A comprehensive evaluation method and storage medium for power quality based on multidimensional space volume

Abstract

The present invention discloses a method for comprehensive evaluation of power quality based on multidimensional space volume, comprising: step S10, collecting power monitoring data at a predetermined collection frequency; step S11, calculating the numerical deviation ratio of each evaluation index according to the power monitoring data; step S12, obtaining the level value corresponding to each evaluation index deviation ratio according to a preset mapping table of each evaluation index deviation and level, and obtaining the vertex coordinates of the corresponding multidimensional space cube; step S13, obtaining the comprehensive power quality value of the power monitoring data corresponding to the sampling moment of this sampling period; step S14, storing the comprehensive power quality value and vertex coordinates of the power monitoring data in a massive database. The present invention also discloses a storage medium. The implementation of the present invention can improve the certainty and understandability of comprehensive evaluation of power quality.

Description

Technical Field

[0001] The present invention relates to the technical field of quality monitoring and evaluation, and in particular to a comprehensive power quality evaluation method and storage medium based on multi-dimensional space volume. Background Art

[0002] In order to achieve the goal of carbon neutrality, a large number of wind farms and photovoltaic power plant projects need to be built, and more and more distributed wind power and photovoltaic projects will appear in the distribution network. Because wind power and photovoltaic projects have intermittent power generation, they have a great impact on the power quality of the regional power grid, and it is necessary to strengthen the monitoring and evaluation of the power quality of the regional power grid. In response to the problem of power quality, various countries have successively issued a series of national standards for power quality. my country's State Administration of Technical Supervision has also promulgated national standards involving five aspects of power quality, namely: the allowable deviation of supply voltage, the allowable fluctuation and flicker of supply voltage, the allowable imbalance of three-phase power supply voltage, the harmonics of the public power grid, and the allowable deviation of power supply frequency.

[0003] Since the evaluation of power quality involves many indicators, it is difficult to give a comprehensive evaluation index of power quality to guide the implementation of bidding for power grid access, pricing according to quality, and high quality and high price. Therefore, it is of great significance to conduct a comprehensive evaluation of power quality in the power market environment. This requires weighted merging of multiple power quality evaluation indicators into a one-dimensional comprehensive evaluation indicator. This merging can be done in various ways. There have been many research results on power quality evaluation methods at home and abroad, mainly including two major categories of evaluation methods: subjective and objective and intelligent: such as evidence theory method, rank sum ratio method, vector algebra method, probability distance method, fuzzy comprehensive evaluation method, probability statistics and fuzzy number combination method, hierarchical analysis method, matter element analysis method, genetic projection pursuit method, artificial neural network method, etc.

[0004] However, due to the objective irrelevance of each single indicator of power quality, it is difficult to determine the relative weight. The existing various comprehensive power quality evaluation methods have considered the mutual influence of various indicators when fusing data, and added uncertain factors such as subjective fuzzy judgment. Most of them are integrated by assigning different permissions to each indicator. Therefore, the evaluation results are subjective and arbitrary, and the evaluation results are not intuitive and difficult to understand. Summary of the invention

[0005] The technical problem to be solved by the present invention is to propose a comprehensive power quality evaluation method and storage medium based on multidimensional space volume, which can combine the comprehensive power quality evaluation results with the multidimensional space, and better improve the certainty and comprehensibility of the comprehensive power quality evaluation.

[0006] In order to solve the above technical problems, as one aspect of the present invention, a method for comprehensive evaluation of power quality based on multidimensional space volume is provided, which comprises the following steps:

[0007] Step S10, collecting power monitoring data at a predetermined collection frequency;

[0008] Step S11, according to the electric energy monitoring data collected each time, calculating the numerical deviation ratio of each corresponding evaluation index; the evaluation index includes multiple of the following indicators: voltage deviation, voltage flicker, frequency deviation, three-phase unbalance and total harmonic distortion rate index;

[0009] Step S12, according to a preset mapping table of deviations of each evaluation indicator and the corresponding level, obtain the level value corresponding to the deviation ratio of each evaluation indicator, establish a multidimensional space cube according to the number of the evaluation indicators and the level value, and obtain the vertex coordinates of the multidimensional space cube;

[0010] Step S13, calculating according to the coordinates of the vertices of the multidimensional space cube to obtain the comprehensive value of the power quality of the power monitoring data corresponding to the sampling time of this sampling period;

[0011] Step S14, storing the comprehensive power quality value and vertex coordinates of the power monitoring data into a massive database.

