CN112016838B - Contribution rate calculation method, system and terminal equipment of power distribution network energy efficiency index system - Google Patents

Contribution rate calculation method, system and terminal equipment of power distribution network energy efficiency index system Download PDF

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CN112016838B
CN112016838B CN202010897276.XA CN202010897276A CN112016838B CN 112016838 B CN112016838 B CN 112016838B CN 202010897276 A CN202010897276 A CN 202010897276A CN 112016838 B CN112016838 B CN 112016838B
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CN112016838A (en
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王天霖
高崇
张黎明
罗强
张俊潇
唐俊熙
吴亚雄
曹华珍
李�浩
陈沛东
何璇
黄烨
李阳
欧阳森
张真
杨墨缘
李卓环
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Guangdong Power Grid Co Ltd
Grid Planning Research Center of Guangdong Power Grid Co Ltd
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Guangdong Power Grid Co Ltd
Grid Planning Research Center of Guangdong Power Grid Co Ltd
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Abstract

The embodiment of the invention relates to a contribution rate calculation method, a system and terminal equipment of an energy efficiency index system of a power distribution network, wherein the energy efficiency index system is established through a medium voltage power distribution network, a flexible transformer substation and a low voltage power distribution network, a third-level index and a second-level index in the energy efficiency index system are combined to calculate a second subjective weight of the third-level index, a second objective weight of the third-level index is calculated for the third-level index in the energy efficiency index system, weighting and fusion processing is adopted for the second subjective weight and the second objective weight of the third-level index, so that the contribution rate of the third-level index is obtained, and an improvement scheme for improving the energy efficiency level of the power electronic power distribution network is proposed according to the third-level index with large contribution rate. The method can establish a comprehensive and proper energy efficiency index system of the energy efficiency influence factors, more scientifically and effectively calculates the contribution rate of the three-level indexes corresponding to the influence factors by adopting combined weighting, and provides accurate guidance and reasonable planning for improving the energy efficiency level of the power electronic distribution network and improving the planning, transformation and construction of the distribution network.

Description

Contribution rate calculation method, system and terminal equipment of power distribution network energy efficiency index system
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a contribution rate calculation method, a system and terminal equipment of a power distribution network energy efficiency index system.
Background
Along with the development of society, the conservation and environmental protection become the subjects of the development trend of society, and at present, the loss ratio of a power distribution network in China is serious, and how to realize energy conservation and loss reduction and power grid loss reduction in the power distribution network is one of energy conservation.
In a power distribution network, the problems of low energy efficiency level, unstable electric energy quality and the like of the traditional alternating current power distribution network exist, the problems are well improved by introducing a direct current power supply technology, meanwhile, a large number of distributed power sources DG are connected into the power distribution network, and a large number of power electronic devices such as power electronic transformers (Power Electronic Transformer, PET) and converters are introduced, so that the power distribution network is developed towards a more controllable power electronization direction. On the premise of ensuring the power supply reliability and safety of the power distribution network, the power distribution network with high energy efficiency level can improve the economy and benefit of power consumption.
The high energy efficiency level of the power distribution network is mainly analyzed through energy efficiency influence factors, and the influence degrees of a plurality of influence factors on the energy efficiency level are different. Therefore, the research on the contribution rate in the expansion identification energy efficiency influence factors is particularly important, and the method has important guiding significance for providing a targeted planning and transformation scheme and improving the energy efficiency level for the power distribution network.
At present, the energy efficiency influence factors of the power distribution network are calculated by adopting a single subjective weighting method such as a common Delphi method and an AHP method and an objective weighting method, but the subjectivity of the single subjective weighting method and the entropy weighting method is too strong, wherein the AHP method also needs consistency check to increase the calculated amount. The objective weighting method ignores experience influence of a decision maker, for example, the entropy weighting method has the defect that independence among indexes cannot be reflected, for example, the combined weighting method is proposed in the prior document AHP-independence weighting method-based train passenger interface design evaluation, so that the advantage of subjective and objective weights can be fully exerted, the independence weighting method can process overlapping information among indexes, but the linear weighting randomness of the subjective and objective weights is larger, and a reliable optimal value cannot be obtained; and a conflict evidence synthesis method is provided in the document 'conflict evidence synthesis method based on the pignistic probability distance', so that the reliability and rationality of a fusion result are improved, but the conflict coefficient of the structure is not reasonable enough. In summary, the energy efficiency influence factors of the power distribution network are analyzed at present, the analysis on distributed power sources DG and power electronic equipment is lacking, and a calculation method for effectively identifying influence energy efficiency main factors is lacking.
Therefore, in the preparation of an effective scheme for energy conservation and loss reduction, a scientific and reliable method for calculating the contribution rate of the energy efficiency index is urgently needed, so that main influencing factors influencing the energy efficiency level are identified, and a targeted effective loss reduction scheme is formulated in sequence.
Disclosure of Invention
The embodiment of the invention provides a contribution rate calculation method, a system and terminal equipment of an energy efficiency index system of a power distribution network, which are used for solving the technical problem that the contribution rate in the energy efficiency influence factors is low because main energy efficiency influence factors cannot be obtained in the existing calculation method of the energy efficiency level of the power distribution network.
In order to achieve the above object, the embodiment of the present invention provides the following technical solutions:
a contribution rate calculation method of a power distribution network energy efficiency index system is applied to a power electronic distribution network and comprises the following steps:
s1, establishing an energy efficiency index system, wherein the energy efficiency index system comprises at least three secondary indexes, and each secondary index comprises a plurality of tertiary indexes;
s2, calculating first subjective weights of all three-level indexes and two-level indexes by adopting a Pignitic probability distance improvement G1 method to obtain index subjective weights of all three-level indexes, and processing the index subjective weight of each three-level index to obtain second subjective weights corresponding to the three-level indexes;
s3, calculating first objective weights of all the three-level indexes by adopting an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes;
S4, weighting and fusing are adopted according to the second subjective weight and the second objective weight corresponding to the three-level index, and the contribution rate of each three-level index is obtained.
Preferably, the index subjective weight of the three-level index calculated by adopting the improved G1 method of the Pignistic probability distance specifically comprises the following steps:
s21, scoring all three-level indexes and two-level indexes in the energy efficiency index system to obtain a three-level index set and a two-level index set which are sequenced according to the magnitude of the sequence relation score, and scoring the relative importance degree of adjacent indexes in the three-level index set and the two-level index set;
s22, calculating first subjective weights of the secondary indexes and the tertiary indexes according to an index weight formula, and multiplying the first subjective weight of each secondary index by the first subjective weight of each tertiary index in the secondary indexes to obtain index subjective weights of all tertiary indexes;
wherein, the index weight formula is:
Figure BDA0002658849560000031
wherein omega is n First subjective weight of nth index in three-level index set or two-level index set, r i K is the index in the three-level index set or the two-level index set, and k=n, n-1, … and 2.
