CN117382471A - Charging power distribution method and device for multi-gun charging pile - Google Patents

Charging power distribution method and device for multi-gun charging pile Download PDF

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Publication number
CN117382471A
CN117382471A CN202311317467.4A CN202311317467A CN117382471A CN 117382471 A CN117382471 A CN 117382471A CN 202311317467 A CN202311317467 A CN 202311317467A CN 117382471 A CN117382471 A CN 117382471A
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Prior art keywords
charging
weight set
index
influence
charging power
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CN202311317467.4A
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CN117382471B (en
Inventor
李奕杰
吕晓荣
汪映辉
白少锋
黄玮
刘兴胜
肖峰
宋恒
姚腾飞
刘昭慧
姚阳
叶晨晖
张虔
叶萍
申庆祥
肖伟
耿群锋
张建伟
戴敏
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State Grid Corp of China SGCC
State Grid Jiangsu Electric Power Co Ltd
Nari Technology Co Ltd
State Grid Electric Power Research Institute
Taizhou Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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State Grid Corp of China SGCC
State Grid Jiangsu Electric Power Co Ltd
Nari Technology Co Ltd
State Grid Electric Power Research Institute
Taizhou Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/65—Monitoring or controlling charging stations involving identification of vehicles or their battery types
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/67—Controlling two or more charging stations

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Secondary Cells (AREA)

Abstract

The invention discloses a charging power distribution method and a charging power distribution device for a multi-gun charging pile, comprising the following steps: acquiring and analyzing charging power data of the charging pile, and giving index factors influencing the charging power data; the hierarchical relation and influence degree of index factors are fused, subjective weights of all index factors are determined, and a subjective weight set is formed; the informativity and fluctuation of the index factors are fused, objective weights of the index factors are determined, and an objective weight set is formed; optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set; and determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set. According to the invention, the influence of each index factor on the charging power is comprehensively considered from subjective and objective aspects, the flexible distribution of the charging power of each charging gun in each charging pile is completed, and the charging requirements of different users are met.

Description

Charging power distribution method and device for multi-gun charging pile
Technical Field
The invention belongs to the technical field of electric automobile charging, and relates to a charging power distribution method and device for a multi-gun charging pile.
Background
At present, the construction level of the electric automobile charging infrastructure is lower, and the phenomena of 'pile finding of the automobile' and 'pile like of the automobile' can often occur, so that inconvenience is caused to the user when the electric automobile is in travel, the user satisfaction degree when the electric automobile is charged is reduced, and the popularization of the electric automobile is not facilitated. The conventional charging mode distributes the same charging power to all the charged vehicles, and does not take into consideration the difference of charging demands of different vehicles and different users.
There is a study on reasonable distribution of charging power of each charging pile through variation of a power curve, as in patent CN111806285a, giving a method for distributing charging power of a common fast charging station with multiple charging piles, each charging pile of the common fast charging station including a plurality of charging guns, the method comprising: determining master and slave charging guns of the charging piles according to the gun inserting sequence, and determining the charging priority of each electric automobile according to the gun inserting sequence; acquiring a power battery acceptable power curve of each electric automobile connected to the charging gun; determining the charging power of the charging electric automobile and the maximum acceptable power of the power battery of each waiting electric automobile according to the acceptable power curve of the power battery; determining the residual power distributed by each electric vehicle waiting for allocation according to the maximum output power of the charging pile, the charging power of the electric vehicle waiting for allocation and the charging priority of the electric vehicle waiting for allocation; and determining the actual distributable charging power of each waiting electric automobile according to the distributed residual power of each waiting electric automobile and the maximum acceptable power of the power battery of each waiting electric automobile.
The patent CN116345477a provides a method for allocating load time sequence of an electric vehicle under the electric quantity type demand response, which comprises the following steps: based on the time sequence process from zero to full charge of the power battery of the electric automobile, configuring a charging characteristic curve and modeling the charging characteristic of the electric automobile; the electric quantity allocation of the electric automobile is subjected to allocation modeling, the charging vehicles are divided into three types according to the charging states, and the total electric quantity is allocated to different vehicles or charging piles in a field based on a classification mode and the allocation modeling; and calculating the electric quantity-load time sequence of the electric automobile based on different categories to obtain the power consumption constraint and the power allocation quantity of each category. The scheme aims to solve the problem that an operator of the electric vehicle charging station possibly faces to reach the upper limit of electricity purchasing or is limited to use electricity under the condition of peak electricity consumption, and further achieves the purpose of distributing the charging quantity of the charging vehicle in the station and guaranteeing normal operation of the charging station.
However, the judgment by the power curve often lacks sufficient data, and the implementation difficulty of the scheme is high, so that the output power of the charging pile cannot be flexibly distributed.
