A method and system for early warning based on power grid harmonic analysis

Abstract

The application discloses a kind of method and system based on power grid harmonic analysis for early warning, belong to data analysis technical field.Therein, method includes: based on the real-time operating state data, generating state estimation data, and obtaining online harmonic monitoring data, and then identifying to obtain harmonic source;Harmonic source monitoring data with time stamp is obtained, based on online multidimensional index fuzzy matching mode, the harmonic source monitoring data with time stamp is matched with state estimation data, generates data mapping relationship, carries out harmonic source online modeling, generates power grid harmonic analysis model;For the large power grid analysis model, harmonic power flow calculation is carried out, and the harmonic power flow calculation result is compared with the allowable limit value, based on the comparison result, for power grid harmonic early warning.The application breaks through the barrier between online data and harmonic analysis, realizes the linkage of online system, while ensuring the accuracy of model calculation, improves the calculation efficiency.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and more specifically, to a method and system for early warning based on power grid harmonic analysis. Background Technology

[0002] Traditional power grid harmonic analysis and calculation typically employs ETAP simulation software developed by OTI. ETAP offers a fully graphical user interface, allowing for the creation of over 100 different graphs, including single-line diagrams, impedance diagrams, and analytical calculation diagrams, in a concise manner. The user interface's editing toolbar allows for the editing and modification of components, graphs, and the interface itself. Clicking on a component allows for the direct input of various parameters, attributes, and operating statuses. ETAP software also boasts powerful calculation, analysis, and design capabilities, enabling functions such as power flow calculations, short-circuit calculations, relay protection coordination, harmonic analysis, transient analysis, motor starting analysis, grounding grid design, and low-voltage distribution system design. After calculation and analysis, the results can be output intuitively in various formats, including direct display, text reports, and curves. ETAP simulation software, with its user-friendly interface, powerful calculation, analysis, and design functions, and intuitive and simple electrical operation, is widely used in the domestic power system industry.

[0003] Currently, harmonic analysis and calculation based on ETAP simulation software remains the mainstream method for power grid harmonic simulation calculation in China. However, with the continuous increase in the capacity and number of nodes in the domestic power grid, the structure and operating conditions of the power system are becoming increasingly complex. The ETAP harmonic calculation method, which has limitations on the number of nodes, requires boundary equivalence before it can be used for calculation and analysis. ETAP harmonic calculation based on a single time section cannot cover the entire network and all operating conditions, and the accuracy of harmonic power flow calculation is low, making it difficult to support harmonic operation risk assessment, level prediction, accident reproduction, and source tracing analysis. At the same time, with the rapid development of digital simulation platforms for power system analysis in China, ADPSS, PSD-BPA, and PSASP have become important tools for domestic power system experimental research, planning and design, and dispatching operation. ETAP simulation software cannot be integrated with these domestic power system analysis software, and there is an urgent need to overcome the technical difficulties in harmonic simulation analysis and operation risk assessment of new domestic power systems.

[0004] Existing simulation methods for harmonics injected into the power system by electrified railways include: building an ETAP power grid model: using the short-circuit calculation and equivalent calculation functions of power system analysis software PSASP and BPA, calculating the three-phase minimum short-circuit current, single-phase minimum short-circuit current, and impedance ratio X / R or positive sequence, negative sequence, and zero sequence impedance at equivalent boundary points, performing equivalent calculations on the power grid outside the ETAP power grid model, and modeling generators, double / triple winding transformers, transmission lines, and conventional loads in the power grid of the study area, inputting the corresponding model parameters, grounding methods, and transformer connection groups, and connecting them one by one according to the actual power grid structure.

[0005] Power flow calculation and comparison of power flow calculation results: Perform power flow calculation on the established ETAP power grid model, and compare the power flow calculation results with the existing planned power grid power flow calculation results to ensure that the comparison error is less than 0.5%. If the result does not meet the requirement, return to the debugging ETAP power grid model according to the result error.

[0006] Build the traction substation load model: Perform fundamental power flow calculations again, and the ETAP power grid model has been debugged.

[0007] Harmonic analysis calculation: In the process of harmonic calculation using the harmonic analysis module, the harmonic calculation settings are first set. In the harmonic calculation settings, the maximum number of iterations, accuracy, frequency scan range, and step size need to be set in the information attributes. In the drawing attributes, the device that needs to output the calculation results is selected. In the alarm attribute page, the boundary limits are set. Then, the harmonic analysis calculation is performed, and the simulation results are viewed.

[0008] The existing technology has low accuracy in power grid component modeling: the modeling of power grid components does not take into account the frequency-varying impedance characteristics of different components, which affects the accuracy of model calculation.

[0009] The calculation scope of harmonic power flow is limited and the reliability of the calculation results is low: the equivalent calculation of the boundary of the power grid to be studied is a simplified equivalent calculation based on the power grid operation condition of a single time section and a single harmonic source under a specific method. It cannot reflect the impact of deep coupling between source, grid and load on the power grid. The calculation scope cannot cover the entire network and all operating conditions, resulting in low accuracy of power flow calculation and poor reliability of calculation results.

