Power quality analysis method and device of power distribution network, storage medium and electronic equipment

Abstract

The invention discloses an electric energy quality analysis method and device of a power distribution network, a storage medium and electronic equipment. The method comprises the following steps: under the condition that new energy is accessed to the power distribution network, respectively acquiring initial power quality parameters of a plurality of key nodes in the power distribution network to obtain a plurality of initial power quality parameters; based on the power quality demand information of the power distribution network, screening the plurality of initial power quality parameters to obtain at least one target power quality parameter, the power quality demand information being used for representing the power demand satisfied by the power quality in the power distribution network; and analyzing the at least one target electric energy quality parameter to obtain an electric energy quality fluctuation trend chart of the power distribution network, the electric energy quality fluctuation trend chart being used for representing the power supply condition of the power distribution network. The technical problem that the electric energy quality of the power distribution network cannot be effectively analyzed is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems of distribution networks, and in particular to a method, device, storage medium and electronic equipment for analyzing power quality of distribution networks. Background Art

[0002] As the proportion of renewable energy in the power system gradually increases, the power quality of the distribution network faces new challenges. Due to the volatility and intermittency of renewable energy generation, it will cause frequent fluctuations in power quality parameters such as voltage, current, and frequency in the distribution network, which in turn affects the power quality of users and damages hardware equipment, resulting in technical problems that make it impossible to effectively analyze the power quality of the distribution network.

[0003] With respect to the above-mentioned technical problem of being unable to effectively analyze the power quality of the distribution network, no effective solution has been proposed so far. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, storage medium and electronic device for analyzing power quality of a distribution network, so as to at least solve the technical problem that the power quality of the distribution network cannot be effectively analyzed.

[0005] According to one aspect of the embodiment of the invention, a method for analyzing power quality of a distribution network is provided. The method includes: when the distribution network is connected to a new energy source, the initial power quality parameters of multiple key nodes in the distribution network are collected respectively to obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; based on the power quality demand information of the distribution network, the multiple initial power quality parameters are screened to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the power demand satisfied by the power quality in the distribution network; at least one target power quality parameter is analyzed to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network.

[0006] Optionally, at least one target power quality parameter is analyzed to obtain a power quality fluctuation trend graph of the distribution network, including: inputting at least one target power quality parameter into a prediction model of the distribution network for prediction to obtain at least one predicted power quality parameter, wherein the prediction model is established based on multiple historical target power quality parameters; and generating a power quality fluctuation trend graph of the distribution network based on the at least one predicted power quality parameter.

[0007] Optionally, based on at least one predicted power quality parameter, a power quality fluctuation trend graph of the distribution network is generated, including: based on a target parameter type of the target power quality parameter, detecting a predicted parameter type of the predicted power quality parameter to obtain a first detection result; in response to the first detection result being that the target parameter type is the same as the predicted parameter type, generating a power quality fluctuation trend graph of the distribution network.

[0008] Optionally, the method also includes: obtaining a power quality parameter threshold corresponding to a target power quality parameter; determining a warning period of the distribution network and generating a warning instruction based on the target power quality parameter and the power quality parameter threshold; and generating warning information within the warning period in response to the warning instruction.

[0009] Optionally, based on the target power quality parameter and the power quality parameter threshold, the warning period of the distribution network is determined and a warning instruction is generated, including: in the power quality fluctuation trend diagram, the time period when the target power quality parameter is greater than the power quality parameter threshold is determined as the warning period, and a warning instruction is generated.

[0010] Optionally, the method further includes: based on the warning period, detecting the operating status of multiple hardware devices in the key node to obtain a second detection result; based on the second detection result, generating fault information of the distribution network.

[0011] Optionally, the method also includes: when the distribution network is connected to new energy, obtaining the priorities of multiple initial nodes of the distribution network, wherein the priorities are used to characterize the degree of influence of the initial nodes on the distribution network; sorting the multiple priorities according to the sorting strategy to obtain a sorting result; and determining multiple key nodes based on the sorting result.

[0012] According to one aspect of an embodiment of the present invention, a power quality analysis device for a distribution network is provided, and the device also includes: a collection unit, which is used to collect initial power quality parameters of multiple key nodes in the distribution network when the distribution network is connected to new energy, and obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; a screening unit, which is used to screen the multiple initial power quality parameters based on power quality demand information of the distribution network, and obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the power demand met by the power quality in the distribution network; an analysis unit, which is used to analyze at least one target power quality parameter, and obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network.

[0013] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method in the embodiment of the present invention.

[0014] According to another aspect of an embodiment of the present invention, a processor is provided. The processor is used to run a program, wherein the method in the embodiment of the present invention is executed when the program is run.

[0015] According to another aspect of the embodiments of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in the embodiments of the present invention is implemented.

[0016] According to another aspect of an embodiment of the present invention, an electronic device is provided, the electronic device comprising a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to execute the instructions to implement the method in the embodiment of the present invention.

