A digital intelligent power control system

Abstract

The present invention provides a digital intelligent power control system, which relates to the technical field of data processing. The method includes: collecting load data of equipment to obtain an initial load data set, preprocessing the initial load data set, and sorting it according to a time series, respectively extracting the load data therein by the time length of seconds and minutes, obtaining short-term load data and long-term load data, analyzing the short-term load data to obtain a transient load change rate and a high-frequency load fluctuation event, analyzing the long-term load data set to obtain a load fluctuation range and a periodic load fluctuation, and merging them to obtain a priority evaluation data set, allocating the load priority of the equipment according to the priority evaluation data set, obtaining a load priority table, and adjusting the allocation of power resources according to the priority evaluation data set to obtain a power allocation strategy, and allocating power resources to the equipment. The present invention can intelligently control electricity.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a digital intelligent power control system. Background Art

[0002] The existing digital intelligent power control system monitors the load changes of electrical equipment and controls the power distribution of the equipment in combination with preset load adjustment rules to achieve energy efficiency optimization, thereby ensuring that all equipment can maintain normal operation under normal circumstances.

[0003] With the continuous changes in production processes and the switching of shifts, the demand for electricity changes frequently. The existing digital intelligent power control system may find it difficult to adapt to such frequently changing power demand, resulting in unreasonable allocation of power resources. For example, in a workshop involving multiple power-consuming equipment, when the load of a device rises rapidly in a short period of time, the existing digital intelligent power control system may not be able to adjust the power supply in time, causing the equipment to shut down due to insufficient power supply, affecting the entire production process of the workshop. Summary of the invention

[0004] The purpose of the present invention is to provide a digital intelligent power control system to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A digital intelligent power control system, the system comprising:

[0007] A data acquisition module is used to collect load data of equipment and obtain an initial load data set;

[0008] A data preprocessing module is used to preprocess the initial load data set and sort it according to the time series to obtain a time series data set;

[0009] A data partitioning module is used to extract the load data in the time series data set by the time length of seconds and minutes to obtain short-term load data and long-term load data;

[0010] The short-term load analysis module is used to calculate the transient load change rate based on the short-term load data, and screen the transient load change rate through the preset load change rate to obtain high-frequency load fluctuation events;

[0011] The long-term load analysis module is used to calculate the load mean value based on the long-term load data, and calculate the load standard deviation based on the load mean value, and determine the load fluctuation range through the load mean value and the load standard deviation;

[0012] The load cycle module is used to analyze long-term load data, identify periodic changes in load, and obtain periodic load fluctuations;

[0013] A data collection module is used to combine high-frequency load fluctuation events, load fluctuation ranges and periodic load fluctuations into one collection to obtain a priority evaluation data set;

[0014] A priority module, used to assign priorities to loads of equipment according to a priority evaluation data set, and obtain a load priority table;

[0015] The power distribution module is used to adjust the distribution of power resources according to the load priority table, obtain the power distribution strategy, and distribute power resources to each device according to the power distribution strategy.

[0016] Furthermore, the short-term load analysis module includes:

[0017] A load change rate calculation unit, used to calculate the load difference between adjacent time points based on short-term load data, and calculate the transient load change rate based on the load difference;

[0018] The load change rate screening unit is used to screen according to the transient load change rate and the preset load change rate. When the transient load change rate is greater than the preset load change rate, the load change is a high-frequency load fluctuation event.

[0019] Furthermore, the load cycle module includes:

[0020] A potential cycle unit is used to obtain normal load data by removing sudden peaks in long-term load data, and analyze the normal load data to obtain a potential cycle;

[0021] The window analysis unit is used to divide the normal load data by fixed time length to obtain time windows, and identify the peak and valley values ​​of the load in each time window. When the peak and valley values ​​of each time window are at the same time point, the time length of the time window is the window period;

[0022] The cycle division unit is used to divide the long-term load data according to the potential cycle and the window cycle to obtain the periodic load fluctuation.

[0023] Furthermore, the potential periodic unit includes:

[0024] The autocorrelation coefficient unit is used to divide the normal load data by the time length of minutes, hours, days and weeks, and calculate the autocorrelation coefficient to obtain the autocorrelation coefficient sequence. The calculation formula of the autocorrelation coefficient is:

[0025] ,

[0026] in, is the autocorrelation coefficient, is the index of the data point, For the The load demand of each data point, For the The load demand of each data point, For the The load demand of each data point, is the load mean, is the total number of data points in the normal load data, is the length of time, and is the adjustment coefficient;

[0027] The potential cycle judgment unit is used to determine that when the difference between an autocorrelation coefficient in the autocorrelation coefficient series and other autocorrelation coefficients is greater than a preset coefficient difference, the time length of the autocorrelation coefficient series is a potential cycle.

[0028] Furthermore, the priority module includes:

[0029] The instantaneous load demand unit is used to calculate the load change factor according to the instantaneous load change rate, and obtain the instantaneous load demand according to the load change factor;

[0030] The load priority unit is used to assign priorities to the loads of the equipment according to the transient load change rate to obtain a first priority table, and to adjust the first priority table according to the priority evaluation data set and the transient load demand to obtain a load priority table.

