A method for planning the expansion of power-transportation coupling networks considering traffic balance

Abstract

The present invention proposes a method for planning the expansion of a power-transportation coupling network taking into account traffic equilibrium, specifically including: Based on the user equilibrium principle, the present invention proposes a method for planning the expansion of a power-transportation coupling network taking into account traffic equilibrium. The method comprehensively considers the safe operation constraints of the transportation network and the distribution network, and takes the minimum sum of the construction costs of the expansion facilities as the goal. The method is solved by CPLEX to determine the optimal expansion plan for electric vehicles in different travel scenarios. The present invention considers that the road expansion plan can effectively improve the travel time and bring convenience to the car owners, which also verifies the effectiveness of the expansion planning model of the present invention in solving the road congestion problem. Compared with the shortest path travel, the traffic equilibrium model used in the present invention can better reflect the actual road traffic conditions and the interaction between vehicles, improve the operation of the transportation network system and the travel time of car owners.

Description

Technical Field

[0001] The invention relates to a method for expansion planning of an electric power-transportation coupling network, in particular to a method for expansion planning of an electric power-transportation coupling network taking traffic balance into consideration. Background Art

[0002] Electric vehicles have been gradually sought after in recent years because of their low power consumption and pollution-free characteristics and their compliance with the concept of low-carbon travel. Their ownership is increasing rapidly. The traffic load and charging load generated by large-scale electric vehicles traveling in the transportation network further strengthen the coupling between the transportation network and the distribution network. On the one hand, the large-scale concentration of charging demand will increase the risk of traffic congestion and even paralysis; on the other hand, if these charging loads are not controlled, it will cause the load peak of the urban power grid to be added to the peak, and the voltage will exceed the limit. Therefore, ensuring that the transportation network and distribution network can meet the travel needs of more electric vehicles under the safe operation is of great significance for the expansion planning and construction of the power-transportation coupling network.

[0003] The increase in the number of electric vehicles will make the coupling between the transportation network and the distribution network more and more significant. For the distribution network, the increase in the number of electric vehicles means that more power facilities will be needed to meet its charging needs. The planning of power facilities usually takes into account the economic and safe operation constraints of the distribution network to reduce the investment cost brought by the upgrade of the power system. For the transportation network, large-scale electric vehicle travel will increase the risk of traffic congestion and even paralysis. Therefore, it is necessary to study the expansion planning of power facilities and transportation facilities under the coupling of transportation network and distribution network. Summary of the invention

[0004] The present invention mainly solves the technical problems existing in the prior art; for the first time, a method for planning the expansion of a power-traffic coupling network that takes traffic balance into consideration is proposed. Aiming at the increased risk of traffic paralysis and safe operation of the power grid caused by large-scale electric vehicle travel, a traffic equilibrium model for hybrid electric vehicles and ordinary cars is proposed based on the user equilibrium principle and considering the effects of road expansion and charging station congestion. Secondly, an optimal expansion planning model for a power-traffic coupling network is proposed under traffic equilibrium. The model aims to minimize the cost of road travel time, road expansion, new charging piles, substation expansion, and new distribution network lines, and comprehensively considers traffic equilibrium and power grid safe operation constraints to optimize the model.

[0005] The above technical problems of the present invention are mainly solved by the following technical solutions:

[0006] A method for planning the expansion of a power-transportation coupling network considering traffic balance, characterized in that:

[0007] A coupling network is constructed with the transportation network and the distribution network, in which the power flow form of the distribution network adopts the Distflow power flow form;

[0008] Taking the minimum sum of expansion planning costs in the established expansion planning model of the power-transportation coupling network as the optimization goal, the traffic balance constraints, power grid safe operation constraints, road expansion constraints, line expansion constraints, new charging pile constraints, linear and nonlinear constraints of the expansion planning model are taken as constraints to solve the optimal solution of the model and obtain the optimal expansion plan.

[0009] In the above-mentioned power-transportation coupling network expansion planning method considering traffic equilibrium, the establishment of the expansion planning model is based on solving a traffic equilibrium model, specifically:

[0010] Construct a travel path selection network and establish an optimal travel path generation model that takes into account the satisfaction of car owners;

[0011] Based on the user equilibrium principle of hybrid electric vehicles and ordinary cars, the traffic equilibrium model of hybrid electric vehicles and ordinary cars is constructed by considering the road congestion effect, the charging station congestion effect and the road expansion model.

