Reactive power control method for new energy power station
By obtaining the historical data of the new energy power generation station, the coupling relationship between active power and reactive loss is confirmed, and the target reactive loss is predicted by clustering algorithm for compensation control, the voltage fluctuation caused by the change in active power is solved and the stable operation of the station is ensured.
Patent Information
- Application Number
- CN202510585336.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-07
- Publication Date
- 2025-08-08
AI Technical Summary
In new energy power generation stations, changes in active power lead to changes in reactive power loss, causing large fluctuations in the voltage of the network connection point, affecting the safe and stable operation of the station.
By obtaining historical active power data, network connection voltage data and reactive power data, the coupling relationship between active power and reactive loss is confirmed, the data is analyzed using clustering algorithm, the target reactive loss is predicted, and compensation control is performed to stabilize the voltage.
It effectively prevents large fluctuations in the voltage of the connecting point of the new energy power station due to changes in active power, and achieves safe and stable operation of the station.
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Figure CN120454218A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of new energy control technology, and in particular to a method for controlling reactive power of a new energy power generation station. Background Art
[0002] At renewable energy power generation stations, active power and reactive power are controlled separately. Active power is controlled by the Automatic Generation Control (AGC) substation, while reactive power is controlled by the Automatic Voltage Control (AVC) substation. There is no connection between the two systems.
[0003] However, within renewable energy power plants, active power and reactive power are coupled, meaning that changes in active power can cause changes in reactive power loss. At renewable energy power plants connected to weak grids, large fluctuations in active power can cause significant changes in reactive power loss, leading to significant voltage fluctuations at the plant's grid connection point, impacting the plant's safe and stable operation. Summary of the Invention
[0004] The present application provides a reactive power control method for a new energy power generation station, in order to at least solve the problem in the related art that the voltage at the grid connection point of a new energy power generation station fluctuates greatly, affecting the safe and stable operation of the new energy station.
[0005] The present application provides a method for controlling reactive power of a new energy power station, the method comprising:
[0006] Acquiring historical active power data, as well as grid connection point voltage data and reactive power data corresponding to the active power data;
[0007] confirming a coupling relationship between the active power data and the reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data;
[0008] Target reactive power loss data corresponding to the active power data to be predicted is confirmed based on the coupling relationship, and compensation control is performed on the reactive power in the station based on the target reactive power loss data.
[0009] The present invention proposes a reactive power control method for a new energy power station. This method obtains historical active power data, as well as grid connection point voltage and reactive power data corresponding to the active power data. Based on the grid connection point voltage data, the active power data, and the reactive power data, the method determines the coupling relationship between the active power data and reactive loss data. Finally, based on the coupling relationship, the method determines the target reactive loss data corresponding to the predicted active power data, and performs compensation control for the reactive power within the station based on the target reactive loss data. This method thereby compensates for reactive losses caused by active power, preventing significant fluctuations in the grid connection point voltage of the new energy power station due to changes in active power, and ensuring safe and stable operation of the new energy station.
[0010] In some feasible implementations, the step of confirming the coupling relationship between the active power data and the reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data includes:
[0011] Obtaining reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data;
[0012] Clustering the active power data and the reactive loss data based on a preset clustering algorithm to obtain a clustering result; wherein the clustering result includes a plurality of cluster groups;
[0013] The clustering result is used as the coupling relationship between the active power data and the reactive power loss data.
[0014] In some feasible implementations, the active power data includes: active power value, and the reactive power data includes: reactive power value;
[0015] After the step of obtaining historical active power data, and grid connection point voltage data and reactive power data corresponding to the active power data, the method further includes:
[0016] Calculating an active power change per unit time based on the active power value;
[0017] The reactive power loss per unit time is calculated based on the reactive power value, the active power value and the grid connection point voltage data.
[0018] In some feasible implementations, the step of clustering the active power data and the reactive loss data based on a preset clustering algorithm includes:
[0019] Clustering is performed on the active power change and the reactive power loss based on a preset clustering algorithm.