[0031] Furthermore, the instantaneous load demand unit includes:

[0032] A load change factor calculation unit, used for calculating the load change factor according to the transient load change rate;

[0033] The transient load demand calculation unit is used to calculate the transient load demand according to the load change factor. The calculation formula of the transient load demand is:

[0034] ,

[0035] in, For the The transient load demand in seconds, For the The load value in seconds, For the Transient load change rate per second, is the adjustment coefficient, is the load variation factor, is the number of high-frequency load fluctuation events, For the The frequency of high-frequency load fluctuation events, is the time index, For the The transient load change rate of a high-frequency load fluctuation event, is the adjustment coefficient, is a constant.

[0036] Furthermore, the load priority unit includes:

[0037] An initial priority unit, used to assign priorities to loads of equipment according to a transient load change rate and a preset priority change rate, to obtain a first priority table;

[0038] A load mean value adjustment unit, used to obtain a transient load mean value according to the load mean value, compare the transient load demand with the transient load mean value, and when the transient load demand is less than the transient load mean value, adjust the first priority table to reduce the priority of the device to obtain a second priority table;

[0039] The load standard deviation adjustment unit is used to calculate the difference between the transient load demand and the transient load mean to obtain the transient difference, and obtain the transient load standard deviation based on the load standard deviation. When the transient difference is greater than the transient load standard deviation, the second priority table is adjusted to reduce the priority of the equipment and obtain the third priority table.

[0040] Furthermore, the load priority unit also includes:

[0041] The periodic fluctuation adjustment unit is used to identify the periodic state of the equipment according to the periodic load fluctuation data, obtain the load state of the equipment in the current cycle, and when the load state is at a peak period, adjust the third load priority table to increase the priority of the equipment to obtain a fourth priority table;

[0042] The high-frequency fluctuation adjustment unit is used to count the number of high-frequency fluctuations of the equipment according to the high-frequency load fluctuation events to obtain the high-frequency fluctuation frequency. When the high-frequency fluctuation frequency is greater than the preset fluctuation frequency, the fourth priority table is adjusted to increase the priority of the equipment to obtain the load priority table.

[0043] Furthermore, the power distribution module includes:

[0044] The weight coefficient unit is used to analyze the load weight of the equipment in the current time period according to the load priority table to obtain the weight coefficient. The calculation formula of the weight coefficient is:

[0045] ,

[0046] in, For the The weight coefficient of each device, is the index of the device, For the The number of high-frequency load fluctuation events of each device, For the The average load of each device, For the The load standard deviation of each device is For the The load fluctuation range of each device, For the The length of the periodic load fluctuation of each device, is the adjustment coefficient.

[0047] Furthermore, the power distribution module further includes:

[0048] The allocation unit is used to calculate the power allocation of the device in the current time period according to the dynamic weight coefficient. The calculation formula of the power allocation is:

[0049] ,

[0050] in, For the The power distribution of each device, For the The weight coefficient of each device, For the The number of high-frequency load fluctuation events of each device, For the The average load of each device, For the The load standard deviation of each device is For the The load fluctuation range of each device, For the The length of the periodic load fluctuation of each device, is the number of devices, is the total electricity supply, is the adjustment coefficient;

[0051] The distribution adjustment unit is used to adjust the distribution of power resources according to the power distribution amount and the load priority table to obtain a power distribution strategy.

[0052] The above solution of the present invention includes at least the following beneficial effects:

[0053] The present invention captures high-frequency load fluctuation events by calculating the transient load change rate and effectively identifies transient changes in load. This function enables the system to dynamically adapt to short-term changes in equipment load and avoid equipment downtime caused by insufficient power supply. Compared with traditional systems that rely on average load and historical data, this real-time analysis significantly enhances the flexibility of the system, ensures the continuity of the production process, and effectively avoids potential downtime risks caused by sudden increases in load.

[0054] By dividing load data into short-term and long-term load data, the present invention can analyze the load fluctuation characteristics of different time periods respectively, thereby obtaining a priority evaluation data set and a load priority table. The system can flexibly allocate power resources according to real-time conditions to ensure that high-priority equipment can obtain resource support first when the load fluctuates, effectively improving the accuracy of power distribution and optimizing overall energy efficiency.

[0055] The present invention calculates the load mean and load standard deviation through a long-term load analysis module to accurately quantify the load fluctuation range. This function enables the system to adjust resource allocation according to the range of load fluctuations and more accurately reflect the actual needs of the equipment. The system improves the accuracy of load assessment through this quantification method, thereby performing more reasonable power dispatching.

[0056] The present invention can quickly identify the high-frequency fluctuation of equipment through the transient load change rate and the preset load change rate. When the high-frequency fluctuation frequency exceeds the preset value, the system will increase the load priority of the corresponding equipment to ensure that the equipment obtains more stable power support in the short term. This function effectively reduces the unstable power supply caused by drastic load fluctuations, especially in scenarios where high-frequency load changes frequently.

