CN111950913B - A comprehensive evaluation method for microgrid power quality based on node voltage sensitivity - Google Patents
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Abstract
The invention discloses a micro-grid power quality comprehensive evaluation method based on node voltage sensitivity, which specifically comprises the following steps: 1) Constructing an electric energy quality evaluation system based on real-time running information of the micro-grid; 2) Micro-grid single-node electric energy quality real-time scoring; 3) Node scoring entropy weight distribution based on node voltage sensitivity coefficients; 4) Comprehensively evaluating the electric energy quality of the micro-grid; the method fully considers the influence of the importance dynamic change of each electric energy quality index on the single-node electric energy quality evaluation weight in the real-time evaluation process and the influence of the mutual correlation among all electric nodes in the micro-grid on the comprehensive electric energy quality evaluation, not only can effectively evaluate the electric energy quality of the single node of the micro-grid system, but also can effectively evaluate the electric energy quality of the whole micro-grid system; the importance degree of each node in the micro-grid system can be judged, and a theoretical basis is provided for carrying out electric energy quality control on the nodes with poor disturbance rejection capability.
Description
Technical Field
The invention relates to the field of micro-grid power quality evaluation, in particular to a node voltage sensitivity-based micro-grid power quality comprehensive evaluation method, which provides a method for micro-grid power quality comprehensive evaluation.
Background
Micro-Grid (Micro-Grid) is also translated into a Micro-Grid, and refers to a small power generation and distribution system consisting of a distributed power supply, an energy storage device, an energy conversion device, a load, a monitoring and protecting device and the like. The proposal of the micro-grid aims to realize flexible and efficient application of the distributed power supply and solve the problem of grid connection of the distributed power supply with huge quantity and various forms. The development and extension of the micro-grid can fully promote the large-scale access of the distributed power supply and the renewable energy sources, realize the high-reliability supply of various energy forms of loads, and be an effective way for realizing an active power distribution network, so that the traditional power grid is transited to the intelligent power grid.
Compared with the traditional power distribution network, the micro-grid power distribution network has small inertia and weak disturbance rejection, and when the output of a distributed power supply in the micro-grid system fluctuates and loads impact, various electric energy quality indexes in the micro-grid can fluctuate greatly. Meanwhile, various novel electric equipment accessed by a user is a large part of electric sensitive equipment, and high requirements on electric energy quality are provided. The existing electric energy quality evaluation method mainly aims at the problems that the weight of electric energy quality index evaluation is fixed and the fluctuation of electric energy quality of a micro-grid cannot be well reflected in the traditional power distribution network. In addition, most of the existing power quality evaluation methods only consider the power quality evaluation value of a single node, and do not consider the correlation and influence among nodes in the whole system, so that the finally obtained power quality evaluation result cannot accurately reflect the power quality condition of the whole network, and therefore, how to comprehensively and accurately comprehensively evaluate the power quality of the micro-grid is a problem to be solved.
Disclosure of Invention
The invention aims to solve the defects that the existing micro-grid power quality evaluation method only considers the power quality evaluation value of a single node, and does not consider the correlation and influence among nodes in the whole system, so that the evaluation accuracy is low, the reliability is insufficient and the evaluation is not comprehensive.
The invention realizes the above purpose through the following technical scheme: a micro-grid power quality comprehensive evaluation method based on node voltage sensitivity specifically comprises the following steps:
1) Electric energy quality evaluation system based on real-time running information of micro-grid
Selecting an electric energy quality evaluation index according to the requirements of comprehensive electric energy quality evaluation of the micro-grid and the national electric energy quality standard, and constructing an electric energy quality evaluation system based on real-time operation information of the micro-grid;
2) Real-time scoring of micro-grid single-node power quality
Firstly, preprocessing electric energy quality data of the micro-grid for real-time operation of electric energy quality, assigning each electric energy quality index, and then assigning the initial weight of the electric energy quality index of the micro-grid by adopting a fuzzy analytic hierarchy process; then, a single-node power quality index real-time weight evaluation model is established to obtain the single-node power quality index real-time weight; finally, integrating the real-time scoring and real-time weight of each electric energy quality index to obtain a single-node electric energy quality real-time evaluation score;
3) Node scoring entropy weight distribution based on node voltage sensitivity coefficient
Firstly, calculating an active sensitivity coefficient of a voltage amplitude of each node, a reactive sensitivity coefficient of a voltage amplitude of each node, an active sensitivity coefficient of a phase angle value of each node and a reactive sensitivity coefficient of a phase angle value of each node based on a power flow equation of node power balance, and giving an entropy weight to the electric energy quality score of each node by utilizing an entropy weight method;
4) Comprehensive evaluation of micro-grid power quality
And integrating the power quality real-time evaluation score of each node in the micro-grid and the power quality scoring entropy weight of each node to obtain the power quality comprehensive evaluation score of the micro-grid system.
