Power distribution data analysis-based electric energy quality evaluation system and method

Abstract

The invention relates to the technical field of electric energy evaluation, in particular to an electric energy quality evaluation system and method based on power distribution data analysis, and the evaluation method comprises the following steps: analyzing the change condition of a voltage value stored in an electric energy evaluation record, and obtaining the normal fluctuation amplitude and the abnormal proportion time of the voltage value; dividing all electric energy evaluation records on the electric energy quality data management platform according to an evaluation result; external environment information contained in the electric energy evaluation records in different categories after division is extracted respectively, and influence factors of electric energy quality evaluation are generated; constructing an electric energy quality evaluation model; inputting each electric energy evaluation record into an electric energy quality evaluation model for calculation to obtain a risk value of each electric energy evaluation record, and determining a risk threshold value; and the change condition of the voltage value of the currently generated electric energy evaluation record is analyzed, a risk value is obtained by inputting the electric energy quality evaluation model, and whether risk early warning is carried out or not is judged.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy evaluation, and in particular to a system and method for evaluating electric energy quality based on power distribution data analysis. Background Art

[0002] Power quality refers to the characteristics and quality of electric energy in the power system, which mainly reflects the stability, reliability and applicability of power supply; it involves the fluctuation of electrical parameters such as voltage, current and frequency, and the impact of these fluctuations on power equipment and users; good power quality can improve the operating stability of equipment, reduce the failure rate, and thus improve the economy and reliability of the overall system; therefore, the monitoring, evaluation and improvement of power quality are of great significance in power system management.

[0003] Therefore, the accuracy of the power quality assessment will directly affect the normal operation of the equipment; however, different regions and industries may have different standards and requirements for power quality, resulting in subjective evaluation of power quality. For example, short-term voltage and current fluctuations will be ignored, which will lead to deviations in the assessment of power quality and affect the stability of the power system and the normal operation of the equipment. Summary of the invention

[0004] The object of the present invention is to provide a power quality assessment system and method based on power distribution data analysis to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a power quality assessment method based on power distribution data analysis, the assessment method comprising the following steps: Step S100: Obtain the power evaluation record on the power quality data management platform, analyze the change of the voltage value stored in the power evaluation record in a unit cycle, and obtain the normal fluctuation range of the voltage value and the abnormal proportion time of the abnormal voltage value in the power evaluation record; the power quality data management platform is used to store the change of relevant data such as voltage and current in a unit cycle, external environment information and abnormal conditions in the unit cycle; Step S200: obtaining the evaluation results stored in the power evaluation records, and dividing all the power evaluation records on the power quality data management platform according to the evaluation results, analyzing and comparing the normal fluctuation amplitude and abnormal proportion time of the divided power evaluation records; respectively extracting the external environment information contained in the power evaluation records in different categories after the division, and generating the influencing factors of the power quality evaluation by comparing the external environment information; Step S300: Analyze the influence of each influencing factor on the power quality assessment in each power assessment record, and build a power quality assessment model; input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record; Step S400: Obtain the currently generated electric energy assessment record, analyze the change in the voltage value stored in the generated electric energy assessment record in a unit cycle; input the generated electric energy assessment record into the power quality assessment model, obtain the risk value of the generated electric energy assessment record, and determine whether to issue a risk warning for the generated electric energy assessment record.

[0006] Furthermore, step S100 includes the following steps: Step S101: arbitrarily select the ith power evaluation record, set the ith power evaluation record to store the change of the voltage value over time in the ith unit period T, and obtain the average voltage value of the ith unit period T ; Step S102: Divide the i-th unit period T into several time points evenly, and take the time interval between two adjacent time points as the voltage duration of the previous time point; obtain the voltage value of the j-th time point as , the voltage value in the i-th unit period T is The number of time points is , the voltage value is The duration of ,in, is the time interval between two adjacent time points; the voltage value with the largest duration ratio is selected as the stable voltage value of the i-th electric energy assessment record; Step S103: Set the stable voltage value of the i-th electric energy evaluation record to , the maximum normal fluctuation range of the i-th electric energy assessment record is calculated to be ;like , according to the formula: , the maximum normal fluctuation voltage value of the i-th electric energy assessment record is calculated to be , and the average voltage value As the minimum normal fluctuation voltage value of the ith electric energy assessment record, the normal voltage fluctuation range of the ith electric energy assessment record is obtained. ;like , according to the formula: , the minimum normal fluctuation voltage value of the i-th electric energy assessment record is calculated as , and the average voltage value As the maximum normal fluctuation voltage value of the ith electric energy assessment record, the normal voltage fluctuation range of the ith electric energy assessment record is obtained as ; Based on the stable voltage value in the electric energy assessment record, the normal voltage fluctuation range and the abnormal duration ratio are obtained. However, the obtained data are analyzed relative to the voltage change in a unit cycle in a selected electric energy assessment record. If all electric energy assessment records are analyzed, some electric energy assessment records will be in an abnormal state due to volatility, which is different from the actual situation. Therefore, a relative comparison can obtain reference data more accurately, which is conducive to subsequent data comparison and analysis. Step S104: setting the voltage value that is not within the normal voltage fluctuation range as an abnormal voltage value; obtaining the duration of the abnormal voltage value in the unit period T as , calculate the abnormal duration ratio of abnormal voltage value in the i-th electric energy assessment record .

