Power distribution network operation state management control method

Abstract

The invention relates to the technical field of power distribution network state management, and particularly discloses a power distribution network operation state management control method, which comprises the following steps of: determining a power distribution network operation state prediction period category, and if the power distribution network operation state prediction period is a short period, determining a power distribution network operation state prediction period based on a power distribution network real-time operation state data set; judging whether the real-time running state of the power distribution network is qualified or not, if the running state prediction period of the power distribution network is a long term, determining a running state management threshold value of the power distribution network, analyzing the running power quality of the power distribution network, and judging whether the running state of the power distribution network is qualified or not by combining the running state management threshold value of the power distribution network; the problems that a traditional power distribution network control mode depends on periodical scheduling and periodical inspection, is low in real-time performance, lacks a quick response mechanism and cannot effectively process load changes of multi-factor interaction are solved, the operation state, key influence factors and management threshold values can be analyzed through intelligent means, and the method is suitable for large-scale popularization and application. And the automation degree of power distribution network management is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network status management, and in particular to a distribution network operation status management and control method. Background Art

[0002] With the rapid growth of distributed renewable energy such as solar energy and wind energy, traditional centralized power systems are shifting to distributed operation modes. Distributed energy is intermittent and unstable, which puts higher requirements on the operation status management of distribution networks. With the widespread application of sensitive electronic equipment in industrial and commercial fields, users' requirements for power quality are constantly increasing, especially the quality requirements in terms of voltage, frequency, harmonics, etc., which pose new challenges to the stability and reliability of distribution networks. The popularization of IoT devices, sensors and data acquisition technologies in smart grids enables distribution networks to monitor the operation status of power equipment in real time. A large number of equipment in distribution networks are approaching the end of their service life and are facing problems such as aging and frequent failures. Through real-time monitoring and status evaluation, aging equipment can be warned and managed to improve the stability of distribution networks.

[0003] Nowadays, there are still some shortcomings in the research on the management and control of the operating status of distribution networks. Specifically, the traditional distribution network control method relies on periodic scheduling and regular inspections, has low real-time performance, and lacks a rapid response mechanism. When faced with instantaneous load fluctuations, sudden failures or power quality problems, traditional methods are difficult to achieve rapid response, which can easily delay fault isolation and recovery, affecting power supply reliability. Traditional load forecasting methods are mostly based on historical data and static modes, and cannot effectively handle load changes caused by multi-factor interactions, making it difficult to accurately predict future loads. In addition, traditional control systems are mostly rule-based and experience-based management, with a low degree of intelligence, making it difficult to achieve autonomous judgment and optimized control in complex environments. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for managing and controlling the operating status of a distribution network, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a distribution network operation status management and control method, comprising the following steps: analyzing the distribution network load characteristics, and determining the distribution network operation status prediction cycle category: if the distribution network operation status prediction cycle is short-term, obtaining the distribution network real-time operation status data set, analyzing to obtain the distribution network real-time operation status evaluation value, and judging whether the distribution network real-time operation status is qualified; if the distribution network operation status prediction cycle is long-term, analyzing the distribution network historical usage characteristics, and determining the first influencing factor for distribution network operation status management; analyzing the historical usage status of distribution network equipment, and combining the first influencing factor for distribution network operation status management to determine the distribution network operation status management threshold; analyzing the distribution network operation power quality, and combining the distribution network operation status management threshold to judge whether the distribution network operation status is qualified.

[0006] As a further method, the distribution network operation status prediction cycle category is determined, and the specific analysis process is: obtain the distribution network load characteristic data set, the distribution network load characteristic data set specifically includes the average daily load power of the distribution network, the average load current of the distribution network, and the peak-to-valley load ratio of the distribution network; based on the obtained distribution network load characteristic data set, a comprehensive analysis is performed to obtain the distribution network load characteristic value, and the distribution network load characteristic value is used as the analysis basis for determining the distribution network operation status prediction cycle category; the distribution network load characteristic value is compared with the distribution network load characteristic threshold stored in the database; if the distribution network load characteristic value is not lower than the distribution network load characteristic threshold, then the distribution network operation status prediction cycle category corresponding to the distribution network load characteristic value is short-term; if the distribution network load characteristic value is lower than the distribution network load characteristic threshold, then the distribution network operation status prediction cycle category corresponding to the distribution network load characteristic value is long-term.

[0007] As a further method, it is determined whether the real-time operating status of the distribution network is qualified, and the specific analysis process is: obtaining a data set of the real-time operating status of the distribution network, the real-time operating status data set of the distribution network specifically includes the real-time voltage deviation of the distribution network, the real-time power factor of the distribution network, and the real-time transformer winding temperature deviation of the distribution network; based on the obtained real-time operating status data set of the distribution network, a comprehensive analysis is performed to obtain an evaluation value of the real-time operating status of the distribution network, and the evaluation value of the real-time operating status of the distribution network is used as an analysis basis for determining whether the real-time operating status of the distribution network is qualified; the evaluation value of the real-time operating status of the distribution network is compared with a characteristic value of the real-time operating status of the distribution network stored in a database; if the evaluation value of the real-time operating status of the distribution network is not lower than the characteristic value of the real-time operating status of the distribution network, the real-time operating status of the distribution network corresponding to the evaluation value of the real-time operating status of the distribution network is qualified; if the evaluation value of the real-time operating status of the distribution network is lower than the characteristic value of the real-time operating status of the distribution network, the real-time operating status of the distribution network corresponding to the evaluation value of the real-time operating status of the distribution network is unqualified, and an alarm is issued for the distribution network with an unqualified real-time operating status and the backup power supply equipment is started.

[0008] As a further method, the first influencing factor of the distribution network operation status management is determined. The specific analysis process is: obtaining the distribution network historical usage characteristic data set, based on the obtained distribution network historical usage characteristic data set, comprehensive analysis to obtain the first influencing factor of the distribution network operation status management, the first influencing factor of the distribution network operation status management is used as the analysis basis for determining the distribution network operation status management threshold.

