Power supply and distribution system performance health state dynamic monitoring system

Abstract

The invention relates to the technical field of power supply and distribution monitoring, in particular to a power supply and distribution system performance health state dynamic monitoring system which comprises a state acquisition module, a power supply switching module, a power supply monitoring module, a switching matching module and a state evaluation module. The method comprises the following steps: combining power supply equipment as power supply nodes into a power supply distribution network, and checking switching behavior characteristics of a current power supply node according to operation information of the power supply nodes and operation time and switching times of the power supply nodes; the similarity during switching of different power supply modes is checked according to the voltage deviation and the load deviation of the operation information, and updating of the operation information of each power supply node is completed; starting from switching behavior characteristics, describing a switching mode of a current power supply node under power supply mode switching, describing a switching matching network of each power supply node according to a switching sequence of the switching modes, and finally screening an optimal configuration scheme corresponding to each power supply node; the efficiency of anomaly detection and the reliability of switching of the power supply and distribution system are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply and distribution monitoring, and in particular to a system for dynamically monitoring the performance and health status of a power supply and distribution system. Background Art

[0002] The power supply and distribution system is a system that supplies and distributes electrical energy. Its primary function is to obtain electrical energy from the power grid and, through appropriate line and equipment configuration, safely, reliably, economically, and efficiently deliver it to various loads to meet the power needs of different users. However, existing technologies often rely on manual inspections and fixed threshold alarms, making the power supply and distribution system unsuitable for the complex topologies of distributed power sources and microgrids.

[0003] For example, Chinese patent publication number CN119253869A discloses an intelligent monitoring method and system based on a power supply and distribution system, which relates to the field of power grid monitoring technology. The method includes obtaining detection power parameters; establishing a detection interval and determining interval change parameters; determining an interval change combination based on all interval change parameters; establishing a historical interval, and randomly demarcating a comparison interval with a width equal to the detection time in the historical interval, and determining a comparison change combination in each comparison interval; determining a combination similarity value based on the interval change combination and the comparison change combination, and determining the combination similarity value with the largest value based on a sorting rule, and defining the comparison interval corresponding to the combination similarity value as a similar interval; establishing a prediction interval based on the similar interval, and defining the detection power parameter in the prediction interval as a predicted power parameter; and outputting an aging warning signal when the predicted power parameter is greater than a preset warning power parameter.

[0004] For example, Chinese patent publication number CN117913970A discloses an adaptive switching system for power supply and distribution, comprising a state monitoring module, a power monitoring module, a voltage analysis module, a state analysis module, and a switching determination module. The present invention monitors the voltage of power generation equipment in real time, performs matching and comparison judgment, and analyzes the power supply status of the equipment based on the associated current data when the power supply voltage fluctuates significantly. By determining whether the power generation equipment matches the load, it analyzes whether there is a risk of failure in the power generation equipment, predicts the working safety status of the power generation equipment, and determines whether the power generation equipment needs to be shut down in time to avoid failure of the power generation equipment. When the load demand increases, the excess load is isolated, and the power load is gradually switched step by step. When the load demand decreases, the power load is directly switched to another power generation equipment.

[0005] The prior art describes the use of time intervals of distribution nodes to predict aging warning signals based on similar intervals when time intervals are matched, and the use of transformation rate to identify the current need to switch power loads. In the prior art, a fixed threshold is used for power parameters to identify the existence of similar intervals to describe the relevant conditions in the current power supply and distribution scenario, resulting in the inability of identified parameters such as voltage to change according to load, and ignoring the relevant conditions of voltage before and after distribution switching, resulting in difficulty in identifying system performance and voltage instability during distribution switching, thereby reducing the safety and work efficiency of the power supply and distribution system. Summary of the Invention

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a dynamic monitoring system for the performance health status of a power supply and distribution system, including: a status acquisition module for collecting the operating information of power supply equipment under various power supply modes, and combining the power supply equipment as power supply nodes into a power supply distribution network. The operating information includes voltage, frequency and load rate.

[0007] The power supply switching module is used to view the switching behavior characteristics of the current power supply node configuration according to the operation information of the power supply node, the operation time and the number of switching times of the power supply node.

[0008] The power supply monitoring module is used to check the operating information before and after the power supply mode is switched, and to verify the similarity when switching between different power supply modes based on the voltage deviation and load deviation of the operating information. The operating information of each power supply node is updated based on the similarity corresponding to the power supply mode.

[0009] The switching matching module is used to describe the switching mode of the current power supply node under the power supply mode switching based on the switching behavior characteristics, and to describe the switching matching network of each power supply node based on the switching order of the switching mode.

[0010] The status assessment module is used to generate multiple power supply configuration schemes based on the updated operating information of each power supply node and the switching matching network combination, and to screen the optimal configuration scheme corresponding to each power supply node according to the power supply mode involved in the power supply configuration scheme.