[0007] Further, step S200 includes the following steps: Step S201: Set the evaluation result of the i-th electric energy evaluation record to , capture whether there is an abnormal reminder mark in the i-th power evaluation record; if there is an abnormal reminder mark, then If there is no abnormal reminder mark, then ; Get the maximum normal fluctuation range of the i-th electric energy assessment record and abnormal duration ratio , the electric energy data set for generating the i-th electric energy assessment record is ; Classify all power evaluation records on the power quality data management platform according to the evaluation results to obtain a normal power evaluation record set and an abnormal power evaluation record set; Step S202: extracting the normal fluctuation range with the largest value in each power evaluation record of the normal power evaluation record set as the maximum safe fluctuation range of the normal power evaluation record set ; Extract the normal fluctuation amplitude with the smallest value in each electric energy evaluation record of the abnormal electric energy evaluation record set as the minimum abnormal fluctuation amplitude of the abnormal electric energy evaluation record set ;like , then select the fluctuation range , generating a first characteristic range of electric energy assessment records; the first characteristic range is a fluctuation range in which the same voltage fluctuation amplitude exists in a normal electric energy assessment record set and an abnormal electric energy assessment record set; Step S203: extracting the abnormal duration ratio with the largest value in each electric energy evaluation record of the normal electric energy evaluation record set as the maximum abnormal duration ratio of the normal electric energy evaluation record set ; Extract the abnormal duration ratio with the smallest value in each electric energy assessment record of the abnormal electric energy assessment record set as the minimum abnormal duration ratio of the abnormal electric energy assessment record set ;like , then select the abnormal duration ratio range , generating a second characteristic range of electric energy assessment records; the second characteristic range is the proportion range of the same abnormal duration in the normal electric energy assessment record set and the abnormal electric energy assessment record set; Step S204: Establish an environmental impact factor database, which contains several environmental characteristics; when the ith power evaluation record belongs to the abnormal power evaluation record set, and the maximum normal fluctuation range of the ith power evaluation record Or the abnormal duration ratio , obtaining the external environment information contained in the ith electric energy assessment record; dividing the external environment information, matching the divided information segments with each environmental feature, and determining the environmental feature corresponding to each information segment; Step S205: respectively obtain the maximum normal fluctuation range in the normal power evaluation record set The energy evaluation record with the smallest difference and the proportion of abnormal duration The electric energy assessment record with the smallest difference is set as two target comparison records; the external environment information contained in the two target comparison records is divided into information segments, and the environmental characteristics corresponding to each information segment are determined; Step S206: obtaining a number of information segments corresponding to any environmental feature, and setting the number of information segments to a; if a=1, setting the environmental feature as an influencing factor; if a>1, comparing the similarities between the information segments, and if the similarity is less than a set similarity threshold, setting the environmental feature as an influencing factor; comparing each electric energy assessment record in the abnormal electric energy assessment record set with the electric energy assessment record in the normal electric energy assessment record set to obtain a number of influencing factors, and generating an influencing factor set; The reason for the difference in evaluation results is the interference of the power data itself and external environmental factors. By comparing the environmental information stored in each power evaluation record corresponding to an environmental feature, the differences between the comparisons can be used to obtain the specific factors that lead to different evaluation results when the power data itself is similar. Capturing the influencing factors from objective data can more effectively evaluate the power quality.

[0008] Further, step S300 includes the following steps: Step S301: Obtaining the first characteristic range of the electric energy evaluation record and the second characteristic range , the first characteristic reference value is calculated to be and the second characteristic reference value is ; Step S302: Obtain all influencing factors corresponding to the ith electric energy assessment record, and select the mth influencing factor; arbitrarily select an electric energy assessment record containing the mth influencing factor from the normal electric energy assessment record set, perform similarity comparison on two information segments corresponding to the mth influencing factor, set a similarity threshold, and if the similarity between the two information segments is less than the similarity threshold, set the mth influencing factor as the target influencing factor; Step S303: among all target influencing factors of the ith power evaluation record, the set number of the mth influencing factor in each power evaluation record of the abnormal power evaluation record set is , the proportion of the mth influencing factor is calculated as , where p is the number of electric energy assessment records in the abnormal electric energy assessment record set; Step S304: Obtain the electric energy data set of the ith electric energy assessment record And the average voltage value of the i-th unit period T stored ;Build a power quality assessment model:

[0009] Among them, IF() is a judgment function. If the mth influencing factor is the target influencing factor, then ,otherwise, ; The risk value of the i-th power assessment record is calculated through the power quality assessment model ; Obtain the risk value of each power assessment record in the abnormal power assessment record set, and select the risk value with the smallest value as the risk threshold of power quality assessment ; Taking the average value of voltage as the basic data, adjusting the basic data in combination with the influence of abnormal duration ratio and fluctuation amplitude, and adding the influence of various influencing factors on power quality, a more comprehensive judgment can be made on power assessment, making the final risk value more accurate; and the higher the risk value, the lower the power quality.

