EV-SOP configuration parameter optimization method and system considering dynamic interconnection feasible region

Abstract

The invention discloses an EV-SOP configuration parameter optimization method considering a dynamic interconnection feasible region. The method comprises the following steps: determining that the structure of an EV-SOP comprises two access ends; the access end comprises an alternating current port for grid connection; obtaining the working state of the access end according to the structure of the EV-SOP, and establishing an EV-SOP constraint according to the working state; constructing a road topology according to the coupling relationship between the traffic network and the power distribution network, and obtaining the shortest feasible path distance and path information between any two traffic network nodes according to the road topology in combination with a Floyd algorithm; carrying out iterative optimization of preset times by combining a double-layer model with a particle swarm optimization algorithm, wherein the double-layer model considers EV-SOP constraints; the double-layer model comprises an upper-layer model and a lower-layer model. The invention also discloses an EV-SOP configuration parameter optimization system considering the dynamic interconnection feasible region.

Description

Technical Field

[0001] The present invention relates to the field of power system parameter configuration, and particularly to a method and system for optimizing the configuration parameters of EV-SOP considering the dynamic interconnection feasible region. Background Art

[0002] EV-SOP (Energy-Stored Vehicle with SOP, mobile energy storage type intelligent soft switch) can optimize the power flow distribution during the normal operation of the distribution network by integrating the energy storage capacity of the energy storage emergency power vehicle and the flexible interconnection characteristics of the intelligent soft switch, and can provide effective emergency power supply when the distribution network fails, enhancing the reliability of load power supply.

[0003] Related scholars have carried out some research on the capacity configuration of EV-SOP to optimize problems such as capacity redundancy, long-term idle, and high investment costs caused by conventional configuration methods. However, EV-SOP is usually scheduled in the transportation network, and the connection range of its AC ports is limited by the length of the traffic path. Existing EV-SOP capacity configuration methods do not consider this factor, resulting in the difficulty of matching the interconnection length of the EV-SOP AC ports with the connection paths of the distribution network nodes in the configuration results of existing methods, that is, there are deviations in the configuration results based on existing methods and it is difficult to apply them to actual scenarios. Therefore, in the parameter configuration of EV-SOP, it is necessary to consider the limitation of the interconnection length of the EV-SOP AC ports on the connection range, which is of great significance for the application of EV-SOP in actual scenarios and reducing the usage cost of EV-SOP during its entire life cycle, as well as improving the economy and reliability of the distribution network operation.

[0004] In summary, there is an urgent need for a new technical solution to solve the technical problem of how to perform more accurate EV-SOP parameter configuration. Summary of the Invention

[0005] The present invention provides a method and system for optimizing the configuration parameters of EV-SOP considering the dynamic interconnection feasible region to solve the technical problem of how to perform more accurate EV-SOP parameter configuration.

[0006] To achieve the above object, the present invention provides a method for optimizing the configuration parameters of EV-SOP considering the dynamic interconnection feasible region, including:

[0007] Determine that the structure of the EV-SOP includes two access ends; the access ends include AC ports for grid connection;

[0008] Obtain the working state of the access ends according to the structure of the EV-SOP, and establish EV-SOP constraints according to the working state;

[0009] Construct the road topology according to the coupling relationship between the transportation network and the distribution network, and obtain the shortest feasible path distance and path information between any two transportation network nodes based on the road topology combined with the Floyd algorithm;

[0010] Perform iterative optimization for a preset number of times through a two-layer model combined with the particle swarm optimization algorithm. The two-layer model considers the EV-SOP constraints. The two-layer model includes an upper-layer model and a lower-layer model. The iterative optimization includes:

[0011] Generate the optimization of configuration parameters through the upper-layer model. The configuration parameters include the basic parameters of EV-SOP and the interconnection length. Obtain the EV-SOP interconnection feasible region according to the interconnection length, the shortest feasible path distance, and the path information;

[0012] Calculate the first cost through the lower-layer model according to the configuration parameters and the EV-SOP interconnection feasible region. The first cost includes the total operating cost after the distribution network is connected to the EV-SOP;

[0013] Compare the first cost obtained this time with the first cost obtained in the previous time through the upper-layer model, and save the configuration parameters with the lower first cost.

[0014] Preferably, the iterative optimization for a preset number of times includes:

[0015] The basic parameters include the number of EV-SOPs, the grid-connected port capacity, and the energy storage battery power;

[0016] In the first iterative optimization, when the upper-layer model generates the optimization of EV-SOP configuration parameters, it generates random configuration parameters. After the lower-layer model calculates the first cost based on the random configuration parameters, the upper-layer model saves the random configuration parameters.

[0017] Preferably, obtain the working state of the access end according to the structure of the EV-SOP, and establish the EV-SOP constraints according to the working state, including:

[0018] Set the set of EV-SOPs as E = {e m |m = 1, 2, 3, …, M}, and the sets of normal and fault conditions of the distribution network are T 1 = {t x |t x ∈[t 0 , t 0 +Δt]} and T 2 = {t y |t y ∈[t 0 , t 0 +Δt]};

[0019] Introduce the 0-1 variables τ m,t 、τ αm,t and τ β m, used to describe whether the EV - SOP is grid - connected and the working states of the two access ends of the EV - SOP; if e m is in the grid - connected state, then τ m,t = 1, otherwise τ m,t = 0; if τ α m,t takes the value of 1, it means that e m is in the double - end interconnection state, otherwise τ α m,t is 0; if τ β m,t takes the value of 1, it means that e m is in the single - side access state, otherwise τ β m,t is 0; among them, the double - end interconnection state includes the state where the two access ends of the EV - SOP are connected to different distribution network substations, and the single - side access state includes the state where the two access ends of the EV - SOP are connected to the same distribution network substation;

