moment, the values ​​of each dual variable at the previous moment are the corresponding initial values ​​of each dual variable.

[0086] In this embodiment, the current time is Moment, last moment time.

[0087] The edge computing controller first needs to collect Time Node The current voltage measurement value , The measured active power value at the head end of the feeder at the current time , Time Node The values ​​of the dual variables related to the voltage upper and lower bounds and , The value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at any given moment and .

[0088] Then, the edge computing controller will control the lower limit of the voltage range parameter according to and upper bound , the lower limit of the active power control range parameter at the feeder head end and upper bound , Time Node The voltage measurement value , Active power measurement value at the head end of the feeder at any moment ,calculate Time Node The voltage upper limit offset value and lower bound offset , Voltage balance offset value , The offset value between the measured active power value at the head end of the feeder and the upper limit of the active power control range at the head end of the feeder at the moment and lower bound offset .

[0089] Then according to the offset value of the upper and lower limits of the voltage and , and the offset value of the upper and lower limits of the active power control range at the feeder head end and , combined with Time Node The values ​​of the dual variables related to the voltage upper and lower bounds and , The value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at any given moment and , the step size of the dual variable change and the regularization parameter ,calculate Time Node Updated values ​​of dual variables related to voltage upper and lower bounds and , The updated value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at each moment and .

[0090] S304, the distributed photovoltaic on-site controller obtains the actual photovoltaic reactive power measurement value and the actual photovoltaic active power measurement value at the current moment, and then performs an offset analysis of the photovoltaic actual active power and the photovoltaic actual reactive power based on the actual photovoltaic reactive power measurement value, the photovoltaic actual active power measurement value, the dual variable update values ​​and the linearized sensitivity parameter matrix at the current moment to obtain the target active power offset and the target reactive power offset.

[0091] In this embodiment, each distributed photovoltaic local controller first collects Time Node The measured value of actual reactive power of distributed photovoltaic and Time Node The measured value of the actual active power of distributed photovoltaic .

[0092] Get the updated value of the dual variable from the edge computing controller , , , and voltage balance offset After that, according to the measured value of the actual photovoltaic reactive power , the measured value of the actual active power of photovoltaic Updated values ​​of each dual variable , , , , linear sensitivity parameter matrix and And the voltage balance offset value Perform an offset analysis of the actual photovoltaic active power and the actual photovoltaic reactive power to obtain the target active power offset and target reactive power offset .

[0093] In this embodiment, since each voltage control node and distributed photovoltaics will dynamically change with the actual application scenario during the actual operation, it is necessary to dynamically adjust the photovoltaic output parameters at preset intervals.

[0094] This embodiment configures an edge computing controller and a photovoltaic on-site controller, and uses measurement data to replace the mathematical models of voltage and power, thereby reducing the amount of calculation and the demand for model accuracy. It also allows the control process to be adjusted according to real-time changes in the system, making the control effect more precise and achieving precise control of distributed photovoltaic output.

[0095] S305, the distributed photovoltaic on-site controller adjusts the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain the target active power setting value and the target reactive power setting value.

[0096] In this embodiment, each distributed photovoltaic local controller corrects the output setting value of the distributed photovoltaic to obtain the target active power setting value. and target reactive power setting value , the specific calculation method is:

[0097]

[0098]

[0099] in, For the current moment At the node The target active power offset of distributed photovoltaics, For the current moment At the node The target reactive power offset of distributed photovoltaics, for Always at the node The active power output setting value of distributed photovoltaics, for Always at the node The reactive power output setting value of distributed photovoltaics.

[0100] S306, the distributed photovoltaic local controller controls the distributed photovoltaic output according to the target active power setting value and the target reactive power setting value.

[0101] In this embodiment, the final target output setting value is determined and Finally, the distributed photovoltaic output is controlled according to the final target output setting value. At this time, the output of each distributed photovoltaic will change, and the power flow distribution will change accordingly.