[0020] In some feasible implementations, the step of determining target reactive power loss data corresponding to the active power data to be predicted based on the coupling relationship, and performing compensation control on the reactive power in the station based on the target reactive power loss data includes:
[0021] confirming the clustering grouping of the active power data to be predicted in the clustering result;
[0022] The target reactive power loss corresponding to the active power data to be predicted is confirmed in the cluster grouping, and the target reactive power loss rate is obtained based on the target reactive power loss, and compensation control is performed on the reactive power in the station based on the target reactive power loss and the target reactive power loss rate.
[0023] In some feasible implementations, after the step of calculating the reactive power loss per unit time based on the reactive power value, the active power value, and the grid connection point voltage data, the method further includes:
[0024] confirming the relationship between the direction of the active power change and the direction of the reactive power loss;
[0025] The data in which the active power change amount and the reactive power loss amount are in opposite directions are filtered out.
[0026] In some feasible implementations, after the step of obtaining historical active power data, and grid connection point voltage data and reactive power data corresponding to the active power data, the method further includes:
[0027] The reactive power data is filtered out if it is greater than a first preset reactive power threshold, and the reactive power data is filtered out if it is less than a second preset reactive power threshold, and / or data in abnormal operation is filtered out.
[0028] The present application also provides a reactive power control device for a new energy power generation station, comprising:
[0029] An acquisition module is used to acquire historical active power data, as well as grid connection point voltage data and reactive power data corresponding to the active power data;
[0030] a confirmation module, configured to confirm a coupling relationship between the active power data and the reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data;
[0031] The compensation module is used to confirm the reactive loss data corresponding to the active power data to be predicted based on the coupling relationship, and to perform compensation control on the reactive power in the station based on the reactive loss data.
[0032] The present application also provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of any of the above-mentioned reactive power control methods for a new energy power station when executing the computer program.
[0033] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned reactive power control methods for new energy power plants are implemented.
[0034] The present application also provides a computer program product, including a computer program, which implements the steps of any of the above-mentioned reactive power control methods for new energy power plants when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] In order to more clearly illustrate the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0036] Figure 1 1 is a flow chart of a reactive power control method for a new energy power generation station according to an embodiment of the present invention;
[0037] Figure 2 is a flow chart of another reactive power control method for a new energy power station according to an embodiment of the present invention;
[0038] Figure 3 Schematic diagram of the application of the reactive power control method for a new energy power station according to an embodiment of the present invention;
[0039] Figure 4 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION
[0040] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.
[0041] It should be noted that, in the description of this application, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. The terms "first," "second," etc., in this application are used to distinguish similar objects, and are not used to describe a particular order or sequence.
[0042] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.
[0043] At renewable energy power generation stations, active power and reactive power are controlled separately. Active power is controlled by the Automatic Generation Control (AGC) substation, while reactive power is controlled by the Automatic Voltage Control (AVC) substation. There is no connection between the two systems.
[0044] However, within renewable energy power plants, active power and reactive power are coupled, meaning that changes in active power can cause changes in reactive power loss. At renewable energy power plants connected to weak grids, large fluctuations in active power can cause significant changes in reactive power loss, leading to significant voltage fluctuations at the plant's grid connection point, impacting the plant's safe and stable operation.
[0045] In this regard, the embodiment of the present application provides a method for controlling reactive power of a new energy power station, such as Figure 1 As shown, the method is described in detail in combination with the execution process of the reactive power control method of the new energy power station.
[0046] The reactive power control method of the new energy power station includes:
[0047] Step S10: Acquire historical active power data, as well as grid connection point voltage data and reactive power data corresponding to the active power data;
[0048] Specifically, the active power data and reactive power data actually controlled by the new energy station, as well as the actually collected grid connection point voltage data, are extracted from the historical database. It is worth noting that the grid connection point voltage data and reactive power data corresponding to the active power data refer to the reactive power data and grid connection point voltage data for the same time period as the active power data.
[0049] Step S20: confirming a coupling relationship between the active power data and the reactive power loss data based on the grid connection point voltage data, the active power data, and the reactive power data;
[0050] Specifically, actual reactive power loss data is first obtained based on the grid connection point voltage data, the active power data, and the reactive power data, and then a coupling relationship between the active power data and the reactive power loss data is further confirmed. Because changes in active power will cause changes in reactive power loss, a coupling relationship between the active power data and the reactive power loss data is further obtained based on historical active power data and reactive power loss data. The coupling relationship refers to the relationship between the active power data and the changes in reactive power loss data caused by the changes in the active power data. Optionally, the coupling relationship can be specifically a relationship table, which includes changes in active power data and corresponding changes in reactive power loss data.