Preferably, the processing the subjective weight of each three-level index to obtain the second subjective weight corresponding to the three-level index specifically includes:
s23 according to m i The single proposition focal element Pignistic probability function calculates a corresponding vector beta for each index subjective weight i ；
S24, for each vector beta in the evidence fusion optimization model i Calculating to obtain subjective weight vectors corresponding to the three-level indexes, and forming a subjective weight vector set;
s25, eliminating index subjective weights corresponding to the minimum subjective weight vector in the subjective weight vector set, and taking the calculated average value of N-1 index subjective weights remaining in the three-level index as the second subjective weight of the three-level index;
each three-level index contains N index subjective weights.
Preferably, calculating the first objective weights of all the three-level indexes by using an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain the second objective weights of the three-level indexes specifically comprises:
s31, performing dimensionalization and normalization treatment on all three-level indexes in the energy efficiency index system to obtain a matrix B, and obtaining complex correlation coefficients among indexes in the three-level indexes according to elements in the matrix B;
S32, calculating a first objective weight vector of each three-level index by adopting a coefficient of variation method for all three-level indexes in the energy efficiency index system;
s33, calculating a second objective weight vector of each three-level index by adopting an independent weight method for all three-level indexes in the energy efficiency index system according to the complex correlation coefficient;
s34, processing the first objective weight vector and the second objective weight vector by combining a variation coefficient method and an independence weight method to obtain the second objective weight of the three-level index.
Preferably, the method for calculating the contribution rate of the power distribution network energy efficiency index system further comprises the following steps: and (3) carrying out min-max normalization treatment on all three levels of indexes in the energy efficiency index system to obtain a matrix B.
Preferably, calculating the contribution rate of the three-level index specifically includes:
s41, processing the index subjective weight and the first objective weight of the three-level index by adopting a single-proposition focal element Pignistic probability function to obtain a first subjective weight focal element and a first objective weight focal element;
s42, carrying out discount rate weighting treatment on the second subjective weight and the second objective weight in the three-level index by adopting a basic probability distribution value to obtain the subjective weighting weight and the objective weighting weight of the three-level index;
S43, carrying out fusion processing on the first subjective weight focal element, the first objective weight focal element, the subjective weight and the objective weight of the three-level index by adopting a Dempster combination rule to obtain the contribution rate of the three-level index.
Preferably, the conditions of the Dempster combining rule are:
Figure BDA0002658849560000041
wherein m 'is' 1 And m' 2 Respectively subjective weighting weight and objective weighting weight; a is that i For the first subjective weight focal element in the ith three-level index, B i The first objective weight focal element is the ith three-level index, and E is the fused weight focal element; m (E) is the contribution rate of the three-level index; b is the collision coefficient.
Preferably, the method for calculating the contribution rate of the power distribution network energy efficiency index system further comprises the following steps: and sequencing the contribution rates of all three-level indexes to obtain three-level indexes with large contribution rates, namely, the three-level indexes are main influence factors for influencing the energy efficiency level of the power distribution network.
The invention also provides a contribution rate calculation system of the energy efficiency index system of the power distribution network, which is applied to the power electronic power distribution network and comprises an energy efficiency index system establishment unit, a subjective weight obtaining unit, an objective weight obtaining unit and a calculation unit;
the energy efficiency index system establishment unit is used for establishing an energy efficiency index system from a medium-voltage distribution network, a flexible transformer substation and a low-voltage distribution network, wherein the energy efficiency index system comprises at least three secondary indexes, and each secondary index comprises a plurality of tertiary indexes;
The subjective weight obtaining unit is used for calculating first subjective weights of all three-level indexes and two-level indexes by adopting an improved G1 method of Pignistic probability distance to obtain index subjective weights of all three-level indexes, and processing the index subjective weight of each three-level index to obtain second subjective weights corresponding to the three-level indexes;
the objective weight obtaining unit is used for calculating first objective weights of all three-level indexes by adopting an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes;
and the calculation unit is used for obtaining the contribution rate of each three-level index by adopting weighting and fusion processing according to the second subjective weight and the second objective weight corresponding to each three-level index.
The invention also provides a terminal device, which comprises a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
and the processor is used for executing the contribution rate calculation method of the power distribution network energy efficiency index system according to the instructions in the program codes.
From the above technical solutions, the embodiment of the present invention has the following advantages: the contribution rate calculation method, the contribution rate calculation system and the terminal equipment of the power distribution network energy efficiency index system establish the energy efficiency index system through a medium voltage power distribution network, a flexible transformer substation and a low voltage power distribution network, calculate the second subjective weight of the three-level index by combining the three-level index and the two-level index in the energy efficiency index system, calculate the second objective weight of the three-level index for the three-level index in the energy efficiency index system, and adopt weighting and fusion treatment for the second subjective weight and the second objective weight of the three-level index to obtain the contribution rate of the three-level index, wherein the three-level index with the larger contribution rate is the main influencing factor influencing the power electronic power distribution network, so that an improvement scheme for improving the energy efficiency level of the power electronic power distribution network is proposed according to the three-level index with the large contribution rate. The contribution rate calculation method of the energy efficiency index system of the power distribution network can establish a comprehensive and proper energy efficiency index system of energy efficiency influence factors, the contribution rates of three-level indexes corresponding to the influence factors are calculated more scientifically and effectively by adopting combined weighting, accurate guidance and reasonable planning are provided for improving the energy efficiency level of the power electronic power distribution network and improving the planning, transformation and construction of the power distribution network, and the technical problem that the existing calculation method of the energy efficiency level of the power distribution network cannot obtain main energy efficiency influence factors, so that the contribution rate in the energy efficiency influence factors is low is solved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flowchart of steps of a method for calculating a contribution rate of an energy efficiency index system of a power distribution network according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a topology structure of a power electronic distribution network according to a contribution rate calculation method of a power distribution network energy efficiency index system according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a step of obtaining a second subjective weight by the contribution rate calculation method of the power distribution network energy efficiency index system according to the embodiment of the present invention.
Fig. 4 is a flowchart illustrating a step of obtaining a second objective weight by the method for calculating the contribution rate of the energy efficiency index system of the power distribution network according to the embodiment of the present invention.
Fig. 5 is a flowchart illustrating a step of calculating a contribution rate according to a contribution rate calculating method of an energy efficiency index system of a power distribution network according to an embodiment of the present invention.
Fig. 6 is a frame diagram of a contribution rate calculation system of an energy efficiency index system of a power distribution network according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the application provides a contribution rate calculation method, a system and terminal equipment of a power distribution network energy efficiency index system, which are applied to a power electronic distribution network and are used for solving the technical problem that the existing calculation method for the power distribution network energy efficiency level cannot obtain main energy efficiency influence factors, so that the contribution rate in the energy efficiency influence factors is low. In the embodiment of the application, the power electronic distribution network is taken as a case for explanation, and the contribution rate calculation method, the system and the terminal equipment of the power distribution network energy efficiency index system can also be used for other types of distribution networks.