[0009] As a further method, a distribution network historical usage characteristic data set specifically includes the historical usage years of the distribution network, the total historical usage time of the distribution network, and the historical maintenance frequency of the distribution network.

[0010] As a further method, the historical usage status of distribution network equipment is analyzed. The specific analysis process is: obtaining a data set of historical usage status of distribution network equipment, which specifically includes the historical average service life of distribution network equipment, the historical average maintenance frequency of distribution network equipment, and the historical average component replacement ratio of distribution network equipment; based on the obtained data set of historical usage status of distribution network equipment, a comprehensive analysis is performed to obtain the second influencing factor of distribution network operation status management, and the second influencing factor of distribution network operation status management is used as the analysis basis for determining the distribution network operation status management threshold.

[0011] As a further method, the distribution network operation status management threshold is determined. The specific analysis process is: the first influencing factor of the distribution network operation status management and the second influencing factor of the distribution network operation status management are stored as designated tags, and the designated tags are compared with the distribution network operation status management thresholds corresponding to the designated tags stored in the database to obtain the distribution network operation status management thresholds corresponding to the designated tags.

[0012] As a further method, the power quality of the distribution network is analyzed. The specific analysis process is: obtaining the distribution network operation power quality data set, the distribution network operation power quality data set specifically includes the distribution network voltage fluctuation frequency, the distribution network total harmonic distortion rate, and the distribution network three-phase voltage imbalance; based on the obtained distribution network operation power quality data set, a comprehensive analysis is performed to obtain the distribution network operation power quality evaluation value, and the distribution network operation power quality evaluation value is used as the analysis basis for judging whether the distribution network operation status is qualified.

[0013] As a further method, the distribution network operation power quality assessment value, the specific analysis process is:

[0014]

[0015] Wherein, ω is the power quality assessment value of the distribution network, pl is the voltage fluctuation frequency of the distribution network, jb is the total harmonic distortion rate of the distribution network, bph is the three-phase voltage imbalance of the distribution network, μ1 is the compensation factor of the set pl, μ2 is the compensation factor of the set jb, μ3 is the compensation factor of the set bph, and e is a natural constant.

[0016] As a further method, it is determined whether the operating status of the distribution network is qualified. The specific analysis process is: compare the distribution network operating power quality assessment value with the distribution network operating status management threshold; if the distribution network operating power quality assessment value is not lower than the distribution network operating status management threshold, then the distribution network operating status corresponding to the distribution network operating power quality assessment value is qualified; if the distribution network operating power quality assessment value is lower than the distribution network operating status management threshold, then the distribution network operating status corresponding to the distribution network operating power quality assessment value is unqualified, and an alarm is issued for the distribution network with an unqualified real-time operating status and the backup power supply equipment is started.

[0017] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0018] (1) The present invention provides a distribution network operation status management and control method, which divides the prediction period into short-term and long-term, and can accurately predict different power grid load characteristics and demand changes. Short-term prediction can quickly obtain the real-time status of the distribution network, conduct timely monitoring and adjustment, and adapt to real-time load fluctuations and emergencies. Long-term prediction helps the power grid to reasonably allocate resources in future planning and achieve stable long-term operation through historical data analysis and key influencing factor identification. Combined with the first influencing factor of operation status management and historical equipment status analysis, dynamic thresholds are determined to enable the distribution network to adapt to the status requirements under different operating conditions. Combined with real-time and historical data, the operation status, key influencing factors and management thresholds are analyzed through intelligent means to improve the degree of automation of distribution network management.

[0019] (2) The present invention analyzes the load characteristics of the distribution network, determines the distribution network operation status prediction cycle category, and distinguishes between short-term and long-term predictions. This enables the prediction algorithm to focus on the load characteristics within different time periods and improve the prediction accuracy. Short-term predictions can more accurately capture sudden load fluctuations, while long-term predictions are suitable for identifying seasonal and annual load changes. Through accurate load predictions, the distribution network can reasonably allocate power resources and equipment, avoid unnecessary energy consumption and operating costs, improve overall operational efficiency, and help enhance the flexibility of distribution network operation and emergency response capabilities. The distinction between short-term and long-term cycles promotes the intelligent upgrade of the distribution network and helps the management system to more effectively analyze and process data from different cycles and optimize control strategies.

[0020] (3) The present invention analyzes the power quality of the distribution network and determines whether the distribution network is in a qualified operating state by combining the distribution network operating state management threshold. Power quality parameters such as voltage, frequency, and harmonics directly affect the power supply quality. By analyzing the power quality and combining the management threshold, the present invention can timely identify problems such as voltage fluctuations, frequency deviations, or excessive harmonics, and ensure that these key parameters meet the standards, thereby avoiding operating problems caused by substandard power quality. Substandard power quality (such as high harmonic content and frequent voltage fluctuations) will accelerate the loss of distribution network equipment, leading to equipment aging or even failure. By setting management thresholds and issuing early warnings and processing power quality problems that exceed the thresholds, the damage to the equipment can be effectively reduced. By combining the operating state management threshold, the power grid manager can more accurately determine the state of the grid and formulate corresponding maintenance strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] 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.

[0022] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0023] Figure 2 Schematic diagram of the process flow for determining the prediction period category of the distribution network operation status. DETAILED DESCRIPTION

[0024] 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.

[0025] Reference Figure 1 As shown, the present invention provides a distribution network operation status management and control method, including: analyzing the load characteristics of the distribution network and determining the distribution network operation status prediction cycle category.

[0026] like Figure 2As shown in the figure, the specific analysis process is: obtain the distribution network load characteristic data set, which specifically includes the average daily load power of the distribution network, the average load current of the distribution network, and the peak-to-valley load ratio of the distribution network; based on the obtained distribution network load characteristic data set, comprehensively analyze and obtain the distribution network load characteristic value, and the distribution network load characteristic value is used as the analysis basis for determining the distribution network operation status prediction cycle category; compare the distribution network load characteristic value with the distribution network load characteristic threshold stored in the database; if the distribution network load characteristic value is not lower than the distribution network load characteristic threshold, the distribution network operation status prediction cycle category corresponding to the distribution network load characteristic value is short-term; if the distribution network load characteristic value is lower than the distribution network load characteristic threshold, the distribution network operation status prediction cycle category corresponding to the distribution network load characteristic value is long-term.

