Power allocation terminal intelligent power distribution method based on improved entropy weight method

Abstract

The invention discloses a power allocation terminal intelligent power distribution method based on an improved entropy weight method. The method comprises the following steps: acquiring electric vehicle charging information as a charging weight index; constructing an evaluation index original matrix according to the charging information; calculating information entropy redundancy of each piece of charging information; calculating an evaluation value of the electric vehicle according to the information entropy redundancy; and correcting the evaluation value and calculating the power distribution weight of the electric vehicle. According to the technical scheme, the limited available charging power is reasonably distributed to each charging pile by using the entropy weight method, intelligent splitting and allocation of the charging power are realized, reasonable allocation of the charging power is realized on the basis of considering the priority difference between the users, the influence of human subjective factors is avoided, the user priority difference is considered, and the user experience is improved. And the specific distribution scheme of the charging power is more reasonable.

Description

Technical Field

[0001] The present invention relates to the field of electrical engineering technology, and in particular to an intelligent power allocation method for a power allocation terminal based on an improved entropy weight method. Background Art

[0002] Due to the rapid development of science and technology, the penetration rate of flexible and controllable resources in modern power systems has increased year by year, making the regulation of power systems flexible and complex. Among them, electric vehicles, as an environmentally friendly means of transportation, have good energy saving, environmental protection and emission reduction potential. Their number has increased rapidly in recent years and will become the main means of transportation for people in the near future. The considerable number of electric vehicles has brought huge regulation potential, and therefore has become a very important flexible and controllable resource in the power system. Therefore, responding to the regulation of the superior system in the form of charging stations or charging pile clusters can better maintain the stability of the power grid operation and improve its operating status.

[0003] When the superior system regulates the distributed local flexible resources, it will issue regulation instructions to each subordinate resource set according to its own needs or transformer load conditions. The instruction contains the total power that the local resource set should provide, thereby assisting the system to complete frequency regulation, peak regulation, maintain power balance, etc. However, for the local resource set, how to reasonably distribute the total power to each power equipment is still a problem to be studied. Therefore, the present invention focuses on the power allocation terminal of the charging station, and proposes a method for intelligent allocation of charging power to achieve reasonable allocation of the total power among each charging pile. [Power allocation control strategy of photovoltaic electric vehicle charging station based on load forecasting] also carried out research on power distribution, but it mainly cuts in from the aspects of charging station operation mode, bus voltage and load forecasting, and does not fully consider the interests of electric vehicle users.

[0004] Data shows that existing technologies pay less attention to the interests of electric vehicle users and focus more on optimizing system operation, thus ignoring the needs of individual users to a certain extent. With the popularization of electric vehicles and the development of technology, personalized charging services that take into account user differences have become imperative. In addition, when considering the needs of charging users, some existing technologies rely on expert evaluation or experience to determine the weights, which leads to excessive subjectivity and lack of objectivity and fairness. Due to the development of charging services and their commercialization trend, few technologies can take into account the impact of priority differences such as member users on the allocation of charging power.

[0005] Chinese patent document CN109353245A discloses a "method for automatic power distribution of electric vehicle charging clusters". It adopts a cluster control system, an information transmission network, an intelligent charging pile and an automatic power distribution system. The present invention includes the following main steps: monitoring the charging power of the intelligent charging piles belonging to the charging cluster; dynamically dividing the charging areas within the cluster, and allocating the regional power in real time according to the principle of giving priority to fast charging needs; when the charging power in the slow charging area is insufficient, the time for the intelligent charging piles in the slow charging area to start charging is set according to the charging needs of the electric vehicle, and the power distribution of the charging cluster is further adjusted and optimized. The above technical solution is aimed at optimizing the operation of the system and ignores the needs of individual users. Summary of the invention