Embodiment one:
fig. 1 is a flowchart of steps of a method for calculating a contribution rate of an energy efficiency index system of a power distribution network according to an embodiment of the present invention.
As shown in fig. 1, the embodiment of the invention provides a contribution rate calculation method of a power distribution network energy efficiency index system, which is applied to a power electronic distribution network and comprises the following steps:
s1, establishing an energy efficiency index system, wherein the energy efficiency index system is established from a medium-voltage distribution network, a flexible transformer substation and a low-voltage distribution network and comprises at least three secondary indexes, and each secondary index comprises a plurality of tertiary indexes;
s2, calculating first subjective weights of all three-level indexes and two-level indexes by adopting a Pignitic probability distance improvement G1 method to obtain index subjective weights of all three-level indexes, and processing the index subjective weight of each three-level index to obtain second subjective weights corresponding to the three-level indexes;
s3, calculating first objective weights of all the three-level indexes by adopting an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes;
s4, weighting and fusing are adopted according to the second subjective weight and the second objective weight corresponding to the three-level index, and the contribution rate of each three-level index is obtained.
In step S1, by analyzing the energy efficiency influence factors of the power electronic distribution network, the energy efficiency index system comprises a medium-voltage distribution network energy efficiency index system S1, a flexible substation energy efficiency index system S2 and a low-voltage distribution network energy efficiency index system S3.
It should be noted that, the medium voltage distribution network index system S1 includes the following three levels of indexes: the medium-voltage power supply voltage qualification rate, the medium-voltage power supply radius qualification rate, the medium-voltage line sectional area qualification rate, the medium-voltage line average power factor qualification rate, the medium-voltage line load in an economic section number rate, the DG capacity ratio, the DG output fluctuation rate, the Energy Storage (ES) charging and discharging efficiency, the ES capacity ratio and the like. The energy efficiency index system S2 of the flexible transformer substation comprises the following three levels of indexes: the high-efficiency distribution transformer capacity ratio, the transformer load number rate in an economic section, the average power factor qualification rate of the transformer, the reactive compensation capacity ratio, the PET capacity ratio and the like. The low-voltage power distribution network energy efficiency index system S3 comprises the following three levels of indexes: low-voltage power supply voltage qualification rate, low-voltage power supply radius qualification rate, low-voltage line sectional area qualification rate, low-voltage alternating current line average power factor qualification rate, low-voltage line load economic operation number rate, low-voltage alternating current harmonic distortion rate, three-phase load unbalance degree, converter comprehensive efficiency and the like.
Fig. 2 is a schematic diagram of a topology structure of a power electronic distribution network according to a contribution rate calculation method of a power distribution network energy efficiency index system according to an embodiment of the present invention.
In step S1 of the embodiment of the present invention, according to the topology division of the grid structure of the power electronic distribution network, energy efficiency mechanism analysis is performed on three aspects of a line, a transformer and a distributed power source DG, and an index system of the power electronic distribution network is divided into: the first-level index level O is the energy efficiency level of the power electronic distribution network, and the second-level index level S comprises: the medium-voltage distribution network S1, the flexible substation S2 and the low-voltage distribution network S3, and the three-level index level P comprises various single indexes. In this embodiment, the power-electronized distribution network elements include, but are not limited to: distribution lines, power electronic transformers, power transformers, ac circuit breakers, dc circuit breakers, reactive compensation devices, converters, ac-dc buses, and the like.
As shown in fig. 2, the medium voltage distribution network includes a medium voltage direct current distribution network and a medium voltage alternating current distribution network, and the low voltage distribution network includes a low voltage direct current distribution network and a low voltage alternating current distribution network. The distribution line includes a DC cable and an AC cable. The power electronic transformer comprises 5-stage conversion modules such as a first-stage high-voltage side AC/DC converter, a second-stage high-voltage side DC/AC converter, a third-stage high-frequency transformer, a fourth-stage low-voltage AC/DC converter, a fifth-stage low-voltage DC/AC converter and the like, and a distributed power source DG in the power distribution network can be directly connected to a high-voltage side DC end, so that the use of the converter is reduced. The converter includes a DG output side converter, a low voltage AC/DC rectifier, a low voltage DC/AC inverter, and the like. The converter includes DG output side converter, low voltage AC/DC rectifier, low voltage DC/AC inverter, and the like.
In this embodiment, the expression based on the medium-low voltage line energy consumption mechanism is:
Figure BDA0002658849560000081
wherein, delta P is the line loss; i is the root mean square current of the line; r is the equivalent resistance of a circuit in the power distribution network; p is the line load; u is the line operating voltage; lambda is the line power factor; ρ is the wire resistivity; l is the length of the line; a is the sectional area of the line.
In this embodiment, the transformer energy consumption mechanism expression is:
Figure BDA0002658849560000082
wherein DeltaP T Is transformer loss; p (P) Fe Is the iron loss of the transformer; p (P) Cu Copper loss of the transformer; u is the operating voltage of the transformer; u (U) N Rated voltage of the transformer; p (P) 0 The no-load loss is adopted, and P is the actual load of the transformer; s is S N Rated capacity of the transformer; lambda is the power factor of the transformer; p (P) k Is the transformer load loss.
In this embodiment, the mechanism expression of the power loss variation amount of the distributed power source DG before and after accessing the power distribution network is:
Figure BDA0002658849560000083
wherein DeltaP DG Accessing the power consumption variable quantity for DG; p (P) L The total load power supplied by the DG grid-connected bus is calculated; u (U) DC Grid-connected direct current bus voltage is DG; lambda (lambda) DG Is DG capacity duty cycle; μ is VSC converter efficiency; m is the modulation ratio of the current transformer,
Figure BDA0002658849560000091
the power factor angle is the alternating current side power factor angle of the converter; r is R G Is equivalent resistance of alternating current side of the converter, R DG Is DG equivalent resistance.
In step S2 of the embodiment of the present invention, all the three-level indexes and the two-level indexes are ranked and processed according to the improved G1 method of the pitnsitic probability distance, so as to obtain first subjective weights of the three-level indexes and the two-level indexes, the first subjective weights of the three-level indexes and the two-level indexes are processed, so as to obtain index subjective weights of the three-level indexes, and the index subjective weights of each three-level index are processed so as to obtain second subjective weights corresponding to the three-level indexes.
It should be noted that, in step S2, the second subjective weight of each three-level index is calculated, mainly to provide data for calculating the contribution rate of each three-level index in step S4. And calculating the focal element of the first subjective weight of each three-level index, further obtaining the subjective weight vector of the three-level index, removing the index subjective weight with the minimum subjective weight vector, and averaging the subjective weights of the rest indexes to obtain the improved second subjective weight.