[0012] Solve the traffic equilibrium under the optimal path to obtain the steady-state traffic flow distribution;

[0013] Record the routes and road traffic flow, as well as the charging stations selected by electric vehicles on each travel route, and the charging power to obtain the charging load on the coupling node; build an expansion planning model for the power-transportation coupling network; the model includes road travel time cost, road expansion cost, new charging pile cost, substation expansion cost and new distribution network line cost.

[0014] In the above-mentioned power-traffic coupling network expansion planning method considering traffic balance, the congestion effect of charging stations is:

[0015]

[0016] Where: Average waiting time in queues for charging stations; is a binary variable. When the electric vehicle on path p chooses to charge at charging station s, Otherwise 0; x s The power required for the current electric vehicle to charge at charging station s; c s is the capacity of the charging station s.

[0017] In the above-mentioned power-transportation coupling network expansion planning method considering traffic balance, the road expansion model is:

[0018]

[0019] Where: t a represents the time when the vehicle passes through road a; is the free travel time of road a (free travel time refers to the time that vehicles can pass when the current traffic volume of the road is not greater than the upper limit of the traffic capacity); x a is the traffic volume of road a; c a is the upper limit of the original traffic capacity of road a; σ a represents the number of road a expansions, σ a ≥0; Δc represents the road capacity that can be increased by expanding road a.

[0020] In the above-mentioned power-traffic coupling network expansion planning method considering traffic balance, the user balance principle of hybrid electric vehicles and ordinary vehicles is:

[0021]

[0022]

[0023] Where: and are the travel costs of paths p and q on OD pair w respectively; and are the travel costs of OD for electric vehicles and ordinary cars on w in the equilibrium state; and are the traffic flows on path p and path q respectively; Available paths for electric vehicles, that is, paths for electric vehicles with charging requirements are taken as available paths; is the available path for an ordinary car; W is the set of all OD pairs in the traffic network, and w represents one of the OD pairs.

[0024] In the above-mentioned power-traffic coupling network expansion planning method considering traffic balance, the traffic balance model of hybrid electric vehicles and ordinary cars is:

[0025]

[0026]

[0027]

[0028]

[0029] x a ≤c a +Δc·σ a ,

[0030] Where: ω is the unit time cost; a represents a road in traffic; T a represents the road set in the transportation network; S is the set of coupling nodes between the transportation network and the distribution network; is the charging power of the electric vehicle at charging station s on path p; θ is the electricity price of charging station s; g w and h w are the travel demands of electric vehicles and ordinary vehicles on OD pair w respectively; and are binary variables that associate paths with roads, i.e., they are 1 when paths p and q pass through road a, and 0 otherwise.

[0031] In the above-mentioned power-transportation coupling network expansion planning method considering traffic balance, the travel path selection network model is

[0032]

[0033] Where: SOC O is the initial power of the electric vehicle at the starting node; is the distance from the starting node to the charging station s on the path p; L p is the total distance of path p; Q is the power consumption of the electric vehicle per kilometer; SOC φ This is the minimum battery charge threshold that the car owner can accept.

[0034] In the above-mentioned power-traffic coupling network expansion planning method considering traffic balance, the optimal path models considering the satisfaction of electric vehicle and ordinary car owners are:

[0035]

[0036]

[0037] Where: is the traffic volume on the current road; ps is the charging power of charging station s; is a binary variable. When path p passes through road a, Otherwise 0.

[0038] In the above-mentioned power-transportation coupling network expansion planning method considering traffic balance, the expansion planning model of the power-transportation coupling network is:

[0039] minF=C TN +C PDN

[0040] Where: F is the total cost of the expansion plan; C TN Planning costs for transportation network expansion; C PDN Planning costs for distribution network expansion;

[0041] The cost expression of transportation network expansion planning is:

[0042]

[0043]

[0044] Where: κ is the discount factor; c1 is the unit cost of road expansion; c2 is the unit cost of new charging piles; h s is the number of new charging piles at charging station s; r is the discount rate; y is the depreciation period;

[0045] The cost expression of distribution network expansion planning is:

[0046]

[0047]

[0048] Where: c3 is the unit cost of the new line; n ij is the number of new lines between nodes i and j, which are expanded in parallel with the existing distribution network lines and have the same line parameters as the existing lines; c4 is the unit cost of substation expansion; is the expansion capacity of the substation; K s P is the substation assembly; k,e The power of the newly added charging piles in the charging station serving substation k; is the remaining capacity of substation k;

[0049] The system constraints are:

[0050] The traffic equilibrium model constraints are

[0051]

[0052]

[0053]

[0054] x a ≤c a +Δc·σ a ,

[0055] In the above formula: the first line is the conservation constraint of vehicle travel flow; the second line is the conservation constraint of road flow and path flow in the traffic network; the third line is the road capacity constraint;