[0057] The present invention analyzes long-term load data through the load cycle module, identifies the periodic changes in the load, and enables the system to reasonably adjust the power distribution strategy in each cycle to match the regular demand of the equipment load, avoiding the waste of resources and power shortage caused by ignoring periodic fluctuations, and helping to achieve more efficient power management. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flow chart of a digital intelligent power control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0060] like Figure 1 As shown, an embodiment of the present invention provides a digital intelligent power control system, the system comprising:

[0061] A data acquisition module is used to collect load data of equipment and obtain an initial load data set;

[0062] A data preprocessing module is used to preprocess the initial load data set and sort it according to the time series to obtain a time series data set;

[0063] A data partitioning module is used to extract the load data in the time series data set by the time length of seconds and minutes to obtain short-term load data and long-term load data;

[0064] The short-term load analysis module is used to calculate the transient load change rate based on the short-term load data, and screen the transient load change rate through the preset load change rate to obtain high-frequency load fluctuation events;

[0065] The long-term load analysis module is used to calculate the load mean value based on the long-term load data, and calculate the load standard deviation based on the load mean value, and determine the load fluctuation range through the load mean value and the load standard deviation;

[0066] The load cycle module is used to analyze long-term load data, identify periodic changes in load, and obtain periodic load fluctuations;

[0067] A data collection module is used to combine high-frequency load fluctuation events, load fluctuation ranges and periodic load fluctuations into one collection to obtain a priority evaluation data set;

[0068] A priority module, used to assign priorities to loads of equipment according to a priority evaluation data set, and obtain a load priority table;

[0069] The power distribution module is used to adjust the distribution of power resources according to the load priority table, obtain the power distribution strategy, and distribute power resources to each device according to the power distribution strategy.

[0070] In an embodiment of the present invention, the data acquisition module forms an initial load data set by collecting the load data of the equipment, ensuring that the current load status of the equipment can be obtained at any time point, thereby laying the foundation for the analysis of the entire system; the data preprocessing module preprocesses the initial load data set and sorts it according to the time series to obtain the time series data set, thereby improving the accuracy and reliability of the data and reducing the errors that may be affected by data fluctuations in subsequent load analysis, thereby ensuring the rationality of load analysis and allocation; the data partitioning module extracts the load data in the time series data set according to the time length of seconds and minutes, generates short-term load data and long-term load data, and realizes load data analysis at different time scales, so that the system can perform targeted analysis when dealing with instantaneous changes and periodic fluctuations, significantly improving the system's adaptability to diversified load characteristics.

[0071] The short-term load analysis module calculates the transient load change rate based on the short-term load data, and filters the transient load change rate through the preset load change rate to identify high-frequency load fluctuation events. It can quickly detect and judge the drastic changes in the load, effectively identify the load fluctuations that need to be focused on in the short term, and thus reduce the risk of unstable power supply caused by short-term load fluctuations; the long-term load analysis module calculates the load mean based on the long-term load data, and uses the mean and standard deviation to determine the load fluctuation range, providing information on load stability and fluctuation amplitude, so that the system can allocate resources accordingly; the load cycle module analyzes the long-term load data to identify the periodic changes in the load, thereby obtaining periodic load fluctuations, so that the system can identify the law of load peak and valley changes in advance, allocate power resources in a targeted manner, and reduce the problem of power waste or insufficient load supply caused by periodic load fluctuations; the data collection module combines high-frequency load fluctuation events, load fluctuation ranges and periodic load fluctuation information into a priority evaluation data set. Through the data collection module, the system can summarize various types of load characteristic data, thereby conducting a more comprehensive evaluation of equipment load priority.

[0072] The priority module generates a load priority table through the priority evaluation data set and assigns priority to the load of each device. The system identifies the load weight of the current device load and assigns different priorities to it, ensuring the optimal allocation of system resources, so that power resources can give priority to meeting the needs of key equipment when supply and demand are tight, improve overall power efficiency, and ensure the reliability of system operation and the stability of equipment; the power distribution module formulates a power distribution strategy based on the load priority table and allocates power resources according to the strategy, realizing dynamic management of power resources. The system can flexibly adjust power supply as the load changes, ensuring the stable operation of key equipment when power resources are limited, and avoiding the waste of resources caused by excessive power supply.

[0073] Among them, the data acquisition module is used to collect the load data of the equipment and obtain the initial load data set. By combining the monitoring equipment and the sensor network, and collecting data points at intervals per second, the load information of each device is recorded to obtain the load data of each device.

[0074] Among them, the data preprocessing module is used to preprocess the initial load data set and sort it according to the time series to obtain the time series data set. By cleaning the collected initial load data set, removing outliers and noise, analyzing the sudden changes in the load data, and judging whether it is an abnormal fluctuation or collection error, the data points that may affect the subsequent analysis are eliminated, and then they are arranged in the order of collection time and converted into a time series that meets the analysis requirements to obtain the time series data set.

[0075] Among them, the data division module is used to extract the load data in the time series data set according to the time length of seconds and minutes, respectively, to obtain short-term load data and long-term load data. By dividing the time series data, each load data point is classified according to the time scale of seconds and minutes, respectively, to obtain short-term load data and long-term load data; the short-term load data at the second level records the load changes of the equipment in a very short time, so as to capture the transient fluctuations of the load, and the long-term load data at the minute level can reflect the load change trend of the equipment over a longer period.