Therefore, how to distribute reasonable charging power for a charging vehicle to achieve orderly efficient charging is a problem to be solved by those skilled in the art.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a charging power distribution method and a charging power distribution device for a multi-gun charging pile, which comprehensively consider index factors such as vehicle type, battery charge state, expected charging time of a user and the like, determine the charging weight of each charging vehicle, complete reasonable and flexible distribution of the charging power of the charging vehicle based on the charging weight, further adjust the charging power of each vehicle and improve the satisfaction degree of the user and the utilization of electric power.
In a first aspect, the present invention provides a charging power distribution method for a multi-gun charging pile, including the steps of:
acquiring and analyzing charging power data of the charging pile, and giving index factors influencing the charging power data;
the hierarchical relation and influence degree of index factors are fused, subjective weights of all index factors are determined, and a subjective weight set is formed;
the informativity and fluctuation of the index factors are fused, objective weights of the index factors are determined, and an objective weight set is formed;
optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set;
and determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set.
Further, the index factors include a vehicle type, a battery state of charge, and a user desired charge duration.
Further, the hierarchical relationship and influence degree of the index factors are fused, subjective weights of the index factors are determined, and a subjective weight set is formed, and the method specifically comprises the following steps:
hierarchical division is carried out on each index factor, and a multi-order index scale matrix is formed according to the importance degree of the lower index factor on the upper index factor;
obtaining the influence degree of each index factor, and analyzing to obtain an influence degree matrix;
calculating matrix parameters of each index factor through an influence matrix;
in the multi-order index scale matrix, matching to obtain a scale value corresponding to each index factor;
comprehensively analyzing matrix parameters and scale values of each index factor, and determining corresponding subjective weights;
subjective weights of all index factors are collected to form a subjective weight set.
Further, comprehensively analyzing matrix parameters and scale values of each index factor to determine corresponding subjective weights, and specifically comprising the following steps:
wherein w is i As subjective weight of the ith index factor, f () is a function of the weight determined by the scale, s i1 ，s i2 ，s i3 ，s i4 The index factors are respectively the scales of the importance degree of the ith index factor compared with the index factors, H i To influence the influence degree of each index factor in the influence degree matrix on the ith index factor, K i The influence degree of each index factor on the ith index factor in the influence degree matrix is obtained.
Further, the subjective weights of the index factors are collected to form a subjective weight set, and the method specifically comprises the following steps:
W 1 ＝(w 1 ，w 2 ，w 3 ，w 4 )
wherein W is 1 Is a subjective weight set, w 1 Is the subjective weight of the vehicle type, w 2 Is the subjective weight of the battery type, w 3 Is the subjective weight of the charge state of the battery, w 4 Subjective weight for the duration of the charge desired by the user.
Further, the multi-order index scale matrix comprises scales of importance degrees of the index factors compared with each index factor; the influence degree matrix includes influence degrees of the respective index factors compared to each index factor.
Further, the multi-order index scale matrix is specifically expressed as:
wherein S is M Scale matrix for multi-order index s 11 S is a scale of the importance of the vehicle type itself compared to 12 S is a scale of importance of the type of vehicle compared to the type of battery 13 S is a scale of importance of the vehicle type compared to the state of charge of the battery 14 Is of the vehicle typeScale of importance degree of model s compared with charging time period expected by user 21 S is a scale of importance of the battery type compared with the vehicle type 22 S is a scale of the importance of the battery type itself compared to 23 S is a scale of importance of the battery type compared with the state of charge of the battery 24 S is a scale of importance of the battery type compared with the charging time period expected by the user 31 S is a scale of the importance of the state of charge of the battery compared with the type of vehicle 32 S is a scale of importance of the state of charge of the battery compared with the type of the battery 33 S is the scale of the importance of the battery state of charge per se compared with the importance of the battery state of charge 34 S is the scale of the importance degree of the charge state of the battery compared with the expected charge time length of the user 41 For a user to expect a scale of importance of the charge duration compared with the vehicle type s 42 For a user to expect a scale of how important the charge duration is compared to the battery type s 43 For a user to expect a scale of importance of the charge duration compared with the charge state of the battery, s 44 A scale of importance for the user's desired charge duration itself;
further, the influence matrix is specifically expressed as:
a∈[0，1]
wherein A is M To influence the degree matrix, a 11 A is the influence of the vehicle type per se 12 A is the influence degree of the type of the vehicle on the type of the battery 13 A is the influence degree of the vehicle type on the charge state of a battery 14 A, influencing the expected charging time length of a user for the type of the vehicle 21 A is the influence degree of the battery type on the vehicle type 22 A is the influence of the battery type per se 23 A is the influence degree of the battery type on the state of charge of the battery 24 A, the influence of the battery type on the expected charging time length of a user 31 A is the influence of the charge state of the battery on the type of the vehicle 32 A is the influence of the charge state of the battery on the battery type 33 Is electric powerThe influence of the charge state of the cell per se, a 34 A is the influence of the charge state of the battery on the expected charging time length of a user 41 A, the influence degree of the charging duration on the type of the vehicle is expected by a user 42 A, the influence degree of the charging time length on the battery type is expected by a user 43 A, the influence degree of the expected charging time on the charge state of the battery for a user 44 The degree of charge duration itself is expected for the user.