In the step S3 of the embodiment of the present invention, an improved objective weighting method in a coefficient of variation-independence method is mainly adopted to calculate a first objective weight of the three-level index in the step S1, and the first objective weight of the three-level index is processed to obtain a second objective weight of the three-level index.
It should be noted that, in step S3, the second objective weight of each three-level index is calculated, mainly to provide data for calculating the contribution rate of each three-level index in step S4.
In step S4 of the embodiment of the present invention, the contribution rate of the three-level index is calculated after the three-level index is processed according to the index subjective weight, the first objective weight, the second subjective weight and the second objective weight of the three-level index obtained in step S2 and step S3, and the three-level index with the larger contribution rate is the main influencing factor influencing the power electronic distribution network, so that an improvement scheme for improving the energy efficiency level of the power electronic distribution network is provided according to the three-level index with the large contribution rate, and compared with the traditional one-cut energy-saving and loss-reducing reconstruction measure, the improvement scheme is more targeted. The contribution rate calculation method of the energy efficiency index system of the power distribution network can establish a comprehensive and proper energy efficiency index system of the energy efficiency influence factor, and the contribution rate of the three-level index corresponding to the influence factor is calculated more scientifically and effectively by adopting the combined weighting, so that the method has practical significance for improving the energy efficiency level of the power electronic power distribution network and improving the blindness of planning, reconstruction and construction of the power distribution network.
According to the contribution rate calculation method of the energy efficiency index system of the power distribution network, the energy efficiency index system is built from a medium-voltage power distribution network, a flexible transformer substation and a low-voltage power distribution network, the third-level index and the second-level index in the energy efficiency index system are combined to calculate the second subjective weight of the third-level index, the second objective weight of the third-level index is calculated on the third-level index in the energy efficiency index system, weighting and fusion processing is adopted on the second subjective weight and the second objective weight of the third-level index, the contribution rate of the third-level index is obtained, the three-level index with the larger contribution rate is the main influence factor affecting the power electronic power distribution network, and therefore an improvement scheme for improving the energy efficiency level of the power electronic power distribution network is proposed according to the three-level index with the large contribution rate. The contribution rate calculation method of the energy efficiency index system of the power distribution network can establish a comprehensive and proper energy efficiency index system of energy efficiency influence factors, the contribution rates of three-level indexes corresponding to the influence factors are calculated more scientifically and effectively by adopting combined weighting, accurate guidance and reasonable planning are provided for improving the energy efficiency level of the power electronic power distribution network and improving the planning, transformation and construction of the power distribution network, and the technical problem that the existing calculation method of the energy efficiency level of the power distribution network cannot obtain main energy efficiency influence factors, so that the contribution rate in the energy efficiency influence factors is low is solved.
In the embodiment of the invention, index values of three levels of indexes in the energy efficiency index system of the power electronic distribution network are calculated as follows:
the influence factor of the running voltage of the medium voltage line is evaluated by three-level indexes of the medium voltage supply voltage qualification rate, and the formula for calculating the medium voltage supply voltage qualification rate is as follows:
Figure BDA0002658849560000101
in the method, in the process of the invention,
Figure BDA0002658849560000102
the qualification rate of the medium-voltage power supply voltage is achieved; t is t i The voltage of the ith medium-voltage direct-current bus is qualified total time; t is t j The voltage of the jth medium-voltage alternating-current bus is qualified total time; />
Figure BDA0002658849560000103
Is the voltage of a medium-voltage direct-current busThe number of the qualified bars; />
Figure BDA0002658849560000104
The number of grids is pressed for the medium-voltage alternating current bus; />
Figure BDA0002658849560000105
The total number of the medium-voltage buses is; />
Figure BDA0002658849560000106
For a single bus total run time.
The influence factor of the line length is evaluated by three-level indexes, namely medium-voltage power supply radius qualification rate, and a formula for calculating the medium-voltage power supply radius qualification rate is as follows:
Figure BDA0002658849560000107
in the method, in the process of the invention,
Figure BDA0002658849560000108
radius qualification rate for medium-voltage power supply; />
Figure BDA0002658849560000109
The radius of the medium-voltage direct current power supply is qualified; />
Figure BDA00026588495600001010
The radius of the medium-voltage alternating current power supply is qualified; />
Figure BDA00026588495600001011
Is the total number of medium voltage loops.
The influence factor of the cross section area of the medium voltage circuit is evaluated by three-level indexes of the qualification rate of the cross section area of the medium voltage circuit, and the formula for calculating the qualification rate of the cross section area of the medium voltage circuit is as follows:
Figure BDA0002658849560000111
In the method, in the process of the invention,
Figure BDA0002658849560000112
the cross-sectional area qualification rate of the medium-voltage circuit is obtained; />
Figure BDA0002658849560000113
Is the qualified number of the sectional area of the medium-voltage direct current circuit; />
Figure BDA0002658849560000114
Is the qualified number of the sectional area of the medium-voltage alternating current line; />
Figure BDA0002658849560000115
Is the total number of medium voltage lines. />
The factor influence factor of the medium voltage line power is evaluated by three-level indexes of the medium voltage line average power factor qualification rate, and a formula for calculating the medium voltage line average power factor qualification rate is as follows:
Figure BDA0002658849560000116
in the method, in the process of the invention,
Figure BDA0002658849560000117
the average power factor qualification rate of the medium-voltage line is obtained; />
Figure BDA0002658849560000118
The number of the medium-voltage direct-current loops is in accordance with the standard;
Figure BDA0002658849560000119
is the number of medium-voltage alternating current flows which meet the standard; />
Figure BDA00026588495600001110
Is the total number of medium voltage lines.
The influence factor of the medium voltage line load is evaluated by three-level indexes of the medium voltage line load in the economic interval, and a formula for calculating the medium voltage line load in the economic interval is as follows:
Figure BDA00026588495600001111
in the method, in the process of the invention,
Figure BDA00026588495600001112
the number rate of the medium-voltage line load in the economic interval is calculated; t is t i Economic run time for the ith medium voltage dc line; t is t j Economic run time for the jth medium voltage ac line; />
Figure BDA00026588495600001113
The economic operation numbers of the medium-voltage direct current and alternating current circuits are respectively; />
Figure BDA00026588495600001114
Is the total number of medium voltage lines, +.>
Figure BDA00026588495600001115
For a single line total run time.
The penetration condition of renewable energy sources is evaluated by three-level indexes of DG capacity ratio, and the formula for calculating the DG capacity ratio is as follows:
Figure BDA00026588495600001116
Wherein lambda is DG The DG capacity is the ratio; n (N) DG The DG category number in the power distribution network; n is n i The DG number is the i-th class; p (P) i * For the rated power of the class i DG,
Figure BDA00026588495600001117
is the maximum value of the load power of the distribution network.