[0012] Preferably, it further comprises:

[0013] A mapping table corresponding to the deviations of each evaluation indicator and the level is generated in advance, in which each evaluation indicator is divided into a predetermined number of levels, each level corresponds to a numerical deviation ratio range of the evaluation indicator, each level corresponds to a level value, and the level values ​​corresponding to levels of different evaluation indicators are the same.

[0014] Preferably, the vertex coordinates P obtained in step S12 are expressed as: (P1, P2, P3, ..., P n ), where P n It is the grade value corresponding to each selected evaluation indicator.

[0015] Preferably, in step S13, the following formula is used for calculation to obtain the comprehensive power quality value P of the power monitoring data corresponding to the sampling time t of this sampling period: t :

[0016] P t =(P1*P2*P3*...*P n ) / (K*n);

[0017] Among them, K is the total number of levels of each evaluation indicator, and n is the total number of selected evaluation indicators.

[0018] Preferably, it further comprises:

[0019] Access the massive database to find the comprehensive power quality value P of all sampling moments within a period of time t , the comprehensive power quality index P during the period is calculated by the following formula:

[0020]

[0021] Among them, t1 and t2 are the first and last moments of this time period; T is the collection frequency of power monitoring data.

[0022] Preferably, it further comprises:

[0023] Accessing a massive database, selecting vertex coordinates of a multidimensional space cube at a sampling time, mapping them to a multidimensional space cube, and displaying the multidimensional space cube;

[0024] Select the comprehensive value P of power quality at each sampling time within a period t , and form a distribution curve for display; or

[0025] The comprehensive power quality index P in multiple time periods is selected and a distribution curve is formed for display.

[0026] Correspondingly, another aspect of the present invention further provides a computer-readable storage medium having a series of computer-executable instructions stored thereon, which, when the series of computer-executable instructions are executed by one or more computing devices, enables the one or more computing devices to implement the method as described above.

[0027] The implementation of the embodiments of the present invention has the following beneficial effects:

[0028] The present invention provides a comprehensive power quality evaluation method and storage medium based on multi-dimensional space volume. In an embodiment of the present invention, each evaluation index is taken as a vector, and these index vectors construct an N-dimensional space, which can reflect the irrelevance between the evaluation indexes. At the same time, the evaluation value of the index is mapped to the value of the coordinates of the N-dimensional space, and a set of measurement values ​​of each index is mapped to a surface in the N-dimensional space; the spatial volume formed by the surface, the origin and each coordinate surface is used for evaluation.

[0029] In the embodiment of the present invention, the comprehensive value of power quality is monitored and calculated synchronously and recorded in a massive database. Relevant personnel can form a distribution curve of the comprehensive evaluation value of power quality by searching the massive database, and can also view the multidimensional space cube corresponding to each sampling point, thereby improving the comprehensibility of power quality changes.

[0030] In summary, the present invention grants the same authority to multiple different evaluation indicators for integration, which can overcome the subjective arbitrariness of weighting indicators in the evaluation system; at the same time, it can provide a comprehensive power quality evaluation curve instead of a single comprehensive power quality value, which can not only obtain a specific comprehensive power quality value from the curve distribution, but also enable users to increase the comprehensibility of power quality changes by observing the graphical changes of the distribution of the comprehensive power quality values. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying creative labor, other drawings obtained based on these drawings still belong to the scope of the present invention.

[0032] Figure 1 It is a main flow diagram of an embodiment of a comprehensive power quality evaluation method based on multi-dimensional space volume provided by the present invention;

[0033] Figure 2 It is a schematic diagram of the multi-dimensional space volume involved in the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0035] like Figure 1 FIG. 1 is a schematic diagram showing a main flow chart of an embodiment of a method for comprehensive power quality evaluation based on multidimensional space volume provided by the present invention; and FIG. Figure 2 As shown, in this embodiment, the method includes the following steps:

[0036] Step S10, collecting the power monitoring data at a predetermined collection frequency; in a specific example, considering that the collection frequency of the power monitoring data is very high, generally two minutes is used as the sampling period, so the power quality monitoring data accumulates over time and continues to grow, and a massive storage mechanism is needed to store the power monitoring data.