[0020] Then the EV - SOP constraints include:

[0021] Since the two access ends of the EV - SOP are in either the double - end interconnection state or the single - side access state under the grid - connected state, there is:

[0022]

[0023] The EV - SOP needs to meet its own working - state constraints under the grid - connected state, including:

[0024]

[0025] Among them, P n,m,t sop represents the active power transmitted by the nth port among all ports of e m at time t; Q n,m,t sop represents the reactive power transmitted by the nth port among all ports of e m at time t; P n,m,t sop,Loss represents the loss of the nth port among all ports of e m at time t; η represents the port efficiency of the EV - SOP; S n,m sop represents the rated apparent power of the nth port among all ports of e m at time t; P m,t b represents the output power of the energy storage battery of e m at time t; P max b and Pmin b respectively represent the upper and lower limits of the charging and discharging power of the energy storage battery; N and N DC represent all ports and the DC-DC port of a single EV-SOP; all ports of a single EV-SOP include two access ends and the DC-DC port of a single EV-SOP;

[0026] Introduce the 0-1 variable C m,t b,ch and C m,t b,dis When e m the energy storage battery is in the charging state at time t, C m,t b,ch takes the value of 1, otherwise 0; when e m the energy storage battery is in the discharging state at time t, C m,t b,dis takes the value of 1, otherwise 0; since the EV-SOP cannot charge and discharge simultaneously in the grid-connected state, there is:

[0027]

[0028] To ensure the long-term connection of the distribution network under normal conditions and still have electricity for subsequent dispatching after the fault condition ends, there is:

[0029]

[0030] where S oc,0 represents the initial state of charge of the energy storage battery.

[0031] Preferably, constructing the road topology according to the coupling relationship between the transportation network and the distribution network includes:

[0032] For a distribution network with n nodes, introduce the road topology adjacency matrix D = (d ij ) n×n to describe the distances between nodes in the transportation network coupled with the distribution network; where i and j represent transportation network nodes; Z is the set of combinations of the two end nodes of the actual road; s ij is the actual distance of the road, in meters; then there is:

[0033]

[0034] where INF indicates that there is no directly connected road between transportation network nodes;

[0035] According to d ij the road topology D can be obtained:

[0036]

[0037] Preferably, the shortest feasible path distance and path information between any two traffic network nodes obtained according to the road topology and the Floyd algorithm include:

[0038] Calculate the shortest feasible path distance between any two traffic network nodes according to the road topology D and the Floyd algorithm, and introduce the matrix H=(h ij ) n×n Describe the shortest feasible path distance between any two traffic network nodes, and introduce P=(p ij ) n×n Describe the path information corresponding to the shortest feasible path distance between any two traffic network nodes in the matrix H; H and P can be expressed as:

[0039]

[0040] Among them, h ij Represents the shortest feasible path distance from traffic network node i to node j, and the H matrix is a symmetric matrix, that is, the shortest path distances between two nodes are mutual; p ij The value is a path sequence, including the numbers of all nodes passed on the shortest feasible path from node i to node j; the - in P represents the distance from the node itself to itself, which is meaningless.

[0041] Preferably, the EV-SOP interconnection feasible region obtained according to the interconnection length, the shortest feasible path distance and the path information includes:

[0042] Assume that h uv Is the element in the u-th row and v-th column of H, and set the scheduling feasible region of EV-SOP as R={d x |x = 1, 2, 3, …, X}, and set the scheduling feasible region of the distribution network under the double-end interconnection state as R α ={d xα |xα = 1, 2, 3, …, XA}; where A represents the interconnection length; then the EV-SOP interconnection feasible region can be expressed as:

[0043]

[0044] Taking Δt as the time span, under normal and fault conditions of the distribution network, the scheduling positions of EV-SOP can be expressed as And ψ x,m,ty , both of which are 0-1 variables, When the value is 1, it represents that e m Is scheduled to position d x During the t x Period; when ψ x,m,ty When the value is 1, it represents that e m Is scheduled to position d y During the t x; d x is a value within the scheduling feasible region R of EV - SOP;

[0045] Since EV - SOP can only be connected to one location within a single time period Δt, there is a scheduling location constraint:

[0046]

[0047] When EV - SOP is in a double - ended interconnected state, the scheduling location is restricted by the scheduling feasible region, including:

[0048]

[0049] Preferably, the upper - layer model includes:

[0050] The objective of the upper - layer model is to minimize the total economic operation cost of the distribution network; the total economic operation cost of the distribution network includes the configuration cost of EV - SOP and the total operation cost of the distribution network after connecting EV - SOP;

[0051] The upper - layer model includes an upper - layer objective function, which can be expressed as:

[0052] minF conf = C E1 + C E2 + C E3

[0053] where C E1 represents the equipment investment cost of EV - SOP; C E2 represents the operation cost of the distribution network under normal conditions; C E3 represents the operation cost of the distribution network under fault conditions;

[0054] The equipment investment cost C of EV - SOP E1 includes:

[0055] C E1 = c sop S sop N AC + c b S b + c a A

[0056] where c sop and c b represent the unit - capacity investment costs of EV - SOP and energy storage battery respectively; N AC represents the number of AC ports of EV - SOP; S sop represents the capacity of EV - SOP to be configured; S b represents the capacity of the energy storage battery to be configured; c aIt represents the investment cost per unit length of the EV-SOP cable, and A represents the length of the EV-SOP interconnection to be configured;

[0057] The operating cost C of the distribution network under normal conditions E2 includes:

[0058]

[0059] Among them, ω α represents the network line loss cost coefficient; I represents the line current value of the distribution network; r represents the line resistance value of the distribution network; ε e represents the operating cost coefficient of the EV-SOP; y e represents the service life of the EV-SOP;