Further, in the step 1), the step of constructing the power quality evaluation system is as follows:
According to the requirements of comprehensive electric energy quality evaluation of the micro-grid and the national electric energy quality standard, and comprehensively considering the influence of a distributed power supply, a power grid and a distributed load on the electric energy quality of the micro-grid, selecting voltage deviation, three-phase unbalance degree of voltage/current, total harmonic distortion rate of voltage/current, voltage fluctuation, flicker and frequency deviation as electric energy quality evaluation indexes, and constructing an electric energy quality evaluation system based on real-time running information of the micro-grid.
Further, in the step 2), the step of scoring the electric energy quality index of the micro-grid in real time is as follows:
2.1 Dividing each electric energy quality evaluation index in the micro-grid electric energy quality evaluation system established in the step 1) into three different grades of early warning, abnormality and warning according to deviation exceeding the range specified by the electric energy quality national standard, wherein the different grades correspond to different scores, and adopting a multi-piecewise linear regression evaluation method to embody the mapping relation between the electric energy quality evaluation index and the running state of the micro-grid;
2.2 Determining the initial weight of the power quality index in the step 2.1), fully considering the actual condition of the running state of the micro-grid and considering the engineering practice experience of an expert, assigning the initial weight by adopting a fuzzy analytic hierarchy process, and firstly, constructing a fuzzy complementary judgment matrix according to the expert experience for the selected power quality evaluation index of the micro-grid; assuming that there is a power quality index set i= { I 1,I2,…,In }, the fuzzy complementary judgment matrix R representing the importance degree of the index I 1,I2,…,In in a pairwise comparison manner is shown in the following formula:
Wherein the elements in formula (1) satisfy the relationship: r ii＝0.5,i＝1,2,…,n;rij+rji =1, i, j=1, 2, …, n; i, j represents the i, j power quality index, the value of i, j is 1,2,3. Element r ij represents the important degree of membership of index I i to index I j;
Performing consistency test on the formula (1), and if the consistency is smaller than 0.2, judging that the fuzzy judgment matrix R has satisfactory consistency; if the consistency is equal to or greater than 0.2, a determination matrix P '= (P' ij)n×n) having satisfactory consistency is calculated according to equation (2):
P'＝(1-t)R+tP (2)
Wherein t is a consistency coefficient, an initial value is set to be 0.01, and iteration is carried out according to an iteration formula t=t+Δt, wherein Δt is a consistency coefficient step length, and Δt=0.05 is taken; until the judgment matrix has satisfactory consistency, while p= (P ij)n×n is the judgment matrix with complete consistency:
according to the judgment matrix P' with satisfactory consistency obtained in the formula (2), calculating the n-th root M (i) of the element convolution of each row, and then carrying out normalization processing to obtain the initial weight of each index The following formula is shown:
2.3 The purpose of changing the weight according to the value of the evaluation index is realized by a weight changing formula for the initial weight in 2.2), namely, when the electric energy quality score of the index is lower, the corresponding weight is higher; the variable weight formula of the micro-grid single-node power quality evaluation can be expressed as follows:
wherein omega i is the variable weight after the i index is variable weight; alpha is an equalization factor for adjusting the variable weight; An initial weight value of the ith index; Is the subtraction value of the ith power quality index containing the equalization factor; when certain indexes deviate from the national standard seriously, 0 < alpha < 1/2, otherwise 1 is more than or equal to alpha more than or equal to 1/2; wherein α=1 is Chang Quan heavy mode;
2.4 Further consider the duration of time that the index is at a lower level for the variable weight formula in 2.3); for the real-time index, taking the average value of index subtracting values at the current moment and the first 2 moments as the electric energy quality subtracting value in the variable weight calculation; the statistical index is not adjusted; the variable comprehensive expression considering that the power quality index is at a lower level duration is:
taking out the index i in the formula (6) when the index i is a real-time index When the index i is a statistical index, y ωi,yωi is taken as the subtraction value of the index i at the current moment,Subtracting the average value of the values for the index i of the current time and the index i of the previous 2 times;
The real-time index values in the step are voltage deviation, frequency deviation, voltage flicker and the like, and the statistical index values are voltage/current unbalance degree, harmonic voltage/current total distortion rate and the like.