[0037] Step S11, according to the electric energy monitoring data collected each time, calculate the numerical deviation ratio ((% of the normal value of this indicator)) of each corresponding evaluation index; the evaluation index includes multiple of the following indicators: voltage deviation, voltage flicker, frequency deviation, three-phase unbalance and total harmonic distortion rate index;

[0038] Step S12, according to a preset mapping table of deviations of each evaluation indicator and the corresponding level, obtain the level value corresponding to the deviation ratio of each evaluation indicator, establish a multidimensional space cube according to the number of the evaluation indicators and the level value, and obtain the vertex coordinates of the multidimensional space cube;

[0039] It can be understood that in the present invention, it is necessary to pre-generate a mapping table corresponding to the deviations of each evaluation indicator and the level. In the mapping table, each evaluation indicator is divided into a predetermined number of levels, each level corresponds to a numerical deviation ratio range of the evaluation indicator, each level corresponds to a level value, and the level values ​​of the levels corresponding to different evaluation indicators are the same.

[0040] More specifically, in one example, the power quality indicators can be subdivided according to the evaluation value ranges formulated by the country; generally, voltage deviation ≤10% is qualified; voltage flicker ≤10% is qualified; frequency deviation ≤10% is qualified; three-phase unbalance ≤10% is qualified; total harmonic distortion ≤10% is qualified. In the present invention, the comprehensive evaluation weights of the power quality indicators are equally normalized, as shown in the following table, which shows the grading table of the grades of each evaluation indicator (the proportion of the range value is calculated in %):

[0041] Table 1 Evaluation index deviation and level mapping table

[0042]

[0043]

[0044] From the above table, we can see the level corresponding to the deviation of each power quality indicator. There are 8 levels in total, 4 levels for qualified (corresponding to the best, excellent, good and qualified), and 4 levels for unqualified (corresponding to unqualified, poor, very poor and worst). The deviation range of each indicator is converted into a unified value in proportion, and corresponds to the point on (0,8] on the coordinate axis of each indicator.

[0045] Taking into account the irrelevance of each indicator, each indicator is taken as a vector, and this group of vectors is linearly independent. Taking the above table as an example, these 5 power quality indicators constitute a 5-dimensional space, and the coordinates of each dimension are the above-mentioned level values ​​of this coordinate. Obviously, if there are N indicators, an N-dimensional space can be constructed. When N=3, the constructed 3-dimensional space is as follows Figure 2 As shown in the figure, the corresponding vertex value P of the large cube in the coordinate system (voltage deviation, frequency deviation, voltage flicker) is (8,8,8); the small blue cube represents the primary power quality measurement value, and its vertex P t is (4,3,2).

[0046] Therefore, in this step, the vertex coordinates P obtained are expressed as: (P1, P2, P3, ..., P n ), where P n It is the grade value corresponding to each selected evaluation indicator.

[0047] Step S13, calculating according to the coordinates of the vertices of the multidimensional space cube to obtain the comprehensive value of the power quality of the power monitoring data corresponding to the sampling time of this sampling period;

[0048] In a specific example, in step S13, the following formula is used to calculate and obtain the comprehensive power quality value P of the power monitoring data corresponding to the sampling time t of this sampling period: t :

[0049] P t =(P1*P2*P3*...*P n ) / (K*n);

[0050] Wherein, K is the total number of levels of each evaluation indicator (8 in the example shown above), and n is the total number of selected evaluation indicators (less than or equal to 5).

[0051] Step S14, storing the comprehensive power quality value and vertex coordinates of the power monitoring data into a massive database.

[0052] It is understandable that, in the embodiments of the present invention, a massive database may be further accessed to obtain more data or display corresponding data.

[0053] In a specific example, the further comprises:

[0054] Access the massive database to find the comprehensive power quality value P of all sampling moments within a period of time t , the comprehensive power quality index P during the period is calculated by the following formula:

[0055]

[0056] Among them, t1 and t2 are the first and last moments of this time period; T is the collection frequency of power monitoring data.

[0057] In a specific example, the method further comprises:

[0058] Accessing a massive database, selecting vertex coordinates of a multidimensional space cube at a sampling time, mapping them to a multidimensional space cube, and displaying the multidimensional space cube;

[0059] Select the comprehensive value P of power quality at each sampling time within a period t , and form a distribution curve for display; or

[0060] The comprehensive power quality index P in multiple time periods is selected and a distribution curve is formed for display.

[0061] It can be understood that the method adopted by the present invention overcomes the subjective arbitrariness of weighting indicators in the evaluation system, and gives the indicators the same authority for integration; at the same time, it can provide a comprehensive power quality evaluation curve (or a multi-dimensional three-dimensional spatial display of each sampling point) instead of a single comprehensive power quality value, which can not only obtain a specific comprehensive power quality value from the curve distribution, but also enable users to increase the comprehensibility of power quality changes by observing the graphical changes in the distribution of the comprehensive power quality values.