[0017] In an embodiment of the present invention, when a distribution network is connected to a new energy source, initial power quality parameters of multiple key nodes in the distribution network are collected respectively to obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; based on the power quality demand information of the distribution network, the multiple initial power quality parameters are screened to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the electricity demand met by the power quality in the distribution network; at least one target power quality parameter is analyzed to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network. That is to say, in the case where the distribution network is connected to new energy, the embodiment of the present invention can respectively collect the initial power quality parameters of multiple key nodes in the distribution network to obtain multiple initial power quality parameters, and then screen the multiple initial power quality parameters according to the power quality demand information of the distribution network to achieve the purpose of obtaining at least one target power quality parameter. Further, the at least one target power quality parameter is analyzed to achieve the purpose of obtaining a power quality fluctuation trend chart of the distribution network. Considering that after obtaining multiple initial power quality parameters, the multiple initial power quality parameters obtained are screened according to the power quality demand information to obtain at least one target power quality parameter, and then the target power quality parameter is analyzed to obtain a power quality fluctuation trend chart for characterizing the power supply situation of the distribution network, thereby solving the technical problem of being unable to effectively analyze the power quality of the distribution network and achieving the technical effect of being able to effectively analyze the power quality of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of a method for analyzing power quality of a distribution network according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of a power quality analysis device for a distribution network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present invention, a method for analyzing power quality of a distribution network is provided. It should be noted that in the flowchart of the accompanying drawings, the steps shown therein can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0024] The following is an introduction to a power quality analysis method for a distribution network according to an embodiment of the present invention.

[0025] Figure 1 is a flow chart of a method for analyzing power quality of a distribution network according to an embodiment of the present invention. Figure 1As shown, the power quality analysis method of the distribution network may include the following steps:

[0026] Step S101, when the distribution network is connected to a new energy source, initial power quality parameters of multiple key nodes in the distribution network are respectively collected to obtain multiple initial power quality parameters.

[0027] In the technical solution provided in the above step S101 of the present invention, when the distribution network is connected to new energy, the initial power quality parameters of multiple key nodes in the distribution network are collected respectively to achieve the purpose of obtaining multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of the nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network, such as voltage, current, and frequency.

[0028] Optionally, new energy refers to renewable energy, such as solar energy, wind energy, and hydropower. New energy can reduce environmental pollution and resource consumption by converting natural energy into electrical energy. Key nodes are used to characterize locations in the power system that have a greater impact on the power quality in the distribution network or require key monitoring. For example, common key nodes include: transformer nodes, busbar nodes, load side nodes, power switchgear nodes, and distributed photovoltaic grid connection points.

[0029] It should be noted that this is only a preferred implementation method for obtaining multiple initial power quality parameters, and the process and method for obtaining multiple initial power quality parameters are not specifically limited. As long as the distribution network is connected to new energy, the initial power quality parameters of multiple key nodes in the distribution network are collected separately, and the process and method for obtaining multiple initial power quality parameters are within the protection scope of the present invention and are not listed here.

[0030] Step S102: Based on the power quality demand information of the distribution network, a plurality of initial power quality parameters are screened to obtain at least one target power quality parameter.

[0031] In the technical solution provided in the above step S102 of the present invention, multiple initial power quality parameters can be screened according to the power quality demand information of the distribution network to achieve the purpose of obtaining at least one target power quality parameter, wherein the power quality demand information is used to characterize the power demand met by the power quality in the distribution network, for example, the power quality demand information may include requirements for voltage stability, frequency stability, harmonic content, power fluctuation, etc.

[0032] For example, among multiple initial power quality parameters, initial power quality parameters that do not meet the power quality requirement information are deleted, and initial power quality parameters that meet the power quality requirement information are determined as target power quality parameters.

[0033] It should be noted that this is only a preferred implementation method for obtaining at least one target power quality parameter, and the process and method for obtaining at least one target power quality parameter are not specifically limited. As long as multiple initial power quality parameters are screened based on the power quality demand information of the distribution network, the method and process for obtaining at least one target power quality parameter are within the protection scope of the present invention and will not be repeated here.

[0034] Step S103: Analyze at least one target power quality parameter to obtain a power quality fluctuation trend diagram of the distribution network.

[0035] In the technical solution provided in the above step S103 of the present invention, after obtaining at least one target power quality parameter, at least one target power quality parameter can be analyzed to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network.

[0036] Optionally, the target power quality parameters can be analyzed using a machine learning model to obtain analysis results, and a power quality fluctuation trend graph can be generated based on the analysis results. Among them, the machine learning model requires a large amount of power quality parameter data for analysis in order to predict the trend and change of the power quality parameters.

[0037] It should be noted that this is only a preferred implementation method for obtaining the power quality fluctuation trend diagram of the distribution network. The process and method for obtaining the power quality fluctuation trend diagram of the distribution network are not specifically limited. As long as at least one target power quality parameter is analyzed, the process and method for obtaining the power quality fluctuation trend diagram of the distribution network are within the protection scope of the present invention and are not listed here.