2.5 Combining step 2.4) with step 2.1) to obtain a single-node real-time power quality evaluation score f Evaluation as shown in the following formula:
Further, the step of assigning the weight based on the node voltage sensitivity coefficient in the step 3) is as follows:
3.1 According to the step 2), the fluctuation of the power quality of each single node of the micro-grid is mainly related to the fluctuation of the active power, reactive power, phase and voltage amplitude of the voltage, and according to the characteristic, a weight distribution method based on the node voltage sensitivity coefficient is provided; the voltage stability sensitivity analysis of the nodes in the micro-grid system is established on a power flow equation based on node power balance, the power flow equation of the micro-grid system taking the resistance and reactance characteristics of a power line into consideration is as follows, wherein all power quality data are subjected to per unit:
In the formulas (8) and (9), m is the total number of nodes except PCC points in the micro-grid system; p i、Qi represents the active and reactive power at node i, respectively; u i、Uj represents the voltage amplitudes at nodes i, j, respectively; delta i、δj is the voltage phase angle at nodes i, j; y ij∠θij is the admittance of the line between nodes i and j;
The sensitivity of node voltage and phase angle to active and reactive deviation is obtained by the Newton-Lapherson method calculation formulas (8) and (9):
In the formula (10), S δp、Sδp is the active and reactive sensitivities of the node voltage phase angle; s up、Sup is the active and reactive sensitivity of the node voltage amplitude; the four elements form a voltage sensitivity matrix;
3.2 Utilizing the active and reactive sensitivity coefficients of the voltage amplitude/phase angle of each node obtained in the step 3.1), and weighting the electric energy quality scores of each node by adopting an entropy weight method; the micro-grid system has m single-node electric energy quality scores except PCC nodes, and can be used as index values for comprehensive electric energy quality evaluation; the number of the measured items is n, where n=4, specifically refers to the active and reactive sensitivity coefficients of the voltage amplitude/phase angle, and the formed original judgment matrix k= (K ij)n×m is as follows:
in the formula (11), k ij is the evaluation value of the ith measurement item under the jth comprehensive evaluation index;
3.3 Calculating the specific gravity of the index value of the ith item under the jth comprehensive evaluation index based on the evaluation value obtained in 3.2) Then, according to the definition of entropy, the entropy value e j of each index is obtained:
calculating entropy weight gamma j of the j-th evaluation index:
further, in the step 4), the description of the step 2) and the step 3) is combined, so as to obtain a comprehensive electric energy quality score of the micro-grid system as shown in the following formula:
in the formula (14), f Evaluation j is a real-time evaluation score of the j-th node.
The invention has the beneficial effects that:
(1) The method fully considers the influence of the importance dynamic change of each electric energy quality index on the single-node electric energy quality evaluation weight in the real-time evaluation process and the influence of the mutual correlation among all electric nodes in the micro-grid on the comprehensive electric energy quality evaluation, and realizes objective evaluation of the electric energy quality of all the nodes in the micro-grid.
(2) The method not only can effectively evaluate the electric energy quality of a single node of the micro-grid system, but also can effectively evaluate the electric energy quality of the whole micro-grid system, thereby realizing the whole evaluation of the electric energy quality of the whole micro-grid.
(3) The method can judge the importance degree of each node in the micro-grid system and provide theoretical basis for treating the electric energy quality of the node with poor disturbance rejection.
Drawings
Fig. 1 is a flowchart of a comprehensive evaluation method of the micro-grid power quality based on node voltage amplitude and phase sensitivity.
Detailed Description
The invention will be described in detail with reference to the accompanying drawings: the present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are provided, but the protection scope of the present invention is not limited to the following embodiments.