[0056] Road expansion and new distribution network line quantity constraints

[0057] 0≤σ a ≤σ a,max

[0058] 0≤n ij ≤n ij,max

[0059] Where: a,max is the upper limit of the number of expansions for road a; n ij,max is the upper limit of the number of new distribution network lines between nodes i and j;

[0060] New charging pile constraints are

[0061] x s ≤(h s +h s,0 ) s

[0062] Where: h s,0 is the number of existing charging piles in the charging station;

[0063] The branch power flow of the distribution network adopts the Distflow power flow form, without considering the line loss. The simplified distribution network safety operation constraint is:

[0064]

[0065] Where: v i and are the upper and lower limits of the voltage amplitude of node i respectively; P ij is the active power capacity between nodes i and j; is the upper limit of the active power capacity of the line between nodes i and j; r ij and x ij are the resistance and reactance of the line respectively; P j and Q j are the active and reactive power requirements at node j respectively; v i and v j is the voltage amplitude of nodes i and j; p ij and q ij is the active and reactive power flow between nodes i and j; D N is the node set of the distribution network; D A is the line set of the distribution network; (i, j) is the line between nodes i and j; v1 is the voltage amplitude of the equilibrium node; π(j) is the branch line set flowing out from node j; p jm and q jm are the active and reactive power on branch (j, m) respectively; P i and They are the total active power demand and the active power demand of conventional load at distribution network node i respectively.

[0066] In the above-mentioned power-transportation coupling network expansion planning method considering traffic balance, the nonlinear constraints and nonlinear models are linearized as follows:

[0067]

[0068] Where: Δx a and τ a (m,n) are auxiliary variables, where τ a (m,n) is a binary variable, which represents the segment position in the two-dimensional plane; m and n are x a and σ a The current segment number;

[0069] Voltage Drop Constrained Linearization

[0070]

[0071] Where: is a binary variable that satisfies and is a continuous variable that satisfies

[0072] Linearization of Substation Capacity Expansion Function

[0073]

[0074] Where: δ is a binary variable.

[0075] Based on the user equilibrium principle, the present invention proposes a power-traffic coupling network expansion planning method taking into account traffic equilibrium. The method comprehensively considers the safe operation constraints of the traffic network and the distribution network, and takes the minimum sum of the construction costs of the expansion facilities as the goal. The method is solved by CPLEX to determine the optimal expansion plan for electric vehicles in different travel scenarios. The advantages of the present invention are as follows: 1) The increase in OD travel demand will cause the capacity of some roads to exceed its limit, which will lead to a significant increase in travel time. Considering the road expansion plan can effectively improve the travel time and bring convenience to the owner's travel, which also verifies the effectiveness of the expansion planning model of the present invention in solving the road congestion problem. 2) The charging demand on the road will introduce new loads to the distribution network nodes under the coupling network. The access of large-scale charging loads will cause the active power of some distribution network lines to exceed their capacity limits. The proposed line expansion construction model can ensure the transmission of power and meet the charging demand in the charging station. 3) Compared with the shortest path travel, the traffic equilibrium model used in the present invention can better reflect the actual road traffic conditions and the interaction between vehicles, improve the operation of the transportation network system and the travel time of the owner. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 Schematic diagram of the electric vehicle path selection network in this embodiment.

[0077] Figure 2 This is the radial distribution network topology in this embodiment.

[0078] Figure 3 This is the coupled topology of the transportation network and the distribution network in this embodiment.

[0079] Figure 4 It is the expansion planning cost in different scenarios in this embodiment.

[0080] Figure 5 It is the planned number of facility expansion in different scenarios in this embodiment.

[0081] Figure 6 It is the traffic volume of each road when the travel demand of electric vehicles increases by 0% in this embodiment.

[0082] Figure 7 It is the traffic volume of each road when the travel demand of electric vehicles increases by 100% in this embodiment.

[0083] Figure 8 It is the road travel time where the electric vehicle travel demand increases by 0% in this embodiment.

[0084] Fig. 9 It is the travel time of the part of the road where the travel demand of electric vehicles increases by 100% in this embodiment.

[0085] Fig.10 It is the charging queue time of charging station No. 1 in different scenarios in this embodiment. DETAILED DESCRIPTION

[0086] In order to facilitate ordinary technicians in the field to understand and implement the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0087] The following are examples and the attached Figure 1-10 , the technical solution of the present invention is further specifically described.

[0088] 1. First, the principle and process of the method of the present invention are introduced.