[0060] The operating cost C of the distribution network under fault conditions E3 includes:

[0061]

[0062] Among them, ω β represents the power outage cost coefficient, L p and L respectively represent the values corresponding to the load prediction curve and the actual load value. Preferably, the upper-layer model further includes upper-layer constraints, including:

[0063] N e,min ≤N e ≤N e,max

[0064] S e,min ≤S e ≤S e,max

[0065] S b,min ≤S b ≤S b,max

[0066] P b,min ≤P b ≤P b,max

[0067] S e ≤S b

[0068] A min <A<A max

[0069] Among them, N e 、N e,max and N e,min respectively represent the number of EV-SOPs to be configured and the upper and lower limits; S e 、S e,max and S e,minrespectively represent the capacity and upper and lower limits of the EV-SOP ports to be configured; S b 、S b,max and S b,min respectively represent the capacity and upper and lower limits of the energy storage battery to be configured; P b 、P b,max and P b,min respectively represent the rated power and upper and lower limits of the energy storage battery to be configured; A, A max and A min respectively represent the interconnection length and upper and lower limits of the EV-SOP to be configured.

[0070] Preferably, the lower-layer model includes:

[0071] The objective function F of the economic operation scheduling of the EV-SOP under normal operating conditions of the distribution network 1 , can be expressed as:

[0072]

[0073] Among them, I line represents the current of the distribution network line; r line represents the resistance of the distribution network line; ω α represents the loss cost coefficient; T represents the access time of the EV-SOP;

[0074] The objective function F of the emergency power supply scheduling of the EV-SOP under fault conditions of the distribution network 2 , can be expressed as:

[0075]

[0076] Among them, L represents the actual load borne by the distribution network; L P represents the corresponding value of the load prediction curve; ω β represents the loss of power economic loss coefficient;

[0077] In the lower-layer model, the Distflow model is used to model the power flow of the distribution network, and the single commodity flow is used to constrain the radial network, and the solution is obtained through Gurobi.

[0078] The present invention also provides an EV-SOP configuration parameter optimization system considering the dynamic interconnection feasible region for the method of the present invention. The system includes a first module, a second module, a third module, and a fourth module;

[0079] The first module is used to determine that the structure of the EV-SOP includes two access ends; the access end includes an AC port for grid connection;

[0080] The second module is used to obtain the working state of the access end according to the structure of the EV-SOP, and establish EV-SOP constraints according to the working state;

[0081] The third module is used to construct a road topology according to the coupling relationship between the transportation network and the distribution network, and obtain the shortest feasible path distance and path information between any two transportation network nodes according to the road topology combined with the Floyd algorithm;

[0082] The fourth module is used to perform iterative optimization for a preset number of times through a two-layer model combined with the particle swarm optimization algorithm. The two-layer model considers the EV-SOP constraint. The two-layer model includes an upper-layer model and a lower-layer model. The iterative optimization includes:

[0083] Optimizing and generating configuration parameters through the upper-layer model. The configuration parameters include the basic parameters of EV-SOP and the interconnection length; obtaining the EV-SOP interconnection feasible region according to the interconnection length, the shortest feasible path distance, and the path information;

[0084] Calculating the first cost through the lower-layer model according to the configuration parameters and the EV-SOP interconnection feasible region. The first cost includes the total operating cost of the distribution network after connecting to the EV-SOP;

[0085] Comparing the first cost obtained this time with the first cost obtained in the previous time through the upper-layer model, and selecting the configuration parameters with a lower first cost for storage.

[0086] The present invention has the following beneficial effects:

[0087] The method for optimizing the EV-SOP configuration parameters considering the dynamic interconnection feasible region of the present invention obtains the working state of the access end according to the structure of the EV-SOP, and establishes the EV-SOP constraint according to the working state of the access end, providing the basic constraint of the EV-SOP for the subsequent optimization of the configuration parameters, and ensuring the controllability and accuracy of the optimization process. Constructing a road topology according to the coupling relationship between the transportation network and the distribution network, and obtaining the shortest feasible path distance and path information between any two transportation network nodes according to the road topology combined with the Floyd algorithm, so that the method clarifies the shortest feasible path distance and path information between any two transportation network nodes, providing a data basis for the subsequent calculation of the interconnection feasible region. Performing iterative optimization for a preset number of times through a two-layer model combined with the particle swarm optimization algorithm, comprehensively considering the EV-SOP interconnection feasible region, the configuration cost of the EV-SOP, and the operating costs of the distribution network under normal operation and fault conditions, enabling the method to reduce the total economic cost during the whole life cycle of the EV-SOP, having important practical significance for the operation optimization of the distribution network, and at the same time realizing the optimization of the configuration parameters, considering the limitation of the connection range by the interconnection length of the AC ports of the EV-SOP, enabling the EV-SOP to be applied in actual scenarios. This method can improve the economy and reliability of the distribution network operation.

[0088] The EV-SOP configuration parameter optimization system considering the dynamic interconnection feasible region of the present invention is used for the method of the present invention and has the same beneficial effects as the method of the present invention.

[0089] In addition to the purposes, features and advantages described above, the present invention has other purposes, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] The drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0091] Figure 1 is a schematic diagram of the EV-SOP structure of the preferred embodiment of the present invention.

[0092] Figure 2 is a schematic diagram of the overall process of the preferred embodiment of the present invention.

[0093] Figure 3 is a schematic diagram of the iterative optimization process of the preferred embodiment of the present invention

[0094] Figure 4 is a schematic diagram of the coupling situation of a partial traffic network - distribution network in a certain county urban area of the preferred embodiment of the present invention.

[0095] Figure 5 is a schematic diagram of the voltage deviation of the configuration scheme obtained by the method of the present invention in the preferred embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0096] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways defined and covered by the claims.