[0027] In a specific embodiment, the average load power of the distribution network in a day is usually collected as the load power value per hour in a day, and the average value is calculated to reflect the daily average power supply load level of the distribution network, which is obtained through smart meters and load monitoring systems. The average load current value of the distribution network in a day during operation indicates the current intensity level of the grid load, which is usually the average of the load current values ​​in each period of a day, and is used to understand the current demand of the grid operation. The load current in the grid is measured in real time through current transformers (CT) and power monitoring equipment. The ratio of the peak load to the valley load of the distribution network in a day is used to measure the load fluctuation amplitude. A higher peak-to-valley ratio usually indicates a larger load fluctuation and a higher grid pressure, while a lower peak-to-valley ratio reflects a more stable load. The load power data for the whole day is obtained through smart meters and load monitoring systems.

[0028] The average daily load power of the distribution network is directly related to the average load current of the distribution network. Under the condition that the voltage and power factor are basically constant, the load power and load current are in positive proportion. When the average daily load power of the distribution network is high, the average load current is usually also large. The peak-to-valley load ratio describes the fluctuation amplitude of the load. A larger peak-to-valley load ratio indicates that the load fluctuation is large (that is, the peak load is much higher than the valley load), while a smaller peak-to-valley ratio means that the load is relatively stable. The average daily load power can be regarded as the "middle value" of the power throughout the day, and the peak-to-valley load ratio can reveal the fluctuation trend of the power. If the peak-to-valley ratio is high, the difference between the average load power and the peak and valley values ​​is large. The peak-to-valley load ratio can also indirectly affect the fluctuation of the average load current. When the peak-to-valley load ratio is high, it means that the current may increase significantly at the peak value and decrease significantly at the valley value. The average load current is between the peak and valley values, but the size of the peak-to-valley ratio will affect the fluctuation range of the current.

[0029] The long-term prediction cycle is monthly, and the short-term prediction cycle is daily. By comparing the load characteristic value with the threshold, the dynamic change trend of the distribution network load can be more accurately judged, so as to select a more suitable prediction cycle to make the prediction more targeted and reliable. The short-term prediction cycle corresponds to a higher load characteristic value, which usually indicates that the system needs to be closely monitored and dynamically responded, so the dispatching strategy of the distribution network can be adjusted at a higher frequency, while the long-term prediction cycle corresponds to a lower load characteristic value, indicating that the system load is relatively stable, which can reduce the monitoring frequency and save resources. Reasonable selection of the prediction cycle and timely response to large load fluctuations can effectively reduce the instability of the power grid operation caused by load fluctuations, thereby ensuring the continuity and stability of power supply. For distribution networks with low load characteristic values ​​and relatively stable operating conditions, the use of a long-term prediction cycle helps to reduce unnecessary frequent maintenance and reduce operating costs. It provides a data basis for the periodic evaluation of the operating status of the distribution network, helps to formulate long-term and short-term load management strategies, and supports more scientific power dispatching and planning decisions.

[0030] The specific analysis process of distribution network load characteristic value is as follows:

[0031]

[0032] Wherein, δ is the load characteristic value of the distribution network, go is the average daily load power of the distribution network, dl is the average load current of the distribution network, fg is the peak-to-valley load ratio of the distribution network, ε1 is the compensation factor of the set go, ε2 is the compensation factor of the set dl, ε3 is the compensation factor of the set fg, and e is a natural constant.

[0033] It needs to be explained that the above distribution network load characteristic values ​​are calculated through the average daily load power of the distribution network, the average load current of the distribution network, and the peak-to-valley load ratio of the distribution network. Go, dl, and fg are normalized. The distribution network load characteristic values ​​integrate the average power, current intensity, and load fluctuation (peak-to-valley ratio) of the load, provide an overall view of the distribution network load, more accurately reflect the load status of the power grid, and provide a reliable basis for operation decisions. The load characteristic values ​​can help power grid operators quickly understand the current load demand and load fluctuation amplitude, thereby optimizing the load scheduling strategy. The peak-to-valley load ratio can be used to formulate load peak shaving and valley filling strategies to alleviate peak load pressure. The load characteristic values ​​can identify the load fluctuation trend, help to predict the possible overload risk of the power grid in advance, reduce power supply interruptions caused by load instability, and thus improve the reliability of power supply to the power grid. Through the calculation of the load characteristic values, it is possible to identify which areas have large load fluctuations and high load density, so as to more accurately configure power generation resources and regulation equipment, and effectively improve the operation efficiency and energy efficiency of the power grid.

[0034] It should be explained that the compensation factors of go, dl, and fg set above are obtained from the database. According to historical data, a mapping set of the historically measured average daily load power of the distribution network, the average load current of the distribution network, the peak-to-valley load ratio of the distribution network and the compensation factors of go, dl, and fg is established to obtain the compensation factors of go, dl, and fg corresponding to the current go, dl, and fg.

[0035] It should be noted that θ1, θ2, θ3, σ1, σ2, σ3, τ1, τ2, τ3, μ1, μ2, and μ3 mentioned below are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained based on the current data.

[0036] If the distribution network operation status prediction period is short-term, the distribution network real-time operation status data set is obtained, the distribution network real-time operation status evaluation value is obtained by analysis, and whether the distribution network real-time operation status is qualified is determined.