[0011] The beneficial effects of the present invention are: 1. The present invention constructs a power supply distribution network based on the equipment topology relationship, calculates the voltage deviation amplitude, frequency deviation amplitude and load distribution ratio as characteristic values, and uses the characteristic difference between adjacent moments and the relative number of power supply nodes to mark the current power supply distribution network to illustrate the abnormal equipment existing in the power supply and distribution switching operation state; then, the switching frequency and average switching time are counted to identify the abnormal mode, and the switching behavior characteristic difference and conditional probability of adjacent nodes are used to model the combination with similar switching behavior. After identifying the combination, the output data is used as its switching behavior feature to identify the behavioral characteristics of the power supply and distribution switching when an abnormality occurs, so as to realize adaptive prediction of switching behavior and abnormal warning.

[0012] 2. The present invention constructs a similarity matrix based on the time series distribution of voltage deviation and load deviation. After marking the deviation type corresponding to the current power supply node with the similarity matrix, the deviation type is marked in the form of time points to improve the timing correlation during switching tracking.

[0013] Third, this invention classifies switching modes based on parameters such as voltage interruption time and power type. Based on the switching behaviors under these parameters, a switching matching network is constructed to describe the multipath switching sequence and device dependencies. This switching matching network, combined with updated operational information and the least squares method, is used to determine the optimal target mode for each power supply node under the current power supply configuration, improving parameter configuration efficiency and processing effectiveness in multi-parameter optimization scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below with reference to the accompanying drawings and examples.

[0015] Figure 1 It is a system framework diagram of a power supply and distribution system performance health status dynamic monitoring system.

[0016] Figure 2 The present invention is a flow chart of a status acquisition module of a dynamic monitoring system for the performance and health status of a power supply and distribution system.

[0017] Figure 3 The present invention is a flow chart of a power supply monitoring module of a power supply and distribution system performance health status dynamic monitoring system.

[0018] Figure 4 The present invention is a structural diagram of the switching mode in the switching matching module of the dynamic monitoring system for the performance health status of the power supply and distribution system.

[0019] Figure 5 The present invention is a flow chart of a status assessment module of a dynamic monitoring system for the performance and health status of a power supply and distribution system. DETAILED DESCRIPTION

[0020] The following embodiments of the present invention are described in detail. The embodiments described below are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention. Where specific techniques or conditions are not specified in the embodiments, the techniques or conditions described in the literature in the art or in the product specifications shall be followed.

[0021] See Figure 1 A dynamic monitoring system for the performance and health status of a power supply and distribution system includes: a status acquisition module, a power supply switching module, a power supply monitoring module, a switching matching module and a status evaluation module; the output end of the status acquisition module is connected to the power supply switching module, the output end of the power supply switching module is connected to the power supply monitoring module, the output end of the power supply monitoring module is connected to the switching matching module, and the output end of the switching matching module is connected to the status evaluation module.

[0022] The status acquisition module is used to collect the operating information of the power supply equipment under each power supply mode, and combine the power supply equipment as power supply nodes to form a power distribution network. The operating information includes voltage, frequency and load rate.

[0023] The power supply switching module is used to view the switching behavior characteristics of the current power supply node configuration according to the operation information of the power supply node, the operation time and the number of switching times of the power supply node.

[0024] The power supply monitoring module is used to check the operating information before and after the power supply mode is switched, and to verify the similarity when switching between different power supply modes based on the voltage deviation and load deviation of the operating information. The operating information of each power supply node is updated based on the similarity corresponding to the power supply mode.

[0025] The switching matching module is used to describe the switching mode of the current power supply node under the power supply mode switching based on the switching behavior characteristics, and to describe the switching matching network of each power supply node based on the switching order of the switching mode.

[0026] The status assessment module is used to generate multiple power supply configuration schemes based on the updated operating information of each power supply node and the switching matching network combination, and to screen the optimal configuration scheme corresponding to each power supply node according to the power supply mode involved in the power supply configuration scheme.

[0027] It should be noted that, at the location of the power supply equipment, multiple current and voltage meters are used to identify the working conditions of the multiple power supply equipment in the entire power distribution network.

[0028] In the status parameter module, the current power supply method will be collected first, such as the equipment actually supplying power, whether there is any backup equipment for power supply, and the voltage, frequency and load rate of the power supply equipment during operation. These relevant data will be used as the operating information collected at this time.

[0029] like Figure 2As shown, the status acquisition module further includes: regarding the power supply equipment as a power supply node, and forming a power distribution network based on the connection relationship between the power supply equipment.

[0030] The voltage, frequency and load rate of each power supply node in the power distribution network are used to calculate the voltage deviation amplitude, frequency deviation amplitude and load distribution ratio of each power supply node respectively, and use them as the characteristic values ​​of the operation information.

[0031] Determine the change characteristic value of the operating information at two adjacent moments, and use the number of nodes corresponding to each change characteristic value to determine the degree of change of the power distribution network under the corresponding power supply mode. Mark the power supply equipment with the difference in the degree of change between each two adjacent moments.