[0097] Referring to Figure 1 , in the preferred embodiment of the present invention, the EV-SOP architecture includes at least three SOP ports. The EV-SOP includes a bidirectional DC-DC module and two AC-DC modules. One end of the bidirectional DC-DC module is connected to the energy storage battery, and the other end shares the DC side with the two AC-DC modules. The AC side of the AC-DC module is connected to the busbar of the load node, so as to realize flexible energy interaction between the energy storage battery and the load node. The EV-SOP can not only actively support the power supply of multiple substation areas at the same time, but also transfer energy from other substation areas after its own energy is consumed. In addition, multiple AC ports can also be connected to a busbar at the same time to realize the expansion support of single-point load power supply.

[0098] Referring to Figure 2, in a preferred embodiment of the present invention, a method for optimizing the configuration parameters of EV-SOP considering the dynamic interconnection feasible region is provided, including:

[0099] S1. Determine that the structure of the EV-SOP includes two access ends; the access ends include AC ports for grid connection.

[0100] S2. Obtain the working states of the access ends according to the structure of the EV-SOP, and establish EV-SOP constraints based on the working states. Specifically, it includes:

[0101] Set the set of EV-SOPs as E = {e m |m = 1, 2, 3, …, M}, and the sets of normal and fault conditions of the distribution network are T 1 = {t x |t x ∈[t 0 , t 0 +Δt]} and T 2 = {t y |t y ∈[t 0 , t 0 +Δt]};

[0102] Introduce 0-1 variables τ m,t , τ α m,t and τ β m, to describe whether the EV-SOP is grid-connected and the working states of the two access ends of the EV-SOP; if e m is in the grid-connected state, then τ m,t = 1, otherwise τ m,t = 0; if τ α m,t takes the value of 1, it means that e m is in the double-end interconnection state, otherwise τ α m,t is 0; if τ β m,t takes the value of 1, it means that e m is in the single-side access state, otherwise τ β m,t is 0; among them, the double-end interconnection state includes the state where the two access ends of the EV-SOP are connected to different distribution network areas, and the single-side access state includes the state where the two access ends of the EV-SOP are connected to the same distribution network area;

[0103] Then the EV-SOP constraints include:

[0104] Since the two access ends of the EV-SOP are in either the double-end interconnection state or the single-side access state under the grid-connected state, there is:

[0105]

[0106] The EV-SOP needs to satisfy its own operating state constraints under the grid-connected state, including:

[0107]

[0108] Among them, P n,m,t sop represents the active power transmitted by the nth port among all ports at time t; Q m represents the reactive power transmitted by the nth port among all ports at time t; P n,m,t sop represents the loss of the nth port among all ports at time t; η represents the port efficiency of the EV-SOP; S m represents the rated apparent power of the nth port among all ports; P n,m,t sop,Loss represents the output power of the energy storage battery at time t; P m and P n,m sop represent the upper and lower limits of the charge and discharge power of the energy storage battery respectively; N and N m represent all ports and the DC-DC port of a single EV-SOP; all ports of a single EV-SOP include two access ends and the DC-DC port of a single EV-SOP; m,t b represents the output power of the energy storage battery at time t; P m represents the output power of the energy storage battery at time t; P max b and P min b represent the upper and lower limits of the charge and discharge power of the energy storage battery respectively; N and N DC represent all ports and the DC-DC port of a single EV-SOP; all ports of a single EV-SOP include two access ends and the DC-DC port of a single EV-SOP;

[0109] Introduce 0-1 variables C m,t b,ch and C m,t b,dis , when m the energy storage battery is in the charging state at time t, C m,t b,ch takes the value of 1, otherwise 0; when m the energy storage battery is in the discharging state at time t, C m,t b,dis takes the value of 1, otherwise 0; Since the EV-SOP cannot charge and discharge simultaneously under the grid-connected state, there is:

[0110]

[0111] To ensure the long-term connection under normal conditions of the distribution network and still have electricity for subsequent dispatching after the fault condition ends, there is:

[0112]

[0113] Among them, S oc,0 represents the initial state of charge of the energy storage battery.

[0114] S3. Construct a road topology according to the coupling relationship between the transportation network and the power distribution network, and obtain the shortest feasible path distance and path information between any two transportation network nodes according to the road topology combined with the Floyd algorithm.

[0115] In a preferred embodiment of the present invention, constructing a road topology according to the coupling relationship between the transportation network and the power distribution network includes:

[0116] For a power distribution network with n nodes, introduce a road topology adjacency matrix D = (d ij ) n×n to describe the distances between nodes in the transportation network coupled with the power distribution network; where i and j represent transportation network nodes; Z is the set of combinations of the two end nodes of the actual road; s ij is the actual distance of the road, in meters; then there is:

[0117]

[0118] Among them, INF indicates that there is no directly connected road between transportation network nodes;

[0119] According to d ij the road topology D can be obtained:

[0120]

[0121] In a preferred embodiment of the present invention, obtaining the shortest feasible path distance and path information between any two transportation network nodes according to the road topology combined with the Floyd algorithm includes:

[0122] Calculate the shortest feasible path distance between any two transportation network nodes according to the road topology D combined with the Floyd algorithm, and introduce a matrix H = (h ij ) n×n to describe the shortest feasible path distance between any two transportation network nodes, and introduce P = (p ij ) n×n to describe the path information corresponding to the shortest feasible path distance between any two transportation network nodes in the matrix H; H and P can be expressed as:

[0123]

[0124]

[0125] Among them, h ijDenote the shortest feasible path distance from traffic network node i to node j, and the H matrix is a symmetric matrix, that is, the shortest path distances between two nodes are mutual; p ij The value of p is a path sequence, including the numbers of all nodes passed on the shortest feasible path from node i to node j; the - in P represents the distance from a node to itself, which is meaningless.