The uncertainty of renewable energy sources is evaluated by three-level indexes of DG output fluctuation rate, and a formula for calculating the DG output fluctuation rate is as follows:
Figure BDA00026588495600001118
wherein, gamma DG The fluctuation rate of the DG output is given; n is DG total number; p (P) i rea (jt m )、P i rea ((j+1)t m ) The actual output of the ith DG in the two adjacent measurement time periods is respectively; p (P) i * The ith DG rated power; n is n t The total time interval number of the whole day; t is t m For adjacent time intervals, typically 15min is taken.
The capacity of the energy storage device for peak clipping and valley filling is evaluated by three-level indexes of the capacity ratio of the ES, and a formula for calculating the capacity ratio of the ES is as follows:
Figure BDA0002658849560000121
wherein lambda is ES Is ES capacity duty cycle;
Figure BDA0002658849560000122
rated capacity of a single ES; />
Figure BDA0002658849560000123
Is the maximum value of the load power of the distribution network.
The efficiency of the energy storage device is evaluated by three-level indexes of the charge and discharge efficiency of the ES, and the formula for calculating the charge and discharge efficiency of the ES is as follows:
Figure BDA0002658849560000124
wherein eta is ES Charging and discharging efficiency for the ES; Σp dis Total power discharged for ES; Σp cha Total power to charge ES.
The no-load loss and the load loss in the transformer are evaluated by the three-level index of the capacity ratio of the high-efficiency distribution transformer, and the formula for calculating the capacity ratio of the high-efficiency distribution transformer is as follows:
Figure BDA0002658849560000125
Wherein ρ is eff_T The capacity ratio of the high-efficiency distribution transformer is calculated; n (N) eff The number of the high-efficiency distribution transformers is the number;
Figure BDA0002658849560000126
rated capacity of the i-th high-efficiency distribution transformer; />
Figure BDA0002658849560000127
Is the rated total capacity of the transformer.
The actual load of the transformer is evaluated by three-level indexes of the transformer load in the economic section, and the formula for calculating the transformer load in the economic section is as follows:
Figure BDA0002658849560000128
ρ E_T for the number rate of the transformer load in the economic section, N E_T The number of distribution transformers is calculated for economic operation; n (N) T Is the total number of transformers.
The power factor of the transformer is evaluated by three-level indexes, namely the average power factor qualification rate of the transformer, and the formula for calculating the average power factor qualification rate of the transformer is as follows:
Figure BDA0002658849560000131
wherein ρ is λT The average power factor qualification rate of the transformer is obtained; n (N) λ N is the number of transformers with average power factor larger than 0.9 T Is the total number of transformers.
The operation voltage is evaluated by the three-level index of the reactive compensation capacity to the transformer capacity ratio, and the formula for calculating the reactive compensation capacity to the transformer capacity ratio is as follows:
Figure BDA0002658849560000132
wherein ρ is q The reactive compensation capacity is the capacity ratio of the transformer; sigma S Q For the reactive compensation capacity,
Figure BDA0002658849560000133
is the sum of the rated capacities of all transformers.
The energy-saving and loss-reducing effect of PET is evaluated by three-level indexes of PET capacity ratio, and the formula for calculating the PET capacity ratio is as follows:
Figure BDA0002658849560000134
Wherein ρ is PET Is PET capacity ratio;
Figure BDA0002658849560000135
for the sum of PET rated capacities, +.>
Figure BDA0002658849560000136
Is the sum of the rated capacities of all transformers.
The formula for calculating the three-level index of the low-voltage alternating-current harmonic distortion rate is as follows:
Figure BDA0002658849560000137
wherein, HRI is low-voltage alternating-current harmonic distortion rate; i 1 Is the fundamental current effective value; i h Is the effective value of the h harmonic current component.
The formula for calculating the three-level index of the three-phase load unbalance degree is as follows:
Figure BDA0002658849560000138
wherein ρ is unb Is the imbalance degree of the three-phase load;
Figure BDA0002658849560000139
is a three-phase negative sequence voltage component; />
Figure BDA00026588495600001310
Figure BDA00026588495600001311
Is a three-phase positive sequence voltage component.
The formula for calculating the three-level index of the comprehensive efficiency of the converter is as follows:
Figure BDA00026588495600001312
wherein ρ is co The comprehensive efficiency of the converter is achieved; k (K) co For the class number of the current transformer, N S Is the number of various converters, ρ i The capacity ratio of the current transformer is i type;
Figure BDA0002658849560000141
active power is output for the jth converter in the ith class; />
Figure BDA0002658849560000142
Active power is input to a jth converter in the ith class; n (N) co The total number of the converters.
In this embodiment, the calculation formulas of the three-level indexes of the low-voltage power supply voltage qualification rate, the low-voltage power supply radius qualification rate, the low-voltage line sectional area qualification rate, the low-voltage alternating-current line average power factor qualification rate, the low-voltage line load in the economic operation number rate in the low-voltage power distribution network index system are the same as the calculation formulas of the three-level indexes of the medium-voltage power supply voltage qualification rate, the medium-voltage power supply radius qualification rate, the medium-voltage line sectional area qualification rate, the medium-voltage line average power factor qualification rate, the medium-voltage line load in the economic operation number rate in the medium-voltage power distribution network index system, and only the calculation parameters are different, and in this embodiment, the calculation formulas of the three-level indexes of the low-voltage power supply voltage qualification rate, the low-voltage power supply radius qualification rate, the low-voltage line sectional area qualification rate, the low-voltage alternating-current line average power factor qualification rate and the low-voltage line load in the economic operation number rate are not described in detail.
Fig. 3 is a flowchart illustrating a step of obtaining a second subjective weight by the contribution rate calculation method of the power distribution network energy efficiency index system according to the embodiment of the present invention.
As shown in fig. 3, in an embodiment of the present invention, calculating the subjective weight of the index of the three-level index by using the modified G1 method of the pitucitic probability distance specifically includes:
s21, scoring all three-level indexes and two-level indexes in the energy efficiency index system in order to obtain a three-level index set and a two-level index set which are ordered according to the magnitude of the order relation score, and scoring the relative importance degree of adjacent indexes in the three-level index set and the two-level index set;
s22, calculating first subjective weights of the secondary indexes and the tertiary indexes according to an index weight formula, and multiplying the first subjective weight of each secondary index by the first subjective weight of each tertiary index in the secondary indexes to obtain index subjective weights of all tertiary indexes;
wherein, the index weight formula is:
Figure BDA0002658849560000143
wherein omega is n First subjective weight of nth index in three-level index set or two-level index set, r i K is the index in the three-level index set or the two-level index set, and k=n, n-1, … and 2.
Processing the index subjective weight of each three-level index to obtain a second subjective weight corresponding to the three-level index specifically comprises the following steps:
s23 according to m i The single proposition focal element Pignistic probability function calculates a corresponding vector beta for each index subjective weight i ；
S24, for each vector beta in the evidence fusion optimization model i Calculating to obtain subjective weight vectors corresponding to the three-level indexes, and forming a subjective weight vector set;
s25, eliminating index subjective weights corresponding to the minimum subjective weight vector in the subjective weight vector set, and calculating an average value of N-1 index subjective weights remained in the three-level index as a second subjective weight of the three-level index;
each three-level index contains N index subjective weights.