[0032] Preferably, the power supply equipment can be represented as transformers, switch cabinets, generator sets, UPS uninterruptible power supplies and photovoltaic inverters, etc., which are used to illustrate the current power supply situation. The identified voltage and frequency can assist in checking the stability of the current passing through each device. As for the load rate, it is mainly aimed at the generator sets, UPS power supplies and other equipment directly related to power generation in the power supply equipment to check whether the nodes of these devices have excessive loads that cause abnormalities in the equipment.

[0033] The voltage deviation amplitude and frequency deviation amplitude are used to illustrate the proportional value when the deviation occurs. The load distribution ratio is calculated by using the extracted load rate to calculate the proportion of each node relative to the total number of nodes.

[0034] Preferably, the above-mentioned degree of change is used to illustrate the weighted sum of the voltage deviation amplitude, frequency deviation amplitude and load distribution ratio to illustrate whether the current current is stable at two adjacent moments. If the degree of change can take a larger value, it can be considered that there may be unstable abnormal conditions under the current power supply mode. If the value is small, it will indicate that it is relatively stable, indicating that the operating state is relatively stable.

[0035] That is, the degree of replacement Expressed as: ;in, It is expressed as the degree of change at time t; It is represented as the characteristic value of the voltage deviation amplitude change of the i-th power supply node at time t; It is represented by the characteristic value of the frequency deviation amplitude change of the i-th power supply node at time t; It is represented as the characteristic value of the load distribution ratio change of the i-th power supply node at time t; 、 and They are respectively represented by the weights corresponding to the voltage deviation amplitude, frequency deviation amplitude and load distribution ratio, and their weight values ​​can be set to 0.4, 0.3 and 0.3 respectively, or other values, and their sum is set to 1; Represented as the number of power supply nodes, i ranges from 1 to N. The weighted sum of the iteration degree is used to examine each power supply node based on the number of nodes currently involved. The average value and standard deviation of the iteration degree are then set as thresholds. The average value plus three times the standard deviation is used as the standard threshold for judging whether the current is stable between two adjacent moments. The corresponding power supply equipment is then flagged based on the difference in the iteration degree to indicate whether there are any related issues with the current power supply mode.

[0036] Preferably, when combined into a power supply distribution network, its implementation method also includes: based on the topological relationship of the power supply equipment, detecting the continuous operating time of the power supply equipment under the corresponding current distribution requirements, and using the operating information of any power supply equipment when it is turned on, counting the proportion of the operating time of each power supply equipment to all power supply equipment in the power supply distribution network, and connecting the power supply equipment with the same operating time ratio as adjacent power supply nodes.

[0037] At this time, after describing the connection between the power supply equipment and the physical devices, the parts of these devices with the same operating time ratio are connected, so that when the operating information of the relevant equipment is compared, the equipment load can be evenly distributed among the devices to prevent the existence of single-point overload. Then, the devices with the same ratio usually have similar operating states. After connection, redundant paths are formed to improve the network's tolerance to equipment failures. At this time, when the power distribution network identifies its adjacent nodes, in addition to judging the power supply equipment with a physical connection relationship, it will also check some devices with the same operating time ratio to improve the network's tolerance to equipment abnormalities. When some equipment fails, it can quickly switch according to the redundantly connected devices to maintain power supply continuity.

[0038] It should be noted that when the power supply equipment related to the operating time ratio is used as an additionally described adjacent node, it is also necessary to traverse the topological relationship between the relevant power supply equipment. If some connections such as circuits corresponding to the topological relationship cannot be connected, the corresponding power supply equipment will not be connected, and only some power supply equipment connected in the same topological relationship will be selected to prevent the situation where some power supply nodes are unrelated when connected; at the same time, the purpose of the power supply nodes regarded as adjacent is to associate power supply nodes that are not directly adjacent but may be under the same power supply requirements, to illustrate whether the relevant content of the operating information of multiple power supply nodes under the same power supply requirements is similar or has a high correlation, to assist in identifying whether the voltage, frequency and load rate of the power supply of each power supply device under the overall power supply mode are operating normally.

[0039] In one embodiment of the present invention, when checking the relevant information of the power supply node during switching, the main focus is on checking the time point of each switching, the type of power supply connected before and after the switching, whether the switching is successful, and the voltage interruption time or frequency offset amplitude during the switching; through these parameters directly related to the current during switching, it is possible to identify whether the current power supply switching process is in a normal state.

[0040] The power supply type before and after the above-mentioned switching will directly indicate the power supply node currently used. The successful switching can reflect whether the work is completed normally under the switching times, and the voltage interruption time and frequency offset amplitude describe the relevant status of the operation information. At this time, it is mainly based on the frequency and average switching time corresponding to the switching time point to check whether the current power supply equipment can complete the power supply and distribution processing normally. If there is an abnormality, the corresponding content will be marked and output as the switching behavior characteristics. Based on the switching behavior characteristics in the power supply and distribution scenario, the operation status of the entire system is judged.