[0010] The mixed use of domestic and foreign simulation software results in data incompatibility, system disconnect, and uncontrollable calculation time: Before using ETAP simulation software for harmonic analysis calculation, it is necessary to first use domestic BPA and PSASP power system simulation analysis software for short-circuit current calculation / equivalent calculation. Since the systems cannot be linked, it is necessary to manually model the power grid on two separate software platforms. The process is redundant and complicated, which increases the difficulty of harmonic analysis calculation. Summary of the Invention

[0011] To address the above problems, this invention proposes a method for early warning based on power grid harmonic analysis, comprising: Acquire real-time operating status data associated with the online operation of the power grid; generate state estimation data based on the real-time operating status data; and acquire online harmonic monitoring data. Based on multiple attributes and harmonic emission characteristics of various types of harmonic sources in online harmonic monitoring data, a linear regression method is used to fit the online harmonic monitoring data to obtain the harmonic emission characteristics of each monitoring point. The harmonic emission characteristics are compared with the harmonic emission characteristics of various harmonic sources to obtain the identification results. Combined with the power grid topology model determined by the state estimation data, the bus node where the harmonic source is located is determined. The identification results are then verified using the harmonic monitoring type attribute, thereby identifying the harmonic source. Harmonic source monitoring data with timestamps is obtained, and based on the online multidimensional index fuzzy matching method, the harmonic source monitoring data with timestamps is matched with the state estimation data to generate a data mapping relationship. The online multidimensional index fuzzy matching method includes: constructing a multidimensional index key using the bus name, voltage level, and timestamp of the monitoring point of the harmonic source; and performing fuzzy query matching on the state estimation data and the harmonic source monitoring data based on the bus name and voltage level, provided that the harmonic source monitoring data and the state estimation data belong to the same time segment. Based on the data mapping relationship, online modeling of harmonic sources is performed to generate a power grid harmonic analysis model; Harmonic power flow calculations are performed based on the power grid harmonic analysis model to obtain harmonic power flow calculation results. The calculation results are compared with allowable limits, and based on the comparison results, it is determined whether to issue an early warning for power grid harmonics.

[0012] Preferably, the method further includes calculating the fundamental wave power flow based on the state estimation data, and solving the fundamental wave power flow calculation by iteratively applying Newton's method.

[0013] Preferably, the method further includes: after identifying the harmonic source, performing data processing on the harmonic source monitoring data, including: Based on the attenuation law of harmonic power flow within the same substation, invalid data in the harmonic source monitoring data is cleaned. After the data cleaning is completed, it is determined whether the harmonic source monitoring data is missing key node data. If it is missing, the missing key node data is supplemented with statistical data of the same voltage level and the same equipment attributes. The invalid data includes: monitoring data of harmonic sources that do not meet the attenuation law of harmonic power flow within the same substation.

[0014] Preferably, the method further includes selecting the reference short-circuit capacity of the PCC point based on the voltage level of the PCC point, and dynamically adjusting the allowable limit through the ratio of the individual user agreement capacity to the power supply capacity of the PCC point.

[0015] Preferably, the calculation result is compared with the allowable limit, including: The harmonic current value, voltage content rate value, and total distortion rate value in the calculation results are compared with their respective allowable limits to determine whether the harmonic current value, voltage content rate value, and total distortion rate value meet the requirements of their respective allowable limits.

[0016] Preferably, if the reference short-circuit capacity of the PCC point is different from the minimum short-circuit capacity of the PCC point, the harmonic current limit in the allowable limit is converted, as shown in the following formula: in: The minimum short-circuit capacity of the PCC point. The baseline short-circuit capacity at the PCC point. For the first Permissible value of subharmonic current This is the calculated allowable value for the h-th harmonic current; Among them, the limit of harmonic current injected into the power grid by each user at the same power grid connection point (PCC) is dynamically adjusted according to the agreement capacity and power supply equipment capacity of each user at the same power grid connection point (PCC). Among them, at the same power grid connection point PCC point, the first The first user's Limits of subharmonic current The calculation formula is as follows: in: For the first Electricity capacity agreed upon by each user The power supply capacity of the common connection point. This is the phase superposition coefficient.

[0017] Preferably, the online multidimensional index fuzzy matching method further includes: verifying monitoring points that cannot be matched in the fuzzy query matching by using voltage level; after a successful match, using the bus ID number in the state estimation data as the unique identifier of the corresponding bus node, and establishing a data mapping relationship between the harmonic source monitoring data and the state estimation data.

[0018] According to another aspect of the present invention, a system for early warning based on power grid harmonic analysis is proposed, comprising: The data acquisition unit is used to acquire real-time operating status data associated with the online operation of the power grid, generate state estimation data based on the real-time operating status data, and acquire online harmonic monitoring data. The matching unit is used to fit the online harmonic monitoring data based on multiple attributes and harmonic emission characteristics of multiple types of harmonic sources in the online harmonic monitoring data using a linear regression method to obtain the harmonic emission characteristics of each monitoring point. The harmonic emission characteristics are compared with the harmonic emission characteristics of multiple harmonic sources to obtain identification results. The unit then combines this with the power grid topology model determined by the state estimation data to determine the bus node where the harmonic source is located. Finally, the identification results are verified using the harmonic monitoring type attribute, thereby identifying the harmonic source. The unit also acquires timestamped harmonic source monitoring data and matches it with the state estimation data using an online multidimensional index fuzzy matching method to generate a data mapping relationship. The online multidimensional index fuzzy matching method includes: constructing a multidimensional index key using the bus name, voltage level, and timestamp of the monitoring point of the harmonic source; and performing fuzzy query matching on the state estimation data and the harmonic source monitoring data based on the bus name and voltage level, provided that the harmonic source monitoring data and the state estimation data belong to the same time segment. The modeling unit is used to perform online modeling of harmonic sources based on the data mapping relationship and generate a power grid harmonic analysis model. The early warning unit is used to perform harmonic power flow calculation based on the power grid harmonic analysis model to obtain the harmonic power flow calculation results, compare the calculation results with the allowable limits, and determine whether to issue an early warning for power grid harmonics based on the comparison results.

[0019] Preferably, it further includes a computing unit for performing fundamental wave power flow calculation based on the state estimation data, and solving the fundamental wave power flow calculation by Newton's method iteratively.