[0051] Step S30: confirming target reactive power loss data corresponding to the active power data to be predicted based on the coupling relationship, and performing compensation control on the reactive power in the station based on the target reactive power loss data.
[0052] Specifically, after obtaining the active power data to be predicted, the active power data to be predicted is confirmed in the coupling relationship, and the target reactive loss data corresponding to the active power data to be predicted is confirmed. The target reactive loss data may specifically include the target reactive loss data amount and the target reactive loss change rate. The reactive power data to be controlled is obtained, and the target reactive loss amount is superimposed on the reactive power data to be controlled according to the target reactive loss change rate, thereby preventing the voltage at the grid connection point of the new energy power generation station from fluctuating greatly due to changes in active power, and realizing the safe and stable operation of the new energy station. It is worth noting that the active power data to be predicted can be obtained in a preset manner.
[0053] The present invention proposes a reactive power control method for a new energy power station. This method obtains historical active power data, as well as grid connection point voltage and reactive power data corresponding to the active power data. Based on the grid connection point voltage data, the active power data, and the reactive power data, the method determines the coupling relationship between the active power data and reactive loss data. Finally, based on the coupling relationship, the method determines the target reactive loss data corresponding to the predicted active power data, and performs compensation control for the reactive power within the station based on the target reactive loss data. This method thereby compensates for reactive losses caused by active power, preventing significant fluctuations in the grid connection point voltage of the new energy power station due to changes in active power, and ensuring safe and stable operation of the new energy station.
[0054] In some feasible implementations, step S20 includes:
[0055] Step 1: Obtaining reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data;
[0056] Specifically, the grid connection point voltage data is actual grid connection point voltage data. Predicted grid connection point voltage data can be calculated based on the active power data and the reactive power data. The difference between the actual grid connection point voltage data and the predicted grid connection point voltage data is then calculated. Actual reactive power loss data is then obtained based on the difference and the reactive power data. The reactive power loss data includes reactive power loss information. Optionally, the reactive power loss data includes reactive power loss amount and reactive power loss rate.
[0057] For example, the active power data and reactive power data are taken as a set G i .
[0058] Step 2: clustering the active power data and the reactive loss data based on a preset clustering algorithm, and obtaining a clustering result; wherein the clustering result includes a plurality of cluster groups;
[0059] Optionally, the preset clustering algorithm can be a K-means clustering algorithm (partition-based unsupervised learning algorithm), which specifically divides the active power data and reactive loss data into K clusters through iterative optimization, so that the similarity of samples in the same cluster is maximized and the difference between different clusters is maximized.
[0060] Specifically, based on the K-means clustering algorithm, the set G i Clustering is performed. The clustering formula is:
[0061]
[0062] Where k is the number of clusters, C i is the i-th cluster, s is the sample point of the i-th cluster, X i is the center of cluster i. s and X i Set the preset value in advance. K-means clustering algorithm is used for iterative calculation. Figure 3 , according to the clustering formula, the simulation curve is obtained. The curve is a line graph in the shape of an elbow. The k value corresponding to the "elbow" is the number of cluster groups obtained.
[0063] It is worth noting that, since the relationship between the active power data and the reactive loss data is not linear, the potential relationship between the active power data and the reactive loss data is obtained through a clustering algorithm.
[0064] Step 3: Using the clustering result as the coupling relationship between the active power data and the reactive loss data.
[0065] Specifically, the clustering result may be a simulation curve of cluster grouping, or a cluster grouping table, in which there are multiple cluster grouping numbers, and each cluster grouping number contains corresponding active power data and reactive power loss data.
[0066] In some feasible implementations, the active power data includes: active power value, and the reactive power data includes: reactive power value, such as Figure 2 As shown, after step S10, the following steps are included:
[0067] Step S40: Calculating the active power variation per unit time based on the active power value;
[0068] Specifically, after obtaining the historical active power value, the active power change within a preset unit time is calculated.