[0041] That is, the implementation method of the power supply switching module also includes: according to the operating time and switching number of the power supply node, counting the switching frequency and average switching time of the current power supply node. At this time, after knowing the operating time and switching number of the power supply node, the time point of the current switching and the average switching time under the operating time can be found to describe the overall switching process. At the same time, the switching frequency is used to describe the current number of switching times, so that the power supply node can describe the switching situation of the power supply node in a relatively fixed time period in the form of time intervals or unit time when switching the power supply mode, to prevent the occurrence of excessive switching anomalies and the problem of increased load on other power supply nodes due to too few switching times.

[0042] Threshold detection is performed on the switching frequency and average switching time to identify the switching behavior characteristics of the current power supply node. The switching behavior characteristics are represented as normal switching, frequent switching, abnormal switching, and delayed switching time. This describes whether the current power supply node is in at least one of the following states: normal, warning, abnormal, or pending maintenance when performing power supply mode switching. The threshold detection method is based on the switching frequency and average switching time of the power supply node in historical data. A confidence interval corresponding to the switching frequency and average switching time is constructed, and the upper and lower limits of the confidence interval at the 95% level are extracted as the thresholds. If the switching frequency and average switching time are within the confidence interval, it is considered normal. If the switching frequency and average switching time are close to the upper and lower limits of the confidence interval, if the difference between the upper and lower limits is less than 5%, it is considered to have entered a warning state. If the switching frequency and average switching time are greater than the upper limit of the confidence interval or less than the lower limit of the confidence interval, it is considered abnormal. If multiple consecutive time periods are considered abnormal, it is considered necessary to perform maintenance.

[0043] At this time, the detection needs to check whether the currently selected power supply node can switch the power supply mode normally in the power supply and distribution scenario, and whether the operating time is stable.

[0044] As for identifying the switching behavior characteristics of the current power supply node, its implementation method also includes: based on the threshold detection result of the same power supply node, combining adjacent power supply nodes for judgment, and determining adjacent change combinations based on the difference in switching behavior characteristics of adjacent power supply nodes.

[0045] Based on the conditional probability of adjacent change combinations on the time axis in the switching behavior feature values, a preset time interval corresponding to the current time point is established, and multiple comparison intervals of equal size are delineated in the preset time interval. The change probability of the conditional probability of the switching behavior feature values ​​is identified and used as the comparison behavior feature combination.

[0046] Based on the comparison of the most similar part of the behavior feature combination, the switching behavior feature is output.

[0047] The above-mentioned switching behavior characteristics will form a characteristic vector of the switching behavior characteristics based on the states of switching frequency and average switching time, and select power supply nodes adjacent to the current power supply node in the power supply distribution network to check whether there are differences in their switching behavior characteristics. After these power supply nodes are combined into multiple adjacent change combinations, the conditional probability of the switching behavior characteristic difference in multiple time periods on the time axis is used to describe the correlation between the power supply nodes in the combination.

[0048] For example, assuming that there are three power supply nodes in an adjacent relationship, this adjacent relationship means that after the existence of adjacent nodes on the power supply distribution network, the four states of normal, warning, abnormal and to be repaired correspond to the four forms of labels S0, S1, S2, and S3 respectively. After the probability values ​​of the switching frequency and average switching time of the current power supply node in these four states are obtained, the conditional probability calculation formula is used to express the probability values ​​of the current three power supply nodes using the conditional probability formula, that is, under the condition that the power supply node A is in any of the four states of normal, warning, abnormal and to be repaired, the conditional probability values ​​of the power supply nodes B and C appear in the corresponding state; then each conditional probability is expressed in Whether there are changes when comparing multiple time periods, similarity calculation is performed using multiple change probabilities. For example, after inputting multiple change probabilities in the form of the Pearson correlation coefficient, a similarity value is obtained. Then, the time period and related power supply nodes corresponding to the largest similarity value are found, and they are output as switching behavior features that need to be processed later. At this time, the switching behavior features obtained will show that there is a high correlation between multiple adjacent power supply nodes, and data combinations that may be in abnormal or normal states at the same time, as well as correlations between multiple power supply nodes in the time period when abnormalities occur; this facilitates subsequent processing of the correlations between power supplies to identify whether the current power supply and distribution system is operating normally.

[0049] Preferably, the above-mentioned adjacent change combination represents a group of adjacent power supply nodes with a specific switching behavior characteristic difference. At this time, the adjacent change combination obtained will be divided into multiple adjacent change combinations in pairs based on different switching behavior difference values.

[0050] Preferably, the above-mentioned preset time interval represents the time interval extracted for the current time point. The time interval will be extracted with half the size of the time window for collecting the operating information of the power supply equipment to extract the state changes of different power supply nodes when switching the power supply mode within the local time period, and use the content of the power supply node in any state of normal, warning, abnormal and waiting for maintenance as the state identifier of the corresponding switching behavior feature.

[0051] Preferably, the above-mentioned comparative behavior feature combination is to describe the change probability of the conditional probability to show the advancement process after the power supply mode is switched under relative time.