[0020] Preferably, the matching unit is further configured to: after identifying the harmonic source, perform data processing on the harmonic source monitoring data. The matching unit is also used for: Based on the attenuation law of harmonic power flow within the same substation, invalid data in the harmonic source monitoring data is cleaned. After the data cleaning is completed, it is determined whether the harmonic source monitoring data is missing key node data. If it is missing, the missing key node data is supplemented with statistical data of the same voltage level and the same equipment attributes. The invalid data includes: monitoring data of harmonic sources that do not meet the attenuation law of harmonic power flow within the same substation.

[0021] Preferably, the method further includes selecting the reference short-circuit capacity of the PCC point based on the voltage level of the PCC point, and dynamically adjusting the allowable limit through the ratio of the individual user agreement capacity to the power supply capacity of the PCC point.

[0022] Preferably, the calculation result is compared with the allowable limit, including: The harmonic current value, voltage content rate value, and total distortion rate value in the calculation results are compared with their respective allowable limits to determine whether the harmonic current value, voltage content rate value, and total distortion rate value meet the requirements of their respective allowable limits.

[0023] Preferably, if the reference short-circuit capacity of the PCC point is different from the minimum short-circuit capacity of the PCC point, the harmonic current limit in the allowable limit is converted, as shown in the following formula: in: The minimum short-circuit capacity of the PCC point. The baseline short-circuit capacity at the PCC point. For the first Permissible value of subharmonic current This is the calculated allowable value for the h-th harmonic current; Among them, the limit of harmonic current injected into the power grid by each user at the same power grid connection point (PCC) is dynamically adjusted according to the agreement capacity and power supply equipment capacity of each user at the same power grid connection point (PCC). Among them, at the same power grid connection point PCC point, the first The first user's Limits of subharmonic current The calculation formula is as follows: in: For the first Electricity capacity agreed upon by each user The power supply capacity of the common connection point. This is the phase superposition coefficient.

[0024] Preferably, the matching unit is further configured to: verify monitoring points that cannot be matched in the fuzzy query matching by using voltage levels; and after a successful match, establish a data mapping relationship between the harmonic source monitoring data and the state estimation data by using the bus ID number in the state estimation data as the unique identifier of the corresponding bus node.

[0025] In another aspect, the present invention also provides a computing device, comprising: one or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described above is implemented.

[0026] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the method described above.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method for early warning based on power grid harmonic analysis, comprising: acquiring real-time operating status data associated with the online operation of the power grid; generating state estimation data based on the real-time operating status data; and acquiring online harmonic monitoring data; fitting the online harmonic monitoring data to the data using a linear regression method based on multiple attributes and harmonic emission characteristics of multiple types of harmonic sources in the online harmonic monitoring data to obtain harmonic emission characteristics for each monitoring point; comparing the harmonic emission characteristics with the harmonic emission characteristics of multiple harmonic sources to obtain identification results; and combining the harmonic emission characteristics with the power grid topology model determined by the state estimation data to determine the harmonic emission characteristics of each source. The bus node where the harmonic source is located is then identified by verifying the identification results using the harmonic monitoring type attribute. Harmonic source monitoring data with timestamps is acquired, and based on an online multidimensional index fuzzy matching method, the timestamped harmonic source monitoring data is matched with state estimation data to generate a data mapping relationship. Based on this data mapping relationship, online modeling of the harmonic source is performed to generate a power grid harmonic analysis model. Harmonic power flow calculation is then performed based on the power grid harmonic analysis model to obtain the harmonic power flow calculation results. These results are compared with allowable limits, and based on the comparison results, it is determined whether to issue a warning for power grid harmonics.

[0028] This invention breaks down the barriers between online data and harmonic analysis, enabling the linkage of online systems and improving computational efficiency while ensuring the accuracy of model calculations. Attached Figure Description

[0029] Figure 1 This is a flowchart of an embodiment of the method of the present invention; Figure 2 This is a data fusion flowchart of an embodiment of the method of the present invention; Figure 3 This is a structural diagram of an embodiment of the system of the present invention. Detailed Implementation

[0030] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0031] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0032] Example 1: This invention proposes a method 100 for early warning based on power grid harmonic analysis, such as... Figure 1 As shown. Method 100 includes: S101, acquire real-time operating status data associated with the online operation of the power grid, generate state estimation data based on the real-time operating status data, and acquire online harmonic monitoring data; S102, based on multiple attributes and harmonic emission characteristics of multiple types of harmonic sources in the online harmonic monitoring data, the online harmonic monitoring data is fitted using a linear regression method to obtain the harmonic emission characteristics of each monitoring point. The harmonic emission characteristics are compared with the harmonic emission characteristics of multiple harmonic sources to obtain the identification results. Combined with the power grid topology model determined by the state estimation data, the bus node where the harmonic source is located is determined. Then, the identification results are verified using the harmonic monitoring type attribute, thereby identifying the harmonic source. Harmonic source monitoring data with timestamps is obtained. Based on the online multidimensional index fuzzy matching method, the harmonic source monitoring data with timestamps is matched with the state estimation data to generate a data mapping relationship. The online multidimensional index fuzzy matching method includes: constructing a multidimensional index key using the bus name, voltage level, and timestamp of the monitoring point of the harmonic source; and performing fuzzy query matching on the state estimation data and the harmonic source monitoring data based on the bus name and voltage level, provided that the harmonic source monitoring data and the state estimation data belong to the same time segment. S103, Based on the data mapping relationship, perform online modeling of harmonic sources and generate a power grid harmonic analysis model; S104, perform harmonic power flow calculation based on the power grid harmonic analysis model to obtain harmonic power flow calculation results, compare the calculation results with allowable limits, and determine whether to issue an early warning for power grid harmonics based on the comparison results.

