CN-122022302-A - Multi-charging-station cluster economic and efficient mutual aid method and system considering network loss of power distribution network

CN122022302ACN 122022302 ACN122022302 ACN 122022302ACN-122022302-A

Abstract

The invention discloses an economic and efficient mutual-aid method and system for a multi-charging-station cluster considering power distribution network loss. The local energy management system of each charging station acquires photovoltaic output, charging load prediction data, day-ahead electricity price, cost function and local equipment constraint parameters, optimizes and solves the photovoltaic output, the charging load prediction data, the day-ahead electricity price, the cost function and the local equipment constraint parameters by taking the minimum running cost as a target, obtains exchange power with a power grid and uploads the exchange power to the cluster energy management system. The cluster energy management system determines pairing priority by constructing a weight matrix based on the exchange power and with the minimum network loss of the distribution network as a target to form an optimal mutual-aid charging station pair, calculates the mutual-aid power and updates the exchange power and the weight matrix. And iteratively executing pairing, calculating and updating processes until the purchase/sale power of all the paired charging stations is zero, forming a pairing set containing the optimal mutual-aid charging station pair identification and the mutual-aid purchase/sale power, and realizing economic and efficient mutual-aid of the multi-charging station cluster.

Inventors

CHEN CHAOQIANG
LI YUJIA
ZHAO ZIJUN
HUANG JIYUAN
PENG QINGWEN
CHEN YUANYANG
YANG XIAODAN
DENG YAZHI
Lu xinxing
WU JUN

Assignees

国网湖南省电力有限公司长沙供电分公司
国网湖南省电力有限公司
国家电网有限公司

Dates

Publication Date: 20260512
Application Date: 20260123

Claims (10)