[0062] Accordingly, another aspect of the present invention further provides a computer-readable storage medium having a series of computer-executable instructions stored thereon, and when the series of computer-executable instructions are executed by one or more computing devices, the one or more computing devices implement the above-mentioned Figure 1 and Figure 2 For more details, please refer to and combine the above Figure 1 and Figure 2 The description of is not repeated here.

[0063] The implementation of the embodiments of the present invention has the following beneficial effects:

[0064] The present invention provides a comprehensive power quality evaluation method and storage medium based on multi-dimensional space volume. In an embodiment of the present invention, each evaluation index is taken as a vector, and these index vectors construct an N-dimensional space, which can reflect the irrelevance between the evaluation indexes. At the same time, the evaluation value of the index is mapped to the value of the coordinates of the N-dimensional space, and a set of measurement values ​​of each index is mapped to a surface in the N-dimensional space; the spatial volume formed by the surface, the origin and each coordinate surface is used for evaluation.

[0065] In the embodiment of the present invention, the comprehensive value of power quality is monitored and calculated synchronously and recorded in a massive database. Relevant personnel can form a distribution curve of the comprehensive evaluation value of power quality by searching the massive database, and can also view the multidimensional space cube corresponding to each sampling point, thereby improving the comprehensibility of power quality changes.

[0066] In summary, the present invention grants the same authority to multiple different evaluation indicators for integration, which can overcome the subjective arbitrariness of weighting indicators in the evaluation system; at the same time, it can provide a comprehensive power quality evaluation curve instead of a single comprehensive power quality value, which can not only obtain a specific comprehensive power quality value from the curve distribution, but also enable users to increase the comprehensibility of power quality changes by observing the graphical changes of the distribution of the comprehensive power quality values.

[0067] The above disclosure is only a preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A comprehensive power quality evaluation method based on multidimensional space volume, characterized in that: The steps include: Step S10, collecting power monitoring data at a predetermined collection frequency; Step S11, according to the electric energy monitoring data collected each time, calculating the numerical deviation ratio of each corresponding evaluation index; the evaluation index includes multiple of the following indicators: voltage deviation, voltage flicker, frequency deviation, three-phase unbalance and total harmonic distortion rate index; Step S12, according to a preset mapping table of deviations of each evaluation indicator and the corresponding level, obtain the level value corresponding to the deviation ratio of each evaluation indicator, establish a multidimensional space cube according to the number of the evaluation indicators and the level value, and obtain the vertex coordinates of the multidimensional space cube; Step S13, calculating according to the vertex coordinates of the multidimensional space cube to obtain the comprehensive value of power quality of the power monitoring data corresponding to the sampling time of this sampling period; Step S14, storing the comprehensive power quality value and vertex coordinates of the power monitoring data into a massive database; Among them, further include: Pre-generate a mapping table corresponding to the deviation of each evaluation indicator and the level, in which each evaluation indicator is divided into a predetermined number of levels, each level corresponds to a numerical deviation ratio range of the evaluation indicator, each level corresponds to a level value, and the level values ​​of levels corresponding to different evaluation indicators are the same; The vertex coordinates P obtained in step S12 are expressed as: (P1, P2, P3, ..., P n ), where P n is the grade value corresponding to each selected evaluation indicator; In step S13, the following formula is used to calculate and obtain the comprehensive power quality value P of the power monitoring data corresponding to the sampling time t of this sampling period: t : P t =(P1*P2*P3*...*P n ) / (K*n); Among them, K is the total number of levels of each evaluation indicator, and n is the total number of selected evaluation indicators.

2. The method according to claim 1, characterized in that Further including: Access the massive database to find the comprehensive power quality value P of all sampling moments within a period of time t , the comprehensive power quality index P during the period is calculated by the following formula: Among them, t1 and t2 are the first and last moments of this time period; T is the collection frequency of power monitoring data.

3. The method according to claim 1 or 2, characterized in that Further including: Accessing a massive database, selecting vertex coordinates of a multidimensional space cube at a sampling time, mapping the vertex coordinates to a multidimensional space cube, and displaying the multidimensional space cube; Select the comprehensive value P of power quality at each sampling time within a period t , and form a distribution curve for display; or The comprehensive power quality index P in multiple time periods is selected and a distribution curve is formed for display.

4. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a series of computer-executable instructions. When the series of computer-executable instructions are executed by one or more computing devices, the one or more computing devices implement the method according to any one of claims 1 to 3.

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