[0033] Embodiments of the present invention further include performing fundamental wave power flow calculations based on the state estimation data, and solving the fundamental wave power flow calculations using Newton's method iteratively.

[0034] The method also includes: after identifying the harmonic source, performing data processing on the harmonic source monitoring data, including: Based on the attenuation law of harmonic power flow within the same substation, invalid data in the harmonic source monitoring data is cleaned. After the data cleaning is completed, it is determined whether the harmonic source monitoring data is missing key node data. If it is missing, the missing key node data is supplemented with statistical data of the same voltage level and the same equipment attributes. The invalid data includes: monitoring data of harmonic sources that do not meet the attenuation law of harmonic power flow within the same substation.

[0035] According to an embodiment of the present invention, the method further includes selecting the reference short-circuit capacity of the PCC point based on the voltage level of the PCC point, and dynamically adjusting the allowable limit by means of the ratio between the individual user agreement capacity and the power supply capacity of the PCC point.

[0036] According to an embodiment of the present invention, comparing the power flow calculation result with the allowable limit includes: The harmonic current value, voltage content rate value, and total distortion rate value in the power flow calculation results are compared with their respective allowable limits to determine whether the harmonic current value, voltage content rate value, and total distortion rate value meet the requirements of their respective allowable limits.

[0037] According to an embodiment of the present invention, if the reference short-circuit capacity of the PCC point is different from the minimum short-circuit capacity of the PCC point, the harmonic current limit in the allowable limit is converted, and the formula is as follows: in: The minimum short-circuit capacity of the PCC point. The baseline short-circuit capacity at the PCC point. For the first Permissible value of subharmonic current This is the calculated allowable value for the h-th harmonic current; Among them, the limit of harmonic current injected into the power grid by each user at the same power grid connection point (PCC) is dynamically adjusted according to the agreement capacity and power supply equipment capacity of each user at the same power grid connection point (PCC). Among them, at the same power grid connection point PCC point, the first The first user's Limits of subharmonic current The calculation formula is as follows: in: For the first Electricity capacity agreed upon by each user The power supply capacity of the common connection point. This is the phase superposition coefficient.

[0038] According to an embodiment of the present invention, the online multidimensional index fuzzy matching method further includes: verifying monitoring points that cannot be matched in the fuzzy query matching by using voltage levels; after a successful match, using the bus ID number in the state estimation data as the unique identifier of the corresponding bus node, and establishing a data mapping relationship between the harmonic source monitoring data and the state estimation data.

[0039] The following is a detailed explanation of the above implementation steps S101-S104: Among them, the real-time operating status of the power grid is obtained based on the D5000 power grid dispatch control automation system or the new generation energy management system control cloud sub-platform, which is based on the power grid dispatch control automation system or the new generation energy management system, and the status estimation data is generated. The status estimation data is mainly used for fundamental power flow calculation and analysis in the subsequent implementation process. The harmonic online monitoring data is obtained based on the new generation equipment asset lean management system (PMS3.0), and the harmonic online monitoring data and status estimation data under the same time section are matched using data fusion technology. There are two problematic scenarios with the PMS data: 1. Multiple monitoring devices on the same busbar produce inconsistent data; 2. Key nodes lack monitoring data (due to user failure to maintain or upload data). To address these issues, the acquired monitoring data needs to be cleaned according to the harmonic power flow attenuation patterns within the same substation, and missing values ​​need to be replaced with statistics from devices of the same voltage level and with the same equipment attributes to complete the key node data.

[0040] Specifically, the real-time operating status of the power grid is acquired through the D5000 power grid dispatch control automation system or the new generation energy management system's control cloud sub-platform, which is based on dispatch operation control. This data generates status estimation data, including but not limited to equipment operating status, generator terminal voltage, active and reactive power values ​​of generators and loads, line information, and short-circuit capacity. Its purpose is to obtain the basic model and operating mode of the power grid, the power grid topology, and to perform fundamental power flow calculations.

[0041] Specifically, harmonic online monitoring data is acquired based on the new generation Equipment Asset Lean Management System (PMS3.0), including but not limited to harmonic online monitoring point numbers, monitoring times, minimum and maximum harmonic current values ​​and 95% probability values ​​at different frequencies, and minimum, maximum, and 95% probability values ​​of harmonic voltage at different frequencies. Data fusion technology is used to match harmonic online monitoring data and state estimation data at the same time segment. Taking the control cloud sub-platform as an example, the specific process is as follows: Figure 2 As shown, it includes the following: Fuzzy queries are performed based on the bus names and voltage levels of the monitoring points to conduct preliminary matching between the state estimation data based on the control cloud and the monitoring point data. Unmatched monitoring points are manually verified using electrical wiring diagrams, supplemented by voltage level verification. After matching, the bus ID number in the control cloud is used as the unique identifier of the bus node.

[0042] The specific process for identifying harmonic sources is as follows: Considering that online harmonic monitoring data usually does not directly indicate the type of harmonic source, and that the ledger information in the new generation of lean management system for equipment assets may be incomplete or inconsistent with reality, this invention does not rely on the equipment type registered in the ledger, but rather on the harmonic emission characteristics reflected by the online harmonic monitoring data to perform data-driven online identification of harmonic sources. Specifically, for each online harmonic monitoring point, the harmonic current values ​​at different frequencies (e.g., 3rd, 5th, 7th, 11th, and 13th harmonics) at multiple time sections are used as independent variables, and the corresponding harmonic voltage values ​​are used as dependent variables. A linear regression model is established, and the regression coefficients are solved using the least squares method. The obtained regression coefficients can reflect the emission level of each harmonic at the monitoring point and the harmonic contribution of the monitoring point to the system, and are used as the harmonic emission characteristics of the monitoring point.

