Online monitoring system and method of distribution station room based on big data

Abstract

The present invention relates to the field of distribution station monitoring technology, and specifically discloses an online monitoring system and method for distribution station based on big data, the method comprising: a power quality assessment module, a power balance analysis module, a distribution station intelligent scheduling module and a distribution station database. The present invention reduces harmonic pollution by evaluating and analyzing harmonics in the power system, ensures the stability and reliability of power supply, timely discovers and protects electrical equipment, extends its service life, and effectively reduces grid losses, thereby ensuring the safe and stable operation of the power system. At the same time, the distribution station is adjusted through the intelligent scheduling indicators of the distribution station, reducing the volatility and uncertainty of new energy power generation, ensuring the stable operation of the power grid, and helping to smooth the power generation fluctuations of new energy through the energy storage system, improving the utilization efficiency of electric energy, and providing auxiliary services when needed, thereby enhancing the flexibility and reliability of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution station room monitoring, and in particular to a power distribution station room online monitoring system and method based on big data. Background Art

[0002] With the development of social economy, the demand for electricity is growing, and higher requirements are placed on the reliability, safety and efficiency of the power grid. As an important part of the power system, the operating status of the distribution station room directly affects the quality and stability of power supply. The widespread access to new energy sources such as solar energy and wind energy has changed the operation mode and load characteristics of the power grid. The intermittent and uncertain nature of new energy requires distribution stations to have stronger regulation capabilities and adaptability.

[0003] For example, the invention patent with announcement number: CN112800212B discloses a distribution station health assessment method based on knowledge graph and FAHP. Based on the distribution station knowledge graph, the status characteristics of equipment and indicators are set to obtain the subjective weights of equipment and indicators under different circumstances; it proposes to construct a degradation function combining linear and exponential to describe the degree of deviation of the indicator and calculate the objective weight of the dynamic change of the indicator; the combined weighting method is used to obtain the combined weight that includes both subjective and objective influences, and the improved combined weight based on the knowledge graph is obtained after the failure rate is introduced to optimize the combined weight; according to the constructed membership matrix and the improved combined weight, a fuzzy comprehensive evaluation is performed to obtain the evaluation matrix of each layer, and the evaluation score is obtained according to the maximum membership principle, and the health status of the distribution station is determined according to the evaluation score; the present disclosure uses the knowledge graph to construct a distribution station equipment indicator system, obtains the combined weight including subjective and objective influencing factors, and introduces the failure rate to correct the combined weight, and obtains the improved combined weight based on the knowledge graph, thereby improving the accuracy of the evaluation results.

[0004] For example, the invention patent with announcement number: CN116186361B discloses a method for collecting, analyzing and processing distribution station monitoring information based on big data. The method includes detector deployment and information acquisition, detector monitoring priority analysis, detector monitoring information acquisition, distribution station status analysis and judgment, detector monitoring information review acquisition, distribution station status review analysis, distribution station status review judgment and dangerous status warning. By monitoring and analyzing the status corresponding to each monitoring position in the target monitoring distribution transformer station, the limitations and one-sidedness of the current technology are solved, and the intelligent and automated monitoring and analysis of sulfur hexafluoride gas in the distribution station is realized, which effectively ensures the pertinence and scientific nature of the detector monitoring data, and also eliminates the deviation of the monitoring data caused by detector failure, greatly improving the safety of the environment in the distribution station.

[0005] Based on the above solution, it is found that there are still some deficiencies in the monitoring of distribution station rooms. Specifically, the overcurrent protection data processing of the power system is not comprehensive enough, which may cause the temperature of the power equipment to rise, accelerate the aging of the equipment and reduce its life span, and may cause mechanical damage to the equipment. As a result, the power system cannot effectively isolate faults when encountering overload or short circuit, affecting the stability and reliability of the entire system. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides an online monitoring system and method for a distribution station room based on big data, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an online monitoring system for a distribution station room based on big data, including: a power quality assessment module, which is used to monitor the harmonic data of the distribution station room and obtain the power quality assessment parameters of the power system after processing.

[0008] Furthermore, the harmonic data and abnormal power data of the distribution station room are monitored, and power quality assessment parameters are obtained after processing. The specific analysis process is: power data of harmonic frequencies are collected according to a preset time period, and fundamental wave data are extracted from the distribution station room database, and the harmonic voltages and harmonic currents of each harmonic are obtained by processing. The abnormal degree value of the harmonic content of the distribution station room is obtained by comprehensive analysis, and the abnormal degree value of the harmonic content of the distribution station room and the total harmonic voltage distortion rate are comprehensively analyzed to obtain the power quality assessment parameters of the power system.

[0009] The power balance analysis module is used to analyze the overcurrent protection data of the power system and obtain the power balance index of the distribution station room after processing.

[0010] Furthermore, the overcurrent protection data of the power system is analyzed and processed to obtain the power balance index of the distribution station room. The specific analysis process is: the number of overcurrent protection actions in the distribution station room and the actual action current of each overcurrent protection are monitored, and the power balance index of the distribution station room is obtained by comprehensive analysis.

[0011] The intelligent dispatching module of the distribution station room is used to obtain the intelligent dispatching index of the distribution station room according to the comprehensive analysis of the power quality evaluation parameters of the power system and the power balance degree index of the distribution station room, and obtain the power quality evaluation parameter interval of the power system according to the analysis and processing, compare the intelligent dispatching index of the distribution station room with the power quality evaluation parameter interval of the power system, and perform intelligent dispatching of the distribution station room according to the comparison results.

