CN111080041A - A method and system for comprehensive evaluation of distribution network interactivity - Google Patents

A method and system for comprehensive evaluation of distribution network interactivity Download PDF

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CN111080041A
CN111080041A CN201811214417.2A CN201811214417A CN111080041A CN 111080041 A CN111080041 A CN 111080041A CN 201811214417 A CN201811214417 A CN 201811214417A CN 111080041 A CN111080041 A CN 111080041A
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李德智
田野
何永秀
董明宇
陈蓉珺
光峰涛
王美艳
陈奋开
刘剑宁
程法民
张小奇
石坤
陈宋宋
韩凝晖
宫飞翔
龚桃荣
田世明
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China Electric Power Research Institute Co Ltd CEPRI
Hon Hai Precision Industry Co Ltd
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Hon Hai Precision Industry Co Ltd
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Abstract

本发明提供了一种配电网互动性综合评价方法,包括以下步骤:基于预先构建的配电网互动特性指标体系中的互动特性指标,获取所述互动特性指标对应的电网数据;基于所述电网数据,确定所述互动特性指标对应的综合权重;将所述综合权重带入到预先构建的配电网特性综合评价模型中,评价配电网的互动性;其中所述互动特性指标对应的综合权重由:采用熵值法确定客观权重和采用ANP法确定主观权重计算得到本发明考虑了大规模广义负荷接入配电网的态势,从互动效果和互动基础两方面建立了广义负荷耦合互动综合评价指标体系,解决了广义负荷耦合互动特性指标定量化的问题,为城市配电网未来建设提供了发展方向。

Figure 201811214417

The invention provides a comprehensive evaluation method for the interaction of a distribution network, comprising the following steps: obtaining grid data corresponding to the interactive characteristic index based on the interactive characteristic index in a pre-built distribution network interactive characteristic index system; Power grid data, determine the comprehensive weight corresponding to the interactive characteristic index; bring the comprehensive weight into the pre-built distribution network characteristic comprehensive evaluation model to evaluate the interactivity of the distribution network; wherein the interactive characteristic index corresponds to The comprehensive weight is calculated by: using the entropy method to determine the objective weight and using the ANP method to determine the subjective weight. The present invention considers the situation of large-scale generalized loads accessing the distribution network, and establishes the generalized load coupling interaction from the aspects of interaction effect and interaction basis. The comprehensive evaluation index system solves the problem of quantification of the generalized load coupling interactive characteristic index, and provides a development direction for the future construction of the urban distribution network.

Figure 201811214417

Description

Comprehensive evaluation method and system for interactivity of power distribution network
Technical Field
The invention relates to the field of comprehensive evaluation of a power distribution network, in particular to a comprehensive evaluation method for interactivity of the power distribution network.
Background
In recent years, with the development of communication technology and network technology, the research and construction of smart grids has risen globally. The relatively mature test point projects comprise an intelligent substation, a power distribution automation system, a power utilization information acquisition system and the like.
As an important component of a power grid, the intellectualization of a power distribution network becomes a new trend of future power grid development, and plays a significant role in realizing the overall goal of smart power grid construction.
The construction of the smart grid is rapidly developed, and a future power system becomes cleaner, more efficient, safer and more reliable under the support of the smart grid. The generalized load actively participates in the operation of the power grid, and the demand side management means is combined, so that the consumption of renewable energy sources is promoted, the environment is improved, the peak clipping and valley filling are realized, and the development of the smart power grid is promoted. The generalized load refers to a load composed of elements such as a static load, a dynamic load, a low-voltage transmission network, a medium-and-small-capacity generator and the like in an electric power receiving end system, wherein the generator can be regarded as a negative load. Typical generalized loads include distributed power supplies, electric vehicles, energy storage devices and the like, but the problem of quantification of generalized load coupling interaction characteristic indexes still exists.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a comprehensive evaluation method for interactivity of a power distribution network.
The technical scheme provided by the invention is as follows:
a comprehensive evaluation method for interaction of a power distribution network comprises the following steps:
acquiring power grid data corresponding to interaction characteristic indexes based on the interaction characteristic indexes in a pre-constructed power distribution network interaction characteristic index system;
determining comprehensive weight corresponding to the interaction characteristic index based on the power grid data;
the comprehensive weight is brought into a pre-constructed comprehensive evaluation model of the characteristics of the power distribution network, and the interactivity of the power distribution network is evaluated;
wherein the comprehensive weight corresponding to the interaction characteristic index is as follows: and determining objective weight by adopting an entropy method and determining subjective weight by adopting an ANP method.
Preferably, the construction of the power distribution network interaction characteristic index system includes:
constructing a first-level index according to the influence factors of the generalized load coupling interaction characteristics;
constructing a secondary index for each primary index based on the influence factors of the primary indexes;
constructing a third-level index for each second-level index based on the influence factors of the second-level indexes;
the first-level index belongs to the control layer;
the second level index and the third level index belong to a network layer.
Preferably, the determining the comprehensive weight corresponding to the interaction characteristic index based on the power grid data includes:
1) determining objective weight of the index by using an entropy method;
2) determining subjective weight of the index by adopting a network analytic hierarchy process;
3) and determining the comprehensive weight by adopting an additive integration method according to the objective weight and the subjective weight of the index.
Preferably, the objective weight of the index is calculated as follows:
Figure BDA0001832666190000021
in the formula, pjObjective weight as jth index; e.g. of the typejEntropy value of j index;
wherein, the entropy of the j index is calculated according to the following formula:
Figure BDA0001832666190000022
in the formula, pijThe specific gravity of the ith index value under the jth index;
the proportion of the index value of the ith item under the jth index is calculated according to the following formula:
Figure BDA0001832666190000023
in the formula, rijIs the value of the ith index under the jth index.
Preferably, the determining the subjective weight of the index by using the network analytic hierarchy process includes:
comparing and analyzing every two of the three-level indexes corresponding to each two-level index according to the influence to form a judgment matrix;
obtaining normalized sorting weight by a characteristic root method by adopting a ninth division method scale proposed by Satty based on the judgment matrix;
constructing an ANP super matrix from the three-level indexes based on the normalized ranking weight;
comparing every two second indexes corresponding to the first-level indexes to construct a judgment matrix, and calculating an importance sorting vector of the judgment matrix to obtain a weighting matrix;
obtaining a weighted super matrix from the ANP super matrix and the weighted matrix;
and calculating subjective weight of the index based on the weighted hypermatrix.