[0089] Step 1: Based on the user equilibrium principle, considering the road congestion effect, charging station congestion effect and road expansion model, a traffic equilibrium model for hybrid electric vehicles and ordinary cars is proposed;

[0090] The congestion effect of the charging station described in step 1 is:

[0091]

[0092] Where: Average waiting time in queues for charging stations; is a binary variable. When the electric vehicle on path p chooses to charge at charging station s, Otherwise 0; x s The power required for the current electric vehicle to charge at charging station s; c s is the capacity of the charging station s;

[0093] The road expansion model described in step 1 is:

[0094]

[0095] Where: t a represents the time it takes for a vehicle to pass through road a; x a is the traffic volume of road a; c a is the upper limit of the original traffic capacity of road a; σ a represents the number of road a expansions, σ a ≥0; Δc represents the road capacity that can be increased by expanding road a.

[0096] The user balancing principle of the hybrid electric vehicle and the ordinary car described in step 1 is:

[0097]

[0098]

[0099] Where: and are the travel costs of paths p and q on OD pair w respectively; and are the travel costs of OD for electric vehicles and ordinary cars on w in the equilibrium state; and are the traffic flows on path p and path q respectively; Available paths for electric vehicles, that is, paths for electric vehicles with charging requirements are taken as available paths; Available paths for ordinary cars;

[0100] The traffic equilibrium model of hybrid electric vehicles and ordinary cars described in step 1 is:

[0101]

[0102]

[0103]

[0104]

[0105] x a ≤c a +Δc·σ a ,

[0106] Where: ω is the unit time cost; S is the set of coupling nodes between the transportation network and the distribution network; is the charging power of the electric vehicle at charging station s on path p; θ is the electricity price of charging station s; g w and h w are the travel demands of electric vehicles and ordinary vehicles on OD pair w respectively; and are binary variables that associate paths with roads, i.e., they are 1 when paths p and q pass through road a, and 0 otherwise;

[0107] Step 2: In order to solve the traffic equilibrium in step 1, a travel path selection network is constructed and an optimal travel path generation model considering the owner's satisfaction is proposed. The traffic equilibrium is solved under the optimal path to obtain the steady-state traffic flow distribution;

[0108] The travel path selection network model described in step 2 is as follows: Figure 1 Shown

[0109]

[0110] Where: SOC O is the initial power of the electric vehicle at the starting node; is the distance from the starting node to the charging station s on the path p; L p is the total distance of path p; Q is the power consumption of the electric vehicle per kilometer; SOC φ The minimum battery charge threshold that the car owner can accept;

[0111] The optimal path considering the satisfaction of electric car and ordinary car owners is:

[0112]

[0113]

[0114] Where: is the current road traffic volume; p s is the charging power of charging station s; is a binary variable. When path p passes through road a, Otherwise, 0;

[0115] Step 3: After obtaining traffic equilibrium, record the path and road traffic volume, as well as the charging station selected by the electric vehicle on each travel path, and use the charging power to obtain the charging load on the coupling node. An expansion planning model for the power-traffic coupling network is proposed. The model includes the road travel time cost, road expansion cost, new charging pile cost, substation expansion cost, and new distribution network line cost;

[0116] The expansion planning model of the power-transportation coupling network described in step 3 is:

[0117] minF=C TN +C PDN

[0118] Where: F is the total cost of the expansion plan; C TN Planning costs for transportation network expansion; C PDN Planning costs for distribution network expansion;

[0119] The cost expression of transportation network expansion planning is:

[0120]

[0121]

[0122] Where: κ is the discount factor; c1 is the unit cost of road expansion; c2 is the unit cost of new charging piles; h s is the number of new charging piles at charging station s; r is the discount rate; y is the depreciation period;

[0123] The cost expression of distribution network expansion planning is:

[0124]

[0125]

[0126] Where: c3 is the unit cost of the new line; n ij is the number of new lines between nodes i and j, which are expanded in parallel with the existing distribution network lines and have the same line parameters as the existing lines; c4 is the unit cost of substation expansion; is the expansion capacity of the substation; K s P is the substation assembly; k,e The power of the newly added charging piles in the charging station serving substation k; is the remaining capacity of substation k;

[0127] Step 4: Taking the minimum sum of the expansion planning costs of the power-transportation coupling network as the optimization goal, construct system constraints through traffic balance constraints, power grid safety operation constraints, road expansion, line expansion and new charging pile constraints;

[0128] The traffic equilibrium model constraints are

[0129]

[0130]

[0131]

[0132] x a ≤c a +Δc·σ a ,

[0133] In the above formula: the first line is the conservation constraint of vehicle travel flow; the second line is the conservation constraint of road flow and path flow in the traffic network; the third line is the road capacity constraint;

[0134] Road expansion and new distribution network line quantity constraints

[0135] 0≤σ a ≤σ a,max

[0136] 0≤n ij ≤n ij,max

[0137] Where: a,max is the upper limit of the number of expansions for road a; n ij,max is the upper limit of the number of new distribution network lines between nodes i and j;

[0138] New charging pile constraints are

[0139] x s ≤(h s +h s,0 ) s

[0140] Where: h s,0 It is the number of existing charging piles in the charging station.