In step S21 of the embodiment of the present invention, N experts score the order relationship and the relative importance degree of the three-level index and the two-level index in the energy efficiency index system, and the two-level index is s= { S 1 ,S 2 ,S 3 The second level index comprises a third level index of
Figure BDA0002658849560000151
i=1 represents a three-level index set of the medium-voltage distribution network, i=2 represents a three-level index set of the flexible substation, and i=3 represents a three-level index set of the low-voltage distribution network. Each three-level index set after the N experts sequence the three-level index sequence relation is X= { X 1 ,x 2 ,…,x n Index sequence relationships, x 1 ＞x 2 ＞…＞x n . Determining importance degree between adjacent indexes after ordering of each index set in order relation, and setting adjacent indexes x determined by expert according to index scale table k-1 And x k The ratio of the importance levels is as follows:
Figure BDA0002658849560000152
wherein, the index scale table is shown in the following table:
Figure BDA0002658849560000153
first, the first subjective weight of the last three-level index in the three-level index set X can be obtained through an index weight formula, and then the first subjective weight of the last three-level index in the three-level index set X can be obtained through the adjacent index X k-1 And x k The ratio of the importance levels sequentially determines the first subjective weight of the rest three-level indexes in the three-level index set X. And similarly, calculating the first subjective weight of the secondary index.
In step S22 of the embodiment of the present invention, the weight of the secondary index obtained in step S21 is W S ＝[w S1 ,w S2 ,w S3 ]The weight of the three-level index is
Figure BDA0002658849560000161
All three-level indexes determined by the jth expert have subjective index weights +.>
Figure BDA0002658849560000162
In step S23 of the embodiment of the present invention, the vector β of the pitnsitic probability function corresponding to the index subjective weight of the three-level index of the N experts i The method comprises the following steps:
Figure BDA0002658849560000163
wherein Θ is an identification frame, 2 Θ Is a power set on Θ, m i To identify the ith basic trustworthiness allocation function on the framework Θ,
Figure BDA0002658849560000164
is m i Pignistic function on Θ.
Figure BDA0002658849560000165
Where A is a subset of Θ, A is the radix of A, θ i Is the i-th element in a.
In step S24 of the embodiment of the present invention, the evidence fusion optimization model is:
Figure BDA0002658849560000166
wherein w' i The subjective weight vector to be solved;
Figure BDA0002658849560000167
for the desired evidence->
Figure BDA0002658849560000168
And weighted evidence w' i m i The smaller the Pignism probability distance of which the value is, the closer the evidence is to the expected evidence; />
Figure BDA0002658849560000169
Respectively the average value and beta of weighted evidence i Average value weighted with corresponding weight, ||w' i ·β i -β'|| 2 The subjective weight vector set is obtained by the method as the square of the sum of the coordinate differences' o ＝(w' 1 ,w' 2 ,…,w' N )。
In step S25 of the embodiment of the present invention, the subjective weight vector set of each three-level index eliminates the relative weight vector minimum w' k Subjective weight w of index (f) ks Obtaining an index subjective weight set of each three-level index
Figure BDA00026588495600001610
And calculating the arithmetic average value of the index subjective weights obtained by the remaining N-1 experts in the index subjective weight set as the second subjective weight of the three-level index.
Fig. 4 is a flowchart illustrating a step of obtaining a second objective weight by the method for calculating the contribution rate of the energy efficiency index system of the power distribution network according to the embodiment of the present invention.
As shown in fig. 4, in one embodiment of the present invention, calculating the first objective weights of all the three-level indicators by using the improved objective weighting method in the coefficient of variation-independence method, and processing the first objective weights of the three-level indicators to obtain the second objective weights of the three-level indicators specifically includes:
S31, performing dimensionalization and normalization treatment on all three-level indexes in the energy efficiency index system to obtain a matrix B, and obtaining complex correlation coefficients among the three-level indexes according to elements in the matrix B;
s32, calculating a first objective weight vector of each three-level index by adopting a coefficient of variation method for all three-level indexes in the energy efficiency index system;
s33, calculating a second objective weight vector of each three-level index by adopting an independent weight method for all three-level indexes in the energy efficiency index system according to the complex correlation coefficient;
s34, processing the first objective weight vector and the second objective weight vector by combining a variation coefficient method and an independence weight method to obtain the second objective weight of the three-level index.
The contribution rate calculation method of the power distribution network energy efficiency index system further comprises the step of adopting min-max normalization processing to all three-level indexes in the energy efficiency index system to obtain a B matrix.
In step S31 of the embodiment of the present invention, the values of all three-level indexes are preprocessed by using a min-max normalization method, so as to obtain a B matrix, where elements in the B matrix are values of all three-level indexes after normalization processing.
Note that, the normalization process is:
for the very large three-level index, namely, the larger and the better the index value of the three-level index is, the more:
Figure BDA0002658849560000171
For a very small three-level index, i.e. the smaller the index value of the three-level index is, the better is:
Figure BDA0002658849560000172
in the method, in the process of the invention,
Figure BDA0002658849560000173
the j-th three-level index original value of the i-th power distribution network evaluation object.
In step S31 of the embodiment of the present invention, the calculation formula of the complex correlation coefficient is:
Figure BDA0002658849560000174
wherein R is j Complex correlation coefficient of j-th index, b j To normalize the j-th column element in the matrix,
Figure BDA0002658849560000175
scratch out B for normalized B matrix j The remaining matrix average value of that column, +.>
Figure BDA0002658849560000176
For normalizing the average value of the B matrix, n is the number of three-level indexes.
In step S32 of the embodiment of the present invention, the index variation coefficient and the first objective weight w are determined by using the variation coefficient method o1 If the index set of the three-level index in the energy efficiency index system is { x } 1 ,x 2 ,…x n And (3) the index variation coefficient is:
Figure BDA0002658849560000181
wherein V is j A variation coefficient sigma of the j-th three-level index j Is the standard deviation of the j-th three-level index,
Figure BDA0002658849560000182
is the mean value of the j-th three-level index. From the coefficient of variation a first customer weight vector +.>
Figure BDA0002658849560000183
Obtaining:
Figure BDA0002658849560000184
in step S33 of the embodiment of the present invention, the independent weight method is used to determine the complex phase relationship between the three-level indexesNumber and second objective weight vector w o2 The calculation formula of the second objective weight vector is as follows:
Figure BDA0002658849560000185
from the above formula, complex correlation coefficients between the three-level index are used to determine the second objective weight vector
Figure BDA0002658849560000186
In step S34 of the embodiment of the present invention, a second objective weight w is determined by combining the coefficient of variation method and the independence weight method o The calculation formula of the second objective weight is as follows:
Figure BDA0002658849560000187
the second objective weight mode of calculating the three-level index by the contribution rate calculation method of the power distribution network energy efficiency index system can avoid the defect that the independence of the index and the understanding of an evaluator on the index value cannot be embodied by the variation coefficient method, and solves the problem of information overlapping among indexes by combining the independence weight method.