[0043] Furthermore, for common types of harmonic sources, such as six-pulse rectifiers, electrified railway traction loads, new energy inverter grid-connected devices, and electric arc furnaces, typical harmonic emission characteristics are statistically analyzed to form a standard harmonic emission characteristic library. The harmonic emission characteristics of each monitoring point obtained from the above fitting are compared with the various categories in the standard harmonic emission characteristic library, and the one with the highest similarity is selected as the candidate harmonic source type for that monitoring point. At the same time, combined with the power grid topology model determined by the state estimation data, i.e., the connection relationship and node admittance relationship between each bus, the bus node corresponding to the candidate harmonic source in the power grid is determined, avoiding misjudgment based on data from a single monitoring point.

[0044] Finally, the identification results are verified using harmonic monitoring type attributes, which include, but are not limited to, current-type or voltage-type monitoring at the monitoring point, and the phase of harmonic source access, such as three-phase symmetrical access or single-phase access. When the harmonic emission mode expected of a candidate harmonic source type is inconsistent with the actual harmonic monitoring type attribute of the monitoring point—for example, if a candidate type should be three-phase symmetrical injection but the monitoring attribute shows single-phase injection—the identification result corresponding to that candidate harmonic source is eliminated. Through the above three steps of linear regression fitting, type comparison and topology location, and type verification, harmonic sources in the power grid can be automatically identified without relying on ledger registration.

[0045] Furthermore, in the online multidimensional index fuzzy matching process, since the harmonic online monitoring data and the state estimation data come from different online systems, their acquisition and transmission cycles may not be consistent. To ensure that the two types of data participating in the matching belong to the same time segment, this invention constructs a multidimensional index key using the bus name, voltage level, and timestamp. Based on the timestamp, the harmonic source monitoring data and state estimation data with timestamps are aligned to the same time segment according to a preset time tolerance, such as 5 minutes or 15 minutes. Then, fuzzy query matching is performed based on the bus name and voltage level, thereby avoiding data mismatch between different time segments.

[0046] Among them, based on the ledger information of the new generation equipment asset lean management system (PMS3.0), the data type of harmonic monitoring is determined to match the data, the harmonic source is automatically identified and online harmonic source modeling is performed according to the specified text format; Specifically, ledger information is obtained based on the new generation Equipment Asset Lean Management System (PMS3.0), including but not limited to the name of the online monitoring object, the status of the monitoring point, the name of the monitoring bus, the name of the associated substation, the type of monitoring equipment, the capacity of the power supply equipment, the user agreement capacity, and the minimum short-circuit capacity. After identifying the harmonic sources in the aforementioned manner, the harmonic sources are modeled online according to the prescribed text format based on the monitoring data obtained in step S101. An HMC card must be filled out for harmonic power flow calculation. The HMC card definition is shown in Table 1. Table 1

[0047] This invention employs a decoupled algorithm for harmonic power flow calculation. The fundamental power flow is solved iteratively using Newton's method, while the harmonic power flow is solved directly using a system of linear equations. The reference short-circuit capacity of the PCC (Power Connection Center) is selected based on its voltage level. The current limit for each harmonic source is allocated according to the ratio of individual user agreement capacity to PCC power supply capacity. The harmonic power flow calculation results are compared to determine if the harmonic current, voltage content, and total distortion rate meet the allowable limits. Based on the comparison between the harmonic power flow calculation results and the allowable limits, three levels of harmonic monitoring and early warning are set according to the needs of the application area: normal, warning, and alarm. While offline calculations result in fixed allowable limits for a specific scenario, the allowable value calculation method described in this invention, although based on national standards, dynamically changes with the system, extracting fundamental power flow data for state estimation and updating the allowable value every 15 minutes. This makes it more accurate for practical engineering applications.

[0048] Specifically, when the minimum short-circuit capacity at the point of common coupling differs from the reference short-circuit capacity, the harmonic current limit must first be converted. The conversion formula is as follows: In the formula: Sk 1 represents the minimum short-circuit capacity of the common junction, in MVA; Sk 2 represents the baseline short-circuit capacity at the point of common coupling, in MVA; I hp For the first h Permissible value of subharmonic current I h For short-circuit capacity is Sk 1 o'clock h Permissible value for subharmonic current.

[0049] The permissible harmonic current injected into the grid by each user at the same point of common coupling is allocated according to the ratio of the user's agreed capacity at that point to the capacity of the power supply equipment at the point of common coupling.i The first user's h Subharmonic current limit Calculate using the following formula: In the formula: I h For the converted number h Permissible value of subharmonic current, A; S i For the first i Electricity consumption agreement capacity per user, MVA; S t The power supply capacity of the common junction point, in MVA; The phase superposition coefficient is selected according to Table 2.

[0050] Table 2

[0051] Compared to existing technologies: This invention considers the impedance characteristics of components at different harmonic frequencies, an adaptive model for transformer connection groups, a distributed parameter model for compatible lines, a practical grid capacitor series reactance model, three-phase harmonic sources, inter-harmonic sources, and imbalance models. The model is updated and iterated rapidly with high accuracy. For example, on April 5, 2025, the Huaneng Lingao offshore wind farm experienced a complete grid disconnection of its 300MW wind turbines due to excessive harmonic voltage distortion. In the accident reproduction using harmonic calculation analysis, the wind turbine impedance characteristics had a significant impact on the system impedance. As the number of wind turbines connected increased, the fifth harmonic characteristic gradually disappeared, while the second harmonic characteristic gradually emerged. By comparing with on-site measured data, the calculation accuracy of the model considering the frequency-varying impedance characteristics of the wind turbines was improved by more than 50%.