[0038] In the above steps S101 to S103 of the present invention, when the distribution network is connected to new energy, the initial power quality parameters of multiple key nodes in the distribution network can be respectively collected to obtain multiple initial power quality parameters, and then the multiple initial power quality parameters are screened according to the power quality demand information of the distribution network to achieve the purpose of obtaining at least one target power quality parameter. Further, the at least one target power quality parameter is analyzed to achieve the purpose of obtaining a power quality fluctuation trend chart of the distribution network. Considering that after obtaining multiple initial power quality parameters, the multiple initial power quality parameters obtained are screened according to the power quality demand information to obtain at least one target power quality parameter, and then the target power quality parameter is analyzed to achieve a power quality fluctuation trend chart for characterizing the power supply situation of the distribution network, thereby solving the technical problem of being unable to effectively analyze the power quality of the distribution network and achieving the technical effect of being able to effectively analyze the power quality of the distribution network.

[0039] The above method of this embodiment is further introduced below.

[0040] As an optional implementation method, at least one target power quality parameter is analyzed to obtain a power quality fluctuation trend graph of the distribution network, including: inputting at least one target power quality parameter into a prediction model of the distribution network for prediction to obtain at least one predicted power quality parameter, wherein the prediction model is established based on multiple historical target power quality parameters; based on the at least one predicted power quality parameter, generating a power quality fluctuation trend graph of the distribution network.

[0041] In this embodiment, at least one target power quality parameter can be input into the prediction model of the distribution network for prediction, so as to obtain at least one predicted power quality parameter, and then generate a power quality fluctuation trend graph of the distribution network based on the at least one predicted power quality parameter obtained above.

[0042] Optionally, the prediction model can be implemented by a machine learning algorithm, such as a long short-term memory network (LSTM), a support vector machine (SVM), etc. It should be noted that only examples are given here to illustrate the implementation of the prediction model, and the implementation of the prediction model is not specifically limited.

[0043] For example, after obtaining the target power quality parameters such as target voltage, target current, and target frequency, the power quality trend is predicted through machine learning algorithms such as long short-term memory networks or support vector machines, and a power quality fluctuation trend graph is generated, thereby providing early warning of potential risks.

[0044] As an optional implementation method, based on at least one predicted power quality parameter, a power quality fluctuation trend graph of the distribution network is generated, including: based on a target parameter type of a target power quality parameter, detecting a predicted parameter type of the predicted power quality parameter to obtain a first detection result; in response to the first detection result being that the target parameter type is the same as the predicted parameter type, generating a power quality fluctuation trend graph of the distribution network.

[0045] In this embodiment, after obtaining the target power quality parameter, the predicted parameter type of the predicted power quality parameter is detected according to the target parameter type of the target power quality parameter to obtain a first detection result, and when the first detection result at this time is that the target parameter type is the same as the predicted parameter type, a power quality fluctuation trend graph can be generated.

[0046] For example, when there are three types of target parameters of the target power quality parameters, such as target voltage, target current and target frequency, it is necessary to detect the types of predicted parameters of the predicted power quality parameters. If there are also three types of predicted parameters of the predicted power quality parameters, namely predicted voltage, predicted current and predicted frequency, it means that complete predicted power quality parameters are obtained. At this time, a power quality fluctuation trend chart can be generated based on the predicted power quality parameters. It should be noted that only the number of target parameter types is exemplified here, and the number of target parameter types is not specifically limited.

[0047] As an optional implementation mode, the method also includes: obtaining a power quality parameter threshold corresponding to a target power quality parameter; determining a warning period of the distribution network and generating a warning instruction based on the target power quality parameter and the power quality parameter threshold; and generating warning information within the warning period in response to the warning instruction.

[0048] In this embodiment, a power quality parameter threshold corresponding to the target power quality parameter can be obtained, and then based on the target power quality parameter and the power quality parameter threshold, the warning period of the distribution network can be determined and the warning quality can be generated. According to the warning instructions obtained above, warning information can be generated within the warning period.

[0049] Optionally, the power quality parameter threshold may be a preset value. The early warning information is used to prompt the target object distribution network that a power system failure has occurred, wherein the target object may be a staff member or maintenance personnel of the distribution network. After the early warning information is generated, the early warning information may be displayed in the power system in the form of a pop-up window, or may be broadcasted by voice to prompt the staff. It should be noted that only examples are given here to illustrate the early warning method of the early warning information, and no specific limitation is imposed on the early warning method of the early warning information.

[0050] For example, after obtaining the power quality parameter threshold, the warning period of the distribution network can be determined according to the target power quality parameter and the power quality parameter threshold, and a warning instruction can be generated. The warning instruction obtained above is executed to generate warning information, and the warning information is displayed in the form of a pop-up window or broadcast in the form of a warning voice to prompt the staff, so that the staff can discover and handle the fault as soon as possible.

[0051] As an optional implementation method, based on the target power quality parameter and the power quality parameter threshold, the warning period of the distribution network is determined and a warning instruction is generated, including: in the power quality fluctuation trend diagram, the time period when the target power quality parameter is greater than the power quality parameter threshold is determined as the warning period, and a warning instruction is generated.

[0052] In this embodiment, after obtaining the target power quality parameter and the power quality parameter threshold, in the power quality fluctuation trend diagram, the time period when the target power quality parameter is greater than the power quality parameter threshold is determined as the warning period, thereby generating a warning instruction.