[0076] Among them, the data collection module is used to merge high-frequency load fluctuation events, load fluctuation ranges and periodic load fluctuations into one set to obtain a priority evaluation data set. By standardizing data from different sources, first removing the units of the data, and then converting all the data into a dimensionless form through ratio calculation, they are merged into one set to obtain a priority evaluation data set to comprehensively reflect the load status of the equipment, providing a rich information basis for subsequent priority sorting.

[0077] In a preferred embodiment of the present invention, the short-term load analysis module includes:

[0078] A load change rate calculation unit, used to calculate the load difference between adjacent time points based on short-term load data, and calculate the transient load change rate based on the load difference;

[0079] The load change rate screening unit is used to screen according to the transient load change rate and the preset load change rate. When the transient load change rate is greater than the preset load change rate, the load change is a high-frequency load fluctuation event.

[0080] In an embodiment of the present invention, a load change rate calculation unit calculates the load difference between adjacent time points based on short-term load data, and calculates a transient load change rate based on the load difference, and uses the load change in a short time interval to reflect the severity or trend change of the current load of the equipment, thereby accurately capturing the instantaneous fluctuation of the load; the load change rate comparison unit compares the transient load change rate with the preset load change rate to identify high-frequency load fluctuation events, and screens out abnormal load fluctuations through simple and efficient rules, providing the system with a rapid response mechanism to high-frequency load fluctuations, and being able to timely identify and mark severe load fluctuations, so that the system can give priority to taking corresponding power distribution measures for these high-frequency fluctuation events, thereby improving the system's ability to cope with sudden load changes and ensuring stable power supply to equipment during high-load periods.

[0081] Among them, according to the short-term load data, the load difference between adjacent time points is calculated, and the transient load change rate is calculated according to the load difference, which specifically includes:

[0082] According to the short-term load data, the load value at the current time point is compared with the load value at the previous time point to obtain the load difference, and then the transient load change rate within the time period is calculated based on the load difference and the time interval.

[0083] Among them, the preset load change rate is based on the historical load data of the equipment. Usually, the load change data of the equipment during normal operation is collected, the load change rate in different time periods is calculated, and the average or peak value of the load change rate within a certain time range is taken as the preset load change rate.

[0084] In a preferred embodiment of the present invention, the load cycle module comprises:

[0085] A potential cycle unit is used to obtain normal load data by removing sudden peaks in long-term load data, and analyze the normal load data to obtain a potential cycle;

[0086] The window analysis unit is used to divide the normal load data by fixed time length to obtain time windows, and identify the peak and valley values ​​of the load in each time window. When the peak and valley values ​​of each time window are at the same time point, the time length of the time window is the window period;

[0087] The cycle division unit is used to divide the long-term load data according to the potential cycle and the window cycle to obtain the periodic load fluctuation.

[0088] In an embodiment of the present invention, the potential cycle unit screens the long-term load data, removes sudden peaks or abnormal fluctuations in the data, so as to extract more regular normal load data, analyze the periodic trend therein, and obtain the potential cycle; the window analysis unit groups the normal load data according to a fixed time length, and by comparing the load changes in each time window, the system can confirm whether the load characteristics of different time periods are regular, and infer the load cycle of the equipment; the cycle division unit divides the long-term load data into different cycle segments based on the analysis results of the potential cycle and the window cycle, so as to clearly show the load changes of the equipment in each cycle.

[0089] Among them, the normal load data is divided by a fixed time length to obtain a time window, and the peak and valley values ​​of the load in each time window are identified. When the peak and valley values ​​of each time window are at the same time point, the time length of the time window is the window period, which specifically includes:

[0090] Normal load data is grouped according to fixed time lengths (such as hours, days, and weeks) to obtain multiple time windows. The peak and valley values ​​of the load are identified in each time window, and their change patterns are analyzed. When the peak and valley values ​​of multiple time windows appear at the same time point or show similar change trends, the time length of the time window can be determined as the window period.

[0091] In a preferred embodiment of the present invention, the potential period unit comprises:

[0092] The autocorrelation coefficient unit is used to divide the normal load data by the time length of minutes, hours, days and weeks, and calculate the autocorrelation coefficient to obtain the autocorrelation coefficient sequence. The calculation formula of the autocorrelation coefficient is:

[0093] ;

[0094] in, is the autocorrelation coefficient, is the index of the data point, For the The load demand of each data point, For the The load demand of each data point, For the The load demand of each data point, is the load mean, is the total number of data points in the normal load data, is the length of time, and is the adjustment coefficient;

[0095] The potential cycle judgment unit is used to determine that when the difference between an autocorrelation coefficient in the autocorrelation coefficient series and other autocorrelation coefficients is greater than a preset coefficient difference, the time length of the autocorrelation coefficient series is a potential cycle.

[0096] In an embodiment of the present invention, the autocorrelation coefficient unit divides the normal load data into different time units, such as minutes, hours, days and weeks, so as to observe the periodic characteristics of the data on different time scales. The system calculates the autocorrelation coefficient based on the load data in each time segment. The autocorrelation coefficient is used to quantify the similarity of the data at different time points. The potential period judgment unit confirms the periodicity of the data by identifying significant changes in the autocorrelation coefficient, and can accurately lock the potential period of the load to form an estimate of the periodic demand.