[0010] Furthermore, step S400 includes the following steps: Step S401: Obtain the power evaluation record currently generated on the power quality data management platform, obtain the voltage change of the generated power evaluation record in the unit period T, and obtain the average voltage value and power data collection ; Step S402: extract the external environment information contained in the generated electric energy assessment record, match it with the environmental characteristics in the environmental impact factor database, obtain several target impact factors of the generated electric energy assessment record, and calculate the proportion of each target impact factor in the abnormal electric energy assessment record set; Step S403: average voltage value , Electric energy data collection The number and proportion of each target influencing factor are input into the power quality assessment model to obtain the risk value of the generated power assessment record ; Set risk thresholds ,like , a risk warning is issued for the generated electric energy assessment record.

[0011] In order to better implement the above method, a power quality assessment system based on distribution data analysis is also proposed. The assessment system includes an assessment record analysis module, an influencing factor analysis module, a model building module and a risk judgment module; An assessment record analysis module is used to obtain the power assessment records on the power quality data management platform, analyze the changes in the voltage values ​​stored in the power assessment records in a unit cycle, and obtain the normal fluctuation range of the voltage values ​​in the power assessment records and the abnormal proportion time of the abnormal voltage values; The influencing factor analysis module is used to obtain the evaluation results stored in the power evaluation records, and divide all the power evaluation records on the power quality data management platform according to the evaluation results, and analyze and compare the normal fluctuation range and abnormal proportion time of the divided power evaluation records; respectively extract the external environment information contained in the power evaluation records in different categories after division, and generate the influencing factors of power quality evaluation by comparing the external environment information; The model building module is used to analyze the influence of various influencing factors on the power quality assessment in each power assessment record and build a power quality assessment model; input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record; The risk judgment module is used to obtain the currently generated electric energy assessment record, analyze the change of the voltage value stored in the generated electric energy assessment record in a unit cycle; input the generated electric energy assessment record into the power quality assessment model, obtain the risk value of the generated electric energy assessment record, and judge whether to issue a risk warning for the generated electric energy assessment record.

[0012] Further, the evaluation record analysis module includes a voltage data analysis unit and a correlation data calculation unit; The voltage data analysis unit is used to obtain the power evaluation records on the power quality data management platform and analyze the changes in the voltage values ​​stored in the power evaluation records in a unit cycle; the associated data calculation unit is used to obtain the normal fluctuation range of the voltage value in the power evaluation record and the abnormal proportion time of the abnormal voltage value.

[0013] Further, the impact factor analysis module includes an evaluation record comparison unit and an impact factor extraction unit; The evaluation record comparison unit is used to obtain the evaluation results stored in the power evaluation records, and divide all the power evaluation records on the power quality data management platform according to the evaluation results, and analyze and compare the normal fluctuation range and abnormal proportion time of the divided power evaluation records; the influencing factor extraction unit is used to respectively extract the external environment information contained in the power evaluation records in different categories after division, and generate the influencing factors of power quality evaluation by comparing the external environment information.

[0014] Furthermore, the model building module includes a model generation unit and a model training unit; The model production unit is used to analyze the influence of various influencing factors on the power quality assessment in each power assessment record and build a power quality assessment model; the model training unit is used to input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record.