[0012] Specifically, the analysis and processing obtains the power quality assessment parameter interval of the power system, and the specific analysis process is: extracting the reference standard power quality assessment parameters and the allowable deviation power quality assessment parameters from the distribution station room database, performing difference operation and sum operation on the reference standard power quality assessment parameters and the allowable deviation power quality assessment parameters respectively, and marking the difference result as the lower limit of the power quality assessment parameter interval, marking the sum result as the upper limit of the power quality assessment parameter interval, and processing to obtain the power quality assessment parameter interval.

[0013] Furthermore, the intelligent dispatching index of the distribution station room is compared with the power quality assessment parameter interval of the power system, and the distribution station room is intelligently dispatched according to the comparison result. The specific analysis process is: compare the power quality assessment parameter of the power system with the power quality assessment parameter interval of the power system. If the power quality assessment parameter of the power system is less than the upper limit of the power quality assessment parameter interval and is greater than or equal to the lower limit of the power quality assessment parameter interval, then maintain the current operation state of the distribution station room; if the power quality assessment parameter of the power system is less than the lower limit of the power quality assessment parameter interval or is greater than or equal to the upper limit of the power quality assessment parameter interval, then control the distribution station room.

[0014] Furthermore, the power quality assessment parameters of the power system are quantitative assessment data obtained by analyzing the abnormal degree of harmonic content and total harmonic voltage distortion rate of the distribution station room, which are used to quantitatively assess the power quality and provide a basis for the intelligent scheduling indicators of the distribution station room.

[0015] Furthermore, the intelligent dispatching index of the distribution station room is a quantitative evaluation data obtained through a comprehensive analysis of the power quality evaluation parameters of the power system and the power balance index of the distribution station room, which is used to quantitatively evaluate the conditions for dispatching the distribution station room and provide a basis for intelligent dispatching of the distribution station room.

[0016] Furthermore, the power quality evaluation parameter of the power system is specifically expressed as:

[0017]

[0018] In the formula, G M represents the power quality assessment parameter of the power system, e represents the natural constant, X represents the abnormal degree of harmonic content in the distribution station room, D represents the total harmonic voltage distortion rate, n=2,3,4,...,N, N represents the upper limit of harmonic order, V n It represents the effective value of the nth harmonic voltage, V1 represents the fundamental voltage, Indicates the power quality impact factor corresponding to the abnormal degree of harmonic content in the set distribution station room. Indicates the power quality impact factor corresponding to the set total harmonic voltage distortion rate.

[0019] Furthermore, the specific numerical expression of the intelligent dispatching index of the distribution station room is:

[0020]

[0021] In the formula, represents the intelligent dispatching index of the distribution station room, G M Represents the power quality assessment parameter of the power system, G W It represents the power balance index of the distribution station room, ρ1 represents the influence factor of the intelligent dispatching index of the distribution station room corresponding to the set power quality assessment parameter of the power system, and ρ2 represents the influence factor of the intelligent dispatching index of the distribution station room corresponding to the set power balance index of the distribution station room.

[0022] Furthermore, the online monitoring method for distribution station room based on big data is characterized by: including: monitoring the harmonic data of the distribution station room, and obtaining the power quality evaluation parameters of the power system after processing; analyzing the overcurrent protection data of the power system, and obtaining the power balance degree index of the distribution station room after processing; obtaining the intelligent dispatching index of the distribution station room according to the comprehensive analysis of the power quality evaluation parameters of the power system and the power balance degree index of the distribution station room, and obtaining the power quality evaluation parameter interval of the power system according to the analysis and processing, comparing the intelligent dispatching index of the distribution station room with the power quality evaluation parameter interval of the power system, and performing intelligent dispatching of the distribution station room according to the comparison result.

[0023] The second aspect of the present invention provides an online monitoring method for a distribution station room based on big data, comprising: monitoring the harmonic data of the distribution station room, and obtaining power quality evaluation parameters of the power system after processing.

[0024] The overcurrent protection data of the power system is analyzed and processed to obtain the power balance index of the distribution station room.

[0025] Based on the comprehensive analysis of the power quality assessment parameters of the power system and the power balance index of the distribution station, the intelligent dispatching index of the distribution station is obtained, and the power quality assessment parameter range of the power system is obtained according to the analysis and processing. The intelligent dispatching index of the distribution station is compared with the power quality assessment parameter range of the power system, and the distribution station is intelligently dispatched according to the comparison results.

[0026] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0027] (1) The present invention provides an online monitoring system and method for a distribution station room based on big data, which can quickly collect various operating data of the distribution station room, and regulate the power generation of new energy based on the control indicators obtained through analysis, so as to reasonably allocate resources and avoid waste of resources, which is helpful to improve the operating efficiency, safety and reliability of the power system.

[0028] (2) The present invention reduces harmonic pollution by evaluating and analyzing harmonics in the power system, ensures the stability and reliability of power supply, timely detects and protects electrical equipment, and extends its service life. It can effectively reduce grid losses and save energy, thereby ensuring safe and stable operation of the power system.

[0029] (3) The present invention analyzes the overcurrent protection data of the power system to prevent the equipment from overheating due to overcurrent, protect the equipment from damage, avoid electrical fires, improve system stability, extend equipment life, and improve the reliability of the power system, thereby optimizing the operation of the power system and improving the system efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0031] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0032] Figure 2 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0033] The technical solutions 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, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0034] Reference Figure 1 As shown, the first aspect of the present invention provides an online monitoring system for a distribution station room based on big data, including: a power quality assessment module for monitoring the harmonic data of the distribution station room and obtaining power quality assessment parameters of the power system after processing.