[0053] Optionally, the power quality parameter threshold is determined as a first power quality parameter threshold. In the power quality fluctuation trend diagram, if the target power quality parameter is less than the first power quality parameter threshold and greater than the second power quality parameter threshold, it means that the power system is in a normal operating state at this time and there is no need to perform relevant early warning operations, wherein the first power quality parameter threshold is greater than the second power quality parameter threshold, and the second power quality parameter threshold can be a preset value.

[0054] As an optional implementation manner, the method further includes: based on the warning period, detecting the operating status of multiple hardware devices in the key node to obtain a second detection result; based on the second detection result, generating fault information of the distribution network.

[0055] In this embodiment, after obtaining the early warning period, the operating status of multiple hardware devices in the key nodes can be detected to obtain a second detection result, and then based on the above-obtained second detection result, fault information of the distribution network can be generated, thereby achieving the effect of effectively processing the above-mentioned fault information.

[0056] Optionally, the hardware devices in the key nodes may include transformers, power switching devices, distributed photovoltaic devices, etc. It should be noted that only examples are given here for the hardware devices in the key nodes, and no specific limitations are given to the hardware devices in the key nodes.

[0057] Optionally, during the early warning period, the operating status of multiple hardware devices in the key nodes is detected to obtain a second detection result, and when the second detection result is that the hardware device is in an abnormal operating state, the fault information of the distribution network can be generated. For example, after predicting the fluctuation trend of power quality in advance, the equipment on the key nodes can be detected for abnormalities and faults can be identified during the early warning period, ultimately achieving optimized maintenance and fault prevention of the power grid.

[0058] It can be understood that this is only a preferred implementation method for obtaining the fault information of the distribution network, and does not specifically limit the process and method for obtaining the fault information of the distribution network.

[0059] As an optional implementation method, the method also includes: when the distribution network is connected to new energy, obtaining the priorities of multiple initial nodes of the distribution network, wherein the priorities are used to characterize the degree of influence of the initial nodes on the distribution network; sorting the multiple priorities according to the sorting strategy to obtain the sorting results; and determining multiple key nodes based on the sorting results.

[0060] In this embodiment, when the distribution network is connected to new energy, the priorities of multiple initial nodes of the distribution network can be obtained, and then the multiple priorities can be sorted according to the sorting strategy to obtain a sorting result. Furthermore, based on the sorting result, multiple key nodes can be determined, wherein the sorting strategy can be to sort the priorities from large to small.

[0061] Optionally, the priorities of the multiple initial nodes are sorted from large to small to obtain the sorted multiple initial nodes, and the first target value initial nodes of the sorted multiple initial nodes are determined as multiple key nodes, wherein the target value can be a preset value, such as 10, 15, etc.

[0062] It should be noted that this is only a preferred implementation method for determining multiple key nodes, and does not specifically limit the process and method for determining multiple key nodes.

[0063] In this embodiment, when the distribution network is connected to new energy, the initial power quality parameters of multiple key nodes in the distribution network can be collected separately to obtain multiple initial power quality parameters, and then the multiple initial power quality parameters are screened according to the power quality demand information of the distribution network to achieve the purpose of obtaining at least one target power quality parameter. Further, the at least one target power quality parameter is analyzed to achieve the purpose of obtaining a power quality fluctuation trend chart of the distribution network. Considering that after obtaining multiple initial power quality parameters, the multiple initial power quality parameters obtained are screened according to the power quality demand information to obtain at least one target power quality parameter, and then the target power quality parameter is analyzed to achieve a power quality fluctuation trend chart for characterizing the power supply situation of the distribution network, thereby solving the technical problem of being unable to effectively analyze the power quality of the distribution network and achieving the technical effect of being able to effectively analyze the power quality of the distribution network.

[0064] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0065] As the proportion of renewable energy (such as wind power, solar energy, etc.) in the power system gradually increases, the power quality of the distribution network faces new challenges. The volatility and intermittency of renewable energy generation will cause frequent fluctuations in parameters such as voltage, current, and frequency in the distribution network, and may cause power quality problems such as harmonics, frequency offset, and voltage flicker. These problems not only affect the quality of users' electricity consumption, but may also damage equipment and increase the maintenance cost of the power grid.

[0066] At present, centralized monitoring systems are often used to monitor and process the power quality parameters of distribution networks in real time, so that staff can promptly discover faults in the distribution network. However, centralized monitoring systems are suitable for industrial environments and respond slowly when large-scale new energy sources are connected, resulting in technical problems that make it impossible to effectively analyze the power quality of the distribution network.

[0067] Therefore, in order to solve the above problems, the present invention proposes a power quality analysis method for a distribution network. When the distribution network is connected to a new energy source, the method can respectively collect initial power quality parameters of multiple key nodes in the distribution network to obtain multiple initial power quality parameters, and then screen the multiple initial power quality parameters according to the power quality demand information of the distribution network to achieve the purpose of obtaining at least one target power quality parameter. Further, the at least one target power quality parameter is analyzed to achieve the purpose of obtaining a power quality fluctuation trend diagram of the distribution network. Considering that after obtaining multiple initial power quality parameters, the multiple initial power quality parameters obtained are screened according to the power quality demand information to obtain at least one target power quality parameter, and then the target power quality parameter is analyzed to obtain a power quality fluctuation trend diagram for characterizing the power supply situation of the distribution network, thereby solving the technical problem that the power quality of the distribution network cannot be effectively analyzed, and achieving the technical effect that the power quality of the distribution network can be effectively analyzed.