[0126] S4. Through the double-layer model combined with the particle swarm optimization algorithm, perform iterative optimization for a preset number of times, and the double-layer model considers EV-SOP constraints; the double-layer model includes an upper-layer model and a lower-layer model.

[0127] See Figure 3 , in the preferred embodiment of the present invention, the iterative optimization includes:

[0128] F1. Through the upper-layer model, optimize and generate configuration parameters, and the configuration parameters include the basic parameters of EV-SOP and the interconnection length; obtain the EV-SOP interconnection feasible region according to the interconnection length, the shortest feasible path distance, and the path information.

[0129] In the preferred embodiment of the present invention, obtaining the EV-SOP interconnection feasible region according to the interconnection length, the shortest feasible path distance, and the path information includes:

[0130] Assume that h uv is the element located in the u-th row and v-th column of H, set the scheduling feasible region of EV-SOP as R = {d x |x = 1, 2, 3,..., X}, set the scheduling feasible region of the distribution network under the double-end interconnection state as R α = {d xα |xα = 1, 2, 3,..., XA}; where A represents the interconnection length; then the EV-SOP interconnection feasible region can be expressed as:

[0131]

[0132] Taking Δt as the time span, under normal and fault conditions of the distribution network, the scheduling positions of EV-SOP can be respectively expressed as and ψ x,m,ty , both of which are 0-1 variables, when taking the value of 1, they respectively represent that e m is scheduled to position d x at time t x ; when ψ x,m,ty takes the value of 1, they respectively represent that e m is scheduled to position d y at time t x ; d x is a value within the scheduling feasible region R of EV-SOP;

[0133] Since only one location can be accessed by the EV-SOP within a single time period Δt, there is a scheduling location constraint:

[0134]

[0135] When the EV-SOP is in a double-ended interconnected state, the scheduling location is restricted by the scheduling feasible region, including:

[0136]

[0137] F2. Calculate the first cost through the lower-layer model based on the configuration parameters and the EV-SOP interconnection feasible region; the first cost includes the total operating cost of the distribution network after connecting the EV-SOP.

[0138] F3. Compare the first cost obtained this time with the first cost obtained in the previous time through the upper-layer model, and select the configuration parameters with the lower first cost for saving.

[0139] In the preferred embodiment of the present invention, the iterative optimization for a preset number of times includes:

[0140] The basic parameters include the number of EV-SOPs, the grid-connected port capacity, and the energy storage battery power;

[0141] In the first iterative optimization, when the upper-layer model generates random configuration parameters during the EV-SOP configuration parameter optimization generation, after the lower-layer model calculates the first cost based on the random configuration parameters, the upper-layer model saves the random configuration parameters.

[0142] In the preferred embodiment of the present invention, the upper-layer model includes:

[0143] The goal of the upper-layer model is to minimize the total economic operation cost of the distribution network; the total economic operation cost of the distribution network includes the configuration cost of the EV-SOP and the total operation cost of the distribution network after connecting the EV-SOP;

[0144] The upper-layer model includes an upper-layer objective function, which can be expressed as:

[0145] minF conf =C E1 +C E2 +C E3

[0146] Wherein, C E1 represents the equipment investment cost of the EV-SOP; C E2 represents the operating cost of the distribution network under normal conditions; C E3 represents the operating cost of the distribution network under fault conditions;

[0147] The equipment investment cost C E1 of the EV-SOP includes:

[0148] C E1 = c sop S sop N AC + c b S b + c a A

[0149] Among them, c sop and c b respectively represent the unit capacity investment costs of EV - SOP and energy storage batteries; N AC represents the number of AC ports of EV - SOP; S sop represents the capacity of EV - SOP to be configured; S b represents the capacity of energy storage batteries to be configured; c a represents the unit length investment cost of EV - SOP cables, and A represents the interconnection length of EV - SOP to be configured;

[0150] The operating cost C of the distribution network under normal conditions E2 includes:

[0151]

[0152] Among them, ω α represents the network line loss cost coefficient; I represents the line current value of the distribution network; r represents the line resistance value of the distribution network; ε e represents the operating cost coefficient of EV - SOP; y e represents the service life of EV - SOP;

[0153] The operating cost C of the distribution network under fault conditions E3 includes:

[0154]

[0155] Among them, ω β represents the power outage cost coefficient, L p and L respectively represent the values corresponding to the load forecast curve and the actual load value. The upper - layer model also includes upper - layer constraints, including:

[0156] N e,min ≤ N e ≤ N e,max

[0157] S e,min ≤ S e ≤ S e,max

[0158] S b,min ≤ S b ≤ S b,max

[0159] P b,min ≤P b ≤P b,max

[0160] S e ≤S b

[0161] A min <A<A max

[0162] Among them, N e , N e,max and N e,min respectively represent the quantity and upper and lower limits of the EV-SOP to be configured; S e , S e,max and S e,min respectively represent the port capacity and upper and lower limits of the EV-SOP to be configured; S b , S b,max and S b,min respectively represent the capacity and upper and lower limits of the energy storage battery to be configured; P b , P b,max and P b,min respectively represent the rated power and upper and lower limits of the energy storage battery to be configured; A, A max and A min respectively represent the interconnection length and upper and lower limits of the EV-SOP to be configured.