[0035] Specifically, the harmonic data of the distribution station room is monitored and processed to obtain the power quality assessment parameters of the power system. The specific analysis process is: the power data of the harmonic frequency is collected according to a preset time period, and the fundamental wave data is extracted from the distribution station room database, and the harmonic voltage and harmonic current of each harmonic are processed to obtain the abnormal degree value of the harmonic content of the distribution station room. The abnormal degree value of the harmonic content of the distribution station room and the total harmonic voltage distortion rate are comprehensively analyzed to obtain the power quality assessment parameters of the power system.

[0036] Furthermore, the specific numerical expression of the abnormal degree value of the harmonic content of the distribution station room is:

[0037]

[0038] Where X represents the abnormal degree of harmonic content in the distribution station room, n represents the number of each harmonic, n = 2, 3, 4, ..., N, N represents the upper limit of the harmonic number, V n Indicates the effective value of the nth harmonic voltage, L n represents the effective value of the nth harmonic current, γ represents the harmonic distortion rate, ΔV n Indicates the set nth harmonic voltage critical value, ΔL n represents the set critical value of the nth harmonic current, Δγ represents the set critical harmonic distortion rate, σ1 represents the harmonic content abnormal impact factor corresponding to the set harmonic voltage, σ2 represents the harmonic content abnormal impact factor corresponding to the set harmonic current, and σ3 represents the harmonic content abnormal impact factor corresponding to the set harmonic distortion rate.

[0039] In a specific embodiment, the abnormal degree value of the harmonic content can be obtained not only by the above formula, but also by monitoring the harmonic content in real time through the monitoring equipment installed in the power system, and comparing it with the historical data to evaluate the change trend and abnormal degree of the harmonic content. It can also be obtained by using voltage or current sampling equipment (such as current sensor, voltage transformer, etc.) to obtain the voltage or current signal in the power system. Then, the sampling signal is subjected to Fourier transform (FFT) analysis using a digital signal processor (DSP) or computer software to determine the frequency, amplitude and phase of the harmonic, and the abnormal degree value of the harmonic content is obtained by comprehensive analysis.

[0040] In a specific embodiment, the harmonic content abnormality value is a quantitative evaluation data obtained by comprehensive analysis of the harmonic order, harmonic voltage, harmonic current and harmonic distortion rate, which is used to quantitatively evaluate the power quality and provide a basis for the power quality evaluation parameters.

[0041] It needs to be explained that collecting harmonic data is a complex process that generally includes: Using a power quality analyzer, which can automatically detect and display the harmonic order. Collection of harmonic voltage and harmonic current: Install voltage and current sensors and ensure that they match the power system. Connect the sensors to the data acquisition system and ensure that the sampling rate is high enough to accurately capture the harmonic components. Configure the appropriate channels and sampling rate in the data acquisition system to collect analog signals of voltage and current. Use the Fourier transform algorithm to analyze the collected signals and separate the voltage and current values ​​of each harmonic component. Collection of harmonic distortion: Harmonic distortion is usually evaluated by calculating the total harmonic distortion (THD), which is determined by the relative amplitude of the harmonic voltage and current. Use a power quality analyzer, which can directly measure and display the THD value.

[0042] It should be explained that, in this embodiment, the distribution station room database refers to a database system used to store and manage distribution station related data. The distribution station is an important component of the power system, and is mainly responsible for the last stage of the process of transmitting the electric energy generated by the power plant to the user, including functions such as voltage reduction, distribution and control of electric energy. The distribution station room database usually contains various information such as equipment information, operation data, maintenance records, power load data, etc. of the distribution station. This database plays an important role in the normal operation, operation monitoring, troubleshooting, equipment maintenance and optimized operation of the distribution station. Through the database, the operating status of the distribution station can be monitored in real time, faults can be discovered and handled in time, and the reliability and efficiency of power supply can be improved. At the same time, analysis and prediction can also be carried out based on historical data to provide a scientific basis for the planning, design and operation of the distribution network.

[0043] It should be explained that in this embodiment, the parameter of the critical value of each harmonic voltage represents the maximum value of each harmonic voltage component allowed to exist at a specific node or measurement point in the power system. Harmonic voltage is the voltage distortion caused by the non-sinusoidal current generated by non-linear loads (such as inverters, rectifiers, switching power supplies, etc.) during operation and injected into the power grid, and interacting with the system impedance. The critical values ​​of each harmonic voltage are usually set separately for harmonics of different orders. For example, the critical value of the nth harmonic voltage may be expressed as a percentage of the fundamental voltage, such as 0.5%, 1.0%, etc. These values ​​reflect the highest harmonic voltage level that the node can withstand without affecting the normal operation of the power equipment, causing system failures, and causing serious deterioration of the power quality. The parameter of the critical value of each harmonic current represents the maximum value of each harmonic current allowed to flow at a certain connection point or device terminal in the power grid. Similar to the harmonic voltage, the critical value of the harmonic current is also set for each specific harmonic order, and is usually expressed as a percentage of the fundamental current. Harmonic currents exceeding these critical values ​​may cause problems such as increased grid losses, equipment overheating, malfunction of protection devices, and communication interference.

[0044] Ways to obtain the critical values ​​of each harmonic voltage and each harmonic current: National standards and industry specifications: Countries and regions will formulate standards for power system harmonic management, such as IEEE Std.519, IEC 61000 series standards, GB / T14549 (China), ANSI C84.1 (USA), etc. These standards clearly stipulate the allowable harmonic voltage limits (currents) for different levels of power grids and different types of load access points. Equipment manufacturer requirements: Some sensitive equipment or precision instruments may have more stringent requirements for the quality of their power supply. Equipment manufacturers will provide the allowable harmonic voltage tolerance range (current) in the product manual as a basis for determining the critical value of harmonic voltage (current). Power supply contract: For large industrial users or special users, the power supply contract signed between the power supplier and the power user may contain specific terms regarding power quality, including the allowable harmonic voltage level (current).