Fig. 5 is a flowchart illustrating a step of calculating a contribution rate according to a contribution rate calculating method of an energy efficiency index system of a power distribution network according to an embodiment of the present invention.
As shown in fig. 5, in one embodiment of the present invention, calculating the contribution rate of the three-level index specifically includes:
s41, processing the index subjective weight and the first objective weight of the three-level index by adopting a single-proposition focal element Pignistic probability function to obtain a first subjective weight focal element and a first objective weight focal element;
s42, carrying out discount rate weighting treatment on the second subjective weight and the second objective weight in the three-level index by adopting a basic probability distribution value to obtain the subjective weighting weight and the objective weighting weight of the three-level index;
s43, carrying out fusion processing on the first subjective weight focal element, the first objective weight focal element, the subjective weight and the objective weight of the three-level index by adopting a Dempster combination rule to obtain the contribution rate of the three-level index.
In the embodiment of the invention, the conditions of the Dempster combination rule are as follows:
Figure BDA0002658849560000191
wherein m 'is' 1 And m' 2 Respectively subjective weighting weight and objective weighting weight; a is that i For the first subjective weight focal element in the ith three-level index, B i The first objective weight focal element is the ith three-level index, and E is the fused weight focal element; m (E) is the contribution rate of the three-level index; b is the collision coefficient. Wherein, the larger the value of b reflects the larger the conflict between subjective and objective.
In step S41 of the embodiment of the present invention, the main objective weight and the second objective weight can be obtained from the step S2 and the step S3, and the main objective weight and the second objective weight are recorded as
Figure BDA0002658849560000192
Figure BDA0002658849560000193
For the second subjective weight +.>
Figure BDA0002658849560000194
Is the second objective weight. The manner of obtaining the first subjective weight bin and the first objective weight bin by using the single-proposition bin pitnsistic probability function processing on the index subjective weight and the first objective weight of the three-level index has been described in detail in step S23, the weight bin is obtained by performing the single-proposition bin pitnsistic probability function processing on the weights, the first subjective weight bin and the first objective weight bin are obtained by using the same processing manner as in step S23 again on the index subjective weight and the first objective weight, and therefore the first subjective weight is no longer obtained by using the single-proposition bin pitnsistic probability function processing on the index subjective weight and the first objective weight of the three-level index again The focal element and the first apparent weight focal element are described. />
In step S42 of the embodiment of the present invention, the discount rate weighting process of the base probability distribution value is specifically:
Figure BDA0002658849560000195
in the method, in the process of the invention,
Figure BDA0002658849560000201
the discount rate of the corresponding weight is determined, namely the relative importance of the two weighting methods is determined, and the traditional linear weighting coefficient is replaced, so that the result is more reliable; ζ=1 represents the first subjective weight, and ζ=2 represents the first objective weight; w' ξ Is the main and the second objective weight; m is m ξ (A) Is the original main and the second objective weight value; m's' ξ (A) The weight value A is a three-level index weight set of each item; m is m ξ (Θ)、m' ξ (Θ) is uncertainty of weights before and after the discount rate.
Embodiment two:
fig. 6 is a frame diagram of a contribution rate calculation system of an energy efficiency index system of a power distribution network according to an embodiment of the present invention.
As shown in fig. 6, the embodiment of the present invention further provides a contribution rate calculation system of an energy efficiency index system of a power distribution network, which is applied to a power electronic power distribution network, and includes an energy efficiency index system establishment unit 10, a subjective weight obtaining unit 20, an objective weight obtaining unit 30 and a calculation unit 40;
an energy efficiency index system establishing unit 10 is used for establishing an energy efficiency index system for a medium-voltage distribution network, a flexible transformer substation and a low-voltage distribution network, wherein the energy efficiency index system comprises at least three secondary indexes, and each secondary index comprises a plurality of tertiary indexes;
The subjective weight obtaining unit 20 is configured to calculate first subjective weights of all three-level indexes and two-level indexes by using a modified G1 method of a pitnsitic probability distance to obtain index subjective weights of all three-level indexes, and process the index subjective weight of each three-level index to obtain a second subjective weight corresponding to the three-level index;
an objective weight obtaining unit 30, configured to calculate first objective weights of all three-level indexes by using an improved objective weighting method in a coefficient of variation-independence method, and process the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes;
and a calculating unit 40, configured to obtain the contribution rate of each three-level index by adopting weighting and fusion processing according to each second subjective weight and second objective weight corresponding to the three-level index.
It should be noted that, the units in the second system are set corresponding to the steps in the method in the first embodiment, and the details of the steps corresponding to the respective units have been described in the first embodiment, which is not described in detail in this embodiment.
Embodiment III:
the embodiment of the invention also provides terminal equipment, which comprises a processor and a memory;
a memory for storing program code and transmitting the program code to the processor;
And the processor is used for executing the contribution rate calculation method of the power distribution network energy efficiency index system according to the instructions in the program codes.
Note that the computer-readable storage medium may include: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (7)

1. The contribution rate calculation method of the power distribution network energy efficiency index system is applied to a power electronic distribution network and is characterized by comprising the following steps of:
s1, establishing an energy efficiency index system, wherein the energy efficiency index system comprises at least three secondary indexes, and each secondary index comprises a plurality of tertiary indexes;
s2, calculating first subjective weights of all three-level indexes and two-level indexes by adopting a Pignitic probability distance improvement G1 method to obtain index subjective weights of all three-level indexes, and processing the index subjective weight of each three-level index to obtain second subjective weights corresponding to the three-level indexes;
S2, calculating first subjective weights of all three-level indexes and two-level indexes by adopting a Pignitic probability distance improvement G1 method to obtain index subjective weights of all three-level indexes, and processing the index subjective weight of each three-level index to obtain a second subjective weight corresponding to the three-level index, wherein the method comprises the steps of:
s21, scoring all three-level indexes and two-level indexes in the energy efficiency index system to obtain a three-level index set and a two-level index set which are sequenced according to the magnitude of the sequence relation score, and scoring the relative importance degree of adjacent indexes in the three-level index set and the two-level index set;
s22, calculating first subjective weights of the secondary indexes and the tertiary indexes according to an index weight formula, and multiplying the first subjective weight of each secondary index by the first subjective weight of each tertiary index in the secondary indexes to obtain index subjective weights of all tertiary indexes;
wherein, the index weight formula is:
Figure FDA0004130828880000011
wherein omega is n First subjective weight of nth index in three-level index set or two-level index set, r i K is the index in the three-level index set or the two-level index set, k=n, n-1, …,2, n is the number of indexes, and n is more than or equal to 1;
S23 according to m i The single proposition focal element Pignistic probability function calculates a corresponding vector beta for each index subjective weight i ；
S24, for each vector beta in the evidence fusion optimization model i Calculating to obtain subjective weight vectors corresponding to the three-level indexes, and forming a subjective weight vector set;
s25, eliminating index subjective weights corresponding to the minimum subjective weight vector in the subjective weight vector set, and taking the calculated average value of N-1 index subjective weights remaining in the three-level index as the second subjective weight of the three-level index;
wherein each three-level index comprises N index subjective weights, N is the number of the index subjective weights, and N is more than or equal to 2;
s3, calculating first objective weights of all the three-level indexes by adopting an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes;
s3, calculating first objective weights of all three-level indexes by adopting an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes, wherein the step comprises the following steps:
s31, performing dimensionalization and normalization treatment on all three-level indexes in the energy efficiency index system to obtain a matrix B, and obtaining complex correlation coefficients among indexes in the three-level indexes according to elements in the matrix B;
S32, calculating a first objective weight vector of each three-level index by adopting a coefficient of variation method for all three-level indexes in the energy efficiency index system;
s33, calculating a second objective weight vector of each three-level index by adopting an independent weight method for all three-level indexes in the energy efficiency index system according to the complex correlation coefficient;
s34, processing the first objective weight vector and the second objective weight vector by combining a variation coefficient method and an independence weight method to obtain a second objective weight of the three-level index;
s4, weighting and fusing are adopted according to the second subjective weight and the second objective weight corresponding to the three-level index, and the contribution rate of each three-level index is obtained.