Preferably, the subjective weight is calculated as follows:
Figure BDA0001832666190000031
in the formula, k is the step number of the dominance degree; n is the maximum number of steps;
Figure BDA0001832666190000032
is a weighted super matrix.
Preferably, the comprehensive weight corresponding to the interaction characteristic index is calculated according to the following formula:
Figure BDA0001832666190000033
in the formula, wjIs the composite weight; k is a radical of1Is a constant number 1; k is a radical of2Is a constant number 2; p is a radical ofjIs an objective weight; q. q.sjIs a subjective weight.
Preferably, the bringing the comprehensive weight into a pre-constructed comprehensive evaluation model of the characteristics of the power distribution network to evaluate the interactivity of the power distribution network includes:
setting the maximum weight of the three-level indexes as a positive ideal value and the minimum weight as a negative ideal value, constructing a positive ideal system by using the positive ideal values of all the three-level indexes, and constructing a negative ideal system by using the negative ideal values of all the three-level indexes;
calculating Euclidean distances of a positive ideal system and a negative ideal system of each three-level index according to a weighted distance formula;
calculating a queuing indicating value of the three-level index by using a queuing indicating value formula;
the larger the queuing indicated value is, the stronger the interaction characteristic of the power distribution network is.
Preferably, the euclidean distance of the just-ideal system is calculated as follows:
Figure BDA0001832666190000034
in the formula (I), the compound is shown in the specification,
Figure BDA0001832666190000035
is the Euclidean distance of the positive ideal system; m is the number of the evaluation objects; w is ajIs the composite weight of the jth element; x is the number ofijIs an index value before dimensionless;
Figure BDA0001832666190000036
is the positive ideal value of the jth element;
the Euclidean distance of the negative ideal system is calculated according to the following formula:
Figure BDA0001832666190000041
in the formula (I), the compound is shown in the specification,
Figure BDA0001832666190000042
is the Euclidean distance of the negative ideal system; m is the number of the evaluation objects; w is ajIs the composite weight of the jth elementWeighing; is xijA non-dimensionalized index value;
Figure BDA0001832666190000043
is the positive ideal value of the jth element.
Preferably, the primary indicator includes: generalized load interaction effect and generalized load interaction foundation;
the secondary indexes of the generalized load interaction effect comprise: generalized load participation, daily load curve fluctuation of a power grid and electric power cleanliness;
the secondary indexes of the generalized load interaction basic index comprise: the system comprises a power grid interaction foundation, an electric vehicle interaction foundation, a distributed interaction foundation and an energy storage interaction foundation;
the secondary indicators of the generalized load participation degree comprise: daily generalized load supply rate, generalized load response degree;
the daily load curve fluctuation degree of the power grid comprises the following steps: the number of periodic peak-valley alternation times, daily peak-valley ratio, daily load rate and feeder line load curve variance;
the electric power cleanliness comprises: renewable energy consumption rate and unit generated energy CO2Discharge capacity;
the power grid interaction foundation comprises: coverage rate of the intelligent electric meter, the number of types of interactive service channels and the scale of an interactive business hall;
the electric automobile interaction basis include: the urban charging and battery replacing capacity area density, the utilization rate of a charging and battery replacing facility and the matching degree of the electric automobile and the charging and battery replacing facility;
the distributed interaction foundation comprises: the installed capacity ratio of the distributed power supply and the grid connection reliability of the distributed power supply are determined;
the energy storage interaction foundation comprises: the ratio of the maturity of the energy storage system to the installed capacity of the energy storage system is determined.
A comprehensive evaluation system for power distribution network interactivity comprises:
constructing a module: the method comprises the steps of obtaining power grid data corresponding to interaction characteristic indexes based on the interaction characteristic indexes in a pre-constructed power distribution network interaction characteristic index system;
a determination module: determining comprehensive weight corresponding to the interaction characteristic index based on the power grid data;
an evaluation module: and bringing the comprehensive weight into a pre-constructed comprehensive evaluation model of the characteristics of the power distribution network to evaluate the interactivity of the power distribution network.
Preferably, the building block comprises:
a first building submodule: the method is used for constructing a first-level index according to the influence factors of the generalized load coupling interaction characteristics;
a second building submodule: the method is used for constructing a secondary index for each primary index based on the influence factors of the primary indexes;
a third building submodule: the method is used for constructing a third-level index for each second-level index based on the influence factors of the second-level indexes;
preferably, the evaluation module comprises:
a fourth building submodule: the system comprises a three-level index, a positive ideal value, a negative ideal value, a positive ideal system and a negative ideal system, wherein the maximum weight of the three-level index is set as the positive ideal value, the minimum weight of the three-level index is set as the negative ideal value, the positive ideal values of all the three-level indexes construct the positive ideal system, and the negative ideal values of all the three-level indexes construct the negative ideal system;
a first calculation submodule: the Euclidean distance calculation method is used for calculating the Euclidean distance of a positive ideal system and a negative ideal system of each three-level index according to a weighted distance formula;
a second calculation submodule: the method is used for calculating the queuing indicating value of the three-level index by using a queuing indicating value formula.
An evaluation submodule: and comprehensively evaluating the power grid interactivity by the stronger power distribution network interactive characteristic when the queuing indicated value is larger.
Preferably, the determining module includes:
a first determination sub-module: the objective weight of the index is determined by adopting an entropy method;
a second determination sub-module: the subjective weight used for determining the index by adopting a network analytic hierarchy process;
a third determination sub-module: and the method is used for determining the weight of the comprehensive evaluation model by adopting an additive integration method according to the objective weight of the index and the subjective weight of the index.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a comprehensive evaluation method for interactivity of a power distribution network, which comprises the following steps: acquiring power grid data corresponding to interaction characteristic indexes based on the interaction characteristic indexes in a pre-constructed power distribution network interaction characteristic index system; determining comprehensive weight corresponding to the interaction characteristic index based on the power grid data; the comprehensive weight is brought into a pre-constructed comprehensive evaluation model of the characteristics of the power distribution network, and the interactivity of the power distribution network is evaluated; wherein the comprehensive weight corresponding to the interaction characteristic index is as follows: and determining objective weight by adopting an entropy method and determining subjective weight by adopting an ANP method. According to the comprehensive evaluation method, the situation that large-scale generalized loads are connected into the power distribution network is considered, a generalized load coupling interaction comprehensive evaluation index system is established from two aspects of interaction effect and interaction foundation, the problem of quantification of generalized load coupling interaction characteristic indexes is solved, a comprehensive evaluation model is improved, an entropy method-ANP weighting method based on an addition integration method is selected to comprehensively consider subjective and objective factors, comprehensive evaluation results are more scientific and reasonable, evaluation basis is provided for the development level of the urban power distribution network, and development direction is provided for future construction of the urban power distribution network.