[0069] Step S50: Calculating the reactive power loss per unit time based on the reactive power value, the active power value and the grid connection point voltage data.
[0070] Specifically, the predicted grid connection point voltage data is first calculated based on the active power data and the reactive power data, and then the difference between the actual grid connection point voltage data and the predicted grid connection point voltage data is calculated, and the actual reactive loss that needs to be compensated is obtained based on the difference and the reactive power data.
[0071] In some feasible implementations, step 2 includes:
[0072] Step (1): clustering the active power change and the reactive power loss based on a preset clustering algorithm.
[0073] Specifically, the clustering result includes multiple cluster groups, specifically the first cluster group, the second cluster group, the third cluster group, and so on. The active power change and the reactive power loss are taken as a set G i , that is, G i ={ΔP i , ΔQ i}, where ΔP i Indicates the change in active power, ΔQ i Indicates the amount of reactive power loss.
[0074] Specifically, G i ={ΔP i , ΔQ i}Specifically, it can be G1, G2...G n , through clustering algorithm for G1, G2......G n For example, the first cluster group includes G3, G6, G 10 The first cluster group includes G2, G8, G17 The third cluster group includes G1, G7, G 11 , G 14 , G9. Thus, the n data in the set are clustered. It is worth noting that the number of data included in each cluster group can be inconsistent.
[0075] Specifically, the actual value range can be inferred based on the cluster grouping. For example, the range of active power change of the first cluster grouping is 10-12MW, and the corresponding reactive power loss is 5.1-5.4Mvar. The range of active power change of the second cluster grouping is 13-18MW, and the corresponding reactive power loss is 5.8-6.0Mvar.
[0076] In some feasible implementations, step S30 includes:
[0077] Step (1): confirming the clustering grouping of the active power data to be predicted in the clustering result;
[0078] Specifically, in the multiple clustering groups of the clustering results, the active power data to be predicted is confirmed. It should be noted that if the set G i If the active power data to be predicted is not included in the data, the active power change rate close to the active power data to be predicted is determined.
[0079] For example, G i Including G1 = {ΔP1, ΔQ1}, G2 = {ΔP2, ΔQ2}, G3 = {ΔP3, ΔQ3}, etc. In combination with the above embodiment, if the active power data to be predicted is ΔP1, first confirm the data G1 corresponding to ΔP1, and then confirm that the cluster grouping of G1 is the third cluster grouping.
[0080] Step (2): Confirm the target reactive power loss corresponding to the active power data to be predicted in the cluster grouping, obtain the target reactive power loss rate based on the target reactive power loss, and perform compensation control on the reactive power in the station based on the target reactive power loss and the target reactive power loss rate.
[0081] Specifically, obtain the active power data to be predicted in the next preset time period, confirm that ΔG1 in G1={ΔP1, ΔQ1} is the target reactive power loss ΔQ i , and calculate the target reactive power loss rate based on the target reactive power loss amount and the preset time period Finally, the reactive power is compensated at the target reactive power loss rate. To target reactive power loss ΔQ i .
[0082] For example, if the active power for the next time period increases by 50 MW and the active power change rate is 10 MW / s, the corresponding clustered reactive power loss change rate is -12 MVar / s, and the reactive power loss is -60 Mvar. Therefore, AVC needs to compensate for the reactive power at a rate of 12 MVar / s until it has compensated 60 MVar.
[0083] In some feasible implementations, after step S50, the reactive power control method for a new energy power station further includes:
[0084] Step (1): confirming the relationship between the direction of the active power change and the direction of the reactive power loss;
[0085] Specifically, confirm whether the direction of the active power change and the direction of the reactive power loss are consistent. The active power change includes positive and negative. When the active power change is positive, it indicates that the active power increases. When the active power change is negative, it indicates that the active power decreases. The reactive power loss includes positive and negative. When the reactive power loss is positive, it indicates that the reactive power loss increases. When the reactive power loss is negative, it indicates that the reactive power loss decreases.
[0086] Specifically, the system determines whether the sign of the active power change is consistent with the sign of the reactive power loss. An increase in active power will increase reactive power loss, resulting in a decrease in reactive power at the grid connection point. A decrease in active power will decrease reactive power loss, resulting in an increase in reactive power at the grid connection point. Therefore, it is important to check in advance whether the direction of the active power change and the direction of the reactive power loss are consistent.