Referring to fig. 1, a comprehensive evaluation method for micro-grid power quality based on node voltage amplitude phase sensitivity coefficient includes the following steps:
1) Electric energy quality evaluation system based on real-time running information of micro-grid
Selecting an electric energy quality evaluation index according to the requirements of the comprehensive electric energy quality evaluation of the micro-grid and the corresponding national standard, and constructing an electric energy quality evaluation system based on real-time operation information of the micro-grid;
2) Real-time scoring of micro-grid single-node power quality
Firstly, preprocessing electric energy quality index data acquired by a micro-grid data acquisition system, and establishing an electric energy quality index multi-piecewise linear regression evaluation model by utilizing the electric energy quality index data; then combining the running state of the micro-grid and considering engineering practice experience, and assigning the initial weight of the electric energy quality index of the micro-grid by adopting a fuzzy analytic hierarchy process; then, a single-node power quality index real-time weight evaluation model is established to obtain the single-node power quality index real-time weight; finally, obtaining a single-node power quality real-time evaluation score;
3) Weight distribution based on node voltage amplitude phase sensitivity
Firstly, establishing a power flow equation based on node power balance to obtain active and reactive sensitivity coefficients of voltage amplitude values of all nodes, wherein the voltage phase angle is active and reactive sensitivity coefficients; then, weighting the electric energy quality scores of all the nodes by utilizing an entropy weighting method;
4) Comprehensive evaluation of micro-grid power quality
And comprehensively evaluating the electric energy quality of the micro-grid by using a node weight assignment method based on the voltage phase sensitivity coefficient of each node.
In the embodiment, a 220V low-voltage micro-grid is taken as an example, a distributed power supply is provided with a photovoltaic system, a wind power generation system, an energy storage system and the like, distributed loads are resistive loads, inductive loads and dragging loads, and comprehensive dynamic electric energy quality of the micro-grid is evaluated under different states of fluctuation of output power, fluctuation of load and the like of the distributed power supply.
The flow of the comprehensive evaluation method for the electric energy quality of the micro-grid based on the node voltage sensitivity coefficient is shown in a figure 1, and the comprehensive evaluation method comprises the following steps:
Step 1), construction of an electric energy quality evaluation system based on real-time running information of a micro-grid
The real-time operation data of the electric energy quality are collected at each electric node of the micro-grid, and the collection frequency is recorded for 1 time every 15 minutes, and specifically comprises voltage, current, frequency, phase, active power, reactive power, harmonic wave, flicker and the like. And respectively carrying out statistical calculation on the real-time operation data of the electric energy quality by taking the day, week, month and year as units to obtain state quantities such as voltage/current unbalance degree, harmonic voltage/current total distortion rate, frequency deviation, voltage qualification rate and the like.
And selecting voltage deviation, voltage/current three-phase unbalance degree, voltage/current total harmonic distortion rate, voltage fluctuation and flicker and frequency deviation as power quality evaluation indexes according to the requirements of the micro-grid comprehensive power quality evaluation and corresponding national standards, and constructing a power quality evaluation system based on real-time operation information of the micro-grid.
Step 2), real-time grading of micro-grid single-node electric energy quality
Firstly, carrying out data preprocessing on each index data in the micro-grid power quality evaluation system established in the step 1) so as to effectively filter data disturbance and reject abnormal points; establishing a multi-piecewise linear regression evaluation model of the power quality index according to the preprocessed data, and dividing each power quality evaluation index into three different grades of early warning, abnormality and warning according to deviation values when the power quality index exceeds the national power quality standard range, wherein the different grades correspond to different scores; the critical point reduction scores between the normal and early warning, the early warning and the abnormal, the abnormal and the warning grades are S 1,S2 and S 3 respectively, and a multi-piecewise linear regression evaluation model is adopted to reflect the mapping relation between the electric energy quality evaluation index and the running state of the micro-grid; the score of each power quality is shown as (15):
Wherein i represents an i-th power quality index, and the value of i is 1,2,3. y f is the full value of the single power quality index; y i is the subtracted value of the ith power quality indicator; x i is the deviation value of the i-th index; s 1、S2、S3 is the deduction value of the ith electric energy quality index at the critical points of normal and early warning, early warning and abnormal, abnormal and warning grade respectively; a i、bi、ci is the index deviation value of the ith power quality index at the critical points of normal and early warning, early warning and abnormal, abnormal and warning grade respectively; k i is the division slope multiple (k i is more than or equal to 1) of the ith index deviation under the warning level.