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FIG. 1 is a flow chart of a comprehensive evaluation method for interactivity of a power distribution network according to the present invention;
FIG. 2 is a flowchart of an embodiment of a comprehensive evaluation method for power distribution network interactivity of the present invention;
FIG. 3 is a generalized load coupling interaction characteristic index system diagram of the present invention;
FIG. 4 is a generalized load interaction index system model based on network partition according to the present invention;
FIG. 5 is an ANP network in the Super Decision software according to the present invention.
Detailed Description
For a better understanding of the present invention, reference is made to the following description taken in conjunction with the accompanying drawings and examples.
Detailed description of the preferred embodiment 1
The invention discloses a comprehensive evaluation method for interactivity of a power distribution network, which is shown in figure 1:
1. constructing a power distribution network interactive characteristic index system based on the selected power distribution network interactive characteristic indexes:
2. determining the weight of a comprehensive evaluation model based on the power grid data corresponding to the power distribution network interaction characteristic indexes:
3. according to the weight of the comprehensive evaluation model, comprehensive evaluation is carried out based on a TOPSIS model improved in advance, and the evaluation result of the interactivity of the power distribution network is obtained:
1. constructing a power distribution network interactive characteristic index system based on the selected power distribution network interactive characteristic indexes:
taking six areas of China A, B, C, D, E, F as an example, the method carries out reasonable evaluation on urban generalized load coupling interaction characteristics according to the thought of the research, firstly, a generalized load coupling interaction comprehensive evaluation index system of each area is established, then, for the six areas needing to be evaluated, the 18 three-level index data of each area in 2015 are collected, wherein data of a typical day in 2015 are extracted to obtain 6 three-level index data of daily generalized load supply rate, generalized load response degree, periodic peak-valley times, daily peak-valley ratio, daily load rate and feeder load curve variance of each area. For each type of index data of the selected region, the above-mentioned method of uniformization and non-dimensionalization is used to make all data within 01, as shown in table 1 below.
TABLE 1 nondimensional data of each index in each region
Figure BDA0001832666190000071
2. Determining the weight of a comprehensive evaluation model based on the power grid data corresponding to the power distribution network interaction characteristic indexes:
determining the index weights of all levels according to the entropy method step in the step 3, operating Super Decision software, establishing an index network in the software according to the mutual influence relation among indexes, wherein the influence relation is shown in the attached figure 4, specifically, the index network is shown in the attached figure 5, and obtaining the index weights under the ANP method by adopting the nine-division method scale proposed by Satty.
Applying the formula (16) to the formula (17) to obtain k1=0.47,k2The index integrated weight was obtained as 0.53, as shown in the table below.
TABLE 2 index weights
Figure BDA0001832666190000072
Figure BDA0001832666190000081
And further, by using the comprehensive evaluation method in the step 4, the queue indicating value interactive ordering of the generalized load coupling interactive characteristics in different areas is obtained as shown in the following table.
TABLE 3 Interactive queuing indication values between generalized load and distribution network in the area
Figure BDA0001832666190000082
In the aspect of the weight of an index system, in the weight calculation result optimized by the 'addition' integration method, the proportion of an interaction effect and an interaction basis in a first-level index is equivalent, wherein the weight of the interaction effect is slightly higher than that of the interaction basis, and the reason is that the interaction effect proportion in the calculation result of the ANP method is higher, which indicates that the influence of experts on the power grid load after the generalized load participates in the interaction is more important. In the aspect of secondary weight, the generalized load participation degree, the electric vehicle interaction basis and the energy storage interaction basis are higher, which shows that the energy storage technology is the development direction of a future smart grid, and in the aspect of comprehensive weight of an index system, indexes such as daily generalized load supply rate, generalized load response degree and interactive business hall area density are higher, and the method is more critical in the evaluation of generalized load coupling interaction characteristics.
3. According to the weight of the comprehensive evaluation model, comprehensive evaluation is carried out based on a TOPSIS model improved in advance, and the evaluation result of the interactivity of the power distribution network is obtained:
in the aspect of comprehensive evaluation results, the evaluation sequence is A → D → B → C → F → E, and the area A mainly benefits from the advantages of high generalized load occupation ratio, relatively quick power grid intelligent process and the like. The improved TOPSIS method avoids the defects that the alternative scheme in the classic TOPSIS method has equal distance and can not be relatively good and bad when the connecting lines of the positive ideal street and the negative ideal street are symmetrical, and has higher universality.
Specific example 2
The comprehensive evaluation method for the interactivity of the power distribution network provided by the invention is shown in figure 2:
step 1: and selecting the interactive characteristic indexes of the power distribution network, classifying and grading the interactive characteristic indexes, and constructing a power distribution network interactive characteristic index system.
Step 2: and constructing an improved TOPSIS model for comprehensive evaluation of the interaction characteristics of the urban distribution network.
And step 3: and determining the weight of the comprehensive evaluation model. Collecting relevant data of the power grid based on the interaction characteristic indexes of the power distribution network selected in the step 1, calculating index weights by respectively adopting an entropy method and a network analytic hierarchy process, and obtaining the weights by the entropy method and the weights obtained by the network analytic hierarchy process according to the proportion obtained by an 'addition method' integration method so as to obtain the overall weight of the comprehensive evaluation model.
And 4, step 4: and (3) according to the weight obtained in the step (3), carrying out comprehensive evaluation by using the improved TOPSIS method in the step (2), evaluating the interactivity of the urban distribution network according to an evaluation result, and proposing a development direction.