1. A multi-charging station cluster economic and efficient mutual-aid method considering network loss of a power distribution network is characterized by comprising the following steps: the method comprises the steps of S1, obtaining photovoltaic output prediction data, charging load prediction data, electricity price data, cost functions and local equipment constraint parameters in a preset period by a local energy management system of each charging station, carrying out optimization solving with the running cost of the charging station as a target based on the obtained data, solving to obtain exchange power of the charging station and a power grid, and uploading the exchange power to a charging station cluster energy management system; S2, the charging station cluster energy management system performs mutual-matching pairing among the charging stations based on the exchange power of each charging station and the power grid by taking the minimum network loss of the power distribution network as a target, constructs a weight matrix among a plurality of charging stations to determine the priority of the mutual-matching pairing, and forms an optimal mutual-matching charging station pair according to the weight matrix; And S3, calculating the mutual power between the charging stations according to the exchange power between the charging stations and the power grid in the optimal mutual power charging station pair, updating the exchange power and the weight matrix between the charging stations and the power grid according to the mutual power, and iteratively executing the pairing, calculating and updating processes in S2-S3 until the electricity purchasing or selling power of all paired charging stations is zero, and ending the iteration to form a pairing set, wherein the pairing set comprises the optimal mutual power charging station pair identification and the mutual power purchasing/selling between the optimal mutual power charging station pair.
2. The method according to claim 1, wherein in the step S1, the running cost of the charging station comprises the cost of purchasing electricity of a power grid, the transaction cost generated by mutual compensation among charging stations and the degradation cost related to energy storage, and the local equipment constraint parameters comprise the charging station power balance constraint, the charging station energy exchange constraint, the charging station energy storage constraint and the charging station electric vehicle EV constraint.
3. The method according to claim 2, wherein in the step S1, the optimization solution is performed with the objective of minimizing the running cost of the charging station, and the objective function is: ; In the formula, Is the collection of charging stations, superscript A charging station serial number; to optimize the duration; Is the time step length, superscript Is a time sequence number; Is a charging station Collection of medium energy storage, subscript Is the energy storage serial number, subscript 、、、 Respectively representing electricity purchasing, electricity selling, charging and discharging, wherein the first row represents electricity purchasing and selling cost with a power grid, And (3) with Respectively is The purchase/sale price of electricity released by the power grid at the moment, And (3) with Charging stations respectively At the position of The second row represents the trade charge generated by the mutual compensation between the charging stations, In order to make the price of each other, And (3) with Charging stations respectively With charging station The third row represents the energy storage related degradation cost, To store energy Is used to determine the degradation cost function of (1), And (3) with Charging stations respectively Energy storage The charge/discharge power at the moment of time, Is a charging station Middle energy storage Is used for the charge and discharge efficiency of the battery.
4. A method according to claim 3, wherein in step S1, the constraint of the optimization solution comprises: Charging station power balance constraint, the expression is: ; In the formula, The EV sequence is an electric automobile EV sequence; Is a charging station EV set of (a); Is a charging station At the position of Photovoltaic output at moment; And (3) with Charging stations respectively First, the Vehicle EV in Charging/discharging power at the moment; Is a charging station Middle (f) Charging and discharging efficiency of the vehicle EV; Is a charging station At the position of Load at moment; The energy exchange constraint of the charging station is expressed as follows: ; In the formula, And (3) with Charging stations respectively Purchase/sell electric power limit; And (3) with Charging stations respectively With charging station A medium purchase/sell power limit; And (3) with Limiting charging stations respectively With electric network, charging station 0-1 Variable used for purchasing electricity at the same time; The energy storage constraint of the charging station is expressed as follows: ; In the formula, And (3) with Charging stations respectively Energy storage At the position of And The remaining energy at the moment; And (3) with Charging stations respectively Middle energy storage Upper/lower limit of the remaining energy of (c); And (3) with Charging stations respectively Energy storage At the position of A time charge/discharge power limit; To limit charging station Energy storage At the position of 0-1 Variable used for simultaneous charging and discharging at the moment; charging station EV constraints, the expression is: ; In the formula, And (3) with Charging stations respectively At the position of And The remaining energy at the moment; And (3) with Charging stations respectively Middle (f) The remaining energy upper/lower limit value of the vehicle EV; And (3) with Charging stations respectively First, the Vehicle EV in A time charge/discharge power limit; To limit charging station First, the Vehicle EV in 0-1 Variable used for simultaneous charging and discharging at the moment; Is a charging station Scheduling the duration of the EV; Is a charging station Middle (f) Target remaining energy value to be satisfied when the vehicle EV is offline.
5. The method according to claim 4, wherein in the step S2, if the product of the exchange power between any two charging stations and the power grid is equal to or greater than 0, the power states are determined to be the same, and the possibility of mutual pairing between the two charging stations is eliminated.
6. The method according to claim 5, wherein in step S2, specifically comprising: s2.1, constructing a pairing weight matrix: Because the distribution of the charging stations has regional property, the electrical distances between the charging stations suitable for mutual adjustment are usually relatively close, so the electrical distances are used as weight coefficients to indirectly reflect the network loss of the power distribution network caused by the mutual adjustment of the power between the charging stations, and the charging stations are connected by establishing a two-dimensional Cartesian coordinate system Weighting coefficient between Expressed as: ; In the formula, Indicating a charging station Is defined by the access location coordinates of (a); Indicating a charging station Is defined by the access location coordinates of (a); Is a network loss coefficient, and is self-connection weight Is set to a sufficiently large number ; Since power interchange is only possible between two charging stations which exchange power differently from the grid, intermediate variables are introduced for this purpose: ; In the formula, Is a charging station At the position of Exchange power with the power grid at any time, when charging station The surplus and the deficiency of the power are respectively And Thus excluding mismatched charging station pairs by: ; In the formula, And Charging stations respectively And charging station At the position of The power exchanged with the power grid at the moment and the final weight matrix are as follows: ; s2.2, determining an optimal mutual-aid charging station pair: there is always a pair of Are all minimum values in the respective rows and columns, namely the current optimal mutual-aid charging station pair : ; In the formula, Is a real number set; And (3) with 、 And (3) with Respectively is a weight matrix Is the first of (2) And (3) with Line 1 And (3) with Columns.
7. The method of claim 6, wherein the step S3 of updating the exchange power and weight matrix of the charging station and the power grid according to the mutual power comprises determining that any charging station in the optimal pair of mutual charging stations is in power balance if the exchange power of the charging station and the power grid is 0, and setting the row/column elements in the corresponding weight matrix to be a sufficiently large number 。
8. The method according to claim 7, wherein in step S3, specifically comprising: s3.1, mutual power determination between charging stations: ; In the above, the upper and lower marks The optimal pairing result value of the charging station sequence in S2.2 is respectively and physically defined with the upper and lower marks Is similar to the situation of (2); S3.2, exchanging power update between the charging station and the power grid: ; S3.3, updating a weight matrix: ; S3.4 iteration stop condition: 。
9. a multi-charging station cluster economic and efficient mutual-aid system considering network loss of a power distribution network, comprising: At least two charging stations, each configured with a local energy management system; the local energy management system of each charging station is used for acquiring photovoltaic output prediction data, charging load prediction data, electricity price data, cost functions and local equipment constraint parameters in a preset period, carrying out optimization solution with the minimum running cost of the charging station as a target based on the acquired data, solving to obtain the exchange power of the charging station and a power grid, and uploading the exchange power to the charging station cluster energy management system; The cluster energy management system is in communication connection with the local energy management system of each charging station and is used for carrying out mutual-aid pairing among the charging stations based on the exchange power of each charging station and the power grid, taking the minimum network loss of the power distribution network as a target, constructing a weight matrix among a plurality of charging stations to determine the priority of the mutual-aid pairing, and forming an optimal mutual-aid charging station pair according to the weight matrix; the system enables economical and efficient mutual utilization of a multi-charging station cluster based on the method of any one of claims 1-5.
10. The multi-charging station cluster economic and efficient mutual-aid system accounting for power distribution network losses according to claim 9, further comprising a low-voltage distribution network for enabling power transfer of the charging station clusters.