Secondly, constructing a fuzzy complementary judgment matrix for the selected micro-grid power quality evaluation index according to expert experience; assuming that there is a power quality index set i= { I 1,I2,…,In }, the fuzzy complementary judgment matrix R representing the importance degree of the index I 1,I2,…,In in a pairwise comparison manner is shown in the following formula:
The elements in matrix R satisfy the relationship: r ii＝0.5,i＝1,2,…,n、rij+rji = 1, I, j = 1,2, …, n, the element r ij representing the degree of membership of index I i to index I j, a larger r ij indicating that index I i is more important than index I j, and when r ij = 0.5 representing that the importance of both indices is the same;
Consistency test is carried out on the formula (16), and the calculation formula of consistency ρ is as follows:
If ρ is less than 0.2, judging that the fuzzy judgment matrix R has satisfactory consistency; if ρ is greater than or equal to 0.2, it is determined that the fuzzy judgment matrix needs to be adjusted, and a judgment matrix P '= (P' ij)n×n) with satisfactory consistency is calculated according to the following formula:
P'＝(1-t)R+tP (18)
In the formula, t is a consistency coefficient, an initial value is set to 0.01, and updating is performed according to an iterative formula t=t+Δt (Δt=0.05) until the judgment matrix has satisfactory consistency, and at the same time, p= (P ij)n×n is the judgment matrix with complete consistency:
Calculating n-th square root M (i) of the convolution of each line of elements of P', and then carrying out normalization processing on M to obtain the initial weight of each index The following formula is shown:
then, comprehensively considering real-time scoring and real-time weighting of the micro-grid operation power quality index to determine the micro-grid operation power quality condition, and a variable weight formula of micro-grid single-node power quality evaluation can be expressed as follows:
wherein omega i is the variable weight after the i index is variable weight; alpha is an equalization factor for adjusting the variable weight; An initial weight value of the ith index; is the subtraction value of the ith power quality index containing the equalization factor; taking alpha=0.2 to perform variable weight synthesis on each index;
Taking the average value of index subtracting values at the current time t 0 and the first 2 times t 2、t1 as the electric energy quality subtracting value in the variable weight calculation for the real-time index; the statistical index is not averaged; the variable complex expression considering the duration of time that the power quality index is at a lower level is:
Taking the index i in the formula (22) when the index i is a real-time index When the index i is a statistical index, y ωi,yωi is taken as the subtraction value of the index i at the current moment,The mean value of the values is subtracted for the current time and the first 2 time index i.
Finally, a single-node power quality real-time evaluation score f Evaluation can be obtained, which is shown in the following formula:
step 3, node scoring entropy weight distribution based on node voltage amplitude phase sensitivity
Firstly, after obtaining the electric energy quality scores of all single nodes in the micro-grid according to the step 2), in order to evaluate the whole electric energy quality of the micro-grid, the electric energy quality condition of each node in the micro-grid needs to be considered, and then the comprehensive electric energy quality of the micro-grid is calculated; the voltage stability sensitivity analysis of the nodes in the micro-grid system is established on a power flow equation based on node power balance; the flow equation of the micro-grid system considering the resistance and reactance characteristics of the power line is as follows, wherein all the power quality data are subjected to per unit:
In the formulas (24) and (25), m is the total number of nodes except PCC points in the micro-grid system; p i、Qi represents the active and reactive power at node i, respectively; u i、Uj represents the voltage amplitudes at nodes i, j, respectively; delta i、δj is the voltage phase angle at nodes i, j; y ij∠θij is the admittance of the line between nodes i and j;
The sensitivity of node voltage amplitude, phase angle to active and reactive deviations can be obtained by newton-raphson method equations (24) and (25):
In the formula (26), S δp、Sδp is the active and reactive sensitivities of the node voltage phase angle; s up、Sup is the active and reactive sensitivity of the node voltage amplitude; the four elements form a voltage sensitivity matrix;
Secondly, weighting the electric energy quality scores of all the nodes by adopting an entropy weight method, wherein the micro-grid system is provided with m single-node electric energy quality scores which are used as index values for comprehensive electric energy quality evaluation; the measured term n=4, specifically, refers to an original judgment matrix k= (K ij)n×m is as follows:
In the formula (27), k ij is the evaluation value of the ith measurement item under the jth index;
calculating the specific gravity of the index value of the jth evaluation base i item The entropy value e j of each index is obtained:
calculating entropy weight gamma j of the j-th evaluation index:
The obtained comprehensive electric energy quality scores of the micro-grid system are as follows:
in the formula (30), gamma j is the weight of the node j; f Evaluation j is the real-time evaluation score of the j-th node.