[0052] In one embodiment of the present invention, under the processing of the power supply monitoring module, the voltage deviation and load deviation are checked, and the stability of the overall power supply is explained by the deviations under different power supply modes. The content identified on each power supply node is then updated using the similarity value to explain whether each power supply device can operate normally under multiple switches. If not, it is marked with its similarity value, and the switching status of the power supply mode of the relevant power supply device is checked and described again.

[0053] At this time, if there is a voltage deviation before and after the switching, there are generally voltage sag, voltage offset and voltage imbalance. For example, a voltage sag will cause a sudden drop in voltage at the switching moment, and then cause a current surge, resulting in a decrease in the current stability of the overall power supply output; voltage offset will indicate that the voltage deviates from the rated value after the switching. The similarity of this identification can be based on the long-term operation phenomenon to identify whether there is a long-term reduction problem, and this phenomenon will cause the steady-state current to increase, ultimately affecting the stability of the power supply system; as for voltage imbalance, it will directly display three current imbalances causing motor heating and other phenomena. At this time, it is necessary to use the sequence length and corresponding similarity corresponding to the voltage deviation to identify the type of voltage deviation and describe the current operation information that needs to be updated and processed.

[0054] Preferably, the load deviation is similar to the situation indicated by the voltage deviation. For example, the load deviation generally indicates the phenomena of load surge, load drop and uneven load distribution; the load surge indicates that new high-power equipment may appear when switching the power supply mode, resulting in a sudden increase in current and current exceeding the limit; the load drop then indicates that after the power supply mode is switched, there are problems with disconnection of certain branches, resulting in a decrease in the overall switching current and an impact on the power supply and distribution system; the last uneven load distribution indicates that when the power supply mode is switched, the load difference of each node is too large, there is a current imbalance, and some positions are locally overloaded. At this time, the load deviation is to verify whether each power supply node can have a stable working condition before and after switching the power supply mode, and use some types corresponding to the load rate to illustrate whether the operation of the distribution node meets expectations under the presence of voltage deviation and load deviation.

[0055] like Figure 3As shown, the implementation method of the power supply monitoring module includes: taking the distribution position of the voltage deviation and load deviation of each power supply node before and after the switching in the time series, the distribution position is regarded as the target data point, and the instantaneous value of the target data point and the time series where the target data point is located are used to perform similarity calculation to form a similarity matrix corresponding to the target data point; the similarity matrix is ​​used to describe the instantaneous value and long sequence value similarity of the voltage deviation and load deviation respectively. After these similarity values ​​are combined into a similarity matrix, the working conditions of each power supply node in the corresponding time period before and after the power supply mode is switched are described respectively, and then the similarity matrix is ​​used to complete its problem identification to obtain whether there is an abnormal situation corresponding to the voltage deviation and load deviation at present. After marking the problem, the operation information of each power supply node before and after the power supply mode is switched is updated.

[0056] Preferably, when calculating the similarity in the similarity matrix, the values ​​taken in a time series are extracted at the positions of the time series where the voltage deviation and load deviation are located, and the similarity value of each power supply node at the time period of the corresponding time series with the corresponding voltage deviation or load deviation in the historical data is obtained by calculating the Pearson correlation coefficient, and then a similarity matrix containing all similarity values ​​is formed in the order of each power supply node label; if it is necessary to calculate with instantaneous values, the similarity is calculated with the values ​​at the corresponding time points and the historical data, and then the similarity matrix is ​​obtained; at the same time, in the obtained similarity matrix, the similarity matrices corresponding to the voltage deviation and load deviation will be separated or merged into one similarity matrix, and the merger will make the similarity matrix store each element in the form of a data pair.

[0057] Based on the similarity matrix corresponding to the target data point, the deviation type of the target data point in the predefined deviation types is determined, and the operation information of each power supply node is updated according to the interval time of the deviation type of the target data point in the time series.

[0058] The implementation method of the deviation type also includes: based on the similarity matrix corresponding to the target data point, clustering each power supply node according to the similarity corresponding to the voltage deviation and the load deviation, identifying the cluster cluster where each power supply node is located, and at this time, clustering can be performed using hierarchical clustering or DBSCAN algorithm to group the power supply nodes; for example, first clustering part of the data of the similarity matrix corresponding to the voltage deviation, and then clustering part of the data corresponding to the load deviation. At this time, the current similarity matrix is ​​used as input, and the cluster clusters set for different deviation types in the historical data are input into the corresponding cluster cluster. After identifying the deviation type that the current target data point can correspond to, the corresponding deviation type is marked to each power supply node in the form of a time point.

[0059] When defining the deviation type corresponding to each power supply node, the deviation type includes but is not limited to load surge, load drop, uneven load distribution, voltage sag, voltage offset and voltage imbalance. At this time, it is used to describe the deviation type existing in each power supply node. The interval time obtained later indicates whether a certain interval time will exist when the relevant deviation type occurs. If so, the interval time is updated to the operation information; otherwise, only the deviation type is updated.