[0037] The specific analysis process is as follows: obtaining a data set of the real-time operation status of the distribution network, which specifically includes the real-time voltage deviation of the distribution network, the real-time power factor of the distribution network, and the real-time transformer winding temperature deviation of the distribution network; based on the obtained data set of the real-time operation status of the distribution network, a comprehensive analysis is performed to obtain an evaluation value of the real-time operation status of the distribution network, and the evaluation value of the real-time operation status of the distribution network is used as an analysis basis for judging whether the real-time operation status of the distribution network is qualified; comparing the evaluation value of the real-time operation status of the distribution network with the evaluation characteristic value of the real-time operation status of the distribution network stored in the database; if the evaluation value of the real-time operation status of the distribution network is not lower than the evaluation characteristic value of the real-time operation status of the distribution network, the real-time operation status of the distribution network corresponding to the evaluation value of the real-time operation status of the distribution network is qualified; if the evaluation value of the real-time operation status of the distribution network is lower than the evaluation characteristic value of the real-time operation status of the distribution network, the real-time operation status of the distribution network corresponding to the evaluation value of the real-time operation status of the distribution network is unqualified, and an alarm is issued for the distribution network with unqualified real-time operation status and the backup power supply equipment is started.

[0038] It should be explained that the above voltage deviation refers to the deviation between the real-time voltage and the standard voltage of the distribution network, which is the ratio of the absolute value of the difference between the real-time voltage and the standard voltage of the distribution network to the standard voltage, usually expressed as a percentage, which is used to reflect the degree of deviation of the actual voltage level from the target voltage. High voltage deviation may cause equipment damage, and low voltage deviation may affect the normal operation of electrical equipment. It is measured in real time by voltage sensors and smart meters. Power factor refers to the ratio of actual power to apparent power, usually expressed as a value between 0 and 1. Power factor reflects the effective utilization rate of electric energy. A higher power factor indicates a higher utilization rate of electric energy, and a lower power factor may lead to increased power loss. It is obtained through power factor measurement equipment or power factor meters. Transformer winding temperature deviation refers to the deviation between the actual temperature of the transformer winding and the set safety temperature, which is the ratio of the absolute value of the difference between the actual temperature of the transformer winding and the set safety temperature to the set safety temperature. The rise in winding temperature may cause aging or even burning of the insulation material. When the deviation is large, it needs to be dealt with immediately. Temperature sensors, thermocouples and other equipment are installed at the transformer winding to monitor the temperature.

[0039] Voltage deviation will affect the power factor, especially when the voltage is too low or too high. Larger voltage deviation will often lead to current fluctuations, which will cause the power factor to decrease. When the power factor is low, the transmission efficiency will decrease, and the power system will need additional reactive power to compensate, which may cause voltage fluctuations and increase the possibility of voltage deviation. The voltage deviation and power factor have a mutually influential relationship. When the voltage deviation is large (especially when the voltage drops), the system current will usually increase to meet the load demand, which will increase the load current on the transformer and line, thereby causing the transformer winding temperature to rise, and then cause temperature deviation. A lower power factor indicates that the proportion of reactive power in the system is high, which will cause the current in the transformer and line to increase. Reactive power will increase the load of the equipment, thereby increasing the temperature deviation of the transformer winding.

[0040] The real-time monitoring and alarm mechanism can respond in time when the distribution network status is unqualified, avoiding power supply interruptions caused by load fluctuations or equipment problems, thereby improving the stability and reliability of the distribution network. The unqualified status of the distribution network is usually accompanied by high voltage deviation, low power factor or temperature abnormality. By starting the backup power supply equipment in time, the pressure on the main equipment can be relieved, and the loss of transformers and other key equipment due to overheating, overload and other conditions can be reduced. Issuing alarms and switching to backup power supply in unqualified states can help prevent the further spread of faults and avoid equipment damage from spreading to other areas, thereby ensuring power supply safety in a wider range. Real-time monitoring and automatic alarms make fault location and maintenance response more efficient, avoiding greater impact on the operation of the entire distribution network, thereby optimizing the allocation of maintenance resources and improving operation and maintenance efficiency. Timely intervention in unqualified states can reduce additional repair costs caused by equipment overload or damage, reduce long-term operating costs, and extend the service life of distribution equipment.

[0041] The real-time operation status evaluation value of the distribution network, the specific analysis process is as follows:

[0042]

[0043] In the formula, γ is the real-time operation status evaluation value of the distribution network, yp is the real-time voltage deviation of the distribution network, ys is the real-time power factor of the distribution network, rz is the real-time transformer winding temperature deviation of the distribution network, θ1 is the compensation factor of the set yp, θ2 is the compensation factor of the set ys, and θ3 is the compensation factor of the set rz.

[0044] It needs to be explained that the above-mentioned real-time operation status evaluation value of the distribution network is calculated through the real-time voltage deviation of the distribution network, the real-time power factor of the distribution network, and the real-time transformer winding temperature deviation of the distribution network. Yp, Ys, and Rz are normalized. The voltage deviation, power factor, and transformer winding temperature deviation comprehensively reflect the operation status of the distribution network from three key aspects: voltage stability, energy efficiency, and equipment thermal state, and provide a comprehensive evaluation of the real-time operation status of the power grid. The real-time operation status evaluation value can quickly discover non-standard operation conditions. When an indicator is abnormal (such as excessive voltage deviation, low power factor, or excessive winding temperature), the evaluation value will automatically reflect these abnormalities, which is convenient for timely processing and reduces the risk of accidents. Through the evaluation value, the system can realize an automated early warning mechanism, and immediately issue an alarm or switch to backup equipment when the power grid operation status is unqualified, to ensure the stability and safety of the distribution network, ensure that the power grid remains in a state of efficient operation, reduce unnecessary power loss, and improve the energy efficiency of the system.

[0045] If the distribution network operation status prediction period is long-term, the historical usage characteristics of the distribution network are analyzed to determine the first influencing factor of the distribution network operation status management.

[0046] The specific analysis process is: obtain the distribution network historical usage characteristic data set, based on the obtained distribution network historical usage characteristic data set, comprehensive analysis to obtain the first influencing factor of distribution network operation status management, the first influencing factor of distribution network operation status management is used as the analysis basis for determining the distribution network operation status management threshold.