Further, the informativity and fluctuation of the index factors are fused, and the objective weight of each index factor is determined to form an objective weight set, which specifically comprises the following steps:
acquiring sample data of the influences of each index factor on the charging power to form a sample data matrix;
analyzing and giving out the occurrence proportion of each sample data, and obtaining a first initial weight matrix covering all the sample data through the entropy value of the occurrence proportion;
calculating the average value and standard deviation corresponding to each index factor through the sample data matrix respectively, and analyzing the correlation coefficient to obtain a second initial weight matrix;
and fusing the first initial weight matrix and the second initial weight matrix to obtain objective weights of all index factors, thereby forming an objective weight set.
The method comprises the steps of fusing a first initial weight matrix and a second initial weight matrix to obtain objective weights of all index factors, and forming an objective weight set, wherein the objective weight set is specifically expressed as follows:
W 2 ＝(α 1 W 21 +α 2 W 22 )
α 1 +α 2 ＝1
wherein W is 2 For objective weight set, W 21 For the first initial weight matrix, W 22 For the second initial weight matrix, σ i Is the standard deviation of the ith index in the sample data matrix, R i Correlation coefficient of ith index in sample data matrix, y ji For the impact value of the sample data matrix,for the mean value of the i-th index in the sample data matrix, < >>For the average value of the j-th sample in the sample data matrix, m is the total number of samples, α 1 For coefficients of the first initial weight matrix, α 2 Is the coefficient of the second initial weight matrix.
Further, the sample data matrix comprises the influence value of each index factor in each sample on the charging power;
the first initial weight matrix is specifically expressed as:
wherein W is 21 For the first initial weight matrix, m is the total number of sample sets, r j1 For the occurrence ratio of the value of the influence of the vehicle type on the charging power in the jth sample, r j2 R is the occurrence proportion of the value of the influence of the battery type in the jth sample on the charging power j3 R is the occurrence proportion of the value of the influence of the charge state of the battery in the jth sample on the charging power j4 The appearance proportion of the impact value of the charging time length on the charging power is expected for the user in the j-th sample.
Further, the sample data matrix is specifically expressed as:
wherein Y is M For a matrix of sample data, m is for a sample setTotal, y 11 For the value of the influence of the vehicle type in sample 1 on the charging power, y 12 For the value of the influence of the battery type in sample 1 on the charging power, y 13 The value of the influence of the charge state of the battery in the 1 st sample on the charging power, y 14 The value of the influence of the expected charging time length of the user on the charging power in the 1 st sample, y m1 For the value of the influence of the vehicle type in the mth sample on the charging power, y m2 For the value of the influence of the battery type in the mth sample on the charging power, y m3 Is the value of the influence of the charge state of the battery in the mth sample on the charging power, y m4 The value of the influence of the charging time period on the charging power is expected for the user in the mth sample.
Further, the comprehensive weight set is obtained by optimizing the subjective weight set and the objective weight set, and the method specifically comprises the following steps:
based on the subjective weight set and the objective weight set, determining subjective weight and objective weight of each index factor;
constructing an optimizing function representing the weight difference, and carrying out maximized analysis on the optimizing function to obtain coefficients of a subjective weight set and an objective weight set;
and giving a comprehensive weight set fused with the subjective weight and the objective weight.
Further, the optimizing function specifically represents:
F(p，q)＝(pW 1 +qW 2 )(y 1 +y 2 +y 3 +y 4 )
p 2 +q 2 ＝1
wherein p is the coefficient of the subjective weight set, q is the coefficient of the objective weight set, F (p, q) is the optimizing function for p, q, W 1 For subjective weight set, W 2 For objective weight set, y 1 U is the value of the influence of the vehicle type on the charging power 2 U is the value of the influence of the battery type on the charging power 3 Is the value of the influence of the charge state of the battery on the charging power, y 4 The value of the influence of the charging time period on the charging power is expected for the user.
Further, according to the charging requirement of the charging pile, and through the comprehensive weight set, the power distribution of each charging gun is determined, and the method specifically comprises the following steps:
acquiring and comparing the charging requirement and the available power of the charging pile;
combining the comprehensive weight set, analyzing the power of each charging pile when the charging requirement exceeds the available power;
the power distribution ratio for each charging gun is given.