[0068] In an embodiment of the present invention, an electric energy signal corresponding to the power quality parameter in the distribution network can be obtained, and based on the real-time Fourier transform algorithm and the wavelet transform algorithm, the harmonics in the current signal and the voltage signal in the electric energy signal are decomposed to obtain the target electric energy signal, so that the influence of the harmonics on the electric energy signal can be analyzed; the target electric energy signal is analyzed by machine learning algorithms such as long short-term memory networks or support vector machines, the trend of power quality is predicted, and a power quality fluctuation trend graph is generated, so that potential risks can be warned in advance.

[0069] Optionally, by designing the framework of the edge computing module of the power system, real-time preprocessing of data can be achieved to alleviate communication pressure, while completing part of the data analysis locally to achieve distributed intelligent computing.

[0070] In this embodiment, multi-level sensor nodes are introduced in the substation or distribution network, such as voltage, current, frequency, harmonic, flicker and other sensors, to monitor the power quality parameters of each key node in real time; a centralized processing module and an edge computing module are established to analyze and process the collected power quality parameters to obtain at least one predicted power quality parameter, and a preliminary detection is performed on the predicted power quality parameter. If there is no abnormality in the preliminary detection, the data is directly compressed and transmitted to reduce the load of the central processor.

[0071] Optionally, key nodes are used to characterize locations in the power system that have a greater impact on the power quality in the distribution network or require key monitoring. For example, common key nodes include: transformer nodes, bus nodes, load side nodes, power switchgear nodes, and distributed photovoltaic grid connection points.

[0072] Optionally, the main function of the centralized processing module is to centrally analyze, process and provide decision support for the power quality parameters processed by each edge computing module. The specific processing modules include: a data collection submodule, which is used to collect real-time power quality data uploaded by the edge computing module; a data processing submodule, which is used to perform processing operations such as data filtering, denoising and format conversion to ensure data quality; a data analysis and calculation submodule, which is used to calculate real-time power quality parameters and indicators and identify abnormal power events; a data storage submodule, which is used to store the processed real-time data in the database and store historical data to form a time series data set; a historical data analysis submodule: used to perform statistical analysis using historical data, mine the laws and trends in the data, and find the periodic characteristics of power quality problems through time series; a real-time optimization and control submodule, which is used to dynamically adjust the power quality control strategy based on the real-time data feedback to ensure that the system can maintain the best operating state under different working conditions.

[0073] Optionally, the specific processing modules of the edge computing module include: a data acquisition and aggregation submodule, which is used to collect power quality data such as voltage, current, frequency, harmonics, etc. from each sensor node in real time, and aggregate the data to a centralized processing module; a data processing submodule, which mainly includes processing methods such as filtering, denoising, and removing redundant information to ensure that the input data is accurate and clean; a power quality analysis submodule, which is used to apply Fourier transform, wavelet transform and other technologies to decompose and analyze the harmonics in the current signal and voltage signal, and detect power quality problems such as voltage fluctuation and frequency fluctuation; anomaly detection and alarm submodule, which is used to analyze data according to preset standards or models, detect abnormal conditions (such as voltage exceeding the limit, excessive frequency fluctuation, etc.), and trigger an alarm; a data compression and transmission submodule, which is used to compress the processed data to reduce the amount of data, and transmit it to the centralized processing module through the communication network; a report and visualization submodule, which is used to generate various reports and charts, provide a visual display of power quality, and help users intuitively understand the power quality status.

[0074] Optionally, the centralized processing module is usually located at the core of the system, responsible for global data processing, storage and large-scale computing tasks, such as complex machine learning model training, global trend analysis and processing, etc. It performs in-depth analysis and centralized decision-making on data from various sensor nodes, and usually has more powerful computing capabilities. The edge computing module is a distributed computing unit that mainly processes data in a local or specific area, can respond quickly to data changes, and perform real-time analysis and preliminary decisions on the obtained data, which usually reduces the need to transmit large amounts of data to the centralized processing module, reducing latency and bandwidth pressure.

[0075] In this embodiment, the obtained power quality parameters can be processed by using the functional modules of the power system, and the processed power quality parameters can be uploaded to the cloud, wherein the main implementation process of the functional modules is: using a multi-channel acquisition circuit to collect various power quality indicators such as voltage, current, frequency, etc., so as to meet the monitoring requirements under different new energy access modes; using an embedded processor to process the monitored real-time data for harmonic analysis, frequency fluctuation and voltage flicker detection; predicting the fluctuation trend of power quality through machine learning, and performing abnormal detection and fault identification based on historical data; providing decision support for maintenance and management; configuring large-capacity data storage, and transmitting data to the cloud through the fifth generation mobile communication technology (Fifth Generation Mobile Network, referred to as 5G) or a dedicated communication network, so as to achieve long-term data preservation and remote analysis. An intelligent power management module can be built into the power system to reduce power consumption, especially in remote or distributed environments to extend the life of equipment.