Description

Multi-charging-station cluster economic and efficient mutual aid method and system considering network loss of power distribution network Technical Field The invention relates to the field of collaborative economic operation of a plurality of charging stations in an area, in particular to an economic and efficient mutual aid method and system for a plurality of charging station clusters considering network loss of a power distribution network. Background With the rapid development of the electric automobile industry and the deep advancement of the 'two carbon' target, 2024 nationwide electric automobiles (ELECTRIC VEHICLES, EV) hold up to 3140 tens of thousands, the accumulation of charging infrastructures reaches 1235 tens of thousands, and the explosive growth of charging demands puts higher demands on the running economy of charging stations. At present, most charging stations operate independently as a main, and single-station operation optimization is realized through cooperative operation of resources such as photovoltaic and energy storage in the charging stations. However, the single-station autonomous mode only can consider the optimal local operation cost, and the power complementary characteristics among the charging stations are not fully utilized, so that the overall operation cost of the charging station cluster still has a large optimization space. If an efficient power-assisted mechanism can be established between the charging stations, the charging station operating costs will be significantly reduced. However, the existing mutual-aid strategy focuses on power balance and economic optimization, network loss of the power distribution network in the mutual-aid process of a plurality of charging stations is not fully considered, and the plurality of charging stations are in scattered access in the power distribution network, so that the network loss directly affects actual power transmission efficiency and final economic benefit. Therefore, how to realize the cooperative and economic operation of the multi-charging-station cluster becomes a key problem to be solved in the current charging-station cluster operation. Disclosure of Invention The invention aims to provide an economic and efficient mutual-aid method for a multi-charging-station cluster considering power distribution network loss, which can realize the collaborative and economic operation of the multi-charging-station cluster. In order to solve the technical problems, the invention adopts the following technical scheme: In a first aspect, the present application provides a method for economically and efficiently mutually supplementing a plurality of charging station clusters in consideration of power distribution network loss, including: the method comprises the steps of S1, obtaining photovoltaic output prediction data, charging load prediction data, electricity price data, cost functions and local equipment constraint parameters in a preset period by a local energy management system of each charging station, carrying out optimization solving with the running cost of the charging station as a target based on the obtained data, solving to obtain exchange power of the charging station and a power grid, and uploading the exchange power to a charging station cluster energy management system; S2, the charging station cluster energy management system performs mutual-matching pairing among the charging stations based on the exchange power of each charging station and the power grid by taking the minimum network loss of the power distribution network as a target, constructs a weight matrix among a plurality of charging stations to determine the priority of the mutual-matching pairing, and forms an optimal mutual-matching charging station pair according to the weight matrix; And S3, calculating the mutual power between the charging stations according to the exchange power between the charging stations and the power grid in the optimal mutual power charging station pair, updating the exchange power and the weight matrix between the charging stations and the power grid according to the mutual power, and iteratively executing the pairing, calculating and updating processes in S2-S3 until the electricity purchasing or selling power of all paired charging stations is zero, and ending the iteration to form a pairing set, wherein the pairing set comprises the optimal mutual power charging station pair identification and the mutual power purchasing/selling between the optimal mutual power charging station pair. In some possible implementation manners, in the step S1, the running cost of the charging station includes the purchase and selling cost of the power grid, the transaction cost generated by mutual compensation between charging stations and the degradation cost related to energy storage, and the local equipment constraint parameters include the charging station power balance constraint, the charging station energy exchange constraint, the cha