[0102] To sum up, this embodiment provides a photovoltaic output control method. Through the combination of an edge computing controller and a distributed photovoltaic on-site controller, the computing resources of the central controller can be fully saved, and real-time power distribution of distributed photovoltaics in a distribution network cluster can be realized, supporting the realization of decentralized coordinated control of distributed photovoltaic clusters driven by limited measurements.

[0103] In one embodiment, Figure 4 As shown, according to the voltage measurement value at the current moment, the active power measurement value at the head end of the feeder at the current moment, the voltage control range parameter, the active power control range parameter at the head end of the feeder, and the values ​​of various dual variables at the previous moment, the upper and lower limit offset values ​​of the voltage control range, the voltage balance offset value, the upper and lower limit offset values ​​of the active power control range at the head end of the feeder, and the updated values ​​of various dual variables are calculated respectively, including:

[0104] S401, calculating the upper and lower limit offset values ​​of the voltage control range and the voltage balance offset value according to the upper and lower limit values ​​of the voltage control range parameter and the voltage measurement value at the current moment;

[0105] In this embodiment, the edge computing controller controls the upper and lower limits of the voltage control range parameter. and , Time Node The voltage measurement value ,calculate Time Node The voltage measurement value and the offset value of the voltage upper and lower limits and , and the voltage balance position offset value , the specific calculation method is:

[0106]

[0107]

[0108]

[0109] In the formula, represents the node number of the voltage control node, Indicates the current moment, express Time Node The voltage measurement value modulus, Indicates the minimum value in the voltage control range, Indicates the maximum value in the voltage control range.

[0110] S402, calculating the upper and lower limit offset values ​​of the active power control range of the feeder head end according to the upper and lower limit values ​​of the active power control range parameter of the feeder head end and the active power measurement value of the feeder head end at the current moment;

[0111] In this embodiment, the edge computing controller also controls the lower and upper limits of the range parameters according to the active power control range of the feeder head end. and , Active power measurement value at the head end of the feeder at any moment , calculated by the cluster edge computing controller The offset value between the measured active power value at the head end of the feeder and the upper and lower limits of the active power control range at the head end of the feeder at the moment and , the specific calculation method is:

[0112]

[0113]

[0114] in, Indicates the current moment, express Time Node The voltage measurement value modulus, Indicates the maximum value in the active power control range at the head end of the feeder. Indicates the minimum value in the active power control range at the head end of the feeder.

[0115] S403, based on the dual variable values ​​related to the upper and lower bounds of the voltage at the previous moment, the dual variable values ​​related to the upper and lower bounds of the active power at the feeder head end at the previous moment, the dual variable change step size, and the edge computing controller regularization parameter, respectively calculate the dual variable update values ​​related to the upper and lower bounds of the voltage at the current moment and the dual variable update values ​​related to the upper and lower bounds of the active power at the feeder head end at the current moment.

[0116] In this embodiment, according to the offset values ​​of the upper and lower limits of the voltage and , combined with Time Node The values ​​of the dual variables related to the voltage upper and lower bounds and , dual variable change step , regularization parameter , calculated by the cluster edge computing controller Time Node Updated values ​​of dual variables related to voltage upper and lower bounds , , the specific calculation method is:

[0117]

[0118]

[0119] in, represents the node number of the voltage control node, For the current moment, Indicates the previous moment, , for Time Node The values ​​of the dual variables associated with the upper and lower voltage bounds, and for Time Node The voltage measurement value and the offset value of the voltage upper and lower limits, is the change step size, is the regularization parameter of the edge computing controller, and the regularization parameter of the edge computing controller is formulated based on experience.

[0120] According to the offset value of the upper and lower limits of the active power control range at the feeder head end and , combined with The value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at any given moment and , dual variable change step and the regularization parameter , calculated by the cluster edge computing controller The updated value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at each moment and , the specific calculation method is:

[0121]

[0122]

[0123] in, For the current moment, Indicates the previous moment, , for Time Node The values ​​of the dual variables associated with the upper and lower voltage bounds, and for Time Node The voltage measurement value and the offset value of the voltage upper and lower limits, is the change step size, is the regularization parameter of the edge computing controller, and the regularization parameter of the edge computing controller is formulated based on experience.