[0006] The present invention mainly solves the technical problem that the original technical solution focuses on the optimization of system operation while ignoring the needs of individual users. It provides an intelligent power allocation method for power allocation terminal based on the improved entropy weight method. By considering the limited total available power of the control instructions issued by the superior virtual power plant and the high priority of the designated charging gun, the available power of the remaining charging piles is calculated, and the information entropy of each indicator is calculated according to the charging information such as the charge state, residence time, and charging time of the electric vehicle. The limited available charging power is reasonably allocated to each charging pile using the entropy weight method, and the intelligent splitting and allocation of the charging power is realized. The rational allocation of the charging power is realized on the basis of taking into account the priority differences among users, avoiding the influence of human subjective factors and taking into account the differences in user priorities, so that the specific allocation plan of the charging power is more reasonable.

[0007] The above technical problem of the present invention is mainly solved by the following technical solution: The present invention comprises the following steps:

[0008] S1 obtains the electric vehicle charging information as a charging weight indicator;

[0009] S2 constructs the original matrix of evaluation indicators based on charging information;

[0010] S3 calculates the information entropy redundancy of each charging information;

[0011] S4 calculates the evaluation value of the electric vehicle according to the information entropy redundancy;

[0012] S5 corrects the evaluation value and calculates the electric vehicle power distribution weight.

[0013] The power dispatch terminal first collects various charging information of electric vehicle users in the station, summarizes it into the original matrix of evaluation indicators, and normalizes it. Secondly, the information entropy and information entropy redundancy of each charging information indicator are calculated. Then, the indicator weights of each charging information are calculated, and the evaluation value of each electric vehicle is calculated based on this. Finally, the correction factor representing the priority is introduced to improve the entropy weight method, so that the total power can be reasonably allocated to each charging pile.

[0014] Preferably, the step S1 specifically includes that the electric vehicle going to the charging station for charging has its own charging information, including the arrival time Estimated duration of stay State of charge at arrival Total electricity demand E n , Charging time After the electric vehicle is connected to the charging pile, the charging information will be summarized in the power allocation terminal through communication technology to calculate the charging weight index of each user, which is also the basis for power allocation.

[0015] Preferably, the step S2 specifically includes aggregating the charging information of all vehicles into a matrix, which is called the original matrix A of evaluation indicators. Assuming that there are n electric vehicles in total and each electric vehicle has m charging information, the original matrix A of evaluation indicators has n rows and m columns.

[0016]

[0017] In the formula, x ij is the specific value of the j-th charging information of electric vehicle i.

[0018] Preferably, each data of the charging information is normalized to convert it from an absolute value to a relative value.

[0019]

[0020] In the formula, y ij is the normalized value of the jth charging information of electric vehicle i. Since the data of charging information are in various forms and the units are not uniform, it will affect the determination of the final weight. Therefore, it is necessary to normalize these data and convert them from absolute values ​​to relative values.

[0021] Preferably, the step S3 specifically includes calculating the information entropy of each charging information, calculating the proportion p of electric vehicle i in the jth charging information ij

[0022]

[0023] The information entropy of each charging information is calculated according to the proportion pij of each electric vehicle in the jth charging information.

[0024]

[0025]

[0026] In the formula, e j is the information entropy of the j-th charging information.

[0027] As a preferred method, the information entropy redundancy of each charging information is calculated.

[0028] r j =1-e j

[0029] In the formula, r j is the information entropy redundancy of the j-th charging information.

[0030] Preferably, the step S4 specifically includes calculating the index weight w of the jth charging information according to the information entropy redundancy of each charging information. j :

[0031]

[0032] Based on this indicator weight, the evaluation value of each electric vehicle can be further calculated.

[0033]

[0034] In the formula, c i is the evaluation value of electric vehicle i.

[0035] As a preferred embodiment, the step S5 of correcting the evaluation value specifically includes taking into account the difference in priority of users such as members, and introducing a correction factor v i To improve the entropy weight method, the evaluation value of electric vehicle i after correction is as follows:

[0036] d i =v i c i i=1,2,...,n

[0037] Where, d i is the corrected evaluation value of electric vehicle i, v i A correction factor is introduced to characterize the user priority. This takes into account the difference in user priority, making the technical solution more suitable for the rapid commercialization of charging services today.