[0141] The branch power flow of the distribution network adopts the Distflow power flow form, and its topological structure is as follows: Figure 2 As shown, without considering line loss, the simplified distribution network safety operation constraint is

[0142]

[0143] Where: v i and are the upper and lower limits of the voltage amplitude of node i respectively; is the active power flow capacity of the distribution line between nodes i and j; r ij and x ijare the resistance and reactance of the line respectively; P j and Q j are the active and reactive power requirements at node j respectively; v i and v j is the voltage amplitude between nodes i and j; π(j) is the set of branch lines flowing out from node j; p jm and q jm are the active and reactive power on branch (j, m) respectively; P i and They are the total active power demand and the active power demand of conventional load at distribution network node i respectively.

[0144] Step 5: Linearize the nonlinear constraints and nonlinear models in the extended planning model;

[0145] Linearization of road expansion equation. The road expansion equation is a non-convex, nonlinear function, which is difficult to solve in the expansion planning process. It can be linearized using the three-dimensional incremental piecewise relaxation method.

[0146]

[0147] Where: Δx a and τ a (m,n) are auxiliary variables, where τ a (m,n) is a binary variable, which represents the segment position in the two-dimensional plane; m and n are x a and σ a The current segment number.

[0148] Voltage Drop Constrained Linearization

[0149] g

[0150] Where: is a binary variable that satisfies and is a continuous variable that satisfies

[0151] Linearization of Substation Capacity Expansion Function

[0152]

[0153] Where: δ is a binary variable.

[0154] Step 6: Construct a coupling network with the Nguyen transportation network and the 33-node distribution network, in which the distribution network power flow adopts the Distflow power flow form. The minimum sum of the expansion planning costs in step 3 is taken as the optimization goal, and the constraints in step 4 and the linearized constraints in step 5 are taken as system constraints. The Cplex software package is called on Matlab to solve the model, and the optimal expansion planning strategy is obtained under five scenarios where the electric vehicle travel demand increases by 0%, 25%, 50%, 75% and 100%.

[0155] The Cplex solution process is as follows:

[0156] Step 6.1: Basic parameter input and variable definition. Basic parameters include transportation network, distribution network, investment cost, charging station, coupling node, and travel demand of electric vehicles and ordinary vehicles. Defined variables include integer variables, auxiliary variables and real variables.

[0157] Step 6.2: Initial travel path set construction. The path set can be constructed by using the particle swarm algorithm. First, the initial traffic flow of the current road is set to Considering the owner's satisfaction under this traffic flow, the initial travel path set of electric vehicles and ordinary cars is constructed on each OD pair w and

[0158] Step 6.3: Traffic equilibrium solution. In the initial travel path set and Solve the traffic equilibrium and get the traffic flow on each road under traffic equilibrium and the travel costs of electric vehicles and ordinary cars on the path and

[0159] Step 6.4: The current road traffic flow under traffic equilibrium state is When considering the owner's satisfaction on OD pair w, the optimal paths p and q of electric vehicles and ordinary cars are solved, and the travel cost of the optimal path is obtained and If satisfied and Add paths p and q to and The condition for the iteration to terminate is that all OD pairs in the traffic network do not meet the above conditions; otherwise, return to step three.

[0160] Step 6.5: Charging load statistics. According to the current traffic equilibrium state, record the path and road traffic volume, as well as the charging station selected by the electric vehicle on each travel path, and the charging power to obtain the charging load of the electric vehicle on the coupling node.

[0161] Step 6.6: Write down the constraints. After linearizing the constraints, write down the traffic balance constraints, grid safety operation constraints, road capacity expansion, line capacity expansion, and new charging pile constraints. If the actual traffic volume on the road exceeds the capacity limit, return to step 6.2.

[0162] Step 6.7: Output results: Based on the objective function and constraints of the extended planning model, the Cplex software package is called on Matlab to solve and record the optimal extended planning results.