[0124] In one embodiment, the photovoltaic output control method further includes:

[0125] The edge computing controller and the photovoltaic on-site controller are initialized to obtain the voltage variable step adaptive module coefficient, the active weight adaptive adjustment model parameters and the reactive weight adaptive adjustment model parameters.

[0126] In this embodiment, the initialization processing content of the distributed photovoltaic local controller includes inputting the regularization parameter , voltage variable step adaptive model coefficient , active weights adaptively adjust model parameters and , reactive weight adaptively adjusts model parameters and .

[0127] After the distributed photovoltaic local controller in S304 obtains the actual photovoltaic reactive power measurement value and the actual photovoltaic active power measurement value at the current moment, Figure 5 As shown, the photovoltaic output control method also includes:

[0128] S501, calculating a voltage adaptive adjustment coefficient according to a voltage balance offset value and a voltage variable step size adaptive model coefficient.

[0129] S502, calculating an active weight adaptive adjustment coefficient according to active weight adaptive adjustment model parameters, actual photovoltaic reactive power measurement values, and distributed photovoltaic maximum reactive power output parameters.

[0130] S503, calculating a reactive weight adaptive adjustment coefficient according to reactive weight adaptive adjustment model parameters, actual photovoltaic reactive power measurement values, and distributed photovoltaic maximum reactive output parameters.

[0131] In this embodiment, specifically, the voltage adaptive adjustment coefficient The calculation formula includes:

[0132]

[0133] Active power weight adaptive adjustment coefficient The calculation formula includes:

[0134]

[0135] Reactive weight adaptive coefficient The calculation formula includes:

[0136]

[0137] in, is the voltage variable step adaptive model coefficient, and Adaptive adjustment of model parameters for active weights, and Adaptive adjustment of model parameters for reactive weights, Number the nodes The maximum reactive power that distributed photovoltaic can provide, is the voltage balance offset value, It is the actual photovoltaic reactive power measurement value at the current moment.

[0138] In one embodiment, Figure 6 As shown, according to the current photovoltaic actual reactive power measurement value, photovoltaic actual active power measurement value, various dual variable update values ​​and linearized sensitivity parameter matrix, the offset analysis of photovoltaic actual active power and photovoltaic actual reactive power is performed to obtain the target active power offset and target reactive power offset, including:

[0139] S601, calculating a first part of the offset according to the actual photovoltaic reactive power measurement value, the actual photovoltaic active power measurement value and the photovoltaic local controller regularization parameter;

[0140] In this embodiment, the first part of the offset is the offset of the objective function gradient descent part and the regularization part. The specific calculation method of the first part of the offset is:

[0141]

[0142]

[0143]

[0144]

[0145] In the formula, Indicates the distributed photovoltaic number, and , is the set of node numbers where distributed photovoltaics are located. Indicates the current moment, for The operating cost of each distributed photovoltaic in the distributed photovoltaic cluster at the moment, among which, ; is the regularization part, where ; For the current moment At the node The maximum active power output that distributed photovoltaics can provide, and For Time Node The measured values ​​of actual active power and actual reactive power of distributed photovoltaics, is the regularization parameter of the photovoltaic local controller.

[0146] S602, calculate the second part of the offset based on the linearized sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node, the voltage adaptive adjustment coefficient, the active weight adaptive adjustment coefficient, the reactive weight adaptive adjustment coefficient, and the dual variable update value related to the upper and lower bounds of the voltage at the current moment.

[0147] In this embodiment, the second partial offset is a voltage-constrained partial offset.

[0148] The voltage constraint part offset includes the offset and , and its calculation formula is:

[0149]

[0150]

[0151] in, represents the number of the voltage control node, and , is the set of voltage control node numbers, Indicates the injection node The active power of the node The voltage sensitivity, Indicates the injection node The reactive power of the node The voltage sensitivity, and for Time Node The updated values ​​of the dual variables related to the upper and lower bounds of the voltage, is the active weight adaptive adjustment coefficient, It is the adaptive adjustment coefficient of reactive power weight.