[0052] This invention collects real-time power grid operation data for dispatch control and online harmonic monitoring data of power grids in various provinces and cities, automatically identifies harmonic sources and performs online modeling, and matches the real-time operation data update frequency to perform online harmonic analysis and calculation for the entire network under multiple voltage levels, multiple harmonic sources, and multiple time sections. While ensuring the accuracy of the calculation model, it improves the reliability of harmonic power flow calculation results, providing a strong guarantee for supporting actual power grid operation risk assessment, horizontal prediction, accident reproduction, and source tracing analysis.

[0053] This invention is compatible with PSD-BPA and PSASP data formats, which are widely used in domestic power system simulation and analysis software. It can easily and seamlessly connect with dispatching, power research institutes, economic research institutes, and design institutes to quickly simulate large background power grids. It can perform harmonic analysis calculations based on real-time operating data / offline data and online harmonic monitoring data, breaking down the barriers between online data and harmonic analysis, realizing the linkage of online systems, and improving computational efficiency while ensuring the accuracy of model calculations.

[0054] Example 2: Furthermore, this invention also proposes a power grid harmonic analysis and early warning system 300 based on online data, such as... Figure 3 As shown, it includes: The data acquisition unit 301 is used to acquire real-time operating status data associated with the online operation of the power grid, generate state estimation data based on the real-time operating status data, and acquire online harmonic monitoring data. The matching unit 302 is used to fit the online harmonic monitoring data based on multiple attributes and harmonic emission characteristics of multiple types of harmonic sources in the online harmonic monitoring data using a linear regression method to obtain the harmonic emission characteristics of each monitoring point. The harmonic emission characteristics are compared with the harmonic emission characteristics of multiple harmonic sources to obtain identification results. The unit then combines this with the power grid topology model determined by the state estimation data to determine the bus node where the harmonic source is located. The identification results are then verified using the harmonic monitoring type attribute, thereby identifying the harmonic source. Furthermore, the unit acquires timestamped harmonic source monitoring data and matches it with the state estimation data using an online multidimensional index fuzzy matching method to generate a data mapping relationship. The online multidimensional index fuzzy matching method includes: constructing a multidimensional index key using the bus name, voltage level, and timestamp of the monitoring point of the harmonic source; and performing fuzzy query matching on the state estimation data and the harmonic source monitoring data based on the bus name and voltage level, provided that the harmonic source monitoring data and the state estimation data belong to the same time segment. Modeling unit 303 is used to perform online modeling of harmonic sources based on the data mapping relationship and generate a power grid harmonic analysis model; The early warning unit 304 is used to perform harmonic power flow calculation based on the power grid harmonic analysis model to obtain the harmonic power flow calculation results, compare the calculation results with the allowable limits, and determine whether to issue an early warning for power grid harmonics based on the comparison results.

[0055] The calculation unit 305 is used to perform fundamental wave power flow calculation based on the state estimation data, and to solve the fundamental wave power flow calculation by iteratively applying Newton's method.

[0056] The matching unit 302 is also used to: process the harmonic source monitoring data after the harmonic source is identified.

[0057] The matching unit 302 is specifically used to clean up invalid data in the harmonic source monitoring data according to the attenuation law of harmonic power flow within the same substation. After the data cleaning is completed, it is determined whether the harmonic source monitoring data is missing key node data. If it is missing, the missing key node data is supplemented with statistical data of the same voltage level and the same equipment attributes. The invalid data includes: monitoring data of harmonic sources that do not meet the attenuation law of harmonic power flow within the same substation.

[0058] It also includes selecting the reference short-circuit capacity of the PCC point based on the voltage level of the grid connection point, and dynamically adjusting the allowable limit through the ratio of the individual user agreement capacity to the power supply capacity of the PCC point.

[0059] Preferably, the power flow calculation results are compared with the allowable limits, including: The harmonic current value, voltage content rate value, and total distortion rate value in the power flow calculation results are compared with their respective allowable limits to determine whether the harmonic current value, voltage content rate value, and total distortion rate value meet the requirements of their respective allowable limits.

[0060] Preferably, if the reference short-circuit capacity of the PCC point is different from the minimum short-circuit capacity of the PCC point, the harmonic current limit in the allowable limit is converted, as shown in the following formula: in: The minimum short-circuit capacity of the PCC point. The baseline short-circuit capacity at the PCC point. For the first Permissible value of subharmonic current This is the calculated allowable value for the h-th harmonic current; Among them, the limit of harmonic current injected into the power grid by each user at the same power grid connection point (PCC) is dynamically adjusted according to the agreement capacity and power supply equipment capacity of each user at the same power grid connection point (PCC). Among them, at the same power grid connection point PCC point, the first The first user's Limits of subharmonic current The calculation formula is as follows: in: For the first Electricity capacity agreed upon by each user The power supply capacity of the common connection point. This is the phase superposition coefficient.

[0061] Preferably, the matching unit 302 is further configured to: verify the monitoring points that cannot be matched in the fuzzy query matching by using the voltage level; and after a successful match, establish a data mapping relationship between the harmonic source monitoring data and the state estimation data by using the bus ID number in the state estimation data as the unique identifier of the corresponding bus node.

[0062] Example 3: Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the methods in the above embodiments.

[0063] Example 4: Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiments.