[0076] Optionally, the specific implementation modules of real-time data processing include: a signal filtering and sampling module, which is used to filter and sample the collected voltage, current and other signals to remove noise signals; a data analysis and feature extraction module, which is used to extract key features of power quality (such as harmonic content, frequency fluctuation, voltage flicker, etc.) through digital signal processing algorithms; a real-time monitoring and alarm module, which is used to analyze real-time data to determine whether the power quality exceeds the normal range, thereby triggering an alarm or recording an abnormal event; an abnormal detection and fault identification module, which is used to use an embedded processor for pattern recognition, and identify potential faults or power quality problems through threshold setting, comparison of historical data, etc. This real-time data processing method can ensure that the system can respond quickly to fluctuations in power quality so as to provide timely feedback and take necessary measures.

[0077] Optionally, the data obtained after processing usually has the following characteristics: high precision and high frequency. The data collected and processed in real time by the embedded processor can accurately reflect the real-time status of the power quality; multi-dimensional characteristics, including not only basic power quality indicators such as voltage, current, and frequency, but also more detailed power quality characteristics such as harmonic distortion, frequency fluctuation, and flicker can be extracted; historical data has a strong correlation, and these data can be compared with historical data to form time series data, which is convenient for subsequent prediction and anomaly detection.

[0078] Optionally, after the predicted power quality parameters are obtained, the predicted power quality parameters may be evaluated using a plurality of indicators to obtain evaluation results, wherein the evaluation results are used to characterize the quality of the predicted power quality parameters.

[0079] Optionally, multiple indicators include: accuracy, whether the data can accurately reflect the actual situation of power quality, for example, whether the voltage, current and frequency are consistent with the actual values; integrity, whether the data contains complete power quality information, including all relevant voltage, frequency, harmonics and other indicators; real-time: whether the data can be updated in real time to reflect the changes in power quality in a timely manner and avoid lags; consistency, whether there is consistency between the data to ensure that monitoring data from different sources are comparable.

[0080] In this embodiment, when the distribution network is connected to new energy, initial power quality parameters of multiple key nodes in the distribution network are collected separately to obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; based on the power quality demand information of the distribution network, the multiple initial power quality parameters are screened to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the electricity demand met by the power quality in the distribution network; at least one target power quality parameter is analyzed to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network. That is to say, in the case where the distribution network is connected to new energy, the embodiment of the present invention can respectively collect the initial power quality parameters of multiple key nodes in the distribution network to obtain multiple initial power quality parameters, and then screen the multiple initial power quality parameters according to the power quality demand information of the distribution network to achieve the purpose of obtaining at least one target power quality parameter. Further, the at least one target power quality parameter is analyzed to achieve the purpose of obtaining a power quality fluctuation trend chart of the distribution network. Considering that after obtaining multiple initial power quality parameters, the multiple initial power quality parameters obtained are screened according to the power quality demand information to obtain at least one target power quality parameter, and then the target power quality parameter is analyzed to obtain a power quality fluctuation trend chart for characterizing the power supply situation of the distribution network, thereby solving the technical problem of being unable to effectively analyze the power quality of the distribution network and achieving the technical effect of being able to effectively analyze the power quality of the distribution network.

[0081] According to an embodiment of the present invention, a power quality analysis device for a distribution network is provided. It should be noted that the power quality analysis device for a distribution network can be used to execute a power quality analysis method for a distribution network in an embodiment.

[0082] Figure 2 is a schematic diagram of a power quality analysis device for a distribution network according to an embodiment of the present invention, such as Figure 2As shown, a power quality analysis device 200 for a distribution network may include: a collection unit 201 , a screening unit 202 and an analysis unit 203 .

[0083] The collection unit 201 is used to collect the initial power quality parameters of multiple key nodes in the distribution network when the distribution network is connected to new energy, and obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network.

[0084] The screening unit 202 is used to screen multiple initial power quality parameters based on the power quality demand information of the distribution network to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the power demand satisfied by the power quality in the distribution network.

[0085] The analysis unit 203 is used to analyze at least one target power quality parameter to obtain a power quality fluctuation trend diagram of the distribution network, wherein the power quality fluctuation trend diagram is used to characterize the power supply situation of the distribution network.

[0086] Optionally, the analysis unit 203 may include: an input module, used to input at least one target power quality parameter into a prediction model of the distribution network for prediction, to obtain at least one predicted power quality parameter, wherein the prediction model is established through multiple historical target power quality parameters; a generation module, used to generate a power quality fluctuation trend graph of the distribution network based on at least one predicted power quality parameter.

[0087] Optionally, the generation module may include: a first detection submodule, used to detect the predicted parameter type of the predicted power quality parameter based on the target parameter type of the target power quality parameter to obtain a first detection result; a first generation submodule, used to generate a power quality fluctuation trend graph of the distribution network in response to the first detection result being that the target parameter type is the same as the predicted parameter type.

[0088] Optionally, the generation module may also include: an acquisition submodule for acquiring a power quality parameter threshold corresponding to a target power quality parameter; a determination submodule for determining a warning period of the distribution network and generating a warning instruction based on the target power quality parameter and the power quality parameter threshold; and a second generation submodule for generating warning information within the warning period in response to the warning instruction.