[0060] In one embodiment of the present invention, when using the switching behavior characteristics, the data viewed include the voltage interruption time, the type of power supply connected during switching, and the voltage values ​​before and after the voltage interruption time; the switching behavior characteristics corresponding to these data are used as the subject of identification, and the specific power supply node switched after the switching behavior characteristics complete the power supply mode switching at each power supply node is used as its switching mode, and then the switching order is displayed in the form of a network diagram.

[0061] Therefore, the implementation method of the switching matching module also includes: taking the state identification of the switching behavior characteristics as the basic condition of each power supply node, using the voltage interruption time, power supply type and voltage value before and after the voltage interruption time of each power supply node to divide the switching behavior characteristics, and define the switching mode corresponding to the switching behavior characteristics; using the transfer of the state mark of the switching mode before and after the switching, and the switching order of the switching mode in the time series to form a switching matching network for each power supply node.

[0062] The above-mentioned switching method is used to further describe whether each power supply node is in any of the corresponding states of normal, abnormal, warning and maintenance when the power supply mode is switched, as well as whether the voltage interruption time, power type and voltage value before and after the voltage interruption time of the power supply node are in normal values. Although the voltage value of the power supply node is judged in the switching behavior characteristics, it is also necessary to explain at this time whether it is a problem switching or a problem after switching under different power types and voltage values ​​before and after switching, and form a switching matching network with these existing states as a state transition directional graph, and connect multiple power supply nodes when the switching behavior characteristics are implemented, and use these power supply nodes as the output part at this time to illustrate the real-time working conditions of multiple devices configured under the current power supply and distribution system.

[0063] The above switching order is used to illustrate the order of the switching behavior characteristics of the current input at the time points in the time series. This order will represent the order of abnormal situations with similar patterns in the power supply mode switching scenario to describe the abnormal state changes that occur at different power supply nodes.

[0064] like Figure 4As shown, when defining the switching mode based on the switching behavior characteristics, the problems related to power supply type, voltage, and timing can be divided. Some possible problems are explained in these three aspects in the figure. Then, the switching mode divided in this way can explain the switching behavior characteristics in different situations; then, when these switching modes are composed into a switching matching network according to the situations identified before and after the switching, the time when the power supply mode is switched will be used to indicate whether there are related abnormalities in multiple power supply nodes in the current switching matching network. After displaying the possible problems of the power supply nodes, the time points of each power supply node switching under the timing are gradually connected to form an image of whether all relevant power supply nodes have abnormalities and related abnormal problems under the corresponding power supply mode.

[0065] In one embodiment of the present invention, the operation and switching conditions of a single power supply node in the above four modules need to be integrated in the status assessment module to describe the power supply configuration scheme of multiple nodes under mutual influence, and the contribution degree of each node to the failure of the overall power supply and distribution system under the power supply configuration scheme, to illustrate the influence between multiple nodes. For example, in a parallel timing manner, the data obtained by each power supply node is comprehensively judged upstream and downstream, and the main reason causing the abnormality of the corresponding power supply node is returned to complete the health monitoring of the power supply and distribution system.

[0066] like Figure 5 As shown, the implementation method of the state evaluation module includes: synchronizing the updated operation information of each power supply node to the switching matching network according to the switching order of the corresponding time series.

[0067] Identify the connection paths of the switching matching network, and identify and process the upstream and downstream nodes of each power supply node based on the connection order within each connection path; at this time, there will be multiple paths in the switching matching network. For example, there is a connection path consisting of the main node-static switch-UPS power supply-generator-distribution unit-cabinet. In addition to the power supply node represented by the initial main node, there can be multiple groups of subsequent devices. At the same time, there are connection paths in some scenarios where no generator is set. At this time, it is necessary to process the status of each device in each connection path and the corresponding order during switching, and the causal relationship represented by the upstream and downstream nodes in a parallel timing manner to describe the relative causal relationship between the power supply nodes and the part that needs to be processed in the power supply configuration plan.

[0068] The implementation method of identifying and processing the upstream and downstream nodes of each power supply node includes: responding to the upstream node of the current power supply node, using the status identifier of the upstream node, and configuring the power supply configuration scheme of each upstream node according to the number of status changes when pointing to the current power supply node.

[0069] When configuring upstream nodes, the primary focus is on checking whether the upstream node is in normal, warning, abnormal, or maintenance-required states under the corresponding switching behavior. If an upstream node is abnormal, there is a high probability that the current node will also experience a corresponding abnormality. This allows each node to be traversed one by one to obtain its power supply configuration plan for the upstream node. For upstream nodes, the focus is on analyzing the causal relationship between the current power supply node and the upstream node after the upstream node has an abnormality, thereby resolving any related abnormalities that may have occurred.