Step 1:
in step 1, the method for constructing the power distribution network interaction characteristic index system comprises the following steps:
forming a first-level index of a comprehensive evaluation system of the interaction characteristics of the power distribution network by using two indexes of a generalized load interaction effect and an interaction basis;
the generalized load interaction effect indexes are divided into three secondary indexes of generalized load participation, power grid daily load curve fluctuation and electric power cleanliness; the generalized load interaction basic indexes are divided into four secondary indexes of a power grid interaction basis, an electric vehicle interaction basis, a distributed interaction basis and an energy storage interaction basis.
The generalized load participation degree is reflected by two three-level indexes of daily generalized load supply rate and generalized load response degree; the daily load curve fluctuation degree of the power grid is reflected by four-item three-level indexes of periodic peak-valley alternation times, daily peak-valley ratio, daily load rate and feeder line load curve variance; the electric power cleanliness is realized through the consumption rate of renewable energy sources and the unit generated energy CO2Two three-level indexes of the discharge amount are reflected; the power grid interaction foundation is reflected by three indexes of coverage rate of the intelligent electric meter, the type and quantity of interaction service channels and the scale of an interaction business hall; the electric automobile interaction foundation is reflected by three indexes of city battery charging and replacing capacity area density, battery charging and replacing facility utilization rate and matching degree of an electric automobile and a battery charging and replacing facility; the distributed interaction basis is reflected by two indexes of installed capacity ratio of the distributed power supply and grid connection reliability of the distributed power supply; the energy storage interaction basis is reflected by two indexes of maturity of an energy storage system and the proportion of installed energy storage capacity.
The index system is shown in figure 3.
Step 2:
in step 2, the method for constructing the TOPSIS model for the comprehensive evaluation of the interaction characteristics of the urban distribution network comprises the following steps:
and (3) setting the positive and negative ideal values of the indexes selected in the step (1), wherein the value is usually set as the extreme condition of each index. Is provided with
Figure BDA0001832666190000101
In order to be just as ideal for the system,
Figure BDA0001832666190000102
for a negative ideal system, the Euclidean distance of each scheme from the positive ideal system and the negative ideal system can be calculated according to a weighted distance formula.
Distance formula from positive ideal point:
Figure BDA0001832666190000103
distance formula from negative ideal point:
Figure BDA0001832666190000104
wherein:
Figure BDA0001832666190000105
Figure BDA0001832666190000106
and after the Euclidean distance is calculated, a queuing indicating value formula is used for calculating a queuing indicating value, and the larger the queuing indicating value formula is, the better the generalized load interactive coupling characteristic is. Queuing indication value formula:
Figure BDA0001832666190000107
and step 3:
in step 3, the generalized load interaction characteristic comprehensive evaluation weight determining method comprises the following steps:
(1) and collecting and sorting data. Selecting a region to be evaluated, and collecting the 18 three-level index data of the region, wherein 6 three-level indexes including daily generalized load supply rate, generalized load response degree, periodic peak-valley alternation times, daily peak-valley ratio, daily load rate and feeder load curve variance are obtained by selecting a typical day. Aiming at various index data of the selected region, a consistency and non-dimensionalization method is adopted to enable all data to be in the range of 01, so that the weight is determined by adopting an entropy method in the next step.
1) Method for making uniform
In the constructed index system, indexes such as the periodic peak-valley alternation times, the daily peak-valley ratio, the feeder load curve variance, the unit generated energy CO2 emission, the distributed power supply grid connection reliability and the like are extremely small indexes, and the other indexes are extremely large indexes, and the extremely small indexes are converted into the extremely large indexes based on a formula (6).
x′=M-x (6)
In the formula, x' is a post-alignment index, and M is an allowable upper bound of the index x.
2) Dimensionless method
Figure BDA0001832666190000111
Wherein j is the index number, i is the sample number, xijIs a non-dimensionalized index value, xijIs an index value after non-dimensionalization.
(2) Determining objective weights using entropy method
1) Calculating the specific gravity p of the index value of the ith item under the jth indexij
Figure BDA0001832666190000112
2) Calculating the entropy E of the jth indexj
Figure BDA0001832666190000113
3) Calculating the weight w of the jth indexj
Figure BDA0001832666190000114
(3) Subjective weight determination using ANP
1) And (5) analyzing the problem. And forming elements and element sets, judging whether the elements are independent or not, and judging whether a dependent feedback relation exists or not.
2) And constructing an ANP structure. The ANP comprises a control layer and a network layer, wherein the control layer at least comprises a target and can comprise a decision criterion; the network layer is composed of all elements governed by the control layer, and internally is an interoperable network structure. Let the control layer element of ANP be B1,B2,…,Bm(ii) a Network layer element is C1,C2,…,Cm. Wherein, CiIn is ei1,ei2,…,ein(i ═ 1, 2, …, n). To controlLayer element Bs(s-1, 2, …, m) with C as criterionjMiddle element ejl(l ═ 1, 2, …, n) is a secondary criterion.
3) And calculating the normalized sorting weight.
And determining the influence and influenced relation of all elements in the system based on the established structure. Element set CiIn accordance with its pair ejlThe influence is compared and analyzed pairwise, namely a judgment matrix B is constructeds. In order to quantify each pairwise judgment matrix, nine-division method scale proposed by Satty is adopted, and then a characteristic root method is used for obtaining a sequencing vector
Figure BDA0001832666190000121
4) An ANP hypermatrix is constructed.
Constructing a matrix from all the network element ordering vectors, and recording as
Figure BDA0001832666190000122
5) And comparing every two criteria in the control layer to construct a judgment matrix, and calculating an importance sorting vector by using a calculator so as to obtain a weighting matrix A.
Figure BDA0001832666190000123
Further, a weighted super matrix can be obtained:
Figure BDA0001832666190000124
6) the limit supermatria were calculated as follows.
Figure BDA0001832666190000125
If the limits converge and are unique, then
Figure BDA0001832666190000126
Column j of (A) is a certain standardThe extreme relative ordering of the elements of the network layer below the layer to element j, i.e. the weight value of each element relative to the highest target.
(4) Determination of synthetic weights using additive integration
The entropy method is an objective weighting method based on a 'difference drive' principle, the ANP method is a subjective weighting method based on a 'function drive' principle, and an index x generated by the two methods is setjAre each pj,qjThe "additive" integration method can organically combine the two weighting methods.
When the maximum difference between the objects to be evaluated is to be reflected, k is determined1,k2The value of the following formula is maximized.
Figure BDA0001832666190000131
In the formula, m and n are the number of evaluation targets and the number of evaluation indexes, respectively.