The above embodiments are only preferred embodiments of the present invention, and are not limiting to the technical solutions of the present invention, and any technical solution that can be implemented on the basis of the above embodiments without inventive effort should be considered as falling within the scope of protection of the patent claims of the present invention.
Claims (2)
1. A micro-grid power quality comprehensive evaluation method based on node voltage sensitivity is characterized by comprising the following steps of: the method specifically comprises the following steps:
1) Electric energy quality evaluation system based on real-time running information of micro-grid
According to the requirements of comprehensive power quality evaluation of a micro-grid and the national power quality standard, and comprehensively considering the influence of a distributed power supply, a power grid and a distributed load on the power quality of the micro-grid, selecting voltage deviation, three-phase unbalance of voltage/current, total harmonic distortion of voltage/current, voltage fluctuation, flicker and frequency deviation as power quality evaluation indexes, and constructing a power quality evaluation system based on real-time running information of the micro-grid;
2) Real-time scoring of micro-grid single-node power quality
Firstly, preprocessing electric energy quality data of the micro-grid for real-time operation of electric energy quality, assigning each electric energy quality index, and then assigning the initial weight of the electric energy quality index of the micro-grid by adopting a fuzzy analytic hierarchy process; then, a single-node power quality index real-time weight evaluation model is established to obtain the single-node power quality index real-time weight; finally, integrating the real-time scoring and real-time weight of each electric energy quality index to obtain a single-node electric energy quality real-time evaluation score;
2.1 Dividing each electric energy quality evaluation index in the micro-grid electric energy quality evaluation system established in the step 1) into three different grades of early warning, abnormality and warning according to deviation exceeding the range specified by the electric energy quality national standard, wherein the different grades correspond to different scores, and adopting a multi-piecewise linear regression evaluation method to embody the mapping relation between the electric energy quality evaluation index and the running state of the micro-grid;
2.2 Determining the initial weight of the power quality index in the step 2.1), fully considering the actual condition of the running state of the micro-grid and considering the engineering practice experience of an expert, assigning the initial weight by adopting a fuzzy analytic hierarchy process, and firstly, constructing a fuzzy complementary judgment matrix according to the expert experience for the selected power quality evaluation index of the micro-grid; assuming that there is a power quality index set i= { I 1,I2,…,In }, the fuzzy complementary judgment matrix R representing the importance degree of the index I 1,I2,…,In in a pairwise comparison manner is shown in the following formula:
Wherein the elements in formula (1) satisfy the relationship: r ii＝0.5,i＝1,2,…,n;rij+rji =1, i, j=1, 2, …, n; i, j represents the i, j power quality index, the value of i, j is 1,2,3. Element r ij represents the important degree of membership of index I i to index I j;
Performing consistency test on the formula (1), and if the consistency is smaller than 0.2, judging that the fuzzy judgment matrix R has satisfactory consistency; if the consistency is equal to or greater than 0.2, a determination matrix P' = (P i′j)n×n:
P'＝(1-t)R+tP (2)
In the formula, t is a consistency coefficient, an initial value is set to 0.01, and iteration is performed according to an iteration formula t=t+Δt until the judgment matrix has satisfactory consistency, and at the same time, p= (P ij)n×n is the judgment matrix with complete consistency:
according to the judgment matrix P' with satisfactory consistency obtained in the formula (2), calculating the n-th root M (i) of the element convolution of each row, and then carrying out normalization processing to obtain the initial weight of each index The following formula is shown:
2.3 The purpose of changing the weight according to the value of the evaluation index is realized by a weight changing formula for the initial weight in 2.2), namely, when the electric energy quality score of the index is lower, the corresponding weight is higher; the variable weight formula of the micro-grid single-node power quality evaluation can be expressed as follows:
wherein omega i is the variable weight after the i index is variable weight; alpha is an equalization factor for adjusting the variable weight; An initial weight value of the ith index; is the subtraction value of the ith power quality index containing the equalization factor; when certain indexes deviate from the national standard seriously, 0 < alpha < 1/2, otherwise 1 is more than or equal to alpha more than or equal to 1/2;