[0097] Among them, when the difference between one autocorrelation coefficient and other autocorrelation coefficients in the autocorrelation coefficient series is greater than the preset coefficient difference, the time length of the autocorrelation coefficient series is the potential cycle, specifically:

[0098] The system will analyze each autocorrelation coefficient value in the autocorrelation coefficient sequence. When the difference between a certain autocorrelation coefficient and other autocorrelation coefficients in the sequence is greater than the preset coefficient difference, the time length of the autocorrelation coefficient sequence is regarded as a potential cycle. For example, when the autocorrelation coefficient within a time length is significantly higher than that of other time periods, it means that the load data in this time period shows a high degree of consistency in periodicity.

[0099] Among them, the preset coefficient difference is obtained by performing autocorrelation analysis on long-term load data to obtain the autocorrelation coefficients at multiple time intervals, and then calculating the difference between the autocorrelation coefficients in different time intervals. Through statistical analysis, a set of difference standards can be determined, and finally a difference threshold is set according to these statistical values ​​as the preset coefficient difference.

[0100] In a preferred embodiment of the present invention, the priority module includes:

[0101] The instantaneous load demand unit is used to calculate the load change factor according to the instantaneous load change rate, and obtain the instantaneous load demand according to the load change factor;

[0102] The load priority unit is used to assign priorities to the loads of the equipment according to the transient load change rate to obtain a first priority table, and to adjust the first priority table according to the priority evaluation data set and the transient load demand to obtain a load priority table.

[0103] In an embodiment of the present invention, the instantaneous load demand unit calculates the load change factor through the transient load change rate. The load change factor is a parameter that reflects the fluctuation amplitude of the equipment load demand and is used to quantify the degree of drastic change in the current equipment load. The load change factor is then used to calculate the instantaneous load demand, and the demand value represents the immediate demand for power resources of the equipment at the current moment. The load priority unit assigns a higher allocation priority to equipment with larger load fluctuations according to the transient load change rate of the current equipment to form a first priority table. The first priority table records the priority allocation order of each equipment under the current load state. Subsequently, the system adjusts the first priority table in combination with the priority evaluation data set and the instantaneous load demand, so that the system can respond quickly when the load demand changes, thereby ensuring the rationality and flexibility of resource allocation.

[0104] In a preferred embodiment of the present invention, the instantaneous load demand unit comprises:

[0105] A load change factor calculation unit, used for calculating the load change factor according to the transient load change rate;

[0106] The transient load demand calculation unit is used to calculate the transient load demand according to the load change factor. The calculation formula of the transient load demand is:

[0107] ;

[0108] in, For the The transient load demand in seconds, For the The load value in seconds, For the Transient load change rate per second, is the adjustment coefficient, is the load variation factor, is the number of high-frequency load fluctuation events, For the The frequency of high-frequency load fluctuation events, is the time index, For the The transient load change rate of a high-frequency load fluctuation event, is the adjustment coefficient, is a constant.

[0109] In an embodiment of the present invention, the load change factor calculation unit calculates the load change factor through the transient load change rate. The factor is used to measure the load fluctuation intensity and demand urgency of the equipment at the current moment. The load change factor can reflect the dynamic fluctuation of the equipment load demand, and provides a key parameter for further calculation of the instantaneous load demand. The transient load demand calculation unit incorporates the immediate impact of the equipment load fluctuation into the demand calculation by combining the load change factor, so that the system can more accurately grasp the power demand of the current equipment, and reflect the dynamic data of the equipment's instant power demand, so that the system can make timely power distribution adjustments according to changes in transient demand, thereby effectively avoiding power shortages caused by sudden load increases.

[0110] In a preferred embodiment of the present invention, the load priority unit includes:

[0111] An initial priority unit, used to assign priorities to loads of equipment according to a transient load change rate and a preset priority change rate, to obtain a first priority table;

[0112] A load mean value adjustment unit, used to obtain a transient load mean value according to the load mean value, compare the transient load demand with the transient load mean value, and when the transient load demand is less than the transient load mean value, adjust the first priority table to reduce the priority of the device to obtain a second priority table;

[0113] The load standard deviation adjustment unit is used to calculate the difference between the transient load demand and the transient load mean to obtain the transient difference, and obtain the transient load standard deviation based on the load standard deviation. When the transient difference is greater than the transient load standard deviation, the second priority table is adjusted to reduce the priority of the equipment and obtain the third priority table.

[0114] In an embodiment of the present invention, the initial priority unit compares the transient load change rate with the preset priority change rate to determine the relative priority of each device, establishes a basic priority ranking, and provides a basis for subsequent priority adjustments; the load mean adjustment unit adjusts the first priority table according to the load mean of the device to balance the long-term demand and current demand of the device, and avoids waste of resources due to reduced demand for some devices in a short period of time; the load standard deviation adjustment unit calculates the transient difference based on the difference between the transient load demand and the load mean, and further adjusts the priority based on the load standard deviation to ensure that when the load demand of the device increases abnormally, the system can respond quickly and provide sufficient power resources, while avoiding allocating too many resources to devices with stable demand, thereby improving the flexibility and effectiveness of overall power distribution.