[0045] Table 1 Example of typical critical values ​​of harmonic voltage and current in power system

[0046]

[0047] It should be explained that in this embodiment, the critical harmonic distortion rate (CHDR) refers to the maximum harmonic distortion level allowed in the power system. Exceeding this threshold may cause equipment failure, reduced grid stability, reduced energy efficiency and other problems. In practical applications, the critical harmonic distortion rate is mainly used as an indicator to measure the severity of harmonic pollution and to guide the implementation of harmonic control measures. The critical harmonic distortion rate can be obtained by: national and regional standards: refer to the power quality standards, power system operation procedures, grid access regulations, etc. of the country or region where the critical harmonic distortion rate is obtained. These documents usually specify the critical harmonic distortion rate under different voltage levels, grid types, access point locations and other conditions. For example, China's "Power Quality Public Grid Harmonics" (GBT14549-1993) provides the public grid harmonic voltage limits and harmonic current allowable values, and indirectly gives the limits on the harmonic distortion rate. Industry standards or specifications: For specific industries (such as chemicals, metallurgy, data centers, etc.) or specific electrical equipment (such as inverters, uninterruptible power supplies, etc.), there may be special industry standards or specifications that specify the critical harmonic distortion rate applicable to the industry or equipment. These standards often take into account industry characteristics and equipment sensitivity, and put forward more stringent requirements for harmonic pollution control. Equipment manufacturer recommendations: In product manuals, technical specifications, or application guides, equipment manufacturers usually recommend or require the level of harmonic distortion rate to be maintained when their equipment is connected to the power grid to ensure the normal operation and life of the equipment. Following the equipment manufacturer's recommendations can help avoid equipment damage or performance degradation caused by harmonic problems. Project contracts or agreements: In large-scale power projects, distributed energy access, and power supply agreements between users and power grid companies, the critical harmonic distortion rate may be clearly specified as the basis for the division of responsibilities, performance assessment, or fee settlement between the two parties. For ease of explanation, the following is a reasonable example value for assigning the critical harmonic distortion rate (CHDR): Critical harmonic voltage distortion rate (CHDv): Assume that for a 400V low-voltage power distribution system, according to relevant standards or empirical values, its critical harmonic voltage distortion rate is set to 5%, that is, CHDv = 5%.

[0048] It should be understood that in this embodiment, the harmonic content abnormal impact factor (HVIF) corresponding to the harmonic voltage may be derived from the calculation results of the power system simulation software, experimental test data, expert experience judgment, etc. In the absence of specific standards or literature references, the degree of influence of harmonic voltage on system stability, equipment life, power quality, etc. can be quantitatively evaluated through subjective assignment, weighting method and hierarchical analysis method, etc., and the assignment example is: HVIF = 0.75. The harmonic content abnormal impact factor (HCIF) corresponding to the harmonic current, similarly, HCIF may be derived from simulation analysis, experimental data or expert evaluation, and its purpose is to measure the potential impact of harmonic current on system loss, equipment heating, protection device action and other phenomena. Its assignment example is: HCIF = 0.60. The harmonic content abnormal impact factor (HDIF) corresponding to the harmonic distortion rate can be obtained from the real-time monitoring data of the power quality monitoring system, historical data analysis, or the evaluation of the overall harmonic pollution degree of the system based on the power quality standard (such as THD <596). It reflects the overall impact of harmonic distortion on system efficiency, power quality indicators and equipment performance. An example of an assignment is: HDIF = 0.80.

[0049] Furthermore, the power quality evaluation parameter of the power system is specifically expressed as:

[0050]

[0051] In the formula, G M represents the power quality assessment parameter of the power system, e represents the natural constant, X represents the abnormal degree of harmonic content in the distribution station room, D represents the total harmonic voltage distortion rate, n=2,3,4,...,N, N represents the upper limit of harmonic order, V n It represents the effective value of the nth harmonic voltage, V1 represents the fundamental voltage, Indicates the power quality impact factor corresponding to the abnormal degree of harmonic content in the set distribution station room. Indicates the power quality impact factor corresponding to the set total harmonic voltage distortion rate.

[0052] It should be explained that, in this embodiment, the actual voltage and current of the power system refer to the voltage and current values ​​actually measured in the power system. These values ​​can be alternating current (AC) or direct current (DC), and are usually measured at specific measurement points, such as at distribution stations, transmission lines, transformers or user ends. The values ​​of actual voltage and current will change with time, load conditions, equipment status and grid operation status. The relationship between actual voltage and current and fundamental voltage is as follows: Fundamental voltage: Fundamental voltage refers to the sinusoidal component of the voltage waveform in the power system, which is the most basic component of all voltage components. The amplitude and phase of the fundamental voltage are the most basic information to describe the voltage waveform. Actual voltage: The actual voltage may be the fundamental voltage, or it may be the superposition of the fundamental voltage and other frequency voltages (harmonic voltages). Ideally, if there are no harmonics in the power system, the actual voltage is equal to the fundamental voltage. However, in actual power systems, due to the presence of loads and nonlinear devices, the voltage usually contains harmonic components, so the actual voltage will be greater than the fundamental voltage. Current and fundamental current: Similar to voltage, fundamental current refers to the sinusoidal component of the current waveform, while the actual current may be the superposition of fundamental current and other frequency currents (harmonic currents). Similarly, the actual current is usually greater than the fundamental current because the current is also affected by harmonics.