[0047] It should be explained that the above-mentioned historical usage characteristic data can provide long-term operating trends and load fluctuation patterns. The first influencing factor obtained through analysis can be used as a more accurate indicator to help set management thresholds that are more in line with actual needs and improve the accuracy of power grid operation status management. Through the analysis of influencing factors, the management threshold can be dynamically adjusted according to the load changes and environmental conditions of the power grid, which helps to adapt to changes in seasonal or periodic load demand and make management more flexible and efficient. The first influencing factor is based on historical characteristic data and can reflect the most critical parameters for power grid stability, identify possible abnormal patterns in advance and manage them in a timely manner, and reduce risks such as system overload and equipment damage. Historical data analysis makes the management threshold of the power grid more data-supported, helping power grid operators optimize resource allocation under different load conditions, reduce unnecessary maintenance or energy consumption, improve operating economy, and determine the most critical influencing factors. In an emergency, it can more quickly determine whether it is approaching or exceeding the threshold, thereby quickly launching emergency management strategies and improving the response speed and emergency management capabilities of the power grid.

[0048] Furthermore, the distribution network historical usage characteristic data set specifically includes the historical service life of the distribution network, the total historical usage time of the distribution network, and the historical maintenance frequency of the distribution network.

[0049] It needs to be explained that the above-mentioned historical service life of the distribution network refers to the total time (in years) since the distribution network was put into use to date, which is used to evaluate the aging degree and equipment life of the distribution network. With the increase of service life, the distribution network equipment may face higher failure risks and more frequent maintenance needs, which are recorded, stored and obtained through the distribution network management system or asset management database. The total historical service time of the distribution network refers to the cumulative total time (usually in hours or days) that the distribution network is in operation, including the actual operating time and load conditions of the system. The total historical service time can reflect the workload and consumption of the equipment, which is obtained through the power grid control system or equipment monitoring system. The historical maintenance frequency of the distribution network refers to the maintenance and repair frequency of the distribution network or its key equipment during its service life, which is usually expressed in the number of repairs within a year or month. A higher maintenance frequency may indicate that the equipment is aging or the load pressure is large, and regular maintenance is required to ensure stable operation. It is recorded and obtained through the equipment maintenance management system (such as CMMS) or the asset management system.

[0050] The historical service life represents the total number of years since the equipment was put into use, and the total historical service time is the actual working time of the equipment within this period. The longer the service life, the longer the total service time may be. Especially when the equipment is in operation every day, the total service time reflects the actual load borne by the equipment. With the increase of the historical service life, the aging of the equipment increases and the risk of failure increases. Therefore, the maintenance frequency tends to increase. Equipment with a long service life may require more frequent maintenance to keep it functioning properly. The longer the historical service time, the more load the equipment bears and the more severe the wear and tear may be. Therefore, the equipment is more prone to failure, resulting in an increased maintenance frequency. A high frequency of total service time is usually accompanied by higher maintenance needs.

[0051] The first influencing factor of distribution network operation status management, the specific analysis process is:

[0052]

[0053] Where α is the first influencing factor of the distribution network operation status management, nx is the historical service life of the distribution network, sc is the total historical service time of the distribution network, wx is the historical maintenance frequency of the distribution network, σ1 is the compensation factor of the set nx, σ2 is the compensation factor of the set sc, and σ3 is the compensation factor of the set wx.

[0054] It needs to be explained that the first influencing factor of the distribution network operation status management is calculated through the historical service life of the distribution network, the historical total service time of the distribution network, and the historical maintenance frequency of the distribution network. nx, sc, and wx are normalized. The historical service life, total service time, and maintenance frequency describe the use of the equipment from different dimensions. The first influencing factor combines these indicators and can fully reflect the actual workload and usage status of the equipment. Based on the service life, total service time, and maintenance requirements of the equipment, the first influencing factor provides a more practical parameter, which can provide a basis for setting the operation status management threshold, making the management threshold more reasonable, thereby improving the accuracy of management. The historical total service time and maintenance frequency can reflect the operating intensity and failure probability of the equipment. Using the first influencing factor, equipment with poor operating status can be identified in time, maintenance measures can be taken in advance, the risk of equipment failure can be reduced, and the overall efficiency and stability of the power grid can be improved.

[0055] The historical usage status of distribution network equipment is analyzed, and the distribution network operation status management threshold is determined based on the first influencing factor of distribution network operation status management.

[0056] The specific analysis process is as follows: obtaining the historical usage status data set of distribution network equipment, which specifically includes the historical average service life of distribution network equipment, the historical average maintenance frequency of distribution network equipment, and the historical average component replacement ratio of distribution network equipment; based on the obtained historical usage status data set of distribution network equipment, a comprehensive analysis is performed to obtain the second influencing factor of distribution network operation status management, and the second influencing factor of distribution network operation status management is used as the analysis basis for determining the distribution network operation status management threshold.

[0057] It should be explained that the above-mentioned average historical service life of distribution network equipment refers to the average service life of all equipment in the distribution network, which is the average of the time since the equipment was put into use. It is used to evaluate the aging degree and operation risk of the overall equipment in the distribution network. It is generally measured in years and recorded and obtained through the equipment management system or asset management database. The average historical maintenance frequency of distribution network equipment refers to the average number of maintenance times of all equipment in the distribution network within a certain period of time, usually expressed as the maintenance frequency within a year. A higher maintenance frequency means that the equipment has a higher failure rate or harsh operating conditions. The maintenance history of the equipment is recorded and obtained through the equipment maintenance management system (such as CMMS) or asset management system. The average historical component replacement ratio of distribution network equipment refers to the average ratio of all replaced components of equipment in the distribution network, usually expressed as the ratio of the number of component replacements to the total number of equipment components in a certain period of time. A high replacement ratio usually indicates that the equipment components are highly worn or frequently used. It is obtained through the maintenance management system or the equipment life cycle management system.