In a second aspect, the present invention further provides a charging power analysis device for a multi-gun charging pile, and a charging power distribution method using the multi-gun charging pile, including:
the acquisition unit is used for acquiring and analyzing the charging power data of the charging pile and giving out index factors influencing the charging power data;
the weight analysis unit is used for fusing the hierarchical relation and influence degree of the index factors, determining the subjective weight of each index factor to form a subjective weight set, fusing the informativeness and fluctuation of the index factors, determining the objective weight of each index factor to form an objective weight set, and optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set;
and the power distribution unit is used for determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set.
The invention provides a charging power distribution method and a charging power distribution device for a multi-gun charging pile, which at least comprise the following beneficial effects:
the method comprises the steps of comprehensively considering index factors such as the type of the vehicle, the type of the battery, the charge state of the battery, the expected charge time of a user and the like, determining the charge weight of each charging vehicle, completing reasonable and flexible distribution of the charge power of the charging vehicle based on the charge weight, further adjusting the charge power of each vehicle, and improving the satisfaction degree of the user and the utilization of electric power.
Drawings
Fig. 1 is a schematic flow chart of a charging power distribution method of a multi-gun charging pile provided by the invention;
FIG. 2 is a schematic flow chart of forming a subjective weight set according to the present invention;
FIG. 3 is a schematic flow chart of forming an objective weight set according to the present invention;
FIG. 4 is a schematic flow chart of acquiring a comprehensive weight set according to the present invention;
FIG. 5 is a schematic flow chart of determining the power distribution of each charging gun according to the present invention;
fig. 6 is a schematic diagram of a charging power distribution device for a multi-gun charging pile according to the present invention.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments. It will be apparent that the described embodiments are only some, but not all, embodiments of the 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 terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, the "plurality" generally includes at least two.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a product or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such product or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a commodity or device comprising such element.
The traditional charging mode distributes the same charging power for all charging vehicles, the difference of charging demands among different vehicles and different users is not considered, and the output power of the charging pile cannot be flexibly distributed.
Aiming at the problems that the output power of the charging pile cannot be flexibly distributed and the like, the weight of each index factor affecting the charging requirement to the output power of the charging pile needs to be comprehensively considered, so that the charging power of each charging pile is reasonably distributed, the charging power of each vehicle can be reasonably regulated, thereby realizing orderly efficient charging and improving the satisfaction degree of users.
As shown in fig. 1, the invention provides a charging power distribution method for a multi-gun charging pile, comprising the following steps:
acquiring and analyzing charging power data of the charging pile, and giving index factors influencing the charging power data;
the hierarchical relation and influence degree of index factors are fused, subjective weights of all index factors are determined, and a subjective weight set is formed;
the informativity and fluctuation of the index factors are fused, objective weights of the index factors are determined, and an objective weight set is formed;
optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set;
and determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set.
The index factors include the type of vehicle, the type of battery, the state of charge of the battery, and the duration of charge desired by the user.
In a certain embodiment, for each index factor, investigation and collection of sample data are performed for the charging power influence, and a sample data matrix of m sample sets is obtained, which is specifically expressed as:
wherein Y is M For a matrix of sample data, m is the total number of sample sets, y 11 For the value of the influence of the vehicle type in sample 1 on the charging power, y 12 For the value of the influence of the battery type in sample 1 on the charging power, y 13 Is the firstThe value of the influence of the state of charge of the battery on the charging power in 1 sample, y 14 The value of the influence of the expected charging time length of the user on the charging power in the 1 st sample, y m1 For the value of the influence of the vehicle type in the mth sample on the charging power, y m2 For the value of the influence of the battery type in the mth sample on the charging power, y m3 Is the value of the influence of the charge state of the battery in the mth sample on the charging power, y m4 The value of the influence of the charging time period on the charging power is expected for the user in the mth sample.
The subjective weight determination can be carried out by carrying out fusion judgment from the hierarchical relation among all index factors and the influence degree among the index factors, physicochemical and layering the target decision problem, decomposing all relevant factors into a plurality of layers from high to low according to different attributes, and finally forming a subjective weight set consisting of four index factor subjective weights.