[0163] In the preferred embodiment of the present invention, the lower-layer model includes:

[0164] The objective function F of the economic operation scheduling of EV-SOP under normal operating conditions of the distribution network 1 , which can be expressed as:

[0165]

[0166] Among them, I line represents the current of the distribution network line; r line represents the resistance of the distribution network line; ω α represents the loss cost coefficient; T represents the access time of the EV-SOP;

[0167] The objective function F of the emergency power supply scheduling of EV-SOP under fault conditions of the distribution network 2 , which can be expressed as:

[0168]

[0169] Among them, L represents the actual load borne by the distribution network; L P represents the corresponding value of the load prediction curve; ω β represents the loss economic loss coefficient;

[0170] In the lower-layer model, the Distflow model is used to model the power flow of the distribution network, and the single-commodity flow is used to constrain the radial network, which is solved by Gurobi.

[0171] Verification part:

[0172] To verify the effectiveness and superiority of the method of the present invention, a part of the main roads in the urban area of a certain county and its distribution network system are selected as examples. The urban traffic network of this county contains 40 nodes and 55 roads. The coupling situation of its traffic network - distribution network can be seen in Figure 4 , and the lengths of each road can be seen in Table 1:

[0173] Table 1 Road lengths of the traffic network in the urban area of a certain county

[0174]

[0175]

[0176] Under normal and fault conditions of the distribution network, according to the EV-SOP interconnection distance generated by the upper-layer model, when the feasible path distance of the traffic network node is less than this interconnection distance, it is determined that the EV-SOP can be connected to the bus of the traffic network node. The broken-line lines are set as 8 - 9, 16 - 17, 25 - 26, 29 - 34.

[0177] When using the particle swarm optimization algorithm for iteration, the number of EV-SOPs is set to 2 - 5 vehicles, the capacity of EV-SOPs is 200 kVA - 500 kVA, the power of the energy storage battery is 200 kW - 500 kW, and the interconnection distance of EV-SOPs is 100 m - 200 m. The full life cycle of EV-SOPs is taken as 15 years, and natural disasters occur once a year on average, resulting in the disconnection of the distribution network. Regarding the economic cost of EV-SOPs, the relevant parameters can be seen in Table 2:

[0178] Table 2 Economic cost parameters related to EV-SOPs

[0179]

[0180] According to the calculation of Gurobi and the iteration of the particle swarm optimization algorithm, the configuration scheme of EV-SOPs can be seen in Table 3:

[0181] Table 3 EV-SOP configuration scheme

[0182]

[0183] To verify the method of the present invention, the total economic costs within the service life of EV-SOPs obtained by the method of the present invention and the conventional configuration scheme are calculated, as can be seen in Table 4:

[0184] Table 4 Total costs within the service life of EV-SOPs under different schemes

[0185]

[0186] As shown in Table 4, the bold part in the table is the configuration scheme obtained by the method of the present invention. Compared with other conventional configuration schemes, the configuration scheme obtained by the method of the present invention has the lowest sum of the operation cost of the distribution network and the EV-SOP configuration cost during the entire life cycle of EV-SOP, and this scheme can still ensure that the voltage deviation does not exceed the limit under normal operating conditions of the distribution network. For voltage deviation, refer to Figure 5 .

[0187] The method for optimizing the EV-SOP configuration parameters considering the dynamic interconnection feasible region of the present invention obtains the working state of the access end according to the structure of the EV-SOP, and establishes EV-SOP constraints according to the working state of the access end, providing the basic constraints of the EV-SOP for subsequent optimization of the configuration parameters, and ensuring the controllability and accuracy of the optimization process. The road topology is constructed according to the coupling relationship between the transportation network and the distribution network, and the shortest feasible path distance and path information between any two transportation network nodes are obtained by combining the Floyd algorithm with the road topology, enabling the method of the present invention to clarify the shortest feasible path distance and path information between any two transportation network nodes, and providing a data basis for subsequent calculation of the interconnection feasible region. Through the double-layer model combined with the particle swarm algorithm for iterative optimization for a preset number of times, comprehensively considering the EV-SOP interconnection feasible region, the configuration cost of the EV-SOP, the operation costs under normal operation and fault conditions of the distribution network, the method of the present invention can reduce the total economic cost during the entire life cycle of the EV-SOP, has important practical significance for the operation optimization of the distribution network, realizes the optimization of the configuration parameters at the same time, considers the limitation of the connection range by the interconnection length of the AC ports of the EV-SOP, and enables the EV-SOP to be applied in actual scenarios. The method can improve the economy and reliability of the distribution network operation.

[0188] In a preferred embodiment of the present invention, there is also provided a system for optimizing the EV-SOP configuration parameters considering the dynamic interconnection feasible region, which is used for the method of the present invention. The system includes a first module, a second module, a third module and a fourth module;

[0189] The first module is used to determine that the structure of the EV-SOP includes two access ends; the access end includes an AC port for grid connection;

[0190] The second module is used to obtain the working state of the access end according to the structure of the EV-SOP, and establish EV-SOP constraints according to the working state;

[0191] The third module is used to construct the road topology according to the coupling relationship between the transportation network and the distribution network, and obtain the shortest feasible path distance and path information between any two transportation network nodes by combining the Floyd algorithm with the road topology;

[0192] The fourth module is used to perform iterative optimization for a preset number of times through a two - layer model combined with a particle swarm algorithm. The two - layer model considers EV - SOP constraints. The two - layer model includes an upper - layer model and a lower - layer model. The iterative optimization includes:

[0193] Optimizing and generating configuration parameters through the upper - layer model. The configuration parameters include the basic parameters of EV - SOP and the interconnection length. Obtaining the EV - SOP interconnection feasible region based on the interconnection length, the shortest feasible path distance, and path information;

[0194] Calculating the first cost through the lower - layer model according to the configuration parameters and the EV - SOP interconnection feasible region. The first cost includes the total operating cost after the distribution network accesses EV - SOP;

[0195] Comparing the first cost obtained this time with the first cost obtained in the previous time through the upper - layer model, and selecting the configuration parameters with a lower first cost for storage.