[0015] Further, the risk judgment module includes a current data analysis unit and a risk calculation unit; The current data analysis unit is used to obtain the currently generated electric energy assessment record and analyze the change of the voltage value stored in the generated electric energy assessment record in a unit cycle; the risk calculation unit is used to input the generated electric energy assessment record into the electric energy quality assessment model, obtain the risk value of the generated electric energy assessment record, and determine whether to issue a risk warning for the generated electric energy assessment record.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: (1) The present invention analyzes the various influencing factors affecting the power quality and objectively analyzes the power quality through data, thereby eliminating subjective evaluation and ensuring that the power quality assessment is more scientific and accurate; (2) The present invention specifically analyzes the voltage fluctuation in combination with various influencing factors, thereby solving the problem of different evaluation results under the same fluctuation conditions in the past, ensuring timely discovery of abnormal power quality and avoiding ignoring possible abnormal conditions; (3) The present invention ensures that the staff can discover the existing abnormal conditions in the first place and solve them in a timely manner to avoid affecting the stability of the power system and the normal operation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a schematic diagram of the steps of a power quality assessment method based on power distribution data analysis; Figure 2 It is a structural diagram of a power quality assessment system based on distribution data analysis. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 to Figure 2 The present invention provides a technical solution: a power quality assessment method based on power distribution data analysis, the assessment method comprising the following steps: Step S100: Obtain the power evaluation record on the power quality data management platform, analyze the change of the voltage value stored in the power evaluation record in a unit cycle, and obtain the normal fluctuation range of the voltage value and the abnormal proportion time of the abnormal voltage value in the power evaluation record; Wherein, step S100 includes the following steps: Step S101: arbitrarily select the ith power evaluation record, set the ith power evaluation record to store the change of the voltage value over time in the ith unit period T, and obtain the average voltage value of the ith unit period T ; Step S102: Divide the i-th unit period T into several time points evenly, and take the time interval between two adjacent time points as the voltage duration of the previous time point; obtain the voltage value of the j-th time point as , the voltage value in the i-th unit period T is The number of time points is , the voltage value is The duration of ,in, is the time interval between two adjacent time points; the voltage value with the largest duration ratio is selected as the stable voltage value of the i-th electric energy assessment record; Step S103: Set the stable voltage value of the i-th electric energy evaluation record to , the maximum normal fluctuation range of the i-th electric energy assessment record is calculated to be ;like , according to the formula: , the maximum normal fluctuation voltage value of the i-th electric energy assessment record is calculated to be , and the average voltage value As the minimum normal fluctuation voltage value of the ith electric energy assessment record, the normal voltage fluctuation range of the ith electric energy assessment record is obtained. ;like , according to the formula: , the minimum normal fluctuation voltage value of the i-th electric energy assessment record is calculated as , and the average voltage value As the maximum normal fluctuation voltage value of the ith electric energy assessment record, the normal voltage fluctuation range of the ith electric energy assessment record is obtained as ; Step S104: setting the voltage value that is not within the normal voltage fluctuation range as an abnormal voltage value; obtaining the duration of the abnormal voltage value in the unit period T as , calculate the abnormal duration ratio of abnormal voltage value in the i-th electric energy assessment record .

[0020] Step S200: obtaining the evaluation results stored in the power evaluation records, and dividing all the power evaluation records on the power quality data management platform according to the evaluation results, analyzing and comparing the normal fluctuation amplitude and abnormal proportion time of the divided power evaluation records; respectively extracting the external environment information contained in the power evaluation records in different categories after the division, and generating the influencing factors of the power quality evaluation by comparing the external environment information; Wherein, step S200 includes the following steps: Step S201: Set the evaluation result of the i-th electric energy evaluation record to , capture whether there is an abnormal reminder mark in the i-th power evaluation record; if there is an abnormal reminder mark, then If there is no abnormal reminder mark, then ; Get the maximum normal fluctuation range of the i-th electric energy assessment record and abnormal duration ratio , the electric energy data set for generating the i-th electric energy assessment record is ; Classify all power evaluation records on the power quality data management platform according to the evaluation results to obtain a normal power evaluation record set and an abnormal power evaluation record set; Step S202: extracting the normal fluctuation range with the largest value in each power evaluation record of the normal power evaluation record set as the maximum safe fluctuation range of the normal power evaluation record set ; Extract the normal fluctuation amplitude with the smallest value in each electric energy evaluation record of the abnormal electric energy evaluation record set as the minimum abnormal fluctuation amplitude of the abnormal electric energy evaluation record set ;like , then select the fluctuation range , generating a first characteristic range of an electric energy assessment record; Step S203: extracting the abnormal duration ratio with the largest value in each electric energy evaluation record of the normal electric energy evaluation record set as the maximum abnormal duration ratio of the normal electric energy evaluation record set ; Extract the abnormal duration ratio with the smallest value in each electric energy assessment record of the abnormal electric energy assessment record set as the minimum abnormal duration ratio of the abnormal electric energy assessment record set ;like , then select the abnormal duration ratio range , generating a second characteristic range of the electric energy assessment record; Step S204: Establish an environmental impact factor database, which contains several environmental characteristics; when the ith power evaluation record belongs to the abnormal power evaluation record set, and the maximum normal fluctuation range of the ith power evaluation record Or the abnormal duration ratio , obtaining the external environment information contained in the ith electric energy assessment record; dividing the external environment information, matching the divided information segments with each environmental feature, and determining the environmental feature corresponding to each information segment; Step S205: respectively obtain the maximum normal fluctuation range in the normal power evaluation record set The energy evaluation record with the smallest difference and the proportion of abnormal duration The electric energy assessment record with the smallest difference is set as two target comparison records; the external environment information contained in the two target comparison records is divided into information segments, and the environmental characteristics corresponding to each information segment are determined; Step S206: obtain several information segments corresponding to any environmental feature, and set the number of information segments to a; if a=1, set the environmental feature as an influencing factor; if a>1, compare the similarities between the several information segments, and if the similarity is less than the set similarity threshold, set the environmental feature as an influencing factor; compare each electric energy assessment record in the abnormal electric energy assessment record set with the electric energy assessment record in the normal electric energy assessment record set to obtain several influencing factors, and generate an influencing factor set.