[0064] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0065] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0066] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0067] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0068] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0069] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for early warning based on power grid harmonic analysis, characterized in that, include: Acquire real-time operating status data associated with the online operation of the power grid; generate state estimation data based on the real-time operating status data; and acquire online harmonic monitoring data. Based on multiple attributes and harmonic emission characteristics of multiple types of harmonic sources in online harmonic monitoring data, the online harmonic monitoring data is fitted using a linear regression method to obtain the harmonic emission characteristics of each monitoring point. The harmonic emission characteristics are compared with the harmonic emission characteristics of multiple harmonic sources to obtain the identification results. The bus node where the harmonic source is located is determined by combining the power grid topology model determined by the state estimation data. The identification results are then verified using the harmonic monitoring type attribute, thereby identifying the harmonic source. Harmonic source monitoring data with timestamps is acquired, and the timestamped harmonic source monitoring data is matched with state estimation data based on online multidimensional index fuzzy matching to generate a data mapping relationship; The online multidimensional index fuzzy matching method includes: constructing a multidimensional index key using the bus name, voltage level, and timestamp of the monitoring point of the harmonic source; and performing fuzzy query matching on the state estimation data and the harmonic source monitoring data based on the bus name and voltage level, provided that the harmonic source monitoring data and the state estimation data belong to the same time segment. Based on the data mapping relationship, online modeling of harmonic sources is performed to generate a power grid harmonic analysis model; Harmonic power flow calculations are performed based on the power grid harmonic analysis model to obtain harmonic power flow calculation results. The calculation results are compared with allowable limits, and based on the comparison results, it is determined whether to issue an early warning for power grid harmonics.

2. The method according to claim 1, characterized in that, It also includes calculating the fundamental wave power flow based on the state estimation data, and solving the fundamental wave power flow calculation by iteratively applying Newton's method.

3. The method according to claim 1, characterized in that, The method further includes: after identifying the harmonic source, performing data processing on the harmonic source monitoring data, including: Based on the attenuation law of harmonic power flow within the same substation, invalid data in the harmonic source monitoring data is cleaned. After the data cleaning is completed, it is determined whether the harmonic source monitoring data is missing key node data. If it is missing, the missing key node data is supplemented with statistical data of the same voltage level and the same equipment attributes. The invalid data includes: monitoring data of harmonic sources that do not meet the attenuation law of harmonic power flow within the same substation.

4. The method according to claim 1, characterized in that, It also includes selecting the reference short-circuit capacity of the PCC point based on the voltage level of the grid connection point, and dynamically adjusting the allowable limit through the ratio of the individual user agreement capacity to the power supply capacity of the PCC point.

5. The method according to claim 1, characterized in that, The calculation results are compared with the allowable limits, including: The harmonic current value, voltage content rate value, and total distortion rate value in the calculation results are compared with their respective allowable limits to determine whether the harmonic current value, voltage content rate value, and total distortion rate value meet the requirements of their respective allowable limits.

6. The method according to claim 4, characterized in that, If the reference short-circuit capacity at the PCC point differs from the minimum short-circuit capacity at the PCC point, then the harmonic current limit in the allowable limits should be converted using the following formula: in: The minimum short-circuit capacity of the PCC point. The baseline short-circuit capacity at the PCC point. For the first Permissible value of subharmonic current This is the calculated allowable value for the h-th harmonic current; Among them, the limit of harmonic current injected into the power grid by each user at the same power grid connection point (PCC) is dynamically adjusted according to the agreement capacity and power supply equipment capacity of each user at the same power grid connection point (PCC). Among them, at the same power grid connection point PCC point, the first The first user's Limits of subharmonic current The calculation formula is as follows: in: For the first Electricity capacity agreed upon by each user The power supply capacity of the common connection point. This is the phase superposition coefficient.

7. The method according to claim 1, characterized in that, The online multidimensional index fuzzy matching method also includes: For monitoring points that cannot be matched in the fuzzy query matching, the voltage level is used for verification; after a successful match, the bus ID number in the state estimation data is used as the unique identifier of the corresponding bus node to establish a data mapping relationship between the harmonic source monitoring data and the state estimation data.

8. The method according to claim 1, characterized in that, The method of fitting the online harmonic monitoring data using linear regression to obtain the harmonic emission characteristics of each monitoring point includes: For each monitoring point, a linear regression model is established using the harmonic current values ​​of different frequencies at multiple time sections as independent variables and the corresponding harmonic voltage values ​​as dependent variables. The regression coefficients of the linear regression model are then solved, and these regression coefficients are used as the harmonic emission characteristics of the monitoring point. These harmonic emission characteristics are used to characterize the emission level of each harmonic at the monitoring point.

9. The method according to claim 1, characterized in that, The identification of harmonic sources includes: The harmonic emission characteristics of each monitoring point are compared with the harmonic emission characteristics of a variety of preset harmonic sources, and the type with the highest similarity is selected as the candidate harmonic source for each monitoring point. Based on the bus connection relationships represented by the power grid topology model determined by the state estimation data, the bus node to which the candidate harmonic source belongs in the power grid is determined.

10. The method according to claim 9, characterized in that, The verification of the identification results using harmonic monitoring type attributes includes: Obtain the harmonic monitoring type attribute for each monitoring point, wherein the harmonic monitoring type attribute includes at least one of current-type monitoring, voltage-type monitoring, and harmonic source access phase; When the candidate harmonic source does not match the harmonic monitoring type attribute, the identification result corresponding to the candidate harmonic source is removed.

11. The method according to claim 1, characterized in that, The method of matching the timestamped harmonic source monitoring data with state estimation data based on online multidimensional index fuzzy matching also includes: Based on the timestamp in the multidimensional index key, the timestamped harmonic source monitoring data and the state estimation data are aligned to the same time section according to a preset time tolerance, and fuzzy query matching is performed based on the bus name and voltage level.