[0038] Preferably, the power allocation weights of the electric vehicles are calculated according to the corrected evaluation values ​​of the electric vehicles:

[0039]

[0040] Based on this, the charging power P allocated to electric vehicle i i CH for:

[0041] P i CH =Q i P CS i=1,2,...,n

[0042] Where P CS It is the total power of the charging station, which is affected by the transformer load connected to the charging station or the control instructions of the superior system.

[0043] The beneficial effects of the present invention are as follows: by considering the limited total available power of the control instructions issued by the superior virtual power plant and the high priority of the designated charging gun, the available power of the remaining charging piles is calculated, and the information entropy of each indicator is calculated according to the charging information such as the charge state, residence time, and charging time of the electric vehicle. The limited available charging power is reasonably allocated to each charging pile using the entropy weight method, and the intelligent splitting and allocation of the charging power is realized. The rational allocation of the charging power is realized on the basis of taking into account the priority differences among users, avoiding the influence of human subjective factors and taking into account the differences in user priorities, so that the specific allocation plan of the charging power is more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0046] Embodiment: This embodiment is a method for intelligent power allocation of power allocation terminal based on improved entropy weight method, such as Figure 1 As shown, the following steps are included:

[0047] First, an electric car going to a charging station for charging has its own charging information, such as its arrival time. Estimated duration of stay State of charge at arrival Total electricity demand E n , Charging time After the electric vehicle is connected to the charging pile, this information will be summarized in the power allocation terminal through communication technology, which will be used as the charging weight index for each user and the basis for power allocation.

[0048] The charging information of all vehicles is summarized in a matrix, which is called the original evaluation index matrix A. Assuming there are n electric vehicles and each electric vehicle has m charging information, the original evaluation index matrix A has n rows and m columns.

[0049]

[0050] In the formula, x ij is the specific value of the j-th charging information of electric vehicle i.

[0051] Since the data of charging information are in various forms and the units are not uniform, it will affect the determination of the final weight. Therefore, it is necessary to normalize these data and convert them from absolute values ​​to relative values.

[0052]

[0053] In the formula, y ij is the normalized value of the j-th charging information of electric vehicle i.

[0054] Secondly, it is necessary to calculate the proportion p of electric vehicle i in the jth charging information ij .

[0055]

[0056] According to the proportion p of each electric vehicle in the jth charging information ij The information entropy of each charging information can be calculated.

[0057]

[0058]

[0059] In the formula, e j is the information entropy of the j-th charging information.

[0060] Then it is necessary to calculate the information entropy redundancy of each charging information.

[0061] r j =1-e j (6)

[0062] In the formula, r j is the information entropy redundancy of the j-th charging information.

[0063] Therefore, the index weight w of the jth charging information can be calculated according to the information entropy redundancy of each charging information: j :

[0064]

[0065] Based on this indicator weight, the evaluation value of each electric vehicle can be further calculated.

[0066]

[0067] In the formula, c i is the evaluation value of electric vehicle i.

[0068] In order to take into account the priority differences of members and other users, it is necessary to introduce a correction factor v i To improve the entropy weight method, the evaluation value of electric vehicle i after correction is as follows:

[0069] d i =v i c i i=1,2,...,n (9)

[0070] Where, d i is the corrected evaluation value of electric vehicle i, v i is a correction factor that represents the user priority.

[0071] Finally, the power allocation weights of each electric vehicle are calculated based on the corrected evaluation values:

[0072]

[0073] Based on this, the charging power P allocated to electric vehicle i i CH for:

[0074] P i CH =Q i P CS i=1,2,...,n (11)

[0075] Where P CS It is the total power of the charging station, which is affected by the transformer load connected to the charging station or the control instructions of the superior system.