[0021] Step S300: Analyze the influence of each influencing factor on the power quality assessment in each power assessment record, and build a power quality assessment model; input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record; Wherein, step S300 includes the following steps: Step S301: Obtaining the first characteristic range of the electric energy evaluation record and the second characteristic range , the first characteristic reference value is calculated to be and the second characteristic reference value is ; Step S302: Obtain all influencing factors corresponding to the ith electric energy assessment record, and select the mth influencing factor; arbitrarily select an electric energy assessment record containing the mth influencing factor from the normal electric energy assessment record set, perform similarity comparison on two information segments corresponding to the mth influencing factor, set a similarity threshold, and if the similarity between the two information segments is less than the similarity threshold, set the mth influencing factor as the target influencing factor; Step S303: among all target influencing factors of the ith power evaluation record, the set number of the mth influencing factor in each power evaluation record of the abnormal power evaluation record set is , the proportion of the mth influencing factor is calculated as , where p is the number of electric energy assessment records in the abnormal electric energy assessment record set; Step S304: Obtain the electric energy data set of the ith electric energy assessment record And the average voltage value of the i-th unit period T stored ;Build a power quality assessment model:

[0022] Among them, IF() is a judgment function. If the mth influencing factor is the target influencing factor, then ,otherwise, ; The risk value of the i-th power assessment record is calculated through the power quality assessment model ; Obtain the risk value of each power assessment record in the abnormal power assessment record set, and select the risk value with the smallest value as the risk threshold of power quality assessment .

[0023] Step S400: obtaining the currently generated power evaluation record, analyzing the change of the voltage value stored in the generated power evaluation record in a unit cycle; inputting the generated power evaluation record into the power quality evaluation model, obtaining the risk value of the generated power evaluation record, and determining whether to issue a risk warning for the generated power evaluation record; Wherein, step S400 includes the following steps: Step S401: Obtain the power evaluation record currently generated on the power quality data management platform, obtain the voltage change of the generated power evaluation record in the unit period T, and obtain the average voltage value and power data collection ; Step S402: extract the external environment information contained in the generated electric energy assessment record, match it with the environmental characteristics in the environmental impact factor database, obtain several target impact factors of the generated electric energy assessment record, and calculate the proportion of each target impact factor in the abnormal electric energy assessment record set; Step S403: average voltage value , Electric energy data collection The number and proportion of each target influencing factor are input into the power quality assessment model to obtain the risk value of the generated power assessment record ; Set risk thresholds ,like , a risk warning is issued for the generated electric energy assessment record.

[0024] A power quality assessment system based on power distribution data analysis, the assessment system comprising an assessment record analysis module, an influencing factor analysis module, a model building module and a risk judgment module; An assessment record analysis module is used to obtain the power assessment records on the power quality data management platform, analyze the changes in the voltage values ​​stored in the power assessment records in a unit cycle, and obtain the normal fluctuation range of the voltage values ​​in the power assessment records and the abnormal proportion time of the abnormal voltage values; The influencing factor analysis module is used to obtain the evaluation results stored in the power evaluation records, and divide all the power evaluation records on the power quality data management platform according to the evaluation results, and analyze and compare the normal fluctuation range and abnormal proportion time of the divided power evaluation records; respectively extract the external environment information contained in the power evaluation records in different categories after division, and generate the influencing factors of power quality evaluation by comparing the external environment information; The model building module is used to analyze the influence of various influencing factors on the power quality assessment in each power assessment record and build a power quality assessment model; input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record; The risk judgment module is used to obtain the currently generated electric energy assessment record, analyze the change of the voltage value stored in the generated electric energy assessment record in a unit cycle; input the generated electric energy assessment record into the power quality assessment model, obtain the risk value of the generated electric energy assessment record, and judge whether to issue a risk warning for the generated electric energy assessment record.

[0025] Among them, the evaluation record analysis module includes a voltage data analysis unit and a correlation data calculation unit; The voltage data analysis unit is used to obtain the power evaluation records on the power quality data management platform and analyze the changes in the voltage values ​​stored in the power evaluation records in a unit cycle; the associated data calculation unit is used to obtain the normal fluctuation range of the voltage value in the power evaluation record and the abnormal proportion time of the abnormal voltage value.