In satisfying
Figure BDA0001832666190000132
And k is1>0,k2If the value is more than 0, applying Lagrange conditional extremum principle to obtain:
Figure BDA0001832666190000133
Figure BDA0001832666190000134
Figure BDA0001832666190000135
in the formula, wjIs the integrated weight.
And 4, step 4:
in step 4, the comprehensive evaluation method comprises the following steps:
(1) the comprehensive evaluation was performed by using the TOPSIS method described in step 2, based on the weights obtained in step 3.
1) And (3) processing the data collected in the step (3) to determine a positive ideal point and a negative ideal point of each index, wherein a vector consisting of the maximum elements of each column is the positive ideal point, and a vector consisting of the minimum elements of each column is the negative ideal point.
2) Substituting the weights of the indexes obtained by the formula (17) into the formulas (1) to (2), and calculating the distance y between different index values and the positive and negative ideal points in different regions by using the collected datai +And yi -
3) The distance y between different index values and positive and negative ideal points in different areasi +And yi -And substituting the formula (5) to calculate a queuing indicating value, and sequencing the queuing indicating value, wherein the larger the indicating value is, the stronger the generalized load coupling interaction characteristic of the region is.
(2) And evaluating the interactivity of the urban distribution network based on the evaluation result, analyzing the reasons of the strong and weak interactive characteristics of different regions, and providing the future intelligent power grid construction and development directions of all regions.
Specific example 3
A comprehensive evaluation system for power distribution network interactivity comprises:
constructing a module: the method comprises the steps of obtaining power grid data corresponding to interaction characteristic indexes based on the interaction characteristic indexes in a pre-constructed power distribution network interaction characteristic index system;
a determination module: determining comprehensive weight corresponding to the interaction characteristic index based on the power grid data;
an evaluation module: and bringing the comprehensive weight into a pre-constructed comprehensive evaluation model of the characteristics of the power distribution network to evaluate the interactivity of the power distribution network.
The building module comprises:
a first building submodule: the method is used for constructing a first-level index according to the influence factors of the generalized load coupling interaction characteristics;
a second building submodule: the method is used for constructing a secondary index for each primary index based on the influence factors of the primary indexes;
a third building submodule: the method is used for constructing a third-level index for each second-level index based on the influence factors of the second-level indexes;
the evaluation module comprises:
a fourth building submodule: the system comprises a three-level index, a positive ideal value, a negative ideal value, a positive ideal system and a negative ideal system, wherein the maximum weight of the three-level index is set as the positive ideal value, the minimum weight of the three-level index is set as the negative ideal value, the positive ideal values of all the three-level indexes construct the positive ideal system, and the negative ideal values of all the three-level indexes construct the negative ideal system;
a first calculation submodule: the Euclidean distance calculation method is used for calculating the Euclidean distance of a positive ideal system and a negative ideal system of each three-level index according to a weighted distance formula;
a second calculation submodule: the method is used for calculating the queuing indicating value of the three-level index by using a queuing indicating value formula.
An evaluation submodule: and comprehensively evaluating the power grid interactivity by the stronger power distribution network interactive characteristic when the queuing indicated value is larger.
The determining module comprises:
a first determination sub-module: the objective weight of the index is determined by adopting an entropy method;
a second determination sub-module: the subjective weight used for determining the index by adopting a network analytic hierarchy process;
a third determination sub-module: and the method is used for determining the weight of the comprehensive evaluation model by adopting an additive integration method according to the objective weight of the index and the subjective weight of the index.
Preferably, the first calculation submodule includes: a first calculation unit and a second calculation unit;
the first calculation unit calculates the Euclidean distance of the ideal system according to the following formula:
Figure BDA0001832666190000141
in the formula (I), the compound is shown in the specification,
Figure BDA0001832666190000142
is the Euclidean distance of the positive ideal system; m is the number of the evaluation objects; w is ajIs the composite weight of the jth element; x is the number ofijIs an index value before dimensionless;
Figure BDA0001832666190000151
is the positive ideal value of the jth element;
the second calculation unit calculates the Euclidean distance of the negative ideal system by:
Figure BDA0001832666190000152
in the formula (I), the compound is shown in the specification,
Figure BDA0001832666190000153
is the Euclidean distance of the negative ideal system; m is the number of the evaluation objects; w is ajIs the composite weight of the jth element; is xijA non-dimensionalized index value;
Figure BDA0001832666190000154
is the positive ideal value of the jth element.
Preferably, the determining module includes:
a first determination sub-module: the objective weight of the index is determined by adopting an entropy method;
a second determination sub-module: the subjective weight used for determining the index by adopting a network analytic hierarchy process;
a third determination sub-module: and the method is used for determining the weight of the comprehensive evaluation model by adopting an additive integration method according to the objective weight of the index and the subjective weight of the index.
Preferably, the first determination submodule includes: a third calculation unit, a fourth calculation unit, and a fifth calculation unit;
the third calculation unit: the objective weight is calculated by:
Figure BDA0001832666190000155
in the formula, pjObjective weight as jth index; e.g. of the typejEntropy value of j index;
the fourth calculation unit: calculating an entropy value of the indicator by:
Figure BDA0001832666190000156
in the formula, pijThe specific gravity of the index value of the ith item under the jth index;
the fifth calculation unit: the specific gravity of the index value is calculated by the following formula:
Figure BDA0001832666190000157
in the formula, rijThe index value of the ith item under the jth index attribute.
Preferably, the second determination submodule includes:
a first determination unit: the device is used for carrying out pairwise comparison analysis on the influence of each element concentration element on another element concentration element based on a network layer to form a judgment matrix, and obtaining a normalized sorting weight by a characteristic root method by adopting a nine-division method scale proposed by Satty;
a construction unit: means for constructing an ANP super matrix from the network layer elements based on the normalized ordering weights;
a second determination unit: comparing every two control layers based on the criterion in the control layer to construct a judgment matrix, and calculating an importance ordering vector of the judgment matrix to obtain a weighting matrix;
a third determination unit: the weighted super matrix is obtained by the ANP super matrix and the weighted matrix;
a sixth calculation unit: and the subjective weight used for calculating the index based on the weighted super matrix.