[0053] In a specific embodiment, the power quality evaluation parameters of the power system can be obtained not only by the above formula, but also by using power quality analysis instruments and software, such as power analyzers, spectrum analyzers, etc., to monitor and analyze the power quality in real time or regularly, and can also be obtained by analyzing steady-state power quality and transient power quality. Steady-state power quality refers to the quality of the power system under stable operation, and transient power quality refers to the response capability of the power system when it is disturbed or fails.

[0054] In a specific embodiment, the power quality assessment parameters of the power system are quantitative assessment data obtained by comprehensive analysis of the abnormal degree of harmonic content and total harmonic voltage distortion rate of the distribution station room, which are used to quantitatively assess the power quality and provide a basis for the intelligent scheduling indicators of the distribution station room.

[0055] It should be explained that the power quality assessment parameters of the power system in this embodiment can not only be obtained by applying various algorithms (such as machine learning, artificial intelligence, statistical analysis, etc.) to identify the anomalies of voltage and current signals. These algorithms can judge anomalies based on historical data, preset thresholds, or statistical characteristics of signals. It is also possible to monitor voltage and current values ​​in real time by installing voltage transformers (VT) and current transformers (CT) in the power system. These transformers convert high voltage and high current into low voltage and low current that can be safely measured, and then transmit them to the measuring equipment, and then analyze the measured data to obtain abnormal values.

[0056] It should be explained that the power quality impact factor corresponding to the abnormal degree value of the harmonic content of the set distribution station room can be obtained by monitoring the harmonic content in the power system, calculating the abnormal degree of the harmonic content, and comparing it with the normal value, and by analyzing the power quality data in the power system, calculating the abnormal degree of the power quality, and comparing it with the normal value, so as to determine the size of the value. For example: the power quality impact factor corresponding to the abnormal degree value of the harmonic sum is assigned a value of 0.5, indicating that the value is 50% of the normal value. The power quality impact factor corresponding to the total harmonic voltage distortion rate can be obtained by the following ways: by monitoring the power quality parameters in the power system (such as voltage deviation, current imbalance, etc.), calculating the abnormal degree of the power quality and comparing it with the normal value, and by analyzing the power quality data in the power system, calculating the abnormal value of the power quality, and comparing it with the normal value, so as to determine the size of the value. For example: the power quality impact factor corresponding to the total harmonic voltage distortion rate is assigned a value of 0.8, indicating that the value is 80% of the normal value. It should be noted that these assignments are only examples and actual assignments should be made based on actual conditions.

[0057] The power balance analysis module is used to analyze the overcurrent protection data of the power system and obtain the power balance index of the distribution station room after processing.

[0058] Specifically, the overcurrent protection data of the power system is analyzed, and the power balance index of the distribution station is obtained after processing. The specific analysis process is: the number of overcurrent protection actions in the distribution station and the actual action current of each overcurrent protection are monitored, and the power balance index of the distribution station is obtained through comprehensive analysis.

[0059] It should be explained that the overcurrent protection data of the power system in this embodiment is obtained by detecting the real-time monitoring system, specifically, the number of protection actions is tracked in real time through the interface of the protection device or the integrated monitoring system. These systems usually have a graphical user interface (GUI) that can intuitively display the real-time data and historical records of the protection actions.

[0060] Furthermore, the power balance index of the distribution station room is specifically expressed as:

[0061]

[0062] In the formula, G W It indicates the power balance index of the distribution substation room, h indicates the overcurrent protection action number of each distribution substation room, h=1,2,3,...,H, H indicates the total number of overcurrent protection actions, h 0 Indicates the number of critical overcurrent protection actions set for the distribution station room, L β→h Indicates the actual operating current of the hth overcurrent protection, It represents the actual action current of the set critical overcurrent protection, θ1 represents the influence factor of the power balance index of the distribution station room corresponding to the preset number of overcurrent protection actions of the distribution station room, and θ2 represents the influence factor of the power balance index of the distribution station room corresponding to the actual action current of the overcurrent protection of the preset distribution station room.

[0063] It should be explained that, in this embodiment, the two parameters of the power balance index influence factor of the distribution station room corresponding to the number of overcurrent protection actions and the power balance index influence factor of the distribution station room corresponding to the actual action current of the overcurrent protection are usually obtained from the real-time monitoring data, historical records and related equipment configuration information of the power system. The number of overcurrent protection actions of the distribution station room in the past period of time is collected through the power monitoring system, and analyzed in combination with the rated capacity, load characteristics and other factors of the station. The power balance index influence factor of the distribution station room corresponding to the number of overcurrent protection actions can be obtained, and its assignment example is: if a distribution station room has overcurrent protection actions 5 times in the past month, and the rated capacity of the station room is 1000kVA, and the normal load rate is about 80%, then the degree of influence of its power balance on the overcurrent protection action can be preliminarily evaluated. For example, if the evaluation result shows that the overcurrent protection action has little effect on the power balance, the power balance index influence factor of the distribution station room corresponding to the number of overcurrent protection actions can be assigned 0.1; if the impact is large, it can be assigned 0.5 or higher. The actual operating current of each overcurrent protection action is recorded through the power monitoring system, and analyzed in combination with the rated current of the distribution station, the short-circuit current bearing capacity, etc. The power balance index influencing factor of the distribution station room corresponding to the actual overcurrent protection action current can be obtained. The assignment example is: assuming that the actual action current is 800A when the overcurrent protection is activated, while the rated current of the distribution station is 630A and the short-circuit current bearing capacity is 1200A. Based on this information, the impact of the actual operating current on the power balance of the distribution station room can be evaluated, and the power balance index impact factor of the distribution station room corresponding to the actual operating current of the overcurrent protection can be assigned. If the operating current of 800A is close to but does not exceed the short-circuit current bearing capacity, and does not cause serious consequences, the power balance index impact factor of the distribution station room corresponding to the actual operating current of the overcurrent protection can be assigned 0.2; if the operating current exceeds the rated current but is still within the safe range, the power balance index impact factor of the distribution station room corresponding to the actual operating current of the overcurrent protection can be assigned 0.4; if the operating current is too large and may cause damage to the distribution station room, the power balance index impact factor of the distribution station room corresponding to the actual operating current of the overcurrent protection can be assigned a higher value, such as 0.8 or higher.