[0089] Optionally, the determination submodule is further used to determine, in the power quality fluctuation trend diagram, a time period when the target power quality parameter is greater than a power quality parameter threshold as a warning period, and generate a warning instruction.

[0090] Optionally, the generation module may also include: a second detection submodule, used to detect the operating status of multiple hardware devices in the key node based on the warning period to obtain a second detection result; a third generation submodule, used to generate fault information of the distribution network based on the second detection result.

[0091] Optionally, the device also includes: an acquisition unit, used to acquire the priorities of multiple initial nodes of the distribution network when the distribution network is connected to new energy, wherein the priorities are used to characterize the degree of influence of the initial nodes on the distribution network; a sorting unit, used to sort the multiple priorities according to the sorting strategy to obtain a sorting result; and a determination unit, used to determine multiple key nodes based on the sorting result.

[0092] In this embodiment, when the distribution network is connected to new energy, the acquisition unit respectively acquires initial power quality parameters of multiple key nodes in the distribution network to obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; the screening unit screens the multiple initial power quality parameters based on the power quality demand information of the distribution network to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the electricity demand satisfied by the power quality in the distribution network; the analysis unit analyzes at least one target power quality parameter to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network, thereby solving the technical problem that the power quality of the distribution network cannot be effectively analyzed, and achieving the technical effect that the power quality of the distribution network can be effectively analyzed.

[0093] According to an embodiment of the present invention, a computer-readable storage medium is also provided, which includes a stored program, wherein when the program is executed by a processor, the device where the readable storage medium is located is controlled to execute the power quality analysis method of the distribution network in the embodiment.

[0094] Optionally, the storage medium is used to collect initial power quality parameters of multiple key nodes in the distribution network when the distribution network is connected to new energy, and obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; used to screen multiple initial power quality parameters based on power quality demand information of the distribution network to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the electricity demand met by the power quality in the distribution network; used to analyze at least one target power quality parameter to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network.

[0095] Optionally, the storage medium is used to analyze at least one target power quality parameter to obtain a power quality fluctuation trend graph of the distribution network, including: inputting at least one target power quality parameter into a prediction model of the distribution network for prediction to obtain at least one predicted power quality parameter, wherein the prediction model is established based on multiple historical target power quality parameters; and generating a power quality fluctuation trend graph of the distribution network based on at least one predicted power quality parameter.

[0096] Optionally, the storage medium is used to generate a power quality fluctuation trend graph of the distribution network based on at least one predicted power quality parameter, including: based on a target parameter type of a target power quality parameter, detecting a predicted parameter type of the predicted power quality parameter to obtain a first detection result; in response to the first detection result being that the target parameter type is the same as the predicted parameter type, generating a power quality fluctuation trend graph of the distribution network.

[0097] Optionally, the storage medium is used to obtain a power quality parameter threshold corresponding to a target power quality parameter; to determine a warning period of the distribution network and generate a warning instruction based on the target power quality parameter and the power quality parameter threshold; and to generate warning information within the warning period in response to the warning instruction.

[0098] Optionally, the storage medium is used to determine the warning period of the distribution network and generate a warning instruction based on the target power quality parameter and the power quality parameter threshold, including: in the power quality fluctuation trend diagram, determining the time period when the target power quality parameter is greater than the power quality parameter threshold as the warning period, and generating a warning instruction.

[0099] Optionally, the storage medium is also used to detect the operating status of multiple hardware devices in the key node based on the warning period to obtain a second detection result; and to generate fault information of the distribution network based on the second detection result.

[0100] Optionally, the storage medium is used to obtain the priorities of multiple initial nodes of the distribution network when the distribution network is connected to new energy sources, wherein the priorities are used to characterize the degree of influence of the initial nodes on the distribution network; to sort the multiple priorities according to the sorting strategy to obtain the sorting results; and to determine multiple key nodes based on the sorting results.

[0101] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein the power quality analysis method for a distribution network in the embodiment is executed when the program is run.

[0102] Optionally, the processor is used to collect initial power quality parameters of multiple key nodes in the distribution network when the distribution network is connected to new energy, and obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; used to screen multiple initial power quality parameters based on power quality demand information of the distribution network to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the electricity demand met by the power quality in the distribution network; and used to analyze at least one target power quality parameter to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply situation of the distribution network.

[0103] Optionally, the processor is used to analyze at least one target power quality parameter to obtain a power quality fluctuation trend graph of the distribution network, including: inputting at least one target power quality parameter into a prediction model of the distribution network for prediction to obtain at least one predicted power quality parameter, wherein the prediction model is established based on multiple historical target power quality parameters; and generating a power quality fluctuation trend graph of the distribution network based on at least one predicted power quality parameter.

[0104] Optionally, the processor is used to generate a power quality fluctuation trend graph of the distribution network based on at least one predicted power quality parameter, including: based on a target parameter type of the target power quality parameter, detecting a predicted parameter type of the predicted power quality parameter to obtain a first detection result; in response to the first detection result being that the target parameter type is the same as the predicted parameter type, generating a power quality fluctuation trend graph of the distribution network.