[0115] According to the transient load change rate and the preset priority change rate, the load of the equipment is assigned priority to obtain a first priority table, which specifically includes:

[0116] When the transient load change rate of the equipment is higher than the preset priority change rate, it indicates that the current load demand of the equipment is more urgent, so it will be assigned a higher initial priority, so that it will get priority in power support when resources are allocated; when the transient load change rate of the equipment is not higher than the preset priority change rate, it indicates that the load demand of the equipment is relatively stable, and the system will assign a lower initial priority to such equipment to ensure that power resources are allocated first to equipment with greater load fluctuations and more urgent needs; when the transient load change rate of the equipment is close to but does not reach the preset priority change rate, an intermediate priority is assigned to the equipment for flexible processing to ensure that the flexibility of power supply can be appropriately improved when the load fluctuates slightly. By assigning an initial priority to each device, a first priority table is obtained.

[0117] Among them, the preset priority change rate is obtained by analyzing the historical data of the relationship between the equipment's load demand and priority change. By analyzing the priority change trend of the equipment under different load levels, especially when the equipment load suddenly increases or decreases in a short period of time, the response of the equipment priority can determine the correlation between the load change rate and the priority adjustment, and then set a preset priority change rate.

[0118] Among them, according to the load mean, the transient load mean is obtained, and the transient load demand is compared with the transient load mean. When the transient load demand is less than the transient load mean, the first priority table is adjusted to reduce the priority of the equipment to obtain the second priority table, which specifically includes:

[0119] Based on the average load of the equipment per minute, the average transient load per second is calculated, and the transient load demand is compared with the transient load average. When the transient load demand is lower than the average load of the equipment, the system lowers the priority of the equipment in the first priority table by one level to allocate power resources to other equipment with higher load demands, ensuring that the equipment does not occupy too much power resources when the load is low, and obtaining the second priority table.

[0120] The difference between the transient load demand and the transient load mean is calculated to obtain the transient difference, and the transient load standard deviation is obtained according to the load standard deviation. When the transient difference is greater than the transient load standard deviation, the second priority table is adjusted to reduce the priority of the equipment to obtain the third priority table, which specifically includes:

[0121] The transient difference is calculated based on the difference between the transient load demand and the load mean. When the transient difference is greater than the load standard deviation of the equipment, it means that the current load demand of the equipment exceeds its normal fluctuation range. The priority of the equipment in the second priority table is reduced by one level to avoid allocating too many resources to abnormal equipment, and the third priority table is obtained.

[0122] In a preferred embodiment of the present invention, the load priority unit further includes:

[0123] The periodic fluctuation adjustment unit is used to identify the periodic state of the equipment according to the periodic load fluctuation data, obtain the load state of the equipment in the current cycle, and when the load state is at a peak period, adjust the third load priority table to increase the priority of the equipment to obtain a fourth priority table;

[0124] The high-frequency fluctuation adjustment unit is used to count the number of high-frequency fluctuations of the equipment according to the high-frequency load fluctuation events to obtain the high-frequency fluctuation frequency. When the high-frequency fluctuation frequency is greater than the preset fluctuation frequency, the fourth priority table is adjusted to increase the priority of the equipment to obtain the load priority table.

[0125] In an embodiment of the present invention, a periodic fluctuation adjustment unit identifies the periodic state of the equipment based on the periodic load fluctuation data, and adjusts the load priority table based on the state, so that the system can identify and respond to periodic load fluctuations in advance, ensuring that the equipment obtains sufficient power support during peak demand periods, thereby optimizing resource utilization efficiency and reducing power waste or insufficient power supply due to periodic load fluctuations; a high-frequency fluctuation adjustment unit analyzes the high-frequency load fluctuation events of the equipment, counts the number of high-frequency fluctuations of the equipment within a period of time, and calculates its high-frequency fluctuation frequency. The high-frequency fluctuation frequency reflects the frequency of drastic load fluctuations of the equipment in a relatively short period of time, ensuring that the power demand changes of the equipment can be responded to in a timely manner under conditions of frequent load fluctuations, avoiding short-term insufficient power supply due to high-frequency fluctuations, thereby enhancing the stability and flexibility of the system.

[0126] According to the periodic load fluctuation data, the periodic state of the equipment is identified to obtain the load state of the equipment in the current cycle. When the load state is at a peak period, the third load priority table is adjusted to increase the priority of the equipment to obtain a fourth priority table, which specifically includes:

[0127] According to the periodic load fluctuation data of the equipment, the periodic state of the current equipment is identified, that is, whether the equipment is currently in a peak load period, a stable period or a trough period. When the equipment is in the peak period of the periodic load, the system raises the priority of the equipment in the third priority table by one level to ensure that it can obtain a more stable power supply during the peak load stage. The equipment priority is adjusted through this step to obtain the fourth priority table.