[0064] It should be explained that, in this embodiment, the number of critical overcurrent protection actions is usually set by the power system designer or maintenance personnel based on factors such as the short-term overload capacity allowed by the equipment, the system reliability requirements, the performance and service life of the protection device type (such as circuit breakers, fuses), etc. It can be obtained from the equipment technical manual, the protection device programming interface, and the power system protection strategy document. The actual action current of the critical overcurrent protection refers to the current threshold at which the protection device actually triggers the action in the event of an overcurrent. It depends on the equipment rated current, the protection curve type (such as long delay, short delay, instantaneous), the system operating conditions (such as ambient temperature, altitude), and possible user-defined settings. This parameter can usually be found on the equipment nameplate, the protection device technical manual, the protection device commissioning report, or the protection logic programming interface. For example, in this embodiment, the number of critical overcurrent protection actions is 3, and the actual action current of the critical overcurrent protection is 24A.

[0065] In a specific embodiment, the power balance index of the distribution station room can not only be obtained by the above formula, but also by analyzing the collected data through the power system dispatching center to determine whether the power system is in a balanced state. If it is unbalanced, the dispatching center will take measures, such as adjusting the operating parameters of the generator set, adjusting the network structure of power transmission, starting the backup power supply, etc., to achieve the rebalancing of the power system. It can also collect data on power generation, transmission, transformation, distribution and power consumption in real time through various sensors and monitoring equipment installed in the power system, including the output power of the generator, the load condition of the power grid, the voltage and current and other parameters, and comprehensively analyze to obtain the power balance index of the distribution station room.

[0066] It needs to be explained that the overcurrent protection of the power system is a commonly used protection measure used to detect and isolate faults in the power system to protect equipment and systems from damage. Overcurrent protection: Overcurrent protection is a basic power system protection method that determines whether a fault has occurred by detecting whether the current in the circuit exceeds the set value. When the current exceeds a certain proportion of the rated value, the overcurrent protection will operate and cut off the circuit to prevent the fault from expanding or equipment damage. Overcurrent protection is commonly used for power equipment such as lines, transformers and generators. It is a backup protection used to provide protection when the main protection fails. In a specific embodiment, the power balance index of the distribution station room is a quantitative evaluation data obtained by comprehensive analysis of the number of overcurrent protection actions and the actual action current of each overcurrent protection, which is used to quantitatively evaluate the power quality and provide a basis for the intelligent scheduling indicators of the distribution station room.

[0067] The intelligent dispatching module of the distribution station room is used to obtain the intelligent dispatching index of the distribution station room according to the comprehensive analysis of the power quality assessment parameters and the power balance index, and obtain the power quality assessment parameter interval according to the analysis and processing, compare the intelligent dispatching index of the distribution station room with the power quality assessment parameter interval, and perform intelligent dispatching of the distribution station room according to the comparison results.

[0068] Specifically, the analysis and processing obtains the power quality assessment parameter interval of the power system, and the specific analysis process is: extracting the reference standard power quality assessment parameters and the allowable deviation power quality assessment parameters from the distribution station room database, performing difference operation and sum operation on the reference standard power quality assessment parameters and the allowable deviation power quality assessment parameters respectively, and marking the difference result as the lower limit of the power quality assessment parameter interval, marking the sum result as the upper limit of the power quality assessment parameter interval, and processing to obtain the power quality assessment parameter interval.

[0069] Specifically, the intelligent dispatching index of the distribution station room is compared with the power quality assessment parameter interval of the power system, and the distribution station room is intelligently dispatched according to the comparison result. The specific analysis process is: compare the power quality assessment parameter of the power system with the power quality assessment parameter interval of the power system. If the power quality assessment parameter of the power system is less than the upper limit of the power quality assessment parameter interval and is greater than or equal to the lower limit of the power quality assessment parameter interval, then maintain the current operation state of the distribution station room; if the power quality assessment parameter of the power system is less than the lower limit of the power quality assessment parameter interval or is greater than or equal to the upper limit of the power quality assessment parameter interval, then control the distribution station room.

[0070] In a specific embodiment, regulating the distribution station room is a complex process, which is specifically manifested in: using an automatic voltage regulator (AVR) to adjust the voltage output of the generator. Ensure that the voltage remains within the specified range to avoid overvoltage or undervoltage. Frequency regulation: Use an automatic frequency regulator (AFR) to adjust the generator output to maintain frequency stability. In the event of severe frequency deviation, load shedding may be required, that is, reducing certain non-critical loads to relieve system pressure. Active power regulation: Maintain active power balance by adjusting generator output or adjusting load. Use the power system dispatch center (PSS) to monitor and control the flow of active power. Reactive power regulation: The balance of reactive power is crucial to the stability of the power system. Use capacitors, inductors, phase shifters and other devices to control the flow of reactive power. When necessary, reactive compensation equipment can be switched on to adjust the reactive power of the system. Harmonic regulation: Monitor the harmonic content in the system and use filters (such as LC filters, FFT filters, etc.) to remove specific harmonics. Manage devices that generate harmonics, such as using active power filters (APFs) for real-time harmonic compensation.