[0163] 2. In order to verify the beneficial effects of the method of the present invention, the following simulation experiments were carried out:

[0164] The present invention considers using the 13-node Nguyen-Dupuis transportation network and the IEEE 33-node distribution network to construct a coupling network to simulate and analyze the proposed planning method. Figure 3 As shown in the figure, the planning period y = 10 years, and the discount rate r = 0.08.

[0165] In the transportation network, the road expansion cost c1=7×10 5 RMB / unit; charging pile unit cost c2=3×10 4 Yuan / unit; the unit time cost of road travel ω=80 yuan / hour. The maximum number of single road expansion σ a,max =3; the battery capacity of the electric vehicle is 30kWh, the power consumption is 0.2kWh / km, and the initial SOC is assumed to follow a normal distribution (0.6, 0.12) and the minimum power threshold SOC φ Normal distribution (0.25, 0.12)

[0166] In the distribution network, the upper limit of the node voltage amplitude and lower limit v i =0.95; voltage amplitude of the balancing node v1 = 1.05; cost of new distribution network line c3 = 1.8 × 10 6 Yuan, the maximum number of new lines between two nodes n ij,max =3; Substation expansion cost c4 = 800 yuan / kVA, It is equal to the constant load demand when no new charging piles are added. The active power flow limit of lines D1-D2, D2-D3, D3-D4, D4-D5 and D5-D6 is set to 8pu, and the active power flow limit of the remaining lines is set to 1.8pu.

[0167] The basic parameters of the road are shown in the following table:

[0168] Table 1 Basic parameters of roads

[0169]

[0170]

[0171] The travel demand of electric vehicles and ordinary cars is shown in the following table:

[0172] Table 2 Travel demand of electric vehicles and ordinary cars

[0173]

[0174] The basic parameters of the charging station are shown in the following table

[0175] Table 3 Basic parameters of charging station

[0176]

[0177] The coupling node information is shown in the following table

[0178] Table 4 Coupling node information

[0179]

[0180] This paper considers five different traffic travel scenarios under traffic equilibrium, that is, when the travel demand of ordinary cars between OD pairs remains unchanged, the travel demand of electric vehicles increases by 0%, 25%, 50%, 75% and 100% respectively, to simulate the expansion planning strategy of electric vehicles under different travel penetration rates in the power-traffic coupling network. The investment cost results of the expansion planning model are as follows Figure 4 As shown in Figure 2, the corresponding road expansion, new charging piles and new distribution network lines are as follows: Figure 5 Shown

[0181] exist Figure 4 In the 2016 study, with the increase in demand for electric vehicles, the investment costs in the expansion planning model showed an increasing trend. Among them, the cost of road expansion and the cost of new distribution network lines accounted for the majority of the total investment cost, indicating that the expansion planning strategy needs to increase investment in these two aspects to meet the increase in traffic load and charging load caused by the increase in demand for electric vehicles. Figure 5 The number of expansions of various facilities has increased with the increase in demand for electric vehicle travel, indicating that they need to be continuously expanded to cope with the growing charging demand and traffic load.

[0182] The specific locations and quantities of traffic road expansion in different electric vehicle travel scenarios are shown in the following table

[0183] Table 5 Road expansion planning strategies

[0184]

[0185]

[0186] As can be seen from the table, each road that needs to be expanded can meet the scenario of a 100% increase in electric vehicle travel demand after one expansion. In addition, the number of road expansions in the transportation network does not increase monotonically with the increase in electric vehicle travel traffic, such as in the scenarios where the electric vehicle travel demand increases by 25%, 50%, and 75%. Because when the road capacity is expanded, the original road capacity increases, but the traffic volume passing through the road under traffic equilibrium will not increase exponentially to exceed the road capacity after expansion.

[0187] Figure 6 and Figure 7 The actual traffic volume of each road under the scenarios of 0% and 100% increase in electric vehicle travel demand is given. As the demand for electric vehicle travel increases, the traffic volume of each road section will increase, causing the actual traffic volume of the road to exceed the upper limit of the traffic capacity. Therefore, the expansion planning strategy needs to expand the capacity of these roads. In the scenario of 0% increase in electric vehicle travel, 8 roads need to be expanded, and in the scenario of 100% increase in electric vehicle travel, 11 roads need to be expanded. The travel time before and after the road expansion in the two scenarios is as follows Figure 8 and Fig. 9 shown.

[0188] exist Figure 8 and Fig. 9 In the figure, when traffic is balanced, the travel time of the road without capacity expansion will increase with the increase of electric vehicle travel demand. For example, the travel time of Road 3 is 15.3 minutes when the electric vehicle travel increases by 0%, and the travel time reaches 24.5 minutes when the electric vehicle travel demand increases by 100%. The travel time of the road in both scenarios is reduced after the road capacity expansion, which improves the convenience of car owners' travel, indicating the effectiveness of road capacity expansion in the expansion planning model.