[0026] Among them, the impact factor analysis module includes an evaluation record comparison unit and an impact factor extraction unit; The evaluation record comparison unit is used to obtain the evaluation results stored in the power evaluation records, and divide all the power evaluation records on the power quality data management platform according to the evaluation results, and analyze and compare the normal fluctuation range and abnormal proportion time of the divided power evaluation records; the influencing factor extraction unit is used to respectively extract the external environment information contained in the power evaluation records in different categories after division, and generate the influencing factors of power quality evaluation by comparing the external environment information.

[0027] Among them, the model building module includes a model generation unit and a model training unit; The model production unit is used to analyze the influence of various influencing factors on the power quality assessment in each power assessment record and build a power quality assessment model; the model training unit is used to input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record.

[0028] Among them, the risk judgment module includes a current data analysis unit and a risk calculation unit; The current data analysis unit is used to obtain the currently generated electric energy assessment record and analyze the change of the voltage value stored in the generated electric energy assessment record in a unit cycle; the risk calculation unit is used to input the generated electric energy assessment record into the electric energy quality assessment model, obtain the risk value of the generated electric energy assessment record, and determine whether to issue a risk warning for the generated electric energy assessment record.

[0029] Obtain the power evaluation records on the power quality data management platform, taking the first power evaluation record as an example; obtain the voltage change in the first power evaluation record in a unit period of 1 day, and obtain an average voltage value of 100V; divide 1 day into 24×60 time points, and the interval between two adjacent time points is 1min; count the number of time points with a voltage of 110V as 18×60, and obtain that the duration of the voltage of 110V accounts for 75%; therefore, the voltage of 110V is taken as the stable voltage value of the first power evaluation record; obtain the maximum normal fluctuation range of 9%; because 110V>100V, take 100V as the minimum normal fluctuation voltage value, according to the formula: The maximum normal fluctuation voltage value is calculated to be =119.9V; obtain the duration of the voltage value not being between (100V, 119.9V), and obtain that the abnormal duration accounts for 10%; If there is no abnormal reminder mark in the first electric energy assessment record, then R=0; classify all electric energy assessment records according to whether there is an abnormal reminder mark, and obtain two sets of normal electric energy assessment record set and abnormal electric energy assessment record set, among which the first electric energy assessment record belongs to the normal electric energy assessment set record; The electric energy data set of the first electric energy assessment record is obtained as D=(9%, 10%, 0); the electric energy data set closest to the first electric energy assessment record is selected from the abnormal electric energy assessment record for comparison; the external environment information contained in the two electric energy assessment records is extracted, wherein the first one contains "high temperature, dryness" and the second one contains "low temperature, humidity"; the environmental characteristics are matched with the environmental impact factor database, and the corresponding environmental characteristics are obtained as temperature and humidity; therefore, the two environmental characteristics are set as impact factors; The number of influencing factors obtained, temperature, accounts for 80%, and humidity accounts for 60%; the power quality assessment model is constructed:

[0030] The risk value of the first electric energy assessment record is Z=100×(1+0.02 / 0.06)×(1+0.01 / 0.06)×0.48=133×1.67×0.48=106.61; =0.08, =0.08; = =(0.06, 0.1); From the set of abnormal power assessment records, the risk value of each power assessment record is selected, and the one with the smallest risk value is Z=150 as the risk threshold. Because 106.61<150, there is no abnormality in the first power assessment record.

[0031] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0032] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating power quality based on power distribution data analysis, characterized in that: The evaluation method comprises the following steps: Step S100: Obtain the power evaluation record on the power quality data management platform, analyze the change of the voltage value stored in the power evaluation record in a unit cycle, and obtain the normal fluctuation range of the voltage value and the abnormal proportion time of the abnormal voltage value in the power evaluation record; Step S200: obtaining the evaluation results stored in the power evaluation records, and dividing all the power evaluation records on the power quality data management platform according to the evaluation results, analyzing and comparing the normal fluctuation amplitude and abnormal proportion time of the divided power evaluation records; respectively extracting the external environment information contained in the power evaluation records in different categories after the division, and generating the influencing factors of the power quality evaluation by comparing the external environment information; Step S300: Analyze the influence of each influencing factor on the power quality assessment in each power assessment record, and build a power quality assessment model; input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record; Step S400: Obtain the currently generated electric energy assessment record, analyze the change in the voltage value stored in the generated electric energy assessment record in a unit cycle; input the generated electric energy assessment record into the power quality assessment model, obtain the risk value of the generated electric energy assessment record, and determine whether to issue a risk warning for the generated electric energy assessment record.