[0152] S603, calculates the third part of the offset based on the linearized sensitivity parameter matrix of the active power at the head end of the feeder with respect to the active power and reactive power injected into each node, the active weight adaptive adjustment coefficient, the reactive weight adaptive adjustment coefficient, and the dual variable update value related to the upper and lower bounds of the active power at the head end of the feeder at the current moment.

[0153] In this embodiment, the third part of the offset is the feeder head end active power constraint part offset, the feeder head end active power constraint part offset includes and , the specific calculation formula is:

[0154]

[0155]

[0156] in, Indicates the injection node The sensitivity of the active power to the active power at the feeder head end is Indicates the injection node The sensitivity of the reactive power to the active power at the feeder head end is and for The updated value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at each moment, is the active weight adaptive adjustment coefficient, It is the adaptive adjustment coefficient of reactive power weight.

[0157] S604: Calculate a target active power offset and a target reactive power offset according to the first offset, the second offset, and the third offset.

[0158] In this embodiment, the offsets of each part calculated by S601-S603 are added together to obtain the target active power offset and the target reactive power offset. and .

[0159] Specifically, and The calculation formula is:

[0160]

[0161]

[0162] in, Indicates the injection node The active power of the node The voltage sensitivity, Indicates the injection node The reactive power of the node The voltage sensitivity, and for Time Node The updated values ​​of the dual variables related to the upper and lower bounds of the voltage, and for The updated value of the dual variable related to the upper and lower bounds of the active power at the feeder head end at each moment, is the active weight adaptive adjustment coefficient, is the reactive weight adaptive adjustment coefficient, is the regularization parameter of the photovoltaic local controller.

[0163] This embodiment can make the constraints in the dual update mechanism clearer by comprehensively considering the offset of the gradient descent part and the regularization part of the objective function, the voltage constraint part and the active power constraint part at the head end of the feeder, so as to facilitate the correct modeling of the calculation model of the photovoltaic on-site controller. The dual update mechanism can be used to effectively solve practical problems, improve the response speed of voltage regulation, ensure that the power transmission at the head end of the feeder is within the allowable range, and achieve higher control accuracy.

[0164] In one embodiment, Figure 7 As shown, the photovoltaic output control method also includes:

[0165] After the S306 distributed photovoltaic on-site controller controls the distributed photovoltaic output for a preset time according to the target active power setting value and the target reactive power setting value, it jumps to execute the step of S303 where the edge computing controller collects the current voltage measurement value of each voltage control node, the current active power measurement value of the feeder head end, and the values ​​of each dual variable at the previous moment.

[0166] In this embodiment, the distributed photovoltaic cluster system of the distribution network is in the startup state, and the steps S303-S306 are repeatedly executed at preset intervals to perform voltage-power coordinated control on each distributed photovoltaic in the distributed photovoltaic cluster of the distribution network, so as to ensure that the distributed photovoltaic cluster of the distribution network can operate efficiently and stably.

[0167] In one embodiment, the distributed photovoltaic output setting value includes the distributed photovoltaic active power output setting value and reactive power output setting value at the previous moment;

[0168] Controlling the distributed photovoltaic local controller to adjust the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain the target active power setting value and the target reactive power setting value, including:

[0169] The target active power setting value is calculated according to the target active power offset and the active power output setting value of the distributed photovoltaic at the previous moment;

[0170] The target reactive power setting value is calculated according to the target reactive power offset and the reactive power output setting value of the distributed photovoltaic at the previous moment.

[0171] In this embodiment, the target active power setting value and target reactive power setting value , the specific calculation method is:

[0172]

[0173]

[0174] in, For the current moment At the node The target active power offset of distributed photovoltaics, For the current moment At the node The target reactive power offset of distributed photovoltaics, for Always at the node The active power output setting value of distributed photovoltaics, for Always at the node The reactive power output setting value of distributed photovoltaics.