[0189] The number of new charging piles in each charging station under the five scenarios is shown in the following table

[0190] Table 6 Charging pile expansion planning strategy

[0191]

[0192] As can be seen from the table, with the increase in demand for electric vehicle travel, the number of charging piles in charging stations NO.1, NO.2, NO.3 and NO.5 has increased accordingly, and charging station NO.1 has the largest number of new charging piles, because the transportation network node where it is located has multiple paths passing through and more charging needs passing through. Fig.10 The charging queue time before and after the addition of charging piles in different scenarios is given. The number of charging piles at charging station No. 4 is sufficient to meet the growing charging demand, so it does not need to add more.

[0193] exist Fig.10 In the data, when no new charging piles were added to charging station No. 1, there was a long charging queue time in all scenarios. After the addition of new charging piles, the waiting time at the charging station will be greatly reduced, which shows that the expansion planning strategy of adding new charging piles can effectively improve the charging experience of car owners and increase the convenience of charging.

[0194] The specific locations and quantities of new distribution network lines in different scenarios are shown in the following table

[0195] Table 7 Distribution network line expansion planning strategy

[0196]

[0197] In the table, when the electric vehicle travel demand increases by 25% and 75%, no additional distribution network lines are needed to meet the additional charging load, because the distribution network expansion planning strategy can meet these two scenarios under the scenarios of 0% and 50% increase in electric vehicle travel demand. Under the coupled network, the charging demand brings new loads to the power nodes. As the electric vehicle travel demand increases by 100%, a large amount of charging load will be generated at this time, which will affect the distribution network flow and exceed the line active power flow limit. Therefore, new construction is required for lines D6-D7, D7-D8, D6-D26, D26-D27, D27-D28 and D28-D29 to ensure that electricity can be continuously delivered to the charging stations.

[0198] The specific embodiments described in the present invention are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in similar ways, but they will not deviate from the spirit of the present invention or exceed the scope defined by the attached claims.

Claims

1. A method for planning the expansion of a power-transportation coupling network considering traffic balance, characterized in that: A coupling network is constructed with the transportation network and the distribution network, in which the power flow form of the distribution network adopts the Distflow power flow form; Taking the minimum sum of expansion planning costs in the expansion planning model of the established power-transportation coupling network as the optimization goal, taking traffic balance constraints, power grid safety operation constraints, road expansion constraints, line expansion constraints, new charging pile constraints, linear and nonlinear constraints of the expansion planning model as constraints, solving the optimal solution of the model to obtain the optimal expansion plan; The establishment of the extended planning model is based on solving a traffic equilibrium model, specifically: Construct a travel path selection network and establish an optimal travel path generation model that takes into account the satisfaction of car owners; Based on the user equilibrium principle of hybrid electric vehicles and ordinary cars, the traffic equilibrium model of hybrid electric vehicles and ordinary cars is constructed by considering the road congestion effect, the charging station congestion effect and the road expansion model. Solve the traffic equilibrium under the optimal path to obtain the steady-state traffic flow distribution; Record the routes and road traffic volume, as well as the charging stations selected by electric vehicles on each travel route, and the charging power to obtain the charging load on the coupling node; build an expansion planning model for the power-transportation coupling network; the model includes the road travel time cost, road expansion cost, new charging pile cost, substation expansion cost and new distribution network line cost; The expansion planning model of the power-transportation coupling network is: minF=C TN +C PDN Where: F is the total cost of the expansion plan; C TN Planning costs for transportation network expansion; C PDN Planning costs for distribution network expansion; The cost expression of transportation network expansion planning is: Where: κ is the discount factor; c1 is the unit cost of road expansion; c2 is the unit cost of new charging piles; h s is the number of new charging piles at charging station s; r is the discount rate; y is the depreciation period; The cost expression of distribution network expansion planning is: Where: c3 is the unit cost of the new line; n ij is the number of new lines between nodes i and j, which are expanded in parallel with the existing distribution network lines and have the same line parameters as the existing lines; c4 is the unit cost of substation expansion; is the expansion capacity of the substation; K s P is the substation assembly; k,e The power of the newly added charging piles in the charging station serving substation k; is the remaining capacity of substation k; The system constraints are: The traffic equilibrium model constraints are In the above formula: the first line is the conservation constraint of vehicle travel flow; the second line is the conservation constraint of road flow and path flow in the traffic network; the third line is the road capacity constraint; Road expansion and new distribution network line quantity constraints 0≤σ a ≤σ a,max 0≤n ij ≤n ij,max Where: a,max The upper limit of the number of expansions for road a; n ij,max is the upper limit of the number of new distribution network lines between nodes i and j; New charging pile constraints are x s ≤(h s +h s,0 )p s Where: h s,0 is the number of existing charging piles in the charging station; The branch power flow of the distribution network adopts the Distflow power flow form, without considering the line loss. The simplified distribution network safety operation constraint is: Where: v i and are the lower and upper limits of the voltage amplitude at node i respectively; P ij is the active power capacity between nodes i and j; is the upper limit of the active power capacity of the line between nodes i and j; r ij and x ij are the resistance and reactance of the line respectively; P j and Q j are the active and reactive power requirements at node j respectively; v i and v j is the voltage amplitude of nodes i and j; p ij and q ij is the active and reactive power flow between nodes i and j; D N is the node set of the distribution network; D A is a collection of lines in the distribution network; (i, j) is the line between nodes i and j; v1 is the voltage amplitude of the equilibrium node; π(j) is the set of branch lines flowing out of node j; p jm and q jm are the active and reactive power on branch (j, m) respectively; P i and They are the total active power demand and the active power demand of conventional load at distribution network node i respectively.