[0087] Step (2): Filter out data with opposite directions of the active power change and the reactive power loss.
[0088] Specifically, data in which the active power change amount and the reactive power loss amount are in opposite directions are filtered out, thereby filtering out inaccurate data and improving the stability of compensating for reactive power loss.
[0089] In some feasible implementations, after step S10, the reactive power control method for a new energy power station further includes:
[0090] Step (1): Filter out the reactive power data that is greater than a first preset reactive power threshold, and filter out the reactive power data that is less than a second preset reactive power threshold, and / or filter out data during abnormal operation.
[0091] Specifically, historical data is verified for accuracy. For example, the first preset reactive power threshold is the rated upper reactive power limit of the SVG (Static Var Generator), and the second preset reactive power threshold is the rated lower reactive power limit of the SVG. Operational anomalies include abnormal SVG operation and abnormal communication between the SVG and the automatic voltage control (AVC). In other words, the system also verifies the normal operation of the reactive control device and filters out data indicating abnormal operation. Furthermore, the system also checks the normal communication between the SVG and the AVC (Automatic Voltage Control), filtering out data indicating abnormal communication with the AVC. This prevents abnormal data from affecting subsequent steps and reducing the accuracy of reactive loss compensation.
[0092] For example, even if communication between a reactive device like the SVG and the AVC is interrupted, the AVC still records the SVG's actual reactive power before the interruption in its historical database. This can lead to distorted reactive power data during the period of SVG communication interruption. Additionally, problems with the measurement and control equipment or the communication link can cause anomalies in the active power, reactive power, and voltage data collected by the AVC. For example, the collected voltage at the 220kV busbar connection point may show a significantly incorrect value (300kV).
[0093] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method.
[0094] In this embodiment, a reactive power control device for a new energy power generation station is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the details that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
[0095] This embodiment provides a reactive power control device for a new energy power generation station, such as Figure 4 As shown, including:
[0096] The acquisition module 501 is used to acquire historical active power data, and grid connection point voltage data and reactive power data corresponding to the active power data.
[0097] The confirmation module 502 is configured to confirm a coupling relationship between the active power data and the reactive power loss data based on the grid connection point voltage data, the active power data, and the reactive power data.
[0098] The compensation module 503 is configured to confirm reactive power loss data corresponding to the active power data to be predicted based on the coupling relationship, and perform compensation control on the reactive power in the station based on the reactive power loss data.
[0099] In some optional implementations, the confirmation module 502 includes:
[0100] The first confirmation unit is configured to obtain reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data.
[0101] A clustering unit is used to cluster the active power data and the reactive loss data based on a preset clustering algorithm and obtain a clustering result; wherein the clustering result includes a plurality of cluster groups.
[0102] The second confirmation unit is configured to use the clustering result as a coupling relationship between the active power data and the reactive loss data.
[0103] In some optional implementations, the acquisition module 501 includes:
[0104] The first calculation unit is configured to calculate an active power variation within a unit time based on the active power value.
[0105] The second calculation unit is used to calculate the reactive power loss per unit time based on the reactive power value, the active power value and the grid connection point voltage data.
[0106] In some optional embodiments, the clustering unit includes:
[0107] The clustering subunit is configured to cluster the active power variation and the reactive power loss based on a preset clustering algorithm.
[0108] In some optional implementations, the compensation module 503 includes:
[0109] a third confirming unit, configured to confirm the clustering grouping of the active power data to be predicted in the clustering result;
[0110] The fourth confirmation unit is used to confirm the target reactive power loss corresponding to the active power data to be predicted in the cluster grouping, and obtain the target reactive power loss rate based on the target reactive power loss, and perform compensation control on the reactive power in the station based on the target reactive power loss and the target reactive power loss rate.
[0111] In some optional implementations, the second computing unit includes:
[0112] A first confirmation subunit confirms the relationship between the direction of the active power change and the direction of the reactive power loss;
[0113] The filtering subunit filters out data having opposite directions between the active power change amount and the reactive power loss amount.