[0128] According to the high-frequency load fluctuation event, the number of high-frequency fluctuations of the equipment is counted to obtain the high-frequency fluctuation frequency. When the high-frequency fluctuation frequency is greater than the preset fluctuation frequency, the fourth priority table is adjusted to increase the priority of the equipment to obtain the load priority table, which specifically includes:

[0129] By analyzing the high-frequency load fluctuation events of the equipment, counting the number of high-frequency fluctuations of the equipment within a period of time, and calculating its high-frequency fluctuation frequency, when the high-frequency fluctuation frequency of the equipment exceeds the preset fluctuation frequency threshold, the system will increase the priority of the equipment in the fourth priority table by one level to ensure that during frequent load fluctuations, the equipment can obtain priority power supply so that the equipment can operate normally. The equipment priority is adjusted through this step to obtain compliance with the priority table.

[0130] Among them, the preset fluctuation frequency is achieved by recording the load fluctuation of the equipment in each time period, counting the frequency of high-frequency fluctuations, and calculating the fluctuation frequency under different operating conditions. Through these data, a normal range of equipment load fluctuations can be obtained, and the preset fluctuation frequency can be set based on this range.

[0131] In a preferred embodiment of the present invention, the power distribution module comprises:

[0132] The weight coefficient unit is used to analyze the load weight of the equipment in the current time period according to the load priority table to obtain the weight coefficient. The calculation formula of the weight coefficient is:

[0133] ;

[0134] in, For the The weight coefficient of each device, is the index of the device, For the The number of high-frequency load fluctuation events of each device, For the The average load of each device, For the The load standard deviation of each device is For the The load fluctuation range of each device, For the The length of the periodic load fluctuation of each device, is the adjustment coefficient.

[0135] In an embodiment of the present invention, the weight coefficient unit calculates the load weight of each device based on the priority and the current load status of each device. The calculation of this load weight not only refers to the real-time load demand of the device, but also combines the load priority of the device, so as to give priority to devices with higher priorities when power resources are tight.

[0136] In a preferred embodiment of the present invention, the power distribution module further includes:

[0137] The allocation unit is used to calculate the power allocation of the device in the current time period according to the dynamic weight coefficient. The calculation formula of the power allocation is:

[0138] ;

[0139] in, For the The power distribution of each device, For the The weight coefficient of each device, For the The number of high-frequency load fluctuation events of each device, For the The average load of each device, For the The load standard deviation of each device is For the The load fluctuation range of each device, For the The length of the periodic load fluctuation of each device, is the number of devices, is the total electricity supply, is the adjustment coefficient;

[0140] The distribution adjustment unit is used to adjust the distribution of power resources according to the power distribution amount and the load priority table to obtain a power distribution strategy.

[0141] In an embodiment of the present invention, the allocation unit calculates the power allocation for each device based on the weight coefficient and the total power supply in the current time period. The system can give priority to meeting the needs of high-load and high-priority devices to avoid affecting the normal operation of key equipment due to insufficient power. The allocation adjustment unit further adjusts the actual allocation of power resources based on the power allocation and load priority table to ensure the adaptability of the system under dynamic conditions, so that the power allocation process has adaptive adjustment capabilities. The system can flexibly adjust the allocation plan according to the actual load changes of the equipment to ensure that reasonable power allocation can still be achieved in the case of sudden changes in load demand, thereby improving the stability of the system and resource utilization efficiency.

[0142] According to the power allocation amount and the load priority table, the power resource allocation is adjusted to obtain the power allocation strategy, which specifically includes:

[0143] The system monitors the actual load changes of the equipment. When the load demand of a certain device exceeds the power allocation, the system will adjust the power supply of other devices and transfer more resources to the device to ensure its operational stability. On the contrary, if the load demand of a certain device decreases, the system will reduce the power allocation to the device accordingly and reallocate the saved resources to the device with larger load demand. By adjusting the power resource allocation as above, the power allocation strategy is obtained.