As shown in fig. 2, the hierarchical relationship and influence degree of index factors are fused, and subjective weights of the index factors are determined to form a subjective weight set, which specifically includes the following steps:
hierarchical division is carried out on each index factor, and a multi-order index scale matrix is formed according to the importance degree of the lower index factor on the upper index factor;
the multi-order index scale matrix is specifically expressed as:
wherein S is M Scale matrix for multi-order index s 11 S is a scale of the importance of the vehicle type itself compared to 12 S is a scale of importance of the type of vehicle compared to the type of battery 13 S is a scale of importance of the vehicle type compared to the state of charge of the battery 14 S is a scale of importance of the vehicle type compared with the charge duration desired by the user 21 S is a scale of importance of the battery type compared with the vehicle type 22 S is a scale of the importance of the battery type itself compared to 23 For battery type and battery chargeScale of state versus importance, s 24 S is a scale of importance of the battery type compared with the charging time period expected by the user 31 S is a scale of the importance of the state of charge of the battery compared with the type of vehicle 32 S is a scale of importance of the state of charge of the battery compared with the type of the battery 33 S is the scale of the importance of the battery state of charge per se compared with the importance of the battery state of charge 34 S is the scale of the importance degree of the charge state of the battery compared with the expected charge time length of the user 41 For a user to expect a scale of importance of the charge duration compared with the vehicle type s 42 For a user to expect a scale of how important the charge duration is compared to the battery type s 43 For a user to expect a scale of importance of the charge duration compared with the charge state of the battery, s 44 A scale of importance of the charge duration itself is desired for the user.
The relative importance degree of the index factor of the layer to a certain index factor of the previous layer can be generally assigned by nine-level scale method as shown in table 1. The specific scale values are determined according to different application scenarios, and the invention is not limited to the specific values.
Table 1 nine-level scale table
Scale with a scale bar Meaning of
1 Indicating that the two index factors have the same importance compared with each other
3 The former is slightly more important than the latter in terms of two index factors
5 The former is obviously important than the latter in comparison with two index factors
7 The former is extremely important than the latter in representing two index factors
9 The former is more important than the latter in terms of two index factors
2，4，6，8 Intermediate value representing the above-mentioned adjacency judgment
Reciprocal of 1 to 9 Representing the importance of the comparison of the exchange order of the corresponding two index factors
Obtaining the influence degree of each index factor, and analyzing to obtain an influence degree matrix;
the value of influence degree can be analyzed by a four-level scale to analyze the influence degree between the factors. That is, as shown in table 2, 0, 1, 2, and 3 indicate that there is no influence between the two index factors, the influence is small, the influence is general, and the influence is large, respectively.
Table 2 four-level gauge
Scale with a scale bar Meaning of
0 Has no influence on
1 Less influence
2 Influence in general
3 Has a larger influence
And then carrying out normalization processing on each numerical value in the four-level table to obtain an influence degree matrix, wherein the influence degree matrix is specifically expressed as follows:
a∈[0，1]
wherein A is M To influence the degree matrix, a 11 A is the influence of the vehicle type per se 12 A is the influence degree of the type of the vehicle on the type of the battery 13 A is the influence degree of the vehicle type on the charge state of a battery 14 A, influencing the expected charging time length of a user for the type of the vehicle 21 A is the influence degree of the battery type on the vehicle type 22 A is the influence of the battery type per se 23 A is the influence degree of the battery type on the state of charge of the battery 24 A, the influence of the battery type on the expected charging time length of a user 31 A is the influence of the charge state of the battery on the type of the vehicle 32 A is the influence of the charge state of the battery on the battery type 33 A is the influence of the charge state of the battery per se 34 A is the influence of the charge state of the battery on the expected charging time length of a user 41 A, the influence degree of the charging duration on the type of the vehicle is expected by a user 42 A, the influence degree of the charging time length on the battery type is expected by a user 43 A, the influence degree of the expected charging time on the charge state of the battery for a user 44 The degree of charge duration itself is expected for the user.
The specific value of the influence degree is determined according to different application scenes, and the invention does not limit the specific value further.
Calculating matrix parameters of each index factor through an influence degree matrix, wherein the matrix parameters comprise influence degree and influenced degree of each index, and the influence degree and the influenced degree of each index can be obtained through comprehensive calculation of numerical values of each index in the influence degree matrix; the method of the comprehensive calculation is not particularly limited, and may be an average value, a median, or a value indicating a trend may be set after normalization processing.
In the multi-order index scale matrix, matching to obtain a scale value corresponding to each index factor;
matrix parameters and scale values of each index factor are comprehensively analyzed, and corresponding subjective weights are determined, wherein the method specifically comprises the following steps:
wherein w is i As subjective weight of the ith index factor, f () is a function of the weight determined by the scale, s i1 ，s i2 ，s i3 ，s i4 The index factors are respectively the scales of the importance degree of the ith index factor compared with the index factors, H i To influence the influence degree of each index factor in the influence degree matrix on the ith index factor, K i The influence degree of each index factor in the influence degree matrix on the ith index factor is obtained;
f () is a function of the scale-determined weights that takes into account the relative importance of the individual index factors. The function type of f () is not particularly limited, and may be an average value, a median, or a value representing a trend may be given after normalization processing.