[0058] The longer the equipment is used, the higher the degree of aging is usually, and the possibility of failure will also increase, resulting in an increase in the frequency of maintenance. There is often a positive correlation between the historical average service life and maintenance frequency. As the service life increases, the workload and wear of equipment components increase, and the aging of components accelerates. Therefore, the proportion of parts replacement may increase. After the equipment reaches a certain service life, the frequency of replacing key components may increase significantly. Especially for old equipment, if the proportion of parts replacement continues to increase, it may indicate that the equipment is nearing the end of its life cycle and the overall equipment update or upgrade needs to be considered. When the maintenance frequency is high, equipment parts tend to be replaced more frequently. A high maintenance frequency may indicate that the equipment is not in good operating condition or failures are frequent, thus increasing the proportion of parts replacement.

[0059] The second influencing factor comprehensively considers the service life of the equipment, maintenance frequency and component replacement ratio. It can more comprehensively reflect the actual operating status of the equipment and help set more accurate management thresholds that meet actual needs. The usage status data can reveal which equipment is seriously aged or frequently fails, so as to reasonably arrange maintenance and component replacement plans, avoid blind repairs or replacements, and reduce operation and maintenance costs. By comprehensively analyzing the usage status of the equipment, operation management can foresee the possible failure risks of the equipment and determine the management threshold based on the historical status of the equipment, which can ensure that the equipment operates in the best condition, reduce sudden failures, and improve the overall stability and reliability of the power grid.

[0060] The second influencing factor of distribution network operation status management, the specific analysis process is:

[0061]

[0062] Where β is the second influencing factor of distribution network operation status management, sn is the historical average service life of distribution network equipment, wx is the historical average maintenance frequency of distribution network equipment, gh is the historical average component replacement ratio of distribution network equipment, τ1 is the compensation factor of sn, τ2 is the compensation factor of wx, and τ3 is the compensation factor of gh.

[0063] It should be explained that the second influencing factor of the distribution network operation status management is calculated through the historical average service life of distribution network equipment, the historical average maintenance frequency of distribution network equipment, and the historical average component replacement ratio of distribution network equipment. Sn, wx, and gh are normalized. The historical average service life, maintenance frequency, and component replacement ratio fully reflect the aging degree, maintenance frequency, and component consumption of the equipment, and can clearly reflect the overall health status and reliability of the equipment. Through the actual historical use of the equipment, the second influencing factor can provide a reliable basis for the setting of management thresholds, so that the management thresholds are more in line with the actual use of the equipment, thereby improving the scientificity and accuracy of operation status management. This influencing factor can help determine whether the equipment needs preventive maintenance or replacement, help optimize the investment of maintenance resources, extend the service life of the equipment, and reduce unnecessary maintenance or replacement costs. Equipment with a higher historical average maintenance frequency and component replacement ratio often faces a higher risk of failure. By monitoring the second influencing factor, potential high-risk equipment can be identified in advance, maintenance measures can be taken in time, the probability of failure can be reduced, and the stable operation of the power grid can be ensured.

[0064] Furthermore, the distribution network operation status management threshold is determined. The specific analysis process is: the first influencing factor of the distribution network operation status management and the second influencing factor of the distribution network operation status management are stored as designated tags, and the designated tag is compared with the distribution network operation status management threshold corresponding to each designated tag stored in the database to obtain the distribution network operation status management threshold corresponding to the designated tag.

[0065] It needs to be explained that the above-mentioned label management can make the influencing factors directly correspond to specific operating status management thresholds, ensure that the comparison process is more accurate, reduce misjudgments, and improve the recognition accuracy of the distribution network status. Through label comparison, it is possible to quickly determine whether the operating status of the distribution network is close to or exceeds the threshold. Once the status is unqualified, the early warning and response mechanism can be automatically triggered to shorten the fault handling time. Label processing makes operating status management more modular, convenient for batch management and comparative analysis, helps to simplify data analysis and operating status evaluation processes, and improve management efficiency. When operating conditions or environment changes, the threshold corresponding to the specified label can be dynamically updated to ensure that the management threshold meets actual needs and enhance the adaptability of power grid operation. The specified label facilitates the systematic recording and tracking of each influencing factor and its corresponding management status, which helps the traceability of historical data analysis and equipment management, and provides data support for subsequent optimization.

[0066] Analyze the power quality of the distribution network and determine whether the distribution network operation status is qualified based on the distribution network operation status management threshold.

[0067] The specific analysis process is as follows: obtaining the distribution network operation power quality data set, which specifically includes the distribution network voltage fluctuation frequency, the distribution network total harmonic distortion rate, and the distribution network three-phase voltage imbalance; based on the obtained distribution network operation power quality data set, a comprehensive analysis is performed to obtain the distribution network operation power quality evaluation value, which is used as the analysis basis for judging whether the distribution network operation status is qualified.

[0068] In a specific embodiment, the voltage fluctuation frequency refers to the frequency and amplitude of the voltage deviation from the rated value (usually the steady-state voltage). High-frequency voltage fluctuations will affect the normal operation of the equipment and may cause instability in the power grid. It is usually expressed as the number of times or frequency of fluctuations, and is collected by a voltage monitor or a power quality analyzer. The total harmonic distortion rate refers to the ratio of the harmonic voltage or current to the fundamental voltage or current in the power grid, usually expressed as a percentage. Harmonics will cause additional losses and interference to the power system. A higher harmonic distortion rate will affect the performance of the power grid and electrical equipment, and is collected by a harmonic analyzer or a power quality analyzer. The three-phase voltage imbalance indicates the degree of difference in the three-phase voltage amplitudes in a three-phase power grid, usually expressed as a percentage of the imbalance. When the imbalance is high, it will affect the normal operation of equipment such as motors, increase losses and cause equipment overheating, and is obtained through a three-phase voltage imbalance monitor or a power quality monitoring system.

[0069] Frequent voltage fluctuations may cause distortion of current and voltage waveforms, thereby introducing or increasing harmonics. A higher total harmonic distortion rate in the power grid often leads to increased voltage fluctuations, especially when the load changes frequently. When the three-phase voltage imbalance is high, the voltage differences between the phases are large, which can easily cause voltage fluctuations. When the single-phase load increases, it is easy to cause the voltage of that phase to drop, making the three-phase voltage further unbalanced, resulting in frequent voltage fluctuations. When the three-phase voltage is unbalanced, the nonlinear characteristics of the load may be enhanced, thereby introducing more harmonics. In the case of imbalance, an increase in single-phase load will lead to an increase in odd harmonics, further exacerbating the total harmonic distortion rate.