12. A system for early warning based on power grid harmonic analysis, characterized in that, include: The data acquisition unit is used to acquire real-time operating status data associated with the online operation of the power grid, generate state estimation data based on the real-time operating status data, and acquire online harmonic monitoring data. The matching unit is used to fit the online harmonic monitoring data based on multiple attributes and harmonic emission characteristics of multiple types of harmonic sources in the online harmonic monitoring data using a linear regression method to obtain the harmonic emission characteristics of each monitoring point. The harmonic emission characteristics are compared with the harmonic emission characteristics of multiple harmonic sources to obtain the identification results. The unit also combines the power grid topology model determined by the state estimation data to determine the bus node where the harmonic source is located. Finally, the identification results are verified using the harmonic monitoring type attribute to identify the harmonic source. Harmonic source monitoring data with timestamps is acquired, and the timestamped harmonic source monitoring data is matched with state estimation data based on online multidimensional index fuzzy matching to generate a data mapping relationship; The online multidimensional index fuzzy matching method includes: constructing a multidimensional index key using the bus name, voltage level, and timestamp of the monitoring point of the harmonic source; and performing fuzzy query matching on the state estimation data and the harmonic source monitoring data based on the bus name and voltage level, provided that the harmonic source monitoring data and the state estimation data belong to the same time segment. The modeling unit is used to perform online modeling of harmonic sources based on the data mapping relationship and generate a power grid harmonic analysis model. The early warning unit is used to perform harmonic power flow calculation based on the power grid harmonic analysis model to obtain the harmonic power flow calculation results, compare the calculation results with the allowable limits, and determine whether to issue an early warning for power grid harmonics based on the comparison results.

13. The system according to claim 12, characterized in that, It also includes a computing unit for performing fundamental wave power flow calculation based on the state estimation data, and solving the fundamental wave power flow calculation by iteratively applying Newton's method.

14. The system according to claim 12, characterized in that, The matching unit is further configured to: after identifying the harmonic source, perform data processing on the harmonic source monitoring data. The matching unit is also used for: Based on the attenuation law of harmonic power flow within the same substation, invalid data in the harmonic source monitoring data is cleaned. After the data cleaning is completed, it is determined whether the harmonic source monitoring data is missing key node data. If it is missing, the missing key node data is supplemented with statistical data of the same voltage level and the same equipment attributes. The invalid data includes: monitoring data of harmonic sources that do not meet the attenuation law of harmonic power flow within the same substation.

15. The system according to claim 12, characterized in that, It also includes selecting the reference short-circuit capacity of the PCC point based on the voltage level of the grid connection point, and dynamically adjusting the allowable limit through the ratio of the individual user agreement capacity to the power supply capacity of the PCC point.

16. The system according to claim 12, characterized in that, The calculation results are compared with the allowable limits, including: The harmonic current value, voltage content rate value, and total distortion rate value in the calculation results are compared with their respective allowable limits to determine whether the harmonic current value, voltage content rate value, and total distortion rate value meet the requirements of their respective allowable limits.

17. The system according to claim 15, characterized in that, If the reference short-circuit capacity at the PCC point differs from the minimum short-circuit capacity at the PCC point, then the harmonic current limit in the allowable limits should be converted using the following formula: in: The minimum short-circuit capacity of the PCC point. The baseline short-circuit capacity at the PCC point. For the first Permissible value of subharmonic current This is the calculated allowable value for the h-th harmonic current; Among them, the limit of harmonic current injected into the power grid by each user at the same power grid connection point (PCC) is dynamically adjusted according to the agreement capacity and power supply equipment capacity of each user at the same power grid connection point (PCC). Among them, at the same power grid connection point PCC point, the first The first user's Limits of subharmonic current The calculation formula is as follows: in: For the first Electricity capacity agreed upon by each user The power supply capacity of the common connection point. This is the phase superposition coefficient.

18. The system according to claim 12, characterized in that, The matching unit is also used to: verify monitoring points that cannot be matched in the fuzzy query matching by using voltage level; after a successful match, establish a data mapping relationship between the harmonic source monitoring data and the state estimation data by using the bus ID number in the state estimation data as the unique identifier of the corresponding bus node.

19. The system according to claim 12, characterized in that, The matching unit is also used for, Using the harmonic current values ​​of different frequencies at multiple time sections of the monitoring point as independent variables and the harmonic voltage values ​​of the corresponding frequencies as dependent variables, a linear regression model is established and the regression coefficients of the linear regression model are solved. The regression coefficients are then used as the harmonic emission characteristics of the monitoring point. The harmonic emission characteristics are used to characterize the emission level of each harmonic at the monitoring point; The harmonic emission characteristics of each monitoring point are compared with the harmonic emission characteristics of a variety of preset harmonic sources, and the type with the highest similarity is selected as the candidate harmonic source for each monitoring point. Based on the bus connection relationship represented by the power grid topology model determined by the state estimation data, the bus node to which the candidate harmonic source belongs in the power grid is determined. as well as Obtain the harmonic monitoring type attribute for each monitoring point, wherein the harmonic monitoring type attribute includes at least one of current-type monitoring, voltage-type monitoring, and harmonic source access phase; When the candidate harmonic source does not match the harmonic monitoring type attribute, the identification result corresponding to the candidate harmonic source is removed.

20. The system according to claim 12, characterized in that, The matching unit is also used for, Based on the timestamp in the multidimensional index key, the timestamped harmonic source monitoring data and the state estimation data are aligned to the same time section according to a preset time tolerance, and fuzzy query matching is performed based on the bus name and voltage level.

21. A computer device, characterized in that, include: One or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described in any one of claims 1-11 is implemented.

22. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the method as described in any one of claims 1-11.

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