[0196] The EV - SOP configuration parameter optimization system considering the dynamic interconnection feasible region of the present invention is used for the method of the present invention and has the same beneficial effects as the method of the present invention.

[0197] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An EV-SOP configuration parameter optimization method taking into account a dynamic interconnection feasible domain, characterized in that: include: Determine that the structure of EV-SOP includes two access terminals; the access terminals include an AC port for grid connection; Acquire the working state of the access terminal according to the structure of EV-SOP, and establish EV-SOP constraints according to the working state; Constructing a road topology according to the coupling relationship between the transportation network and the distribution network, and obtaining the shortest feasible path distance and path information between any two transportation network nodes according to the road topology combined with the Floyd algorithm; The iterative optimization is performed for a preset number of times by combining a double-layer model with a particle swarm algorithm, wherein the double-layer model considers the EV-SOP constraint; the double-layer model includes an upper layer model and a lower layer model; and the iterative optimization includes: The configuration parameters are optimized and generated through the upper model, wherein the configuration parameters include basic parameters of EV-SOP and interconnection length; and the EV-SOP interconnection feasible domain is obtained according to the interconnection length, the shortest feasible path distance and path information; Calculate a first cost according to the configuration parameters and the EV-SOP interconnection feasible domain through a lower layer model; the first cost includes the total operating cost after the distribution network is connected to the EV-SOP; The first cost obtained this time is compared with the first cost obtained last time through the upper model, and the configuration parameter with the lower first cost is selected for storage.

2. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 1, characterized in that: The preset number of iterative optimizations includes: The basic parameters include the number of EV-SOPs, grid-connected port capacity, and energy storage battery power; In the first iterative optimization, the upper model generates random configuration parameters when performing EV-SOP configuration parameter optimization generation; after the lower model calculates the first cost based on the random configuration parameters, the upper model saves the random configuration parameters.

3. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 2, characterized in that: The acquiring the working state of the access terminal according to the structure of the EV-SOP and establishing the EV-SOP constraint according to the working state comprises: Set the set of EV-SOP to be E = {e m |m=1,2,3,…,M}, the sets of normal and fault conditions of the distribution network are T1={t x |t x ∈[t0,t0+Δt]} and T2={t y |t y ∈[t0,t0+Δt]}; Introducing the 0-1 variable τ m,t , τ α m,t and τ β m, It is used to describe whether EV-SOP is connected to the grid and the working status of the two access terminals of EV-SOP; if e m In the grid-connected state, τ m,t =1, otherwise τ m,t =0; if τ α m,t If the value is 1, it means e m In the double-ended interconnection state, otherwise τ α m,t is 0; if τ β m,t If the value is 1, it means e m In the unilateral access state, otherwise τ β m,t 0; the double-end interconnection state includes the state where the two access ends of the EV-SOP are connected to different distribution network areas, and the single-side access state includes the state where the two access ends of the EV-SOP are connected to the same distribution network area; The EV-SOP constraints include: Since the two access terminals in the EV-SOP grid-connected state are either in a double-end interconnection state or a single-side access state, there are: When connected to the grid, EV-SOP must meet its own working state constraints, including: Among them, P n,m,t sop Indicates e m The active power transmitted by the nth port among all ports at time t; Q n,m,t sop Indicates e m The reactive power transmitted by the nth port among all ports at time t; P n,m,t sop,Loss Indicates e m The loss of the nth port among all ports at time t; η represents the EV-SOP port efficiency; S n,m sop Indicates e m Rated apparent power of the nth port among all ports; P m,t b Indicates e m The output power of the energy storage battery at time t; P max b and P min b Respectively represent the upper and lower limits of the energy storage battery charging and discharging power; N and N DC Represents all ports and DC-DC ports of a single EV-SOP; all ports of a single EV-SOP include the two access ports and DC-DC ports of a single EV-SOP; Introducing 0-1 variable C m,t b,ch and C m,t b,dis , when e m When the energy storage battery is in the charging state at time t, C m,t b,ch The value is 1, otherwise it is 0; when e m When the energy storage battery is in the discharge state at time t, C m,t b,dis The value is 1, otherwise it is 0; since EV-SOP cannot charge and discharge at the same time when connected to the grid, there are: In order to ensure long-term access to the distribution network under normal conditions and to ensure that there is still power available for subsequent dispatching after the fault condition ends, there are: Among them, S oc,0 Indicates the initial charge of the energy storage battery.

4. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 3, characterized in that: The construction of road topology according to the coupling relationship between the transportation network and the distribution network includes: For a distribution network with n nodes, the road topology adjacency matrix D = (d ij ) n×n Describes the distance between nodes in the traffic network coupled with the distribution network; i and j represent nodes in the traffic network; Z is the set of node combinations at both ends of the actual road; s ij is the actual distance of the road in meters; then there exists: Among them, INF means that there are no directly connected roads between nodes in the transportation network; According to d ij That is, the road topology D is obtained:

5. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 4, characterized in that: According to the road topology combined with the Floyd algorithm, the shortest feasible path distance and path information between any two traffic network nodes are obtained, including: According to the road topology D combined with the Floyd algorithm, the shortest feasible path distance between any two traffic network nodes is calculated, and the matrix H is introduced as (h ij ) n×n Describe the shortest feasible path distance between any two nodes in the transportation network, introduce P = (p ij ) n×n Describe the path information corresponding to the shortest feasible path distance between any two traffic network nodes in the matrix H; H and P can be expressed as: Among them, h ij represents the shortest feasible path distance from node i to node j in the transportation network, and the H matrix is ​​a symmetric matrix, that is, the shortest path distance between two nodes is mutual; p ij The value of is a path sequence, which contains the numbers of all nodes on the shortest feasible path from node i to node j; the - in P represents the distance from the node itself, which is meaningless.

6. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 5, characterized in that: The EV-SOP interconnection feasible domain obtained according to the interconnection length, the shortest feasible path distance and the path information includes: Assume h uv For the element located in the uth row and vth column of H, set the scheduling feasible region of EV-SOP to R = {d x |x=1,2,3,…,X}, and set the dispatching feasible region of the distribution network in the double-end interconnected state to R α ={d xα |xα=1,2,3,…,XA}; where A represents the interconnection length; then the EV-SOP interconnection feasible domain can be expressed as: Taking Δt as the time span, the dispatching position of EV-SOP under normal and fault conditions of the distribution network can be expressed as and ψ x,m,ty , both are 0-1 variables, When the value is 1, it means e m In t x Time slot dispatched to location d x ψ x,m,ty When the value is 1, it means e m In t y Time slot dispatched to location d x ;d x is the value within the scheduling feasible region R of EV-SOP; Since EV-SOP can only access one location within a single period Δt, there is a scheduling location constraint: When EV-SOP is in a dual-end interconnected state, the dispatch position is subject to the constraints of the dispatch feasible domain, including:

7. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 6 is characterized in that: The upper model includes: The goal of the upper model is to minimize the total economic operation cost of the distribution network; the total economic operation cost of the distribution network includes the configuration cost of EV-SOP and the total operation cost after the distribution network is connected to EV-SOP; The upper model includes an upper objective function, which can be expressed as: minF conf =C E1 +C E2 +C E3 Among them, C E1 represents the equipment investment cost of EV-SOP; C E2 Represents the operating cost of the distribution network under normal conditions; C E3 It represents the operating cost under the fault condition of the distribution network; Equipment investment cost C of EV-SOP E1 include: C E1 =c sop S sop N AC +c b S b +c a A Among them, c sop and c b Respectively represent the unit capacity investment cost of EV-SOP and energy storage battery; N AC Indicates the number of EV-SOP communication ports; S sop Indicates the EV-SOP capacity to be configured; S b Indicates the capacity of the energy storage battery to be configured; c a represents the unit length investment cost of the EV-SOP cable, and A represents the EV-SOP interconnection length to be configured; The operating cost of the distribution network under normal conditions C E2 include: Among them, ω α represents the network line loss cost coefficient; I represents the current value of the distribution network line; r represents the resistance value of the distribution network line; ε e represents the operating cost coefficient of EV-SOP; y e Indicates the useful life of EV-SOP; Operation cost C under distribution network fault conditions E3 include: Among them, ω β Denotes the power failure cost coefficient, L p and L represent the value corresponding to the load forecast curve and the actual load value respectively.

8. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 7, characterized in that: The upper model also includes upper constraints, including: N e,min ≤N e ≤N e,max S e,min ≤S e ≤S e,max S b,min ≤S b ≤S b,max P b,min ≤P b ≤P b,max S e ≤S b A min <A<A max Among them, N e 、N e,max and N e,min Respectively represent the number and upper and lower limits of EV-SOP to be configured; S e , S e,max and S e,min Respectively represent the capacity and upper and lower limits of the EV-SOP port to be configured; S b , S b,max and S b,min Respectively represent the capacity and upper and lower limits of the energy storage battery to be configured; P b , P b,max and P b,min Respectively represent the rated power and upper and lower limits of the energy storage battery to be configured; A, A max and A min They respectively represent the interconnection length and upper and lower limits of the EV-SOP to be configured.

9. The EV-SOP configuration parameter optimization method taking into account the dynamic interconnection feasible domain according to claim 8, characterized in that: The lower model includes: The objective function F1 of EV-SOP economic operation dispatch under normal distribution network conditions can be expressed as: Among them, I line Represents the current of the distribution network line; r line Represents the resistance of the distribution network line; ω α represents the loss cost coefficient; T represents the access time of EV-SOP; The objective function F2 of EV-SOP emergency power supply dispatch under distribution network fault conditions can be expressed as: Where L represents the actual load borne by the distribution network; L P Represents the corresponding value of the load forecast curve; ω β Indicates the economic loss coefficient of power failure; In the lower model, the Distflow model is used to model the distribution network flow, and a single commodity flow is used to constrain the radial network, which is solved by Gurobi.

10. An EV-SOP configuration parameter optimization system taking into account a dynamic interconnected feasible domain, used in the method according to any one of claims 1 to 9, characterized in that: The system comprises a first module, a second module, a third module and a fourth module; The first module is used to determine that the structure of the EV-SOP includes two access terminals; the access terminals include an AC port for grid connection; The second module is used to obtain the working state of the access terminal according to the structure of EV-SOP, and establish EV-SOP constraints according to the working state; The third module is used to construct a road topology according to the coupling relationship between the transportation network and the distribution network, and obtain the shortest feasible path distance and path information between any two transportation network nodes according to the road topology combined with the Floyd algorithm; The fourth module is used to perform a preset number of iterative optimizations by combining a double-layer model with a particle swarm algorithm, wherein the double-layer model considers the EV-SOP constraint; the double-layer model includes an upper model and a lower model; and the iterative optimization includes: The configuration parameters are optimized and generated through the upper model, wherein the configuration parameters include basic parameters of EV-SOP and interconnection length; and the EV-SOP interconnection feasible domain is obtained according to the interconnection length, the shortest feasible path distance and path information; Calculate a first cost according to the configuration parameters and the EV-SOP interconnection feasible domain through a lower layer model; the first cost includes the total operating cost after the distribution network is connected to the EV-SOP; The first cost obtained this time is compared with the first cost obtained last time through the upper model, and the configuration parameter with the lower first cost is selected for storage.

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