[0114] In some optional implementations, the acquisition module 501 further includes:
[0115] The filtering unit filters out the reactive power data that is greater than a first preset reactive power threshold, filters out the reactive power data that is less than a second preset reactive power threshold, and / or filters out data during abnormal operation.
[0116] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.
[0117] The reactive power control device of the new energy power station in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.
[0118] The embodiment of the present invention also provides a computer device having the above Figure 4 The reactive power control device of the new energy power station shown.
[0119] See also Figure 4 , Figure 4 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 4A processor 10 is taken as an example.
[0120] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.
[0121] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.
[0122] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0123] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.
[0124] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 4 The bus connection is taken as an example.
[0125] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.
[0126] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.
[0127] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.
[0128] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.
Claims
1. A reactive power control method for a new energy power generation station, characterized in that: The reactive power control method of the new energy power station includes: Acquiring historical active power data, as well as grid connection point voltage data and reactive power data corresponding to the active power data; confirming a coupling relationship between the active power data and the reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data; Target reactive power loss data corresponding to the active power data to be predicted is confirmed based on the coupling relationship, and compensation control is performed on the reactive power in the station based on the target reactive power loss data.
2. The reactive power control method of a new energy power station according to claim 1, characterized in that: The step of confirming the coupling relationship between the active power data and the reactive power loss data based on the grid connection point voltage data, the active power data, and the reactive power data includes: Obtaining reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data; Clustering the active power data and the reactive loss data based on a preset clustering algorithm to obtain a clustering result; wherein the clustering result includes a plurality of cluster groups; The clustering result is used as the coupling relationship between the active power data and the reactive power loss data.
3. The reactive power control method of a new energy power station according to claim 2, characterized in that: The active power data includes: active power value, and the reactive power data includes: reactive power value; After the step of obtaining historical active power data, and grid connection point voltage data and reactive power data corresponding to the active power data, the method further includes: Calculating an active power change per unit time based on the active power value; The reactive power loss per unit time is calculated based on the reactive power value, the active power value and the grid connection point voltage data.
4. The reactive power control method of a new energy power station according to claim 3, characterized in that: The step of clustering the active power data and the reactive loss data based on a preset clustering algorithm includes: Clustering is performed on the active power change and the reactive power loss based on a preset clustering algorithm.
5. The reactive power control method of a new energy power station according to claim 2, characterized in that: The step of confirming target reactive power loss data corresponding to the active power data to be predicted based on the coupling relationship, and performing compensation control on the reactive power in the station based on the target reactive power loss data includes: confirming the clustering grouping of the active power data to be predicted in the clustering result; The target reactive power loss corresponding to the active power data to be predicted is confirmed in the cluster grouping, and the target reactive power loss rate is obtained based on the target reactive power loss, and compensation control is performed on the reactive power in the station based on the target reactive power loss and the target reactive power loss rate.
6. The reactive power control method of a new energy power station according to claim 3, characterized in that: After the step of calculating the reactive power loss per unit time based on the reactive power value, the active power value, and the grid connection point voltage data, the method further includes: confirming the relationship between the direction of the active power change and the direction of the reactive power loss; The data in which the active power change amount and the reactive power loss amount are in opposite directions are filtered out.
7. The reactive power control method of a new energy power station according to claim 1, characterized in that: After the step of obtaining historical active power data, and grid connection point voltage data and reactive power data corresponding to the active power data, the method further includes: The reactive power data is filtered out if it is greater than a first preset reactive power threshold, and the reactive power data is filtered out if it is less than a second preset reactive power threshold, and / or data in abnormal operation is filtered out.
8. A reactive power control device for a new energy power generation station, characterized in that: include: An acquisition module is used to acquire historical active power data, as well as grid connection point voltage data and reactive power data corresponding to the active power data; a confirmation module, configured to confirm a coupling relationship between the active power data and the reactive loss data based on the grid connection point voltage data, the active power data, and the reactive power data; The compensation module is used to confirm the reactive loss data corresponding to the active power data to be predicted based on the coupling relationship, and to perform compensation control on the reactive power in the station based on the reactive loss data.
9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the reactive power control method of a new energy power station as described in any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the reactive power control method for a new energy power station are implemented as described in any one of claims 1 to 7.
11. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the reactive power control method for a new energy power station as claimed in any one of claims 1 to 7 are implemented.