2. A method for planning an expansion of a power-transportation coupling network considering traffic balance according to claim 1, characterized in that: The congestion effect of charging stations is: Where: Average waiting time in queues for charging stations; is a binary variable. When the electric vehicle on path p chooses to charge at charging station s, Otherwise 0; x s The power required for the current electric vehicle to charge at charging station s; c s is the capacity of the charging station s.

3. A method for planning the expansion of a power-transportation coupling network considering traffic balance according to claim 2, characterized in that: The road expansion model is: Where: t a represents the time when the vehicle passes through road a; is the free travel time of road a, which refers to the time when the current traffic volume of the road is not greater than the upper limit of the traffic capacity; x a is the traffic volume of road a; c a is the upper limit of the original traffic capacity of road a; σ a represents the number of road a expansions, σ a ≥0; Δc represents the road capacity that can be increased by expanding road a.

4. The method for planning the expansion of a power-transportation coupling network considering traffic balance according to claim 3, characterized in that: The user equilibrium principle of hybrid electric vehicles and ordinary cars is: Where: and are the travel costs of paths p and q on OD pair w respectively; and are the travel costs of OD for electric vehicles and ordinary cars on w in the equilibrium state; and are the traffic flows on path p and path q respectively; Available paths for electric vehicles, that is, paths for electric vehicles with charging requirements are taken as available paths; is the available path for an ordinary car; W is the set of all OD pairs in the traffic network, and w represents one of the OD pairs.

5. The method for planning the expansion of a power-transportation coupling network considering traffic balance according to claim 4, characterized in that: The traffic equilibrium model of hybrid electric vehicles and ordinary cars is: Where: ω is the unit time cost; a represents a road in traffic; T a represents the road set in the transportation network; S is the set of coupling nodes between the transportation network and the distribution network; is the charging power of the electric vehicle at charging station s on path p; θ is the electricity price of charging station s; g w and h w are the travel demands of electric vehicles and ordinary vehicles on OD pair w respectively; and are binary variables that associate paths with roads, i.e., they are 1 when paths p and q pass through road a, and 0 otherwise.

6. A method for planning the expansion of a power-transportation coupling network considering traffic balance according to claim 5, characterized in that: The travel path selection network model is Where: SOC O is the initial power of the electric vehicle at the starting node; is the distance from the starting node to the charging station s on the path p; L p is the total distance of path p; Q is the power consumption of the electric vehicle per kilometer; SOC φ This is the minimum battery charge threshold that the car owner can accept.

7. A method for planning the expansion of a power-transportation coupling network considering traffic balance according to claim 6, characterized in that: The optimal path models considering the satisfaction of electric car and ordinary car owners are: Where: is the current road traffic volume; p s is the charging power of charging station s; is a binary variable. When path p passes through road a, Otherwise 0.

8. The method for planning the expansion of a power-transportation coupling network considering traffic balance according to claim 7, characterized in that: The nonlinear constraints and nonlinear models are linearized as follows: Where: Δx a and τ a (m,n) are auxiliary variables, where τ a (m,n) is a binary variable, indicating the segment position in the two-dimensional plane; m and n are x a and σ a The current segment number; Voltage Drop Constrained Linearization Where: is a binary variable that satisfies and is a continuous variable, satisfying Linearization of Substation Expansion Function Where: δ is a binary variable.

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