[0070] Indicators such as voltage fluctuation frequency, total harmonic distortion rate, and three-phase voltage imbalance fully reflect the power quality. The comprehensive evaluation value calculated based on these key indicators can more accurately determine whether the power quality meets the standards and reduce misjudgment of power quality abnormalities. Through the power quality evaluation value, the trend of unqualified power quality can be identified in advance, and equipment can be prevented from operating for a long time under poor power conditions. The risk of equipment loss and failure caused by power quality problems can be reduced, and the preventive maintenance strategy of the power grid can be supported. Unqualified power quality may cause unstable equipment operation or damage to user-side equipment. By timely detecting and judging the power quality status, improvement measures can be taken quickly to ensure the reliability of power supply.

[0071] Specifically, the distribution network operation power quality assessment value, the specific analysis process is as follows:

[0072]

[0073] Wherein, ω is the power quality assessment value of the distribution network, pl is the voltage fluctuation frequency of the distribution network, jb is the total harmonic distortion rate of the distribution network, bph is the three-phase voltage imbalance of the distribution network, μ1 is the compensation factor of the set pl, μ2 is the compensation factor of the set jb, and μ3 is the compensation factor of the set bph.

[0074] It needs to be explained that the above-mentioned distribution network operation power quality assessment value is calculated through the voltage fluctuation frequency of the distribution network, the total harmonic distortion rate of the distribution network, and the three-phase voltage imbalance of the distribution network. PL, JB, and BPH are normalized. The voltage fluctuation frequency, the total harmonic distortion rate, and the three-phase voltage imbalance reflect the key indicators of power quality from different aspects, respectively, and can comprehensively and accurately describe the overall power quality status of the power grid. A single indicator may not be able to accurately reflect the complexity of power quality, and the comprehensive assessment value can more accurately identify the quality of power grid power, which is helpful to discover potential problems or hidden dangers and reduce misjudgment. The power quality assessment value provides a quantitative standard for the overall operating status, which can quickly determine whether the power grid needs to adjust the load or compensate, thereby optimizing the operation strategy of the power grid, reducing losses, and enhancing power quality. The comprehensive assessment value converts multiple complex indicators into an intuitive numerical value, making the monitoring and management of power quality more operational, and facilitating the automation system to perform real-time monitoring, analysis, and early warning.

[0075] The distribution network operation power quality assessment value is compared with the distribution network operation status management threshold; if the distribution network operation power quality assessment value is not lower than the distribution network operation status management threshold, the distribution network operation status corresponding to the distribution network operation power quality assessment value is qualified; if the distribution network operation power quality assessment value is lower than the distribution network operation status management threshold, the distribution network operation status corresponding to the distribution network operation power quality assessment value is unqualified, and an alarm is issued for the distribution network with an unqualified real-time operation status and the backup power supply equipment is started.

[0076] It needs to be explained that, in the case of unqualified power quality, timely switching to the backup power supply equipment can avoid power outages caused by power quality problems, thereby ensuring the stability of the power system and improving the user's power experience. Unqualified power quality may cause equipment overload, heating or voltage instability, resulting in equipment damage or shortened life. By switching to the backup equipment in time, the main equipment can be avoided from operating under unqualified power quality conditions, thereby reducing equipment losses and maintenance costs. The automatic alarm mechanism can quickly notify maintenance personnel to conduct inspections, deal with power quality problems as soon as possible, reduce risks, and enable the distribution network to return to normal in a shorter time. When the backup power supply equipment is started, the power grid can continue to provide power services to users, reduce the impact of power outages caused by abnormal power quality, and ensure the continuous power supply needs of key power consumption places. Data analysis after alarm and switching helps to identify the root causes of power quality problems, formulate better power quality management strategies, and continuously optimize the operating conditions and power quality management processes of the distribution network.

[0077] In a specific embodiment, the average daily load power of the distribution network is 1500kW, the average load current of the distribution network is 75A, the peak-to-valley load ratio of the distribution network is 1.8, the compensation factor of go is 0.95, the compensation factor of dl is 1.05, and the compensation factor of fg is 0.9. The calculated load characteristic value of the distribution network is 41.17, the load characteristic threshold of the distribution network is 43, and a long-term prediction period is selected.

[0078] The historical service life of the distribution network is 10 years, the total historical service time of the distribution network is 87,600 hours, the historical maintenance frequency of the distribution network is 5 times / year, the compensation factor of nx is 1.0, the compensation factor of sc is 0.85, and the compensation factor of wx is 0.9. The first influencing factor of the distribution network operation status management is calculated to be 77.784.

[0079] The historical average service life of distribution network equipment is 8 years, the historical average maintenance frequency of distribution network equipment is 6 times / year, the historical average component replacement ratio of distribution network equipment is 0.15, the compensation factor of sn is 1.0, the compensation factor of wx is 0.85, and the compensation factor of gh is 0.9. The second influencing factor of distribution network operation status management is calculated to be 14.165, and the distribution network operation status management threshold is 5.

[0080] The voltage fluctuation frequency is 5 times / day, the total harmonic distortion rate is 2%, the three-phase voltage imbalance is 1.5%, the compensation factor of PL is 0.9, the compensation factor of JB is 0.95, and the compensation factor of BPH is 1.05. The calculated power quality assessment value of the distribution network is -1.864, which is lower than the distribution network operation status management threshold of 5. The distribution network operation status is judged to be unqualified, triggering an alarm and starting the backup power supply equipment.