[0071] Furthermore, the specific numerical expression of the intelligent dispatching index of the distribution station room is:

[0072]

[0073] In the formula, represents the intelligent dispatching index of the distribution station room, G M Represents the power quality assessment parameter of the power system, G W It represents the power balance index of the distribution station room, ρ1 represents the influence factor of the intelligent dispatching index of the distribution station room corresponding to the set power quality assessment parameter of the power system, and ρ2 represents the influence factor of the intelligent dispatching index of the distribution station room corresponding to the set power balance index of the distribution station room.

[0074] It should be explained that in this embodiment, the two parameters of the intelligent dispatching index influencing factor of the distribution station corresponding to the power quality evaluation parameter and the intelligent dispatching index influencing factor of the distribution station corresponding to the power balance index of the distribution station are usually derived from the real-time monitoring data, historical records, power quality test reports and operation data of the intelligent dispatching system of the power system. The power quality data of the distribution station, such as voltage deviation, frequency deviation, harmonic distortion, etc., are collected through the power quality monitoring equipment, and evaluated according to relevant standards. The intelligent dispatching index influencing factor of the distribution station corresponding to the power quality evaluation parameter can be obtained. In a specific embodiment, if the power quality data of the distribution station indicates that the voltage deviation is within +5%, the frequency deviation is within +0.2HZ, and the harmonic distortion is less than 5%, it can be considered that the power quality is good and the impact on intelligent dispatch is small. The intelligent dispatching index influencing factor of the distribution station corresponding to the power quality evaluation parameter can be assigned 0.1. If there are items exceeding the standard in the power quality data, but it has not yet caused serious impact on the system, the intelligent dispatching index influencing factor of the distribution station corresponding to the power quality evaluation parameter can be assigned 0.3. If the power quality problem is serious and affects the effect of intelligent dispatching, a higher value, such as 0.5 or higher, can be assigned to the intelligent dispatching index influencing factor of the distribution station corresponding to the power quality assessment parameter. Through the power monitoring system and historical records, the power balance of the distribution station room, including load fluctuation, power supply reliability, equipment failure rate, etc., can be analyzed, and the intelligent dispatching index influencing factor of the distribution station room corresponding to the power balance index of the distribution station room can be obtained. In a specific embodiment, if the load fluctuation of the distribution station room is small, the power supply reliability is high, and the equipment failure rate is low, it can be considered that its power balance is good and has little impact on intelligent dispatching. The intelligent dispatching index influencing factor of the distribution station room corresponding to the power balance index of the distribution station room can be assigned a value of 0.1. If there are certain load fluctuations or power supply reliability problems, but the impact on intelligent dispatching is not significant, the intelligent dispatching index influencing factor of the distribution station room corresponding to the power balance index of the distribution station room can be assigned a value of 0.2. If the power balance problem is more prominent and affects the efficiency and accuracy of the intelligent adjustment seat, the intelligent dispatching index influencing factor of the distribution station room corresponding to the power balance index of the distribution station room can be assigned a higher value, such as 0.4 or higher. The above are examples of possible values ​​for these two references; these values ​​are based on assumptions and do not represent actual measurements.

[0075] In a specific embodiment, the intelligent dispatching index of the distribution station room can not only be obtained by the above formula, but also by using artificial intelligence algorithms and big data analysis technology to conduct in-depth analysis of a large amount of data of the distribution station, discover operating rules, and predict potential faults. It is also possible to establish a mathematical model and simulation model of the distribution station, simulate the operation of the distribution station in a virtual environment, and evaluate the impact of different operations and strategies on the performance of the distribution station to obtain the intelligent dispatching index of the distribution station room.

[0076] In a specific embodiment, the intelligent dispatching index of the distribution station is a quantitative evaluation data obtained by comprehensively analyzing the power quality evaluation parameters of the power system and the power balance index of the distribution station, which is used to quantitatively evaluate the conditions for dispatching the distribution station and provide a basis for intelligent dispatching of the distribution station.

[0077] It should be explained that the power quality assessment parameter interval of the power system in this embodiment is a quantitative assessment interval obtained by comprehensive calculation of the power quality assessment parameters of the reference standard power system and the power quality assessment parameters of the allowable deviation power system, which provides a basis for intelligent scheduling of the distribution station room.

[0078] Reference Figure 2 As shown, the second aspect of the present invention provides an online monitoring method for a distribution station room based on big data, comprising: monitoring the harmonic data of the distribution station room, and obtaining power quality evaluation parameters of the power system after processing.

[0079] The overcurrent protection data of the power system is analyzed and processed to obtain the power balance index of the distribution station room.

[0080] Based on the comprehensive analysis of the power quality assessment parameters of the power system and the power balance index of the distribution station, the intelligent dispatching index of the distribution station is obtained, and the power quality assessment parameter range of the power system is obtained according to the analysis and processing. The intelligent dispatching index of the distribution station is compared with the power quality assessment parameter range of the power system, and the distribution station is intelligently dispatched according to the comparison results.