[0175] In a more detailed embodiment, in order to fully verify the advancedness of the photovoltaic output control method provided by this embodiment, as shown in FIG. Figure 1 As shown in the figure, the IEEE 33 standard distribution network is adopted. The distribution network includes 33 nodes, and the topological connection is as follows Figure 2 As shown, 23 groups of PV systems are connected to nodes 4, 5, 7, 8, 9, 11, 12, 13, 15, 16, 17, 18, 20, 21, 22, 24, 25, 27, 28, 29, 31, 32 and 33 respectively, and their capacities are 200kWp, 200kWp, 200kWp, 200kWp, 200kWp, 350kWp, 300kWp, 350kWp, 300kWp, 300kWp, 250kWp, 300kWp, 300kWp, 250kWp, 350kWp, 350kWp, 300kWp, 300kWp, 300kWp, 350kWp, 200kWp, 200kWp and 250kWp respectively.

[0176] The 10 voltage measurement points are nodes 2, 3, 6, 10, 14, 18, 22, 25, 30 and 33.

[0177] The source-charge fluctuation curve is as follows Figure 8 As shown. The system voltage is 12.66kV and the reference power is 1MV. The voltage reference value of the distribution network is set to 1.0pu. , regularization coefficient , , voltage variable step adaptive model coefficient , active weights adaptively adjust model parameters and , reactive weight adaptively adjusts model parameters and .

[0178] To verify the effectiveness of this method, the following two control scenarios are used for comparison based on the above distribution network topology interface:

[0179] Solution 1: Do not control the output of distributed photovoltaics.

[0180] Solution 2: Use the photovoltaic output control method proposed in this embodiment for control.

[0181] Fig. 9 The power changes at the head end of the feeder under different control schemes are shown. It can be seen that the power reverse transmission at the head end of the feeder greatly exceeds the limit under the control of scheme 1, while the power reverse transmission at the head end of the feeder is limited to the allowable range under the control of scheme 2.

[0182] Fig.10 The voltage conditions of the voltage control nodes under different control schemes.

[0183] Combination Fig.10 It can be seen that with the changes in the photovoltaic curve and the load curve, the voltage at the voltage control node in Scheme 1 will obviously exceed the limit, while Scheme 2 can limit the voltage near the voltage reference value. It can be seen that Scheme 2 does have significant advantages in maintaining the stability of the voltage level of the distribution system, and provides a strong guarantee for the safe and reliable operation of the power system.

[0184] Fig.11 This is the active power output of distributed photovoltaic nodes 8, 11, and 16 under the control of Scheme 2.

[0185] Fig.12 This is the reactive power output of distributed photovoltaic nodes 8, 11, and 16 under the control of Scheme 2.

[0186] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0187] Based on the same inventive concept, the embodiment of the present application also provides a photovoltaic output control device for implementing the photovoltaic output control method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more photovoltaic output control device embodiments provided below can refer to the limitations of the photovoltaic output control method above, and will not be repeated here.

[0188] In one embodiment, Fig.13 As shown, a photovoltaic output control device 1300 is provided, including: an acquisition module 1310, an analysis module 1320, an adjustment module 1330 and a control module 1340, wherein:

[0189] The acquisition module 1310 is used to obtain the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, various dual variable update values ​​and the linearization sensitivity parameter matrix; wherein the various dual variable update values ​​and the linearization sensitivity parameter matrix are calculated and sent by the edge computing controller;

[0190] The analysis module 1320 is used to perform an offset analysis of the photovoltaic actual active power and the photovoltaic actual reactive power according to the photovoltaic actual reactive power measurement value at the current moment, the photovoltaic actual active power measurement value at the current moment, the dual variable update values ​​and the linearized sensitivity parameter matrix, so as to obtain a target active power offset and a target reactive power offset;

[0191] An adjustment module 1330 is used to adjust the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain a target active power setting value and a target reactive power setting value;

[0192] The control module 1340 is used to control the distributed photovoltaic output according to the target active power setting value and the target reactive power setting value.

[0193] Each module in the photovoltaic output control device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0194] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.14As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a photovoltaic output control method is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0195] Those skilled in the art will understand that Fig.14 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0196] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the photovoltaic output control method in the aforementioned method embodiment are implemented.

[0197] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the photovoltaic output control method in the aforementioned method embodiment are implemented.