[0144] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A digital intelligent power control system, characterized in that: The system comprises: A data acquisition module is used to collect load data of equipment and obtain an initial load data set; A data preprocessing module is used to preprocess the initial load data set and sort it according to the time series to obtain a time series data set; A data partitioning module is used to extract the load data in the time series data set by the time length of seconds and minutes to obtain short-term load data and long-term load data; The short-term load analysis module is used to calculate the transient load change rate based on the short-term load data, and screen the transient load change rate through the preset load change rate to obtain high-frequency load fluctuation events; The long-term load analysis module is used to calculate the load mean value based on the long-term load data, and calculate the load standard deviation based on the load mean value, and determine the load fluctuation range through the load mean value and the load standard deviation; The load cycle module is used to analyze long-term load data, identify periodic changes in load, and obtain periodic load fluctuations; A data collection module is used to combine high-frequency load fluctuation events, load fluctuation ranges and periodic load fluctuations into one collection to obtain a priority evaluation data set; A priority module, used to assign priorities to loads of equipment according to a priority evaluation data set, and obtain a load priority table; The power distribution module is used to adjust the distribution of power resources according to the load priority table, obtain the power distribution strategy, and distribute power resources to each device according to the power distribution strategy; The priority module includes: The instantaneous load demand unit is used to calculate the load change factor according to the instantaneous load change rate, and obtain the instantaneous load demand according to the load change factor; A load priority unit is used to assign priorities to the loads of the equipment according to the transient load change rate to obtain a first priority table, and to adjust the first priority table according to the priority evaluation data set and the transient load demand to obtain a load priority table; The load priority unit comprises: An initial priority unit, used to assign priorities to loads of equipment according to a transient load change rate and a preset priority change rate, to obtain a first priority table; A load mean value adjustment unit, used to obtain a transient load mean value according to the load mean value, compare the transient load demand with the transient load mean value, and when the transient load demand is less than the transient load mean value, adjust the first priority table to reduce the priority of the device to obtain a second priority table; A load standard deviation adjustment unit is used to calculate the difference between the transient load demand and the transient load mean value to obtain a transient difference value, and obtain a transient load standard deviation according to the load standard deviation. When the transient difference value is greater than the transient load standard deviation, the second priority table is adjusted to reduce the priority of the equipment to obtain a third priority table; The load priority unit also includes: The periodic fluctuation adjustment unit is used to identify the periodic state of the equipment according to the periodic load fluctuation data, obtain the load state of the equipment in the current cycle, and when the load state is at a peak period, adjust the third load priority table to increase the priority of the equipment to obtain a fourth priority table; The high-frequency fluctuation adjustment unit is used to count the number of high-frequency fluctuations of the equipment according to the high-frequency load fluctuation events to obtain the high-frequency fluctuation frequency. When the high-frequency fluctuation frequency is greater than the preset fluctuation frequency, the fourth priority table is adjusted to increase the priority of the equipment to obtain the load priority table.

2. A digital intelligent power control system according to claim 1, characterized in that: The short-term load analysis module includes: A load change rate calculation unit, used to calculate the load difference between adjacent time points based on short-term load data, and calculate the transient load change rate based on the load difference; The load change rate screening unit is used to screen according to the transient load change rate and the preset load change rate. When the transient load change rate is greater than the preset load change rate, the load change is a high-frequency load fluctuation event.

3. A digital intelligent power control system according to claim 2, characterized in that: The load cycle module includes: A potential cycle unit is used to obtain normal load data by removing sudden peaks in long-term load data, and analyze the normal load data to obtain a potential cycle; The window analysis unit is used to divide the normal load data by fixed time length to obtain time windows, and identify the peak and valley values ​​of the load in each time window. When the peak and valley values ​​of each time window are at the same time point, the time length of the time window is the window period; The cycle division unit is used to divide the long-term load data according to the potential cycle and the window cycle to obtain the periodic load fluctuation.

4. A digital intelligent power control system according to claim 3, characterized in that: The potential cycle unit includes: The autocorrelation coefficient unit is used to divide the normal load data by the time length of minutes, hours, days and weeks, and calculate the autocorrelation coefficient to obtain the autocorrelation coefficient sequence. The calculation formula of the autocorrelation coefficient is: ， in, is the autocorrelation coefficient, is the index of the data point, For the The load demand of each data point, For the The load demand of each data point, For the The load demand of each data point, is the load mean, is the total number of data points in the normal load data, is the length of time, and is the adjustment coefficient; The potential cycle judgment unit is used to determine that when the difference between an autocorrelation coefficient in the autocorrelation coefficient series and other autocorrelation coefficients is greater than a preset coefficient difference, the time length of the autocorrelation coefficient series is a potential cycle.

5. A digital intelligent power control system according to claim 4, characterized in that: The instantaneous load demand unit comprises: A load change factor calculation unit, used for calculating the load change factor according to the transient load change rate; The transient load demand calculation unit is used to calculate the transient load demand according to the load change factor. The calculation formula of the transient load demand is: ， in, For the The transient load demand in seconds, For the The load value in seconds, For the Transient load change rate per second, is the adjustment coefficient, is the load variation factor, is the number of high-frequency load fluctuation events, For the The frequency of high-frequency load fluctuation events, is the time index, For the The transient load change rate of a high-frequency load fluctuation event, is the adjustment coefficient, is a constant.

6. A digital intelligent power control system according to claim 5, characterized in that: The power distribution module comprises: The weight coefficient unit is used to analyze the load weight of the equipment in the current time period according to the load priority table to obtain the weight coefficient. The calculation formula of the weight coefficient is: ， in, For the The weight coefficient of each device, is the index of the device, For the The number of high-frequency load fluctuation events of each device, For the The average load of each device, For the The load standard deviation of each device is For the The load fluctuation range of each device, For the The length of the periodic load fluctuation of each device, is the adjustment coefficient.

7. A digital intelligent power control system according to claim 6, characterized in that: The power distribution module also includes: The allocation unit is used to calculate the power allocation of the device in the current time period according to the dynamic weight coefficient. The calculation formula of the power allocation is: ， in, For the The power distribution of each device, For the The weight coefficient of each device, For the The number of high-frequency load fluctuation events of each device, For the The average load of each device, For the The load standard deviation of each device is For the The load fluctuation range of each device, For the The length of the periodic load fluctuation of each device, is the number of devices, is the total electricity supply, is the adjustment coefficient; The distribution adjustment unit is used to adjust the distribution of power resources according to the power distribution amount and the load priority table to obtain a power distribution strategy.

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