Subjective weights of all index factors are collected to form a subjective weight set,
W 1 ＝(w 1 ，w 2 ，w 3 ，w 4 )
wherein W is 1 Is a subjective weight set, w 1 Is the subjective weight of the vehicle type, w 2 Is the subjective weight of the battery type, w 3 Is the subjective weight of the charge state of the battery, w 4 Subjective weight for the duration of the charge desired by the user.
The objective weight can be determined by considering the informativity and the fluctuation of each index factor in the sample data, so as to form an objective weight set.
As shown in fig. 3, the information degree and the volatility of the index factors are fused, and the objective weights of the index factors are determined to form an objective weight set, which specifically includes:
acquiring sample data of the influences of each index factor on the charging power to form a sample data matrix; the sample data matrix is obtained mainly by investigation and collection of sample data on the charging power influence aiming at each index factor. Under different application scenarios, the impact values of different index factors on the charging power are also different, and specific values are not further limited.
Wherein Y is M For a matrix of sample data, m is the total number of sample sets, y 11 For the value of the influence of the vehicle type in sample 1 on the charging power, y 12 For the value of the influence of the battery type in sample 1 on the charging power, y 13 The value of the influence of the charge state of the battery in the 1 st sample on the charging power, y 14 The value of the influence of the expected charging time length of the user on the charging power in the 1 st sample, y m1 For the value of the influence of the vehicle type in the mth sample on the charging power, y m2 For the value of the influence of the battery type in the mth sample on the charging power, y m3 Is the value of the influence of the charge state of the battery in the mth sample on the charging power, y m4 The value of the influence of the charging time period on the charging power is expected for the user in the mth sample.
Analyzing and giving out the occurrence proportion of each sample data, and obtaining a first initial weight matrix covering all the sample data through the entropy value of the occurrence proportion;
the first initial weight matrix is specifically expressed as:
wherein W is 21 For the first initial weight matrix, m is the total number of sample sets, r j1 For the occurrence ratio of the value of the influence of the vehicle type on the charging power in the jth sample, r j2 R is the occurrence proportion of the value of the influence of the battery type in the jth sample on the charging power j3 R is the occurrence proportion of the value of the influence of the charge state of the battery in the jth sample on the charging power j4 The appearance proportion of the impact value of the charging time length on the charging power is expected for the user in the j-th sample.
Calculating the average value and standard deviation corresponding to each index factor through the sample data matrix respectively, and analyzing the correlation coefficient to obtain a second initial weight matrix;
the first initial weight matrix and the second initial weight matrix are fused to obtain objective weights of all index factors, and an objective weight set is formed, specifically expressed as:
W 2 ＝(α 1 W 21 +α 2 W 22 )
α 1 +α 2 ＝1
wherein W is 2 For objective weight set, W 21 For the first initial weight matrix, W 22 For the second initial weight matrix, σ i Is the standard deviation of the ith index in the sample data matrix, R i Correlation of the ith index in a sample data matrixCoefficient, y ji For the impact value of the sample data matrix,for the mean value of the i-th index in the sample data matrix, < >>For the average value of the j-th sample in the sample data matrix, m is the total number of samples, α 1 For coefficients of the first initial weight matrix, α 2 Is the coefficient of the second initial weight matrix.
As shown in fig. 4, the comprehensive weight set is obtained by optimizing the subjective weight set and the objective weight set, which specifically comprises the following steps:
based on the subjective weight set and the objective weight set, determining subjective weight and objective weight of each index factor;
constructing an optimizing function representing the weight difference, and carrying out maximized analysis on the optimizing function to obtain coefficients of a subjective weight set and an objective weight set;
the optimizing function specifically represents:
F(p，q)＝(pW 1 +qW 2 )(y 1 +y 2 +y 3 +y 4 )
p 2 +q 2 ＝1
wherein p is the coefficient of the subjective weight set, q is the coefficient of the objective weight set, F (p, q) is the optimizing function for p, q, W 1 For subjective weight set, W 2 For objective weight set, y 1 For the value of the influence of the vehicle type on the charging power, y 2 For the value of the influence of the battery type on the charging power, y 3 Is the value of the influence of the charge state of the battery on the charging power, y 4 The value of the influence of the charging time period on the charging power is expected for the user.
And giving a comprehensive weight set fused with the subjective weight and the objective weight.
The maximization of the optimizing function can also be understood as the analysis of the profit function. Taking the coefficient p of the subjective weight set and the coefficient q of the objective weight set as optimizing parameters of the profit function, and maximizing the profit function.