[0105] Optionally, the processor is used to obtain a power quality parameter threshold corresponding to a target power quality parameter; to determine a warning period of the distribution network and generate a warning instruction based on the target power quality parameter and the power quality parameter threshold; and to generate warning information within the warning period in response to the warning instruction.

[0106] Optionally, the processor is used to determine the warning period of the distribution network and generate a warning instruction based on the target power quality parameter and the power quality parameter threshold, including: in the power quality fluctuation trend diagram, determining the time period when the target power quality parameter is greater than the power quality parameter threshold as the warning period, and generating a warning instruction.

[0107] Optionally, the processor is further used to detect the operating status of multiple hardware devices in the key node based on the warning period to obtain a second detection result; and to generate fault information of the distribution network based on the second detection result.

[0108] Optionally, the processor is used to obtain the priorities of multiple initial nodes of the distribution network when the distribution network is connected to new energy sources, wherein the priorities are used to characterize the degree of influence of the initial nodes on the distribution network; to sort the multiple priorities according to the sorting strategy to obtain a sorting result; and to determine multiple key nodes based on the sorting result.

[0109] According to an embodiment of the present invention, a computer program product is further provided, including a computer program, and when the computer program is executed by a processor, the power quality analysis method for a distribution network in the embodiment of the present invention is implemented.

[0110] According to an embodiment of the present invention, an electronic device is also provided, the electronic device comprising a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to execute instructions to implement the power quality analysis method of the distribution network in the embodiment of the present invention.

[0111] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0112] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0113] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic, for example, the division of units can be a logical function division, and there can be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0114] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0115] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0116] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0117] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for analyzing power quality of a distribution network, characterized in that: include: In the case where the distribution network is connected to a new energy source, initial power quality parameters of multiple key nodes in the distribution network are collected respectively to obtain multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; Based on the power quality demand information of the distribution network, a plurality of the initial power quality parameters are screened to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the power demand satisfied by the power quality in the distribution network; At least one of the target power quality parameters is analyzed to obtain a power quality fluctuation trend graph of the distribution network, wherein the power quality fluctuation trend graph is used to characterize the power supply condition of the distribution network.

2. The method according to claim 1, characterized in that Analyzing at least one of the target power quality parameters to obtain a power quality fluctuation trend diagram of the distribution network includes: Inputting at least one of the target power quality parameters into a prediction model of the distribution network for prediction, thereby obtaining at least one predicted power quality parameter, wherein the prediction model is established based on a plurality of historical target power quality parameters; Based on at least one of the predicted power quality parameters, a power quality fluctuation trend graph of the distribution network is generated.

3. The method according to claim 2, characterized in that Generating a power quality fluctuation trend diagram of the distribution network based on at least one of the predicted power quality parameters includes: Based on the target parameter type of the target power quality parameter, detecting the predicted parameter type of the predicted power quality parameter to obtain a first detection result; In response to the first detection result that the target parameter type is the same as the predicted parameter type, a power quality fluctuation trend graph of the distribution network is generated.

4. The method according to claim 2, characterized in that: The method further comprises: Acquire a power quality parameter threshold value corresponding to the target power quality parameter; Based on the target power quality parameter and the power quality parameter threshold, determining a warning period of the distribution network and generating a warning instruction; In response to the warning instruction, warning information is generated within the warning period.

5. The method according to claim 4, characterized in that Based on the target power quality parameter and the power quality parameter threshold, determining the warning period of the distribution network and generating a warning instruction, including: In the power quality fluctuation trend diagram, the time period during which the target power quality parameter is greater than the power quality parameter threshold is determined as the warning period, and the warning instruction is generated.

6. The method according to claim 4, characterized in that The method further comprises: Based on the warning period, detecting the operating status of multiple hardware devices in the key node to obtain a second detection result; Based on the second detection result, fault information of the power distribution network is generated.

7. The method according to claim 1, characterized in that The method further comprises: When the distribution network is connected to the new energy source, obtaining the priorities of multiple initial nodes of the distribution network, wherein the priorities are used to characterize the degree of influence of the initial nodes on the distribution network; Sorting the plurality of priorities according to the sorting strategy to obtain a sorting result; Based on the sorting result, a plurality of key nodes are determined.

8. A power quality analysis device for a distribution network, characterized in that: include: A collection unit, used for collecting initial power quality parameters of multiple key nodes in the distribution network respectively when the distribution network is connected to a new energy source, and obtaining multiple initial power quality parameters, wherein the importance of the key nodes is higher than the importance of nodes other than the key nodes in the distribution network, and the power quality parameters are used to characterize the power supply quality of the power system of the distribution network; A screening unit, configured to screen the plurality of initial power quality parameters based on the power quality demand information of the distribution network to obtain at least one target power quality parameter, wherein the power quality demand information is used to characterize the power demand satisfied by the power quality in the distribution network; An analysis unit is used to analyze at least one of the target power quality parameters to obtain a power quality fluctuation trend diagram of the distribution network, wherein the power quality fluctuation trend diagram is used to characterize the power supply situation of the distribution network.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The invention comprises one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any one of claims 1 to 7.

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