2. The method for calculating the contribution rate of the energy efficiency index system of the power distribution network according to claim 1, further comprising:
and (3) carrying out min-max normalization treatment on all three levels of indexes in the energy efficiency index system to obtain a matrix B.
3. The method for calculating the contribution rate of the energy efficiency index system of the power distribution network according to claim 1, wherein calculating the contribution rate of the three-level index specifically comprises:
s41, processing the index subjective weight and the first objective weight of the three-level index by adopting a single-proposition focal element Pignistic probability function to obtain a first subjective weight focal element and a first objective weight focal element;
S42, carrying out discount rate weighting treatment on the second subjective weight and the second objective weight in the three-level index by adopting a basic probability distribution value to obtain the subjective weighting weight and the objective weighting weight of the three-level index;
s43, carrying out fusion processing on the first subjective weight focal element, the first objective weight focal element, the subjective weight and the objective weight of the three-level index by adopting a Dempster combination rule to obtain the contribution rate of the three-level index.
4. A method for calculating a contribution rate of an energy efficiency index system of a power distribution network according to claim 3, wherein the condition of the Dempster combination rule is:
Figure FDA0004130828880000031
wherein m 'is' 1 And m' 2 Respectively subjective weighting weight and objective weighting weight; a is that i For the first subjective weight focal element in the ith three-level index, B i The first objective weight focal element is the ith three-level index, and E is the fused weight focal element; m (E) is the contribution rate of the three-level index; b is a collision coefficient;
Figure FDA0004130828880000032
is the intersection of the first subjective weight bin and the first subjective weight bin.
5. The method for calculating the contribution rate of the energy efficiency index system of the power distribution network according to claim 1, further comprising: and sequencing the contribution rates of all three-level indexes to obtain three-level indexes with large contribution rates, namely, the three-level indexes are main influence factors for influencing the energy efficiency level of the power distribution network.
6. The contribution rate calculation system of the energy efficiency index system of the power distribution network is applied to the power electronic power distribution network and is characterized by comprising an energy efficiency index system establishment unit, a subjective weight obtaining unit, an objective weight obtaining unit and a calculation unit;
the energy efficiency index system establishment unit is used for establishing an energy efficiency index system from a medium-voltage distribution network, a flexible transformer substation and a low-voltage distribution network, wherein the energy efficiency index system comprises at least three secondary indexes, and each secondary index comprises a plurality of tertiary indexes;
the subjective weight obtaining unit is used for calculating first subjective weights of all three-level indexes and two-level indexes by adopting an improved G1 method of Pignistic probability distance to obtain index subjective weights of all three-level indexes, and processing the index subjective weight of each three-level index to obtain second subjective weights corresponding to the three-level indexes;
the objective weight obtaining unit is used for calculating first objective weights of all three-level indexes by adopting an improved objective weighting method in a variation coefficient-independence method, and processing the first objective weights of the three-level indexes to obtain second objective weights of the three-level indexes;
the computing unit is used for obtaining the contribution rate of each three-level index by adopting weighting and fusion processing according to the second subjective weight and the second objective weight corresponding to each three-level index;
The subjective weight obtaining unit is specifically configured to:
s21, scoring all three-level indexes and two-level indexes in the energy efficiency index system to obtain a three-level index set and a two-level index set which are sequenced according to the magnitude of the sequence relation score, and scoring the relative importance degree of adjacent indexes in the three-level index set and the two-level index set;
s22, calculating first subjective weights of the secondary indexes and the tertiary indexes according to an index weight formula, and multiplying the first subjective weight of each secondary index by the first subjective weight of each tertiary index in the secondary indexes to obtain index subjective weights of all tertiary indexes;
wherein, the index weight formula is:
Figure FDA0004130828880000041
wherein omega is n First subjective weight of nth index in three-level index set or two-level index set, r i K is the index in the three-level index set or the two-level index set, k=n, n-1, …,2, n is the number of indexes, and n is more than or equal to 1;
s23 according to m i Focus of single propositionPignistic probability function calculates a corresponding vector beta for each subjective weight of the index i ；
S24, for each vector beta in the evidence fusion optimization model i Calculating to obtain subjective weight vectors corresponding to the three-level indexes, and forming a subjective weight vector set;
s25, eliminating index subjective weights corresponding to the minimum subjective weight vector in the subjective weight vector set, and taking the calculated average value of N-1 index subjective weights remaining in the three-level index as the second subjective weight of the three-level index;
wherein each three-level index comprises N index subjective weights, N is the number of the index subjective weights, and N is more than or equal to 2;
the objective weight obtaining unit is specifically configured to:
s31, performing dimensionalization and normalization treatment on all three-level indexes in the energy efficiency index system to obtain a matrix B, and obtaining complex correlation coefficients among indexes in the three-level indexes according to elements in the matrix B;
s32, calculating a first objective weight vector of each three-level index by adopting a coefficient of variation method for all three-level indexes in the energy efficiency index system;
s33, calculating a second objective weight vector of each three-level index by adopting an independent weight method for all three-level indexes in the energy efficiency index system according to the complex correlation coefficient;
s34, processing the first objective weight vector and the second objective weight vector by combining a variation coefficient method and an independence weight method to obtain the second objective weight of the three-level index.
7. A terminal device comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the contribution rate calculation method of the energy efficiency index system of the power distribution network according to any one of claims 1-5 according to the instructions in the program code.
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