As shown in fig. 5, according to the charging requirement of the charging pile, and through the comprehensive weight set, the power distribution of each charging gun is determined, which specifically includes the following steps:
acquiring and comparing the charging requirement and the available power of the charging pile;
combining the comprehensive weight set, analyzing the power of each charging pile when the charging requirement exceeds the available power;
the power distribution ratio for each charging gun is given.
After comparing the charging requirement of the charging pile and the available power, if the charging requirement (namely the total power required by the charging vehicle) is smaller than the available power of the charging pile, charging is directly carried out according to the charging requirement;
if the charging requirement (i.e. the total power required for charging the vehicle is greater than the available power of the charging piles), the power distribution proportion of each charging pile is carried out by means of the given comprehensive weight set.
In a specific application scenario, the distribution ratio of each vehicle after the subjective weight, the objective weight and the comprehensive weight are respectively given, and the distribution ratio is shown in table 3. The power distribution proportion of the vehicle A, the vehicle B and the vehicle C is more reasonable given under the comprehensive weight.
TABLE 3 distribution ratio of respective vehicles in various modes
As shown in fig. 6, the present invention further provides a charging power analysis device for a multi-gun charging pile, and a charging power distribution method for the multi-gun charging pile, which includes:
the acquisition unit is used for acquiring and analyzing the charging power data of the charging pile and giving out index factors influencing the charging power data;
the weight analysis unit is used for fusing the hierarchical relation and influence degree of the index factors, determining the subjective weight of each index factor to form a subjective weight set, fusing the informativeness and fluctuation of the index factors, determining the objective weight of each index factor to form an objective weight set, and optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set;
and the power distribution unit is used for determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set.
The apparatus of the present invention may be a computer device in this embodiment, and perform the method of the present invention described above. The computer device may include one or more processing devices, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device may also include any storage resources for storing any kind of information such as code, settings, data, etc. For example, and without limitation, the storage resources may include any one or more of the following combinations: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage resource may store information using any technology. Further, any storage resource may provide volatile or non-volatile retention of information. Further, any storage resource may represent a fixed or removable component of a computer device. In one case, the computer device may perform any of the operations of the associated instructions when the processing device executes the associated instructions stored in any storage resource or combination of storage resources. The computer device also includes one or more drive mechanisms for interacting with any storage resources, such as a hard disk drive mechanism, an optical disk drive mechanism, and the like.
The computer device may also include an input/output module (I/O) for receiving various inputs (via the input device) and for providing various outputs (via the output device). One particular output mechanism may include a presentation device and an associated Graphical User Interface (GUI). In other embodiments, input/output modules (I/O), input devices, and output devices may not be included, but may be implemented as a single computer device in a network. The computer device may also include one or more network interfaces for exchanging data with other devices via one or more communication links. One or more communication buses couple the above-described components together.
The communication link may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link may comprise any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.
The beneficial effects obtained by the device are consistent with those obtained by the method, and the embodiments of the present disclosure are not repeated.
The invention provides a charging power distribution method and a charging power distribution device for a multi-gun charging pile, which at least comprise the following beneficial effects:
the method comprises the steps of comprehensively considering index factors such as the type of the vehicle, the type of the battery, the charge state of the battery, the expected charge time of a user and the like, determining the charge weight of each charging vehicle, completing reasonable and flexible distribution of the charge power of the charging vehicle based on the charge weight, further adjusting the charge power of each vehicle, and improving the satisfaction degree of the user and the utilization of electric power.
In the several embodiments provided herein, it should be understood that the disclosed apparatus 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. In addition, 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 elements, or may be an electrical, mechanical, or other form of connection.
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 elements may be selected according to actual needs to achieve the objectives of the embodiments herein.
In addition, each functional unit in the embodiments herein 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 solutions herein are essentially or portions contributing to the prior art, or all or portions of the technical solutions may be embodied in the form of a software product stored in a storage medium, including several instructions to cause 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 methods described in the embodiments herein. 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.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims (10)

1. The charging power distribution method of the multi-gun charging pile is characterized by comprising the following steps of:
acquiring and analyzing charging power data of the charging pile, and giving index factors influencing the charging power data;
the hierarchical relation and influence degree of index factors are fused, subjective weights of all index factors are determined, and a subjective weight set is formed;
the informativity and fluctuation of the index factors are fused, objective weights of the index factors are determined, and an objective weight set is formed;
optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set;
and determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set.
2. The method for distributing charging power for a multi-gun charging pile according to claim 1, wherein the index factors include a vehicle type, a battery state of charge, and a user desired charging period.