[0081] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. The online monitoring system of distribution station room based on big data is characterized by: include: The power quality assessment module is used to monitor the harmonic data of the power distribution station room and obtain the power quality assessment parameters of the power system after processing; The power balance analysis module is used to analyze the overcurrent protection data of the power system and obtain the power balance index of the distribution station room after processing; The intelligent dispatching module of the distribution station room is used to obtain the intelligent dispatching index of the distribution station room according to the comprehensive analysis of the power quality evaluation parameters of the power system and the power balance index of the distribution station room, and obtain the power quality evaluation parameter interval of the power system according to the analysis and processing, compare the intelligent dispatching index of the distribution station room with the power quality evaluation parameter interval of the power system, and perform intelligent dispatching of the distribution station room according to the comparison results; The analysis process obtains the power quality assessment parameter interval of the power system, and the specific analysis process is: Extracting reference standard power quality assessment parameters and allowable deviation power quality assessment parameters from the distribution station room database, performing difference operation and sum operation on the reference standard power quality assessment parameters and the allowable deviation power quality assessment parameters respectively, marking the difference result as the lower limit of the power quality assessment parameter interval, marking the sum result as the upper limit of the power quality assessment parameter interval, and processing to obtain the power quality assessment parameter interval; The specific numerical expression of the intelligent dispatching index of the distribution station room is: In the formula, Indicates the intelligent dispatching index of the distribution station room. Represents the power quality assessment parameter of the power system, Indicates the power balance index of the distribution station room. It represents the influencing factor of the intelligent dispatching index of the power distribution station corresponding to the power quality evaluation parameter of the set power system. It represents the influencing factor of the intelligent dispatching index of the distribution station room corresponding to the power balance index of the set distribution station room.

2. According to the big data-based online monitoring system for distribution station rooms according to claim 1, it is characterized in that: The harmonic data of the distribution station room is monitored and processed to obtain the power quality evaluation parameters of the power system. The specific analysis process is as follows: The power data of harmonic frequency is collected according to the preset time period, and the fundamental wave data is extracted from the database of the power distribution station room, including the effective value of the fundamental wave voltage of the power system. The effective value of the harmonic voltage and the effective value of the harmonic current of each harmonic are processed, and the abnormal degree value of the harmonic content of the distribution station room is obtained by comprehensive analysis. The abnormal degree value of the harmonic content and the total harmonic voltage distortion rate of the distribution station room are comprehensively analyzed, and the power quality assessment parameters of the power system are obtained after processing.

3. According to the big data-based online monitoring system for distribution station rooms in claim 1, it is characterized by: The overcurrent protection data of the power system is analyzed and processed to obtain the power balance index of the distribution station room. The specific analysis process is as follows: The number of overcurrent protection actions in the distribution station room and the actual action current of each overcurrent protection are monitored, and a comprehensive analysis is performed to obtain the power balance index of the distribution station room.

4. According to the big data-based online monitoring system for distribution station rooms according to claim 1, it is characterized in that: The intelligent dispatching index of the distribution station room is compared with the power quality assessment parameter interval of the power system, and the distribution station room is intelligently dispatched according to the comparison result. The specific analysis process is as follows: The power quality assessment parameter of the power system is compared with the power quality assessment parameter interval of the power system. If the power quality assessment parameter of the power system is less than the upper limit of the power quality assessment parameter interval and is greater than or equal to the lower limit of the power quality assessment parameter interval, the current operating state of the distribution station room is maintained; if the power quality assessment parameter of the power system is less than the lower limit of the power quality assessment parameter interval or is greater than or equal to the upper limit of the power quality assessment parameter interval, the distribution station room is regulated.

5. The online monitoring system for distribution station room based on big data according to claim 2 is characterized in that: The power quality evaluation parameters of the power system are quantitative evaluation data obtained by analyzing the abnormal degree of harmonic content and total harmonic voltage distortion rate of the distribution station room, which are used to quantitatively evaluate the power quality and provide a basis for the intelligent scheduling index of the distribution station room.

6. The online monitoring system for power distribution station room based on big data according to claim 1 is characterized in that: The intelligent dispatching index of the distribution station room is a quantitative evaluation data obtained by comprehensively analyzing the power quality evaluation parameters of the power system and the power balance index of the distribution station room, which is used to quantitatively evaluate the conditions for dispatching the distribution station room and provide a basis for intelligent dispatching of the distribution station room.

7. The online monitoring system for distribution station room based on big data according to claim 2 is characterized in that: The specific numerical expression of the power quality evaluation parameter of the power system is: In the formula, represents the power quality assessment parameter of the power system, e represents a natural constant, Indicates the abnormal degree of harmonic content in the distribution station room. Indicates the total harmonic voltage distortion rate, , n=2,3,4,...,N, N represents the upper limit of the harmonic order, Indicates the effective value of the nth harmonic voltage, represents the fundamental voltage, Indicates the power quality impact factor corresponding to the abnormal degree of harmonic content in the set distribution station room. Indicates the power quality impact factor corresponding to the set total harmonic voltage distortion rate.

8. A monitoring method using the online monitoring system for a distribution station room based on big data as claimed in any one of claims 1 to 7, characterized in that: include: Monitor the harmonic data of the power distribution station room and obtain the power quality evaluation parameters of the power system after processing; Analyze the overcurrent protection data of the power system and obtain the power balance index of the distribution station room after processing; Based on the comprehensive analysis of the power quality assessment parameters of the power system and the power balance index of the distribution station, the intelligent dispatching index of the distribution station is obtained, and the power quality assessment parameter range of the power system is obtained according to the analysis and processing. The intelligent dispatching index of the distribution station is compared with the power quality assessment parameter range of the power system, and the distribution station is intelligently dispatched according to the comparison results.

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