[0070] In response to the downstream node of the current power supply node, the power supply configuration scheme of the downstream node is configured based on the deviation type of the current power supply node and the number of times the deviation type recurs when the current node is directed to the downstream node. The deviation type mainly describes the deviations related to voltage, load, and frequency, as well as the updated relevant parts of the voltage deviation and load deviation after the update. After examining the deviation type of the current node to explain the main deviation conditions, it explains how the downstream node adjusts the voltage, load, and frequency components related to the current based on the deviation type of the current node to achieve overall power supply and distribution stability.

[0071] As for the above-mentioned method of processing the upstream and downstream corresponding nodes separately, it is mainly because in a certain parallel scenario, the current power supply node may correspond to multiple parallel upstream nodes and downstream nodes. At this time, it is necessary to separate the power supply nodes in parallel using parallel timing and other methods to prevent the abnormalities in the parallel situation from affecting the current node.

[0072] Preferably, when using the parallel timing processing method, the main purpose is to solve the timing-related problems that exist when the switching matching network is connected, to reduce the problems of time recognition misalignment and time recognition delay caused by transmission delays when collecting some data, and to verify these problems using multiple nodes upstream and downstream and collect the types of deviations that can be caused by voltage, frequency and load when updating. The abnormal connection paths of the current power supply node under parallel timing are displayed one by one to illustrate how the power supply configuration scheme after different power supply nodes are combined should be set. Afterwards, the set power supply configuration scheme needs to be adjusted to select the optimal configuration scheme that can complete the processing of the current power supply node.

[0073] The implementation of the state assessment module also includes: counting the power supply configuration plans on each connection path, and screening the power supply configuration plans based on the upstream and downstream nodes of each connection path; during the screening, the power supply configuration plans of the upstream and downstream nodes are traversed for the processing objectives, such as the power supply equipment that needs to be adjusted, the voltage amplitude that needs to be adjusted, etc., and each power supply configuration plan is used as the starting point for screening. The optimization objectives in the configuration plan are optimized, and the global optimal solution and the local optimal solution are obtained. Based on the power supply configuration plans corresponding to the local optimal solution and the global optimal solution, the current power supply node is adjusted and processed, and the optimal configuration plan is output. Using the optimal multi-objective solution after screening, the corresponding power supply configuration plan is used as the output optimal configuration plan.

[0074] Preferably, when the upstream and downstream nodes screen the power supply configuration scheme, the power supply configuration scheme available to each power supply node is extracted. For example, the equipment and parameters that need to be adjusted are extracted from the configuration scheme of the upstream node, such as the input voltage threshold and other parameters. If the upstream node is marked as abnormal, the impact of the current node is marked, such as voltage drop and other abnormalities; then the parameters that need to be adjusted are extracted from the configuration scheme of the downstream node, such as voltage deviation, and then after identifying the deviation marked by the current node, its impact on the downstream distribution unit is calculated, and whether the downstream node has an overload risk or other identification and deviation types appear; the parameters that need to be adjusted by the upstream and downstream nodes are extracted. At this time, the parameters to be viewed also include frequency and load related content, and the viewing method is the same as the voltage related method. Then, the currently extracted parameters that need to be adjusted are used as the optimization target of the power supply configuration scheme. When a single or multiple optimization targets are to solve local problems, all targets are processed at the same time to describe its global target.

[0075] Once the optimization objectives of the power supply configuration scheme are known, local objectives include minimizing the switching delay after adjustment for a single path and minimizing the local load balancing deviation. The global objective is to minimize the total number of deviation types and the number of state identifiers after adjustment for all nodes. The voltage, frequency, load factor, and switching time of each node's power supply configuration scheme are then used as inputs. The least squares method is used to solve the local optimization objectives and the global objectives in a proportional manner. For example, after calculating the deviations of these four values, the four deviations are combined using a weighted sum. The weighted values ​​are weighted by the number of power supply configurations used in historical data relative to the total number of schemes, resulting in the current relative least squares solution. When the sum of the least squares solutions for each combination is minimized, the local and global objectives are balanced, and the corresponding power supply configuration scheme is the optimal combination of multiple schemes. The corresponding power supply configuration scheme is then output to obtain the data that needs to be adjusted for the current power supply node.

[0076] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention, which are still covered by the scope of protection of the present invention.

Claims

1. A dynamic monitoring system for the performance and health status of a power supply and distribution system, characterized in that: include: The status acquisition module is used to collect the operating information of the power supply equipment under each power supply mode, and combine the power supply equipment as power supply nodes to form a power distribution network. The operating information includes voltage, frequency and load rate; The power supply switching module is used to check the switching behavior characteristics of the current power supply node configuration according to the operation information of the power supply node, the operation time of the power supply node and the number of switching times; The power supply monitoring module is used to check the operating information before and after the power supply mode is switched. The voltage deviation and load deviation of the operating information are used to verify the similarity when switching between different power supply modes. The operating information of each power supply node is updated based on the similarity of the power supply modes. The switching matching module is used to describe the switching mode of the current power supply node under the power supply mode switching based on the switching behavior characteristics, and to describe the switching matching network of each power supply node based on the switching order of the switching mode; The status assessment module is used to generate multiple power supply configuration schemes based on the updated operating information of each power supply node and the switching matching network combination, and to screen the optimal configuration scheme corresponding to each power supply node according to the power supply mode involved in the power supply configuration scheme.