Preferably, the sixth calculation unit includes: a calculation subunit;
the calculation subunit: subjective weights were calculated by:
Figure BDA0001832666190000161
in the formula, k is the step number of the dominance degree; n is the maximum number of steps;
Figure BDA0001832666190000162
is a weighted super matrix.
Preferably, the third determining sub-module includes: seventh calculation Unit
The seventh calculation unit: by calculating the composite weight:
Figure BDA0001832666190000163
in the formula, wjIs the composite weight; k is a radical of1Is a constant number 1; k is a radical of2Is a constant number 2; p is a radical ofjIs an objective weight; q. q.sjIs a subjective weight.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (14)

1.一种配电网互动性综合评价方法,其特征在于,包括以下步骤:1. a comprehensive evaluation method for the interaction of distribution network, is characterized in that, comprises the following steps: 基于预先构建的配电网互动特性指标体系中的互动特性指标,获取所述互动特性指标对应的电网数据;Obtain grid data corresponding to the interactive characteristic index based on the interactive characteristic index in the pre-built distribution network interactive characteristic index system; 基于所述电网数据,确定所述互动特性指标对应的综合权重;determining the comprehensive weight corresponding to the interactive characteristic index based on the power grid data; 将所述综合权重带入到预先构建的配电网特性综合评价模型中,评价配电网的互动性;Bringing the comprehensive weight into a pre-built comprehensive evaluation model of distribution network characteristics to evaluate the interaction of the distribution network; 其中所述互动特性指标对应的综合权重由:采用熵值法确定客观权重和采用ANP法确定主观权重计算得到。The comprehensive weight corresponding to the interactive characteristic index is calculated by: using the entropy method to determine the objective weight and using the ANP method to determine the subjective weight. 2.如权利要求1所述的一种配电网互动性综合评价方法,其特征在于,所述配电网互动特性指标体系的构建,包括:2. The method for comprehensive evaluation of the interactivity of a distribution network according to claim 1, wherein the construction of the interactive characteristic index system of the distribution network comprises: 根据广义负荷耦合互动特性的影响因素构建一级指标;Construct the first-level index according to the influencing factors of the generalized load coupling interaction characteristics; 基于一级指标的影响因素为每个一级指标构建二级指标;Construct secondary indicators for each primary indicator based on the influencing factors of primary indicators; 基于二级指标的影响因素为每个二级指标构建三级指标;Construct tertiary indicators for each secondary indicator based on the influencing factors of secondary indicators; 所述一级指标属于控制层;The first-level indicators belong to the control layer; 所述二级指标和三级指标属于网络层。The secondary and tertiary indicators belong to the network layer. 3.如权利要求1所述的一种配电网互动性综合评价方法,其特征在于,所述基于所述电网数据,确定所述互动特性指标对应的综合权重,包括:3 . The method for comprehensive evaluation of the interactivity of a distribution network according to claim 1 , wherein the determining, based on the power grid data, the comprehensive weight corresponding to the interactive characteristic index, comprising: 3 . 1)采用熵值法确定指标的客观权重;1) Using the entropy method to determine the objective weight of the index; 2)采用网络层次分析法确定指标的主观权重;2) The subjective weight of the index is determined by the network analysis hierarchy process; 3)将所述指标的客观权重和主观权重采用加法集成法确定综合权重。3) The objective weight and subjective weight of the indicators are determined by the additive integration method to determine the comprehensive weight. 4.如权利要求3所述的一种配电网互动性综合评价方法,其特征在于,所述指标的客观权重按下式计算:4. A kind of comprehensive evaluation method of distribution network interactivity as claimed in claim 3, is characterized in that, the objective weight of described index is calculated as follows:
Figure FDA0001832666180000011
Figure FDA0001832666180000011
式中,pj为第j个指标的客观权重;ej为第j个指标的熵值;In the formula, p j is the objective weight of the j-th index; e j is the entropy value of the j-th index; 其中,所述第j个指标的熵值,按下式计算:Wherein, the entropy value of the jth index is calculated as follows:
Figure FDA0001832666180000012
Figure FDA0001832666180000012
式中,pij为第j个指标下第i个指标值的比重;In the formula, p ij is the proportion of the i-th index value under the j-th index; 所述第j个指标下第i个项目的指标值的比重,按下式计算:The proportion of the index value of the i-th item under the j-th index is calculated as follows:
Figure FDA0001832666180000021
Figure FDA0001832666180000021
式中,rij为第j个指标下第i个指标的值。In the formula, r ij is the value of the ith index under the jth index.
5.如权利要求3所述的一种配电网互动性综合评价方法,其特征在于,所述采用网络层次分析法确定指标的主观权重,包括:5. The method for comprehensive evaluation of the interactivity of a distribution network according to claim 3, wherein the method of determining the subjective weight of the index by using the network analysis hierarchy process comprises: 基于各个二级指标对应的三级指标两两按影响力大小进行比较分析构成判断矩阵;Based on the comparison and analysis of the third-level indicators corresponding to each second-level index according to their influence, a judgment matrix is formed; 基于所述判断矩阵采用萨蒂提出的九分法标度,由特征根法得到归一化排序权重;Based on the judgment matrix, the scale of nine points proposed by Satie is adopted, and the normalized sorting weight is obtained by the characteristic root method; 基于所述归一化排序权重将所述三级指标构造ANP超矩阵;Constructing an ANP supermatrix based on the normalized ranking weights from the three-level indicators; 基于一级指标对应的二级指标进行两两比较,构造判断矩阵,计算所述判断矩阵重要性排序向量,得到加权矩阵;Based on the pairwise comparison of the secondary indicators corresponding to the primary indicators, a judgment matrix is constructed, and the importance ranking vector of the judgment matrix is calculated to obtain a weighted matrix; 由所述ANP超矩阵和所述加权矩阵得到加权超矩阵;A weighted supermatrix is obtained from the ANP supermatrix and the weighted matrix; 基于所述加权超矩阵计算指标的主观权重。The subjective weights of the indicators are calculated based on the weighted supermatrix. 6.如权利要求5所述的一种配电网互动性综合评价方法,其特征在于,所主观权重,按下式计算:6. A kind of comprehensive evaluation method of distribution network interactivity as claimed in claim 5, is characterized in that, all subjective weights are calculated as follows:
Figure FDA0001832666180000022
Figure FDA0001832666180000022
式中,k为优势度的步数;n为最大步数;
Figure FDA0001832666180000023
为加权超矩阵。
In the formula, k is the number of steps of dominance; n is the maximum number of steps;
Figure FDA0001832666180000023
is a weighted supermatrix.