[0198] In one embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps of the photovoltaic output control method in the aforementioned method embodiment.

[0199] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0200] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0201] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A photovoltaic output control method, characterized in that: A photovoltaic local controller applied to a distributed photovoltaic cluster system of a distribution network, wherein the distributed photovoltaic cluster system of the distribution network comprises an edge computing controller and at least one photovoltaic local controller, wherein the photovoltaic local controller is connected to the edge computing controller, and the method comprises: Obtaining the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, various dual variable update values ​​and the linearization sensitivity parameter matrix; wherein the various dual variable update values ​​and the linearization sensitivity parameter matrix are calculated and sent by the edge computing controller; According to the current photovoltaic actual reactive power measurement value, the current photovoltaic actual active power measurement value, the dual variable update value and the linearized sensitivity parameter matrix, the photovoltaic actual active power and the photovoltaic actual reactive power offset analysis are performed to obtain the target active power offset and the target reactive power offset; Adjusting the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain a target active power setting value and a target reactive power setting value; The distributed photovoltaic output is controlled according to the target active power setting value and the target reactive power setting value.

2. The method according to claim 1, characterized in that The calculation step of the linearized sensitivity parameter matrix includes: The edge computing controller performs initialization processing to obtain the distribution network topology connection relationship, line parameters, voltage control range parameters, feeder head end active power control range parameters and initial values ​​of various dual variables; The edge computing controller calculates the linearized sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node, and the linearized sensitivity parameter matrix of the active power at the head end of the feeder with respect to the active power and reactive power injected into each node according to the topological connection relationship of the distribution network and the line parameters; The linearized sensitivity parameter matrix is ​​transmitted to the photovoltaic local controller.

3. The method according to claim 2, characterized in that The steps of calculating the updated values ​​of the dual variables include: The edge computing controller collects the current voltage measurement value of each voltage control node, the current active power measurement value of the feeder head end, and the values ​​of various dual variables at the previous moment, and calculates the upper and lower limit offset values ​​of the voltage control range, the voltage balance offset value, the upper and lower limit offset values ​​of the active power control range of the feeder head end, and the updated values ​​of various dual variables according to the current voltage measurement value, the current active power measurement value of the feeder head end, the voltage control range parameter, the active power control range parameter of the feeder head end, and the values ​​of various dual variables at the previous moment; wherein, if the current moment is the first collection moment, the values ​​of various dual variables at the previous moment are the corresponding initial values ​​of various dual variables.

4. The method according to claim 3, characterized in that The voltage control range upper and lower limit offset values, voltage balance offset value, feeder head end active power control range upper and lower limit offset values, and various dual variable update values ​​are calculated based on the voltage measurement value at the current moment, the active power measurement value at the feeder head end at the current moment, the voltage control range parameter, the active power control range parameter at the feeder head end, and various dual variable values ​​at the previous moment, respectively, including: Calculate the upper and lower limit offset values ​​of the voltage control range and the voltage balance offset value according to the upper and lower limit values ​​of the voltage control range parameter and the voltage measurement value at the current moment; According to the upper and lower limit values ​​of the active power control range parameter of the feeder head end and the current measured active power value of the feeder head end, the upper and lower limit offset values ​​of the active power control range of the feeder head end are calculated; According to the dual variable values ​​related to the upper and lower bounds of the voltage at the previous moment, the dual variable values ​​related to the upper and lower bounds of the active power at the head end of the feeder at the previous moment, the dual variable change step size, and the regularization parameter of the edge computing controller, the dual variable update values ​​related to the upper and lower bounds of the voltage at the current moment and the dual variable update values ​​related to the upper and lower bounds of the active power at the head end of the feeder at the current moment are calculated respectively.