[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. A distribution network operation status management and control method, characterized in that: The following steps are involved: Analyze the load characteristics of the distribution network and determine the distribution network operation status prediction cycle category: If the distribution network operation status prediction cycle is short-term, the distribution network real-time operation status data set is obtained, the distribution network real-time operation status evaluation value is obtained through analysis, and whether the distribution network real-time operation status is qualified is determined; If the distribution network operation status prediction period is long-term, the historical usage characteristics of the distribution network are analyzed to determine the first influencing factor of the distribution network operation status management; Analyze the historical usage status of distribution network equipment, and determine the distribution network operation status management threshold based on the first influencing factor of distribution network operation status management; Analyze the power quality of the distribution network and determine whether the distribution network operation status is qualified based on the distribution network operation status management threshold.

2. A distribution network operation status management and control method according to claim 1, characterized in that: The specific analysis process of determining the distribution network operation status prediction cycle category is as follows: Obtain a distribution network load characteristic data set, the distribution network load characteristic data set specifically includes the distribution network average daily load power, the distribution network average load current, and the distribution network peak-to-valley load ratio; Based on the acquired distribution network load characteristic data set, the distribution network load characteristic value is obtained through comprehensive analysis, and the distribution network load characteristic value is used as the analysis basis for determining the distribution network operation status prediction period category; Compare the distribution network load characteristic value with the distribution network load characteristic threshold stored in the database; If the distribution network load characteristic value is not lower than the distribution network load characteristic threshold, the distribution network operation state prediction period category corresponding to the distribution network load characteristic value is short-term; If the distribution network load characteristic value is lower than the distribution network load characteristic threshold, the distribution network operation status prediction period category corresponding to the distribution network load characteristic value is long-term.

3. A distribution network operation status management and control method according to claim 1, characterized in that: The specific analysis process of judging whether the real-time operating status of the distribution network is qualified is as follows: Acquire a data set of real-time operation status of the distribution network, which specifically includes a real-time voltage deviation of the distribution network, a real-time power factor of the distribution network, and a real-time transformer winding temperature deviation of the distribution network; Based on the acquired distribution network real-time operation status data set, a comprehensive analysis is performed to obtain a distribution network real-time operation status evaluation value, which is used as an analysis basis for judging whether the distribution network real-time operation status is qualified; Compare the distribution network real-time operation status evaluation value with the distribution network real-time operation status evaluation characteristic value stored in the database; If the distribution network real-time operation status evaluation value is not lower than the distribution network real-time operation status evaluation characteristic value, the distribution network real-time operation status corresponding to the distribution network real-time operation status evaluation value is qualified; If the real-time operation status evaluation value of the distribution network is lower than the real-time operation status evaluation characteristic value of the distribution network, the real-time operation status of the distribution network corresponding to the real-time operation status evaluation value of the distribution network is unqualified, an alarm is issued for the distribution network with unqualified real-time operation status and the backup power supply equipment is started.

4. A distribution network operation status management and control method according to claim 1, characterized in that: The specific analysis process of determining the first influencing factor of the distribution network operation status management is as follows: A distribution network historical usage characteristic data set is obtained. Based on the obtained distribution network historical usage characteristic data set, a comprehensive analysis is performed to obtain the first influencing factor of distribution network operation status management. The first influencing factor of distribution network operation status management is used as an analysis basis for determining the distribution network operation status management threshold.

5. A distribution network operation status management and control method according to claim 4, characterized in that: The distribution network historical usage characteristic data set specifically includes the historical usage years of the distribution network, the historical total usage time of the distribution network, and the historical maintenance frequency of the distribution network.

6. A distribution network operation status management and control method according to claim 1, characterized in that: The analysis of the historical usage status of the distribution network equipment is specifically carried out as follows: Obtain a historical usage status data set of distribution network equipment, which specifically includes the historical average service life of distribution network equipment, the historical average maintenance frequency of distribution network equipment, and the historical average component replacement ratio of distribution network equipment; Based on the acquired historical usage status dataset of distribution network equipment, a comprehensive analysis is performed to obtain the second influencing factor of distribution network operation status management. The second influencing factor of distribution network operation status management is used as the analysis basis for determining the distribution network operation status management threshold.

7. A distribution network operation status management and control method according to claim 1, characterized in that: The specific analysis process of determining the distribution network operation status management threshold is as follows: The first influencing factor of the distribution network operation status management and the second influencing factor of the distribution network operation status management are stored as designated tags, and the designated tags are compared with the distribution network operation status management thresholds corresponding to the designated tags stored in the database to obtain the distribution network operation status management thresholds corresponding to the designated tags.

8. A distribution network operation status management and control method according to claim 1, characterized in that: The specific analysis process of analyzing the power quality of the distribution network is as follows: Obtaining a power quality data set for distribution network operation, which specifically includes the voltage fluctuation frequency of the distribution network, the total harmonic distortion rate of the distribution network, and the three-phase voltage imbalance of the distribution network; Based on the obtained distribution network operation power quality data set, a comprehensive analysis is performed to obtain the distribution network operation power quality assessment value, which is used as the analysis basis for judging whether the distribution network operation status is qualified.

9. A distribution network operation status management and control method according to claim 8, characterized in that: The specific analysis process of the power quality assessment value of the distribution network operation is as follows: Wherein, ω is the power quality assessment value of the distribution network, pl is the voltage fluctuation frequency of the distribution network, jb is the total harmonic distortion rate of the distribution network, bph is the three-phase voltage imbalance of the distribution network, μ1 is the compensation factor of the set pl, μ2 is the compensation factor of the set jb, μ3 is the compensation factor of the set bph, and e is a natural constant.

10. A distribution network operation status management and control method according to claim 1, characterized in that: The specific analysis process of judging whether the distribution network operation status is qualified is as follows: Compare the distribution network operation power quality assessment value with the distribution network operation status management threshold; If the distribution network operation power quality assessment value is not lower than the distribution network operation status management threshold, the distribution network operation status corresponding to the distribution network operation power quality assessment value is qualified; If the distribution network operating power quality assessment value is lower than the distribution network operating status management threshold, the distribution network operating status corresponding to the distribution network operating power quality assessment value is unqualified, an alarm is issued for the distribution network with unqualified real-time operating status and the backup power supply equipment is started.

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