[0076] In summary, the power dispatch terminal first collects various charging information of electric vehicle users in the station, summarizes it into the original matrix of evaluation indicators, and normalizes it. Secondly, the information entropy and information entropy redundancy of each charging information indicator are calculated. Then, the indicator weights of each charging information are calculated, and the evaluation value of each electric vehicle is calculated based on this. Finally, the correction factor representing the priority is introduced to improve the entropy weight method, so that the total power can be reasonably allocated to each charging pile.

Claims

1. A method for intelligent power allocation of power allocation terminals based on improved entropy weight method, characterized in that: The following steps are involved: S1 obtains the electric vehicle charging information as a charging weight indicator; S2 constructs the original matrix of evaluation indicators based on charging information; S3 calculates the information entropy redundancy of each charging information; S4 calculates the evaluation value of the electric vehicle according to the information entropy redundancy; S5 corrects the evaluation value and calculates the electric vehicle power distribution weight.

2. According to claim 1, a method for intelligent power allocation of power allocation terminals based on improved entropy weight method is characterized in that: The step S1 specifically includes that the electric vehicle going to the charging station for charging has its own charging information, including the arrival time Estimated duration of stay State of charge at arrival Total electricity demand E n , Charging time After the electric vehicle is connected to the charging pile, the charging information is summarized in the power allocation terminal as an indicator for calculating the charging weight of each user.

3. According to claim 1 or 2, a method for intelligent power allocation of power allocation terminals based on improved entropy weight method, characterized in that: The step S2 specifically includes aggregating the charging information of all vehicles into a matrix, which is called the original evaluation index matrix A. Assuming that there are n electric vehicles in total and each electric vehicle has m charging information, the original evaluation index matrix A has n rows and m columns. In the formula, x ij is the specific value of the j-th charging information of electric vehicle i.

4. According to claim 3, a method for intelligent power allocation of power allocation terminals based on improved entropy weight method is characterized in that: Normalize the various data of charging information and convert them from absolute values ​​to relative values. In the formula, y ij is the normalized value of the j-th charging information of electric vehicle i.

5. According to claim 1, a method for intelligent power allocation of power allocation terminals based on improved entropy weight method, characterized in that: The step S3 specifically includes calculating the information entropy of each charging information, calculating the proportion p of electric vehicle i in the jth charging information ij The information entropy of each charging information is calculated according to the proportion pij of each electric vehicle in the jth charging information. In the formula, e j is the information entropy of the j-th charging information.

6. According to claim 5, a method for intelligent power allocation of power allocation terminals based on improved entropy weight method is characterized in that: Calculate the information entropy redundancy of each charging information, r j ＝1-e j In the formula, r j is the information entropy redundancy of the j-th charging information.

7. According to claim 1, a method for intelligent power allocation of power allocation terminals based on improved entropy weight method, characterized in that: The step S4 specifically includes calculating the index weight w of the jth charging information according to the information entropy redundancy of each charging information. j : Based on this indicator weight, the evaluation value of each electric vehicle can be further calculated. In the formula, c i is the evaluation value of electric vehicle i.

8. The method for intelligent power allocation of power allocation terminals based on improved entropy weight method according to claim 7 is characterized in that: The step S5 of correcting the evaluation value specifically includes taking into account the difference in priority of members and other users, and introducing a correction factor v i To improve the entropy weight method, the evaluation value of electric vehicle i after correction is as follows: d i =v i c i i=1,2,...,n Where, d i is the corrected evaluation value of electric vehicle i, v i is a correction factor that represents the user priority.

9. The method for intelligent power allocation of power allocation terminals based on improved entropy weight method according to claim 7 or 8, characterized in that: Calculate the power allocation weights of each electric vehicle based on the corrected evaluation value: Based on this, the charging power P allocated to electric vehicle i i CH for: P i CH =Q i P CS i=1,2,...,n Where P CS It is the total power of the charging station, which is affected by the transformer load connected to the charging station or the control instructions of the upper system.

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