5. The method according to claim 3, characterized in that: The method further comprises: Initializing the photovoltaic local controller to obtain voltage variable step adaptive module coefficients, active weight adaptive adjustment model parameters, and reactive weight adaptive adjustment model parameters; After the distributed photovoltaic local controller obtains the actual photovoltaic reactive power measurement value and the actual photovoltaic active power measurement value at the current moment, the method further includes: The voltage adaptive adjustment coefficient is calculated according to the voltage balance offset value and the voltage variable step adaptive model coefficient; The active weight adaptive adjustment coefficient is calculated based on the active weight adaptive adjustment model parameters, the actual photovoltaic reactive power measurement value, and the distributed photovoltaic maximum reactive power output parameters; The reactive weight adaptive adjustment coefficient is calculated according to the reactive weight adaptive adjustment model parameters, the actual reactive power measurement value of photovoltaics, and the maximum reactive power output parameters of distributed photovoltaics.

6. The method according to claim 5, characterized in that The method of performing an offset analysis of the actual photovoltaic active power and the actual photovoltaic reactive power according to the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, the dual variable update values ​​and the linearized sensitivity parameter matrix to obtain a target active power offset and a target reactive power offset includes: The first part of the offset is calculated based on the actual photovoltaic reactive power measurement value, the actual photovoltaic active power measurement value and the photovoltaic local controller regularization parameter; The second part of the offset is calculated according to the linearized sensitivity parameter matrix of each node voltage with respect to the active power and reactive power injected into each node, the voltage adaptive adjustment coefficient, the active weight adaptive adjustment coefficient, the reactive weight adaptive adjustment coefficient, and the dual variable update value related to the upper and lower bounds of the voltage at the current moment; The third part offset is calculated according to the linearized sensitivity parameter matrix of the active power at the head end of the feeder with respect to the active power and reactive power injected into each node, the active weight adaptive adjustment coefficient, the reactive weight adaptive adjustment coefficient, and the dual variable update value related to the upper and lower bounds of the active power at the head end of the feeder at the current moment; The target active power offset and the target reactive power offset are calculated according to the first offset, the second offset and the third offset.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: After controlling the preset time of distributed photovoltaic output according to the target active power setting value and the target reactive power setting value, jump to execute the step of obtaining the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, the updated values ​​of each dual variable and the linearized sensitivity parameter matrix.

8. The method according to claim 1, characterized in that The distributed photovoltaic output setting value includes the distributed photovoltaic active power output setting value and reactive power output setting value at the previous moment; The step of adjusting the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain the target active power setting value and the target reactive power setting value includes: Calculate the target active power setting value according to the target active power offset and the active power output setting value of the distributed photovoltaic at the previous moment; The target reactive power setting value is calculated based on the target reactive power offset and the reactive power output setting value of the distributed photovoltaic system at the previous moment.

9. A photovoltaic output control device, characterized in that: A photovoltaic local controller applied to a distributed photovoltaic cluster system of a distribution network, wherein the distributed photovoltaic cluster system of the distribution network comprises an edge computing controller and at least one photovoltaic local controller, wherein the photovoltaic local controller is connected to the edge computing controller, and the device comprises: An acquisition module is used to acquire the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, various dual variable update values ​​and the linearization sensitivity parameter matrix; wherein the various dual variable update values ​​and the linearization sensitivity parameter matrix are calculated and sent by the edge computing controller; An analysis module is used to perform an offset analysis of the actual photovoltaic active power and the actual photovoltaic reactive power according to the actual photovoltaic reactive power measurement value at the current moment, the actual photovoltaic active power measurement value at the current moment, the updated values ​​of each dual variable and the linearized sensitivity parameter matrix, so as to obtain a target active power offset and a target reactive power offset; An adjustment module, used to adjust the distributed photovoltaic output setting value according to the target active power offset and the target reactive power offset to obtain a target active power setting value and a target reactive power setting value; A control module is used to control the distributed photovoltaic output according to the target active power setting value and the target reactive power setting value.

10. A distributed photovoltaic cluster system for a distribution network, characterized in that: It includes an edge computing controller and at least one photovoltaic on-site controller, wherein the photovoltaic on-site controller is connected to the edge computing controller; The edge computing controller is connected to the voltage control node, the photovoltaic on-site controller is connected to the distributed photovoltaic, and the edge computing controller and the photovoltaic on-site controller are used to execute the steps of the photovoltaic output control method described in any one of claims 1-8.

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