2. The power quality assessment method based on power distribution data analysis according to claim 1 is characterized in that: The step S100 includes the following steps: Step S101: arbitrarily select the ith power evaluation record, set the ith power evaluation record to store the change of the voltage value over time in the ith unit period T, and obtain the average voltage value of the ith unit period T ; Step S102: Divide the i-th unit period T into several time points evenly, and take the time interval between two adjacent time points as the voltage duration of the previous time point; obtain the voltage value of the j-th time point as , the voltage value in the i-th unit period T is The number of time points is , the voltage value is The duration of ,in, is the time interval between two adjacent time points; the voltage value with the largest duration ratio is selected as the stable voltage value of the i-th electric energy assessment record; Step S103: Set the stable voltage value of the i-th electric energy evaluation record to , the maximum normal fluctuation range of the i-th electric energy assessment record is calculated to be ;like , according to the formula: , the maximum normal fluctuation voltage value of the i-th electric energy assessment record is calculated to be , and the average voltage value As the minimum normal fluctuation voltage value of the ith electric energy assessment record, the normal voltage fluctuation range of the ith electric energy assessment record is obtained. ;like , according to the formula: , the minimum normal fluctuation voltage value of the i-th electric energy assessment record is calculated as , and the average voltage value As the maximum normal fluctuation voltage value of the ith electric energy assessment record, the normal voltage fluctuation range of the ith electric energy assessment record is obtained as ; Step S104: setting the voltage value that is not within the normal voltage fluctuation range as an abnormal voltage value; obtaining the duration of the abnormal voltage value in the unit period T as , calculate the abnormal duration ratio of abnormal voltage value in the i-th electric energy assessment record .

3. The power quality assessment method based on power distribution data analysis according to claim 2 is characterized in that: The step S200 includes the following steps: Step S201: Set the evaluation result of the i-th electric energy evaluation record to , capture whether there is an abnormal reminder mark in the i-th power evaluation record; if there is an abnormal reminder mark, then If there is no abnormal reminder mark, then ; Get the maximum normal fluctuation range of the i-th electric energy assessment record and abnormal duration ratio , the electric energy data set for generating the i-th electric energy assessment record is ; Classify all power evaluation records on the power quality data management platform according to the evaluation results to obtain a normal power evaluation record set and an abnormal power evaluation record set; Step S202: extracting the normal fluctuation range with the largest value in each power evaluation record of the normal power evaluation record set as the maximum safe fluctuation range of the normal power evaluation record set ; Extract the normal fluctuation amplitude with the smallest value in each electric energy evaluation record of the abnormal electric energy evaluation record set as the minimum abnormal fluctuation amplitude of the abnormal electric energy evaluation record set ;like , then select the fluctuation range , generating a first characteristic range of an electric energy assessment record; Step S203: extracting the abnormal duration ratio with the largest value in each electric energy evaluation record of the normal electric energy evaluation record set as the maximum abnormal duration ratio of the normal electric energy evaluation record set ; Extract the abnormal duration ratio with the smallest value in each electric energy assessment record of the abnormal electric energy assessment record set as the minimum abnormal duration ratio of the abnormal electric energy assessment record set ;like , then select the abnormal duration ratio range , generating a second characteristic range of the electric energy assessment record; Step S204: Establish an environmental impact factor database, which contains several environmental characteristics; when the ith power evaluation record belongs to the abnormal power evaluation record set, and the maximum normal fluctuation range of the ith power evaluation record Or the abnormal duration ratio , obtaining the external environment information contained in the ith electric energy assessment record; dividing the external environment information, matching the divided information segments with each environmental feature, and determining the environmental feature corresponding to each information segment; Step S205: respectively obtain the maximum normal fluctuation range in the normal power evaluation record set The energy evaluation record with the smallest difference and the proportion of abnormal duration The electric energy assessment record with the smallest difference is set as two target comparison records; the external environment information contained in the two target comparison records is divided into information segments, and the environmental characteristics corresponding to each information segment are determined; Step S206: obtain several information segments corresponding to any environmental feature, and set the number of information segments to a; if a=1, set the environmental feature as an influencing factor; if a>1, compare the similarities between the several information segments, and if the similarity is less than the set similarity threshold, set the environmental feature as an influencing factor; compare each electric energy assessment record in the abnormal electric energy assessment record set with the electric energy assessment record in the normal electric energy assessment record set to obtain several influencing factors, and generate an influencing factor set.

4. The method for evaluating power quality based on power distribution data analysis according to claim 3 is characterized in that: The step S300 includes the following steps: Step S301: Obtaining the first characteristic range of the electric energy evaluation record and the second characteristic range , the first characteristic reference value is calculated to be and the second characteristic reference value is ; Step S302: Obtain all influencing factors corresponding to the ith electric energy assessment record, and select the mth influencing factor; arbitrarily select an electric energy assessment record containing the mth influencing factor from the normal electric energy assessment record set, perform similarity comparison on two information segments corresponding to the mth influencing factor, set a similarity threshold, and if the similarity between the two information segments is less than the similarity threshold, set the mth influencing factor as the target influencing factor; Step S303: among all target influencing factors of the ith power evaluation record, the set number of the mth influencing factor in each power evaluation record of the abnormal power evaluation record set is , the proportion of the mth influencing factor is calculated as , where p is the number of electric energy assessment records in the abnormal electric energy assessment record set; Step S304: Obtain the electric energy data set of the ith electric energy assessment record And the stored average voltage value of the i-th unit period T ;Build a power quality assessment model: ， Among them, IF() is a judgment function. If the mth influencing factor is the target influencing factor, then ,otherwise, ; The risk value of the i-th power assessment record is calculated through the power quality assessment model ; Obtain the risk value of each power assessment record in the abnormal power assessment record set, and select the risk value with the smallest value as the risk threshold of power quality assessment .