3. The method for distributing charging power of a multi-gun charging pile according to claim 2, wherein the method for distributing charging power of the multi-gun charging pile is characterized by integrating the hierarchical relationship and the influence degree of index factors, determining subjective weights of the index factors, and forming a subjective weight set, and specifically comprises the following steps:
hierarchical division is carried out on each index factor, and a multi-order index scale matrix is formed according to the importance degree of the lower index factor on the upper index factor;
obtaining the influence degree of each index factor, and analyzing to obtain an influence degree matrix;
calculating matrix parameters of each index factor through an influence matrix;
in the multi-order index scale matrix, matching to obtain a scale value corresponding to each index factor;
comprehensively analyzing matrix parameters and scale values of each index factor, and determining corresponding subjective weights;
subjective weights of all index factors are collected to form a subjective weight set.
4. A method of charging power distribution for a multi-gun charging pile according to claim 3, wherein the multi-level index scale matrix includes a scale of importance of each index factor compared to each index factor; the influence degree matrix includes influence degrees of the respective index factors compared to each index factor.
5. The method for distributing charging power of a multi-gun charging pile according to claim 2, wherein the method for distributing charging power of the multi-gun charging pile is characterized by integrating informativity and fluctuation of index factors, determining objective weights of the index factors, and forming an objective weight set, and specifically comprises the following steps:
acquiring sample data of the influences of each index factor on the charging power to form a sample data matrix;
analyzing and giving out the occurrence proportion of each sample data, and obtaining a first initial weight matrix covering all the sample data through the entropy value of the occurrence proportion;
calculating the average value and standard deviation corresponding to each index factor through the sample data matrix respectively, and analyzing the correlation coefficient to obtain a second initial weight matrix;
and fusing the first initial weight matrix and the second initial weight matrix to obtain objective weights of all index factors, and forming an objective weight set.
6. The method for distributing charging power to a multi-gun charging pile according to claim 5, wherein the sample data matrix comprises a value of an influence of each index factor in each sample on the charging power;
the first initial weight matrix is specifically expressed as:
wherein W is 21 For the first initial weight matrix, m is the total number of sample sets, r j1 For the occurrence ratio of the value of the influence of the vehicle type on the charging power in the jth sample, r j2 R is the occurrence proportion of the value of the influence of the battery type in the jth sample on the charging power j3 R is the occurrence proportion of the value of the influence of the charge state of the battery in the jth sample on the charging power j4 The appearance proportion of the impact value of the charging time length on the charging power is expected for the user in the j-th sample.
7. The method for distributing charging power of a multi-gun charging pile according to claim 1, wherein the comprehensive weight set is obtained by optimizing a subjective weight set and an objective weight set, comprising the steps of:
based on the subjective weight set and the objective weight set, determining subjective weight and objective weight of each index factor;
constructing an optimizing function representing the weight difference, and carrying out maximized analysis on the optimizing function to obtain coefficients of a subjective weight set and an objective weight set;
and combining the coefficients to give a comprehensive weight set fused with subjective weights and objective weights.
8. The method for distributing charging power for a multi-gun charging pile according to claim 7, wherein the optimizing function specifically represents:
F(p，q)＝(pW 1 +qW 2 )(y 1 +y 2 +y 3 +y 4 )
p 2 +q 2 ＝1
wherein p is the coefficient of the subjective weight set, q is the coefficient of the objective weight set, F (p, q) is the optimizing function for p, q, W 1 For subjective weight set, W 2 For objective weight set, y 1 U is the value of the influence of the vehicle type on the charging power 2 U is the value of the influence of the battery type on the charging power 3 Is the value of the influence of the charge state of the battery on the charging power, y 4 The value of the influence of the charging time period on the charging power is expected for the user.
9. The method for distributing charging power of a multi-gun charging pile according to claim 1, wherein the power distribution to each charging gun is determined by integrating the weight set according to the charging requirement of the charging pile, and the method specifically comprises the following steps:
acquiring and comparing the charging requirement and the available power of the charging pile;
combining the comprehensive weight set, analyzing the power of each charging pile when the charging requirement exceeds the available power;
the power distribution ratio for each charging gun is given.
10. A charging power analysis device for a multi-gun charging pile, characterized in that a charging power distribution method for a multi-gun charging pile according to any one of claims 1 to 9 is adopted, comprising:
the acquisition unit is used for acquiring and analyzing the charging power data of the charging pile and giving out index factors influencing the charging power data;
the weight analysis unit is used for fusing the hierarchical relation and influence degree of the index factors, determining the subjective weight of each index factor to form a subjective weight set, fusing the informativeness and fluctuation of the index factors, determining the objective weight of each index factor to form an objective weight set, and optimizing through the subjective weight set and the objective weight set to obtain a comprehensive weight set;
and the power distribution unit is used for determining the power distribution of each charging gun according to the charging requirement of the charging pile and through the comprehensive weight set.
CN202311317467.4A 2023-10-12 2023-10-12 Charging power distribution method and device for multi-gun charging pile Active CN117382471B (en)

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