7.如权利要求1所述的一种配电网互动性综合评价方法,其特征在于,所述互动特性指标对应的综合权重,按下式计算:7. The method for comprehensive evaluation of the interactivity of a distribution network according to claim 1, wherein the comprehensive weight corresponding to the interactive characteristic index is calculated as follows:
Figure FDA0001832666180000024
Figure FDA0001832666180000024
式中,wj为综合权重;k1为常数1;k2为常数2;pj为客观权重;qj为主观权重。In the formula, w j is the comprehensive weight; k 1 is the constant 1; k 2 is the constant 2; p j is the objective weight; q j is the subjective weight.
8.如权利要求2所述的一种配电网互动性综合评价方法,其特征在于,所述将所述综合权重带入到预先构建的配电网特性综合评价模型中,评价配电网的互动性,包括:8 . The method for comprehensive evaluation of distribution network interactivity according to claim 2 , wherein the comprehensive weight is brought into a pre-built distribution network characteristic comprehensive evaluation model to evaluate the distribution network. 9 . interactivity, including: 设定所述三级指标的最大权重作为正理想值,最小权重作为负理想值,并将所有三级指标的正理想值构建正理想系统,所有三级指标的负理想值构建负理想系统;Set the maximum weight of the three-level indicators as a positive ideal value, and the minimum weight as a negative ideal value, and construct a positive ideal system with the positive ideal values of all the three-level indicators, and construct a negative ideal system with the negative ideal values of all the three-level indicators; 依据加权距离公式计算各个三级指标的正理想系统和负理想系统的欧式距离;Calculate the Euclidean distance of the positive ideal system and the negative ideal system of each three-level index according to the weighted distance formula; 利用排队指示值公式计算三级指标的排队指示值;Use the queuing indication value formula to calculate the queuing indication value of the three-level index; 所述排队指示值越大,配电网互动特性越强。The larger the queuing indication value, the stronger the interactive characteristic of the distribution network. 9.如权利要求8所述的一种配电网互动性综合评价方法,其特征在于,所述正理想系统的欧式距离按下式计算:9. A kind of comprehensive evaluation method of distribution network interactivity as claimed in claim 8, is characterized in that, the Euclidean distance of described positive ideal system is calculated as follows:
Figure FDA0001832666180000031
Figure FDA0001832666180000031
式中,
Figure FDA0001832666180000032
为正理想系统的欧式距离;m为评测对象个数;Wj为第j个元素的综合权重;xij为无量纲化前指标值;
Figure FDA0001832666180000033
为第j个元素的正理想值;
In the formula,
Figure FDA0001832666180000032
is the Euclidean distance of the positive ideal system; m is the number of evaluation objects; W j is the comprehensive weight of the j-th element; x ij is the index value before dimensionless;
Figure FDA0001832666180000033
is the positive ideal value of the jth element;
所述负理想系统的欧式距离按下式计算:The Euclidean distance of the negative ideal system is calculated as follows:
Figure FDA0001832666180000034
Figure FDA0001832666180000034
式中,
Figure FDA0001832666180000035
为负理想系统的欧式距离;m为评测对象个数;Wj为第j个元素的综合权重;为xij无量纲化前指标值;
Figure FDA0001832666180000036
为第j个元素的正理想值。
In the formula,
Figure FDA0001832666180000035
is the Euclidean distance of the negative ideal system; m is the number of evaluation objects; W j is the comprehensive weight of the jth element; it is the index value of x ij before dimensionless;
Figure FDA0001832666180000036
is the positive ideal value of the jth element.
10.如权利要求2所述的一种配电网互动性综合评价方法,其特征在于,所述一级指标包括:广义负荷互动效果和广义负荷互动基础;10 . The method for comprehensive evaluation of distribution network interactivity according to claim 2 , wherein the first-level indicators include: generalized load interaction effect and generalized load interaction basis; 10 . 所述广义负荷互动效果的二级指标包括:广义负荷参与度、电网日负荷曲线波动度、电力清洁度;The secondary indicators of the generalized load interaction effect include: generalized load participation degree, power grid daily load curve fluctuation degree, and power cleanliness; 所述广义负荷互动基础指标的二级指标包括:电网互动基础、电动汽车互动基础、分布式互动基础、储能互动基础;The secondary indexes of the generalized load interaction basic index include: grid interaction basis, electric vehicle interaction basis, distributed interaction basis, and energy storage interaction basis; 所述广义负荷参与度的二级指标包括:日广义负荷供给率、广义负荷响应程度;The secondary indicators of the generalized load participation degree include: daily generalized load supply rate and generalized load response degree; 所述的电网日负荷曲线波动度包括:峰谷周期性交替次数、日峰谷比、日负荷率、馈线负荷曲线方差;The fluctuation degree of the power grid daily load curve includes: peak-valley periodic alternation times, daily peak-to-valley ratio, daily load rate, and feeder load curve variance; 所述的电力清洁度包括:可再生能源消纳率、单位发电量CO2排放量;The power cleanliness includes: renewable energy consumption rate, CO2 emissions per unit of power generation; 所述的电网互动基础包括:智能电表覆盖率、互动服务渠道种类数量、互动化营业厅规模;The power grid interaction basis includes: coverage rate of smart meters, the number of types of interactive service channels, and the scale of interactive business halls; 所述的电动汽车互动基础包括:城市充换电能力面积密度、充换电设施利用率、电动汽车与充换电设施匹配度;The electric vehicle interaction basis includes: area density of urban charging and swapping capacity, utilization rate of charging and swapping facilities, and matching degree between electric vehicles and charging and swapping facilities; 所述的分布式互动基础包括:分布式电源装机容量占比、分布式电源并网可靠性;The distributed interactive basis includes: the proportion of the installed capacity of the distributed power supply, and the grid-connected reliability of the distributed power supply; 所述的储能互动基础包括:通过储能系统成熟度、储能装机容量占比。The energy storage interaction basis includes: the maturity of the energy storage system and the proportion of the installed capacity of the energy storage. 11.一种配电网互动性综合评价系统,其特征在于,包括:11. An interactive comprehensive evaluation system for distribution network, characterized in that it comprises: 构建模块:用于基于预先构建的配电网互动特性指标体系中的互动特性指标,获取所述互动特性指标对应的电网数据;Building module: used to obtain grid data corresponding to the interactive characteristic index based on the interactive characteristic index in the pre-built distribution network interactive characteristic index system; 确定模块:基于所述电网数据,确定所述互动特性指标对应的综合权重;determining module: determining the comprehensive weight corresponding to the interactive characteristic index based on the power grid data; 评估模块:将所述综合权重带入到预先构建的配电网特性综合评价模型中,评价配电网的互动性。