5. The method for evaluating power quality based on power distribution data analysis according to claim 4 is characterized in that: The step S400 includes the following steps: Step S401: Obtain the power evaluation record currently generated on the power quality data management platform, obtain the voltage change of the generated power evaluation record in the unit period T, and obtain the average voltage value and power data collection ; Step S402: extract the external environment information contained in the generated electric energy assessment record, match it with the environmental characteristics in the environmental impact factor database, obtain several target impact factors of the generated electric energy assessment record, and calculate the proportion of each target impact factor in the abnormal electric energy assessment record set; Step S403: average voltage value , Electric energy data collection The number and proportion of each target influencing factor are input into the power quality assessment model to obtain the risk value of the generated power assessment record ; Set risk thresholds ,like , a risk warning is issued for the generated electric energy assessment record.

6. A power quality assessment system, used to execute a power quality assessment method based on power distribution data analysis as claimed in any one of claims 1 to 5, characterized in that: The evaluation system includes an evaluation record analysis module, an impact factor analysis module, a model building module and a risk judgment module; The evaluation record analysis module is used to obtain the power evaluation record on the power quality data management platform, analyze the change of the voltage value stored in the power evaluation record in a unit cycle, and obtain the normal fluctuation range of the voltage value in the power evaluation record and the abnormal proportion time of the abnormal voltage value; The influencing factor analysis module is used to obtain the evaluation results stored in the power evaluation records, and divide all the power evaluation records on the power quality data management platform according to the evaluation results, and analyze and compare the normal fluctuation range and abnormal proportion time of the divided power evaluation records; respectively extract the external environment information contained in the power evaluation records in different categories after the division, and generate the influencing factors of the power quality evaluation by comparing the external environment information; The model building module is used to analyze the influence of various influencing factors on the power quality assessment in each power assessment record and build a power quality assessment model; input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record; The risk judgment module is used to obtain the currently generated electric energy assessment record and analyze the change of the voltage value stored in the generated electric energy assessment record in a unit cycle; The generated electric energy assessment record is input into the electric energy quality assessment model to obtain the risk value of the generated electric energy assessment record, and determine whether to issue a risk warning for the generated electric energy assessment record.

7. A power quality assessment system according to claim 6, characterized in that: The evaluation record analysis module includes a voltage data analysis unit and a correlation data calculation unit; The voltage data analysis unit is used to obtain the power evaluation records on the power quality data management platform and analyze the changes in the voltage values ​​stored in the power evaluation records in a unit cycle; the associated data calculation unit is used to obtain the normal fluctuation range of the voltage value in the power evaluation record and the abnormal proportion time of the abnormal voltage value.

8. A power quality assessment system according to claim 6, characterized in that: The impact factor analysis module includes an evaluation record comparison unit and an impact factor extraction unit; The evaluation record comparison unit is used to obtain the evaluation results stored in the electric energy evaluation records, and divide all the electric energy evaluation records on the power quality data management platform according to the evaluation results, and analyze and compare the normal fluctuation range and abnormal proportion time of the divided electric energy evaluation records; The influencing factor extraction unit is used to respectively extract the external environment information contained in the electric energy evaluation records that are divided into different categories, and generate the influencing factors of the electric energy quality evaluation by comparing the external environment information.

9. A power quality assessment system according to claim 6, characterized in that: The model building module includes a model generation unit and a model training unit; The model production unit is used to analyze the influence of various influencing factors on the power quality assessment in each power assessment record and construct a power quality assessment model; the model training unit is used to input each power assessment record on the power quality data management platform into the power quality assessment model for calculation, obtain the risk value of each power assessment record, and determine the risk threshold of the power assessment record.

10. A power quality assessment system according to claim 6, characterized in that: The risk judgment module includes a current data analysis unit and a risk calculation unit; The current data analysis unit is used to obtain the currently generated electric energy evaluation record and analyze the change of the voltage value stored in the generated electric energy evaluation record in a unit cycle; The risk calculation unit is used to input the generated power assessment record into the power quality assessment model, obtain the risk value of the generated power assessment record, and determine whether to issue a risk warning for the generated power assessment record.

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