2. A power supply and distribution system performance health status dynamic monitoring system according to claim 1, characterized in that: The status acquisition module also includes: The power supply equipment is regarded as a power supply node, and a power distribution network is formed based on the connection relationship between the power supply equipment; Using the voltage, frequency, and load rate of each power supply node in the power distribution network, the voltage deviation amplitude, frequency deviation amplitude, and load distribution ratio of each power supply node are calculated and used as the characteristic values ​​of the operation information; Determine the change characteristic value of the operating information at two adjacent moments, and use the number of nodes corresponding to each change characteristic value to determine the degree of change of the power distribution network under the corresponding power supply mode. Mark the power supply equipment with the difference in the degree of change between each two adjacent moments.

3. A power supply and distribution system performance health status dynamic monitoring system according to claim 1, characterized in that: When combined into a power distribution network, its implementation also includes: Based on the topological relationship of the power supply equipment, the continuous operating time of the power supply equipment under the corresponding current distribution requirements is detected, and the operating information of any power supply equipment when it is turned on is used to count the proportion of the operating time of each power supply equipment to all the power supply equipment in the power distribution network. The power supply equipment with the same operating time ratio is connected as adjacent power supply nodes.

4. A power supply and distribution system performance health status dynamic monitoring system according to claim 1, characterized in that: The implementation of the power supply switching module also includes: According to the operation time and switching times of the power supply node, the switching frequency and average switching time of the current power supply node are counted; Threshold detection is performed on the switching frequency and average switching time to identify the switching behavior characteristics of the current power supply node.

5. A power supply and distribution system performance health status dynamic monitoring system according to claim 4, characterized in that: When identifying the switching behavior characteristics of the current power supply node, the implementation method also includes: Based on the threshold detection results of the same power supply node, adjacent power supply nodes are combined and judged, and adjacent change combinations are determined based on the difference in switching behavior characteristics of adjacent power supply nodes; Based on the conditional probability of adjacent change combinations on the time axis in the switching behavior feature values, a preset time interval corresponding to the current time point is established. Multiple comparison intervals of equal size are delineated in the preset time interval. The change probability of the conditional probability of the switching behavior feature values ​​is identified and used as the comparison behavior feature combination; Based on the comparison of the most similar part of the behavior feature combination, the switching behavior feature is output.

6. A power supply and distribution system performance health status dynamic monitoring system according to claim 1, characterized in that: The power supply monitoring module can be implemented in the following ways: The distribution positions of the voltage deviation and load deviation of each power supply node before and after the switching in the time series are regarded as the target data points. The similarity is calculated based on the instantaneous value of the target data point and the time series where the target data point is located, forming a similarity matrix corresponding to the target data point. Based on the similarity matrix corresponding to the target data point, the deviation type of the target data point in the predefined deviation types is determined, and the operation information of each power supply node is updated according to the interval time of the deviation type of the target data point in the time series.

7. A power supply and distribution system performance health status dynamic monitoring system according to claim 6, characterized in that: The implementation of the corresponding deviation type also includes: Based on the similarity matrix corresponding to the target data point, each power supply node is clustered according to the similarity corresponding to the voltage deviation and load deviation respectively. The corresponding deviation type is marked to each power supply node in the form of a time point using the cluster clusters set for different deviation types in the historical data.

8. A power supply and distribution system performance health status dynamic monitoring system according to claim 1, characterized in that: The implementation of the switching matching module also includes: The state identification of the switching behavior characteristics is used as the basic condition of each power supply node. The voltage interruption time, power type and voltage value before and after the voltage interruption time of each power supply node are used to segment the switching behavior characteristics and define the switching mode corresponding to the switching behavior characteristics.

9. A power supply and distribution system performance health status dynamic monitoring system according to claim 1, characterized in that: The implementation of the status assessment module includes: Synchronize the updated operating information of each power supply node to the switching matching network according to the switching order of the corresponding time series; Identify the connection paths of the switching matching network and identify the upstream and downstream nodes of each power supply node according to the connection order within each connection path; The power supply configuration schemes on each connection path are counted and screened based on the upstream and downstream nodes of each connection path. The corresponding power supply configuration scheme is output as the optimal configuration scheme using the optimal multi-objective solution after screening.

10. A power supply and distribution system performance health status dynamic monitoring system according to claim 9, characterized in that: The implementation methods for identifying and processing the upstream and downstream nodes of each power supply node include: In response to the upstream node of the current power supply node, using the status identifier of the upstream node, configure the power supply configuration scheme of the upstream node according to the number of state changes of each upstream node when pointing to the current power supply node; In response to the downstream nodes of the current power supply node, the power supply configuration scheme of each downstream node is configured according to the state identifier of the downstream node and the number of state changes when each downstream node points to the current power supply node.

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