Evaluation module: bringing the comprehensive weight into a pre-built comprehensive evaluation model of distribution network characteristics to evaluate the interactivity of the distribution network. 12.如权利要求11所述的一种配电网互动性综合评价系统,其特征在于,所述构建模块包括:12. A comprehensive evaluation system for distribution network interactivity according to claim 11, wherein the building module comprises: 第一构建子模块:用于根据广义负荷耦合互动特性的影响因素构建一级指标;The first building sub-module: used to build a first-level index according to the influencing factors of the generalized load coupling interaction characteristics; 第二构建子模块:用于基于一级指标的影响因素为每个一级指标构建二级指标;The second construction sub-module: used to construct a second-level index for each first-level index based on the influencing factors of the first-level index; 第三构建子模块:用于基于二级指标的影响因素为每个二级指标构建三级指标。The third building sub-module: used to construct a third-level index for each second-level index based on the influencing factors of the second-level index. 13.如权利要求12所述的一种配电网互动性综合评价系统,其特征在于,所述评估模块包括:13. A comprehensive evaluation system for distribution network interactivity according to claim 12, wherein the evaluation module comprises: 第四构建子模块:用于设定所述三级指标的最大权重作为正理想值,最小权重作为负理想值,并将所有三级指标的正理想值构建正理想系统,所有三级指标的负理想值构建负理想系统;Fourth construction sub-module: used to set the maximum weight of the three-level indicators as a positive ideal value, and the minimum weight as a negative ideal value, and construct a positive ideal system with the positive ideal values of all the three-level indicators. A negative ideal value constructs a negative ideal system; 第一计算子模块:用于依据加权距离公式计算各个三级指标的正理想系统和负理想系统的欧式距离;The first calculation submodule: used to calculate the Euclidean distance of the positive ideal system and the negative ideal system of each third-level index according to the weighted distance formula; 第二计算子模块:用于利用排队指示值公式计算三级指标的排队指示值。The second calculation submodule: used to calculate the queuing indication value of the third-level index by using the queuing indication value formula. 评估子模块:用于所述排队指示值越大,配电网互动特性越强对电网互动性进行综合评估。Evaluation sub-module: the larger the queuing indication value is, the stronger the interaction characteristic of the distribution network is, and the comprehensive evaluation of the interaction of the power grid is carried out. 14.如权利要求11所述的一种配电网互动性综合评价系统,其特征在于,所述确定模块包括:14. A comprehensive evaluation system for distribution network interactivity according to claim 11, wherein the determining module comprises: 第一确定子模块:用于采用熵值法确定指标的客观权重;The first determination sub-module: used to determine the objective weight of the index by using the entropy method; 第二确定子模块:用于采用网络层次分析法确定指标的主观权重;The second determination sub-module: used to determine the subjective weight of the index by using the network analysis hierarchy process; 第三确定子模块:用于将所述指标的客观权重和所述指标的主观权重采用加法集成法确定综合评价模型的权重。The third determination sub-module is used to determine the weight of the comprehensive evaluation model by adopting the addition integration method between the objective weight of the index and the subjective weight of the index.
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Cited By (9)

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CN111949939A (en) * 2020-08-26 2020-11-17 北京航空航天大学 Evaluation method of smart meter running state based on improved TOPSIS and cluster analysis
CN112001606A (en) * 2020-08-10 2020-11-27 广西斯达市场信息咨询有限公司 Environmental protection work evaluation method and system
CN112215512A (en) * 2020-10-22 2021-01-12 上海交通大学 Comprehensive evaluation index weight quantification method and system considering functional characteristics of microgrid
CN113177739A (en) * 2021-05-26 2021-07-27 广东电网有限责任公司 Power grid comprehensive evaluation method, device, equipment and medium
CN113469533A (en) * 2021-07-02 2021-10-01 河海大学 Power distribution network operation evaluation method containing comprehensive energy system
CN113868304A (en) * 2020-06-30 2021-12-31 中国电力科学研究院有限公司 Method and system for determining redundant data of power distribution network
CN114358601A (en) * 2022-01-04 2022-04-15 国网山东省电力公司经济技术研究院 Method and device for constructing multidimensional evaluation index system of multivariate energy system
CN119168357A (en) * 2024-07-13 2024-12-20 山西漪海源科技有限公司 A smart grid security risk data processing method and system
CN114358601B (en) * 2022-01-04 2025-07-01 国网山东省电力公司经济技术研究院 Method and device for constructing multidimensional evaluation index system of multi-element energy system

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113868304A (en) * 2020-06-30 2021-12-31 中国电力科学研究院有限公司 Method and system for determining redundant data of power distribution network
CN112001606A (en) * 2020-08-10 2020-11-27 广西斯达市场信息咨询有限公司 Environmental protection work evaluation method and system
CN111949939A (en) * 2020-08-26 2020-11-17 北京航空航天大学 Evaluation method of smart meter running state based on improved TOPSIS and cluster analysis
CN112215512A (en) * 2020-10-22 2021-01-12 上海交通大学 Comprehensive evaluation index weight quantification method and system considering functional characteristics of microgrid
CN113177739A (en) * 2021-05-26 2021-07-27 广东电网有限责任公司 Power grid comprehensive evaluation method, device, equipment and medium
CN113469533A (en) * 2021-07-02 2021-10-01 河海大学 Power distribution network operation evaluation method containing comprehensive energy system
CN114358601A (en) * 2022-01-04 2022-04-15 国网山东省电力公司经济技术研究院 Method and device for constructing multidimensional evaluation index system of multivariate energy system
CN114358601B (en) * 2022-01-04 2025-07-01 国网山东省电力公司经济技术研究院 Method and device for constructing multidimensional evaluation index system of multi-element energy system
CN119168357A (en) * 2024-07-13 2024-12-20 山西漪海源科技有限公司 A smart grid security risk data processing method and system

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