2.4 Further consider the duration of time that the index is at a lower level for the variable weight formula in 2.3); for the real-time index, taking the average value of index subtracting values at the current moment and the first 2 moments as the electric energy quality subtracting value in the variable weight calculation; the statistical index is not adjusted; the variable comprehensive expression considering that the power quality index is at a lower level duration is:
taking out the index i in the formula (6) when the index i is a real-time index When the index i is a statistical index, y ωi,yωi is taken as the subtraction value of the index i at the current moment,Subtracting the average value of the values for the index i of the current time and the index i of the previous 2 times;
2.5 Combining step 2.4) with step 2.1) to obtain a single-node real-time power quality evaluation score f Evaluation as shown in the following formula:
3) Node scoring entropy weight distribution based on node voltage sensitivity coefficient
Firstly, calculating an active sensitivity coefficient of a voltage amplitude of each node, a reactive sensitivity coefficient of a voltage amplitude of each node, an active sensitivity coefficient of a phase angle value of each node and a reactive sensitivity coefficient of a phase angle value of each node based on a power flow equation of node power balance, and giving an entropy weight to the electric energy quality score of each node by utilizing an entropy weight method;
4) Comprehensive evaluation of micro-grid power quality
And integrating the power quality real-time evaluation score of each node in the micro-grid and the power quality scoring entropy weight of each node to obtain the power quality comprehensive evaluation score of the micro-grid system.
2. The comprehensive evaluation method for the electric energy quality of the micro-grid based on the node voltage sensitivity is characterized by comprising the following steps of: the step of weight distribution based on the node voltage sensitivity coefficient in the step 3) comprises the following steps:
3.1 According to the step 2), the fluctuation of the power quality of each single node of the micro-grid is mainly related to the fluctuation of the active power, reactive power, phase and voltage amplitude of the voltage, and according to the characteristic, a weight distribution method based on the node voltage sensitivity coefficient is provided; the voltage stability sensitivity analysis of the nodes in the micro-grid system is established on a power flow equation based on node power balance, the power flow equation of the micro-grid system taking the resistance and reactance characteristics of a power line into consideration is as follows, wherein all power quality data are subjected to per unit:
In the formulas (8) and (9), m is the total number of nodes except PCC points in the micro-grid system; p i、Qi represents the active and reactive power at node i, respectively; u i、Uj represents the voltage amplitudes at nodes i, j, respectively; delta i、δj is the voltage phase angle at nodes i, j; y ij∠θij is the admittance of the line between nodes i and j;
The sensitivity of node voltage and phase angle to active and reactive deviation is obtained by the Newton-Lapherson method calculation formulas (8) and (9):
In the formula (10), S δp、Sδp is the active and reactive sensitivities of the node voltage phase angle; s up、Sup is the active and reactive sensitivity of the node voltage amplitude; the four elements form a voltage sensitivity matrix;
3.2 Utilizing the active and reactive sensitivity coefficients of the voltage amplitude/phase angle of each node obtained in the step 3.1), and weighting the electric energy quality scores of each node by adopting an entropy weight method; the micro-grid system has m single-node electric energy quality scores except PCC nodes, and can be used as index values for comprehensive electric energy quality evaluation; the number of the measured items is n, where n=4, specifically refers to the active and reactive sensitivity coefficients of the voltage amplitude/phase angle, and the formed original judgment matrix k= (K ij)n×m is as follows:
in the formula (11), k ij is the evaluation value of the ith measurement item under the jth comprehensive evaluation index;
3.3 Calculating the specific gravity of the index value of the ith item under the jth comprehensive evaluation index based on the evaluation value obtained in 3.2) Then, according to the definition of entropy, the entropy value e j of each index is obtained:
calculating entropy weight gamma j of the j-th evaluation index:
further, in the step 4), the description of the step 2) and the step 3) is combined, so as to obtain a comprehensive electric energy quality score of the micro-grid system as shown in the following formula:
In the formula (14), f Evaluation j is a real-time evaluation score of the j-th node.
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