Electricity-hydrogen production and charging integrated station and electricity-hydrogen-road-vehicle collaborative planning method

Abstract

The invention provides an electricity-hydrogen production and charging integrated station and electricity-hydrogen-road-vehicle collaborative planning method, which comprises the following steps: firstly, establishing a time-flow model to analyze a topological structure of a traffic road, and simulating a driving path of a new energy vehicle in real time by adopting a Dijkstra algorithm, so as to establish a new energy vehicle electricity-hydrogen demand prediction model considering vehicle-road-network coupling; secondly, analyzing the whole process of hydrogen preparation, compression and storage, and constructing an operation framework and an energy flow model of the electro-hydrogen preparation and charging integrated station; then, establishing a regional power-hydrogen production and charging integrated station planning model with minimum economic costs such as investment, operation, network loss and the like as a target, considering road-network coupling constraints, power distribution network and power-hydrogen production and charging integrated station equipment safety operation constraints, and solving an optimal planning scheme by using a second-order cone relaxation technology; and finally, the optimal site and equipment capacity planning result of the electricity-hydrogen production and charging integrated station in the area is obtained according to the actual condition of part of the trunk road in the urban area of a certain city, the station is promoted to carry vehicles, and the development of new energy vehicles is promoted.

Description

Technical Field

[0001] The present invention belongs to the technical field of planning of electric hydrogen production and filling integrated stations, and specifically relates to a method for coordinated planning of electric hydrogen production and filling integrated stations and electricity-hydrogen-road-vehicle. Background Art

[0002] With the green transformation of the energy structure and the proposal of the dual carbon goals, new energy vehicles have received widespread attention as the key to decarbonization in the transportation sector. Under the background of low-carbon travel, traveling by new energy vehicles has become the mainstream of today's era. The development of new energy vehicles requires the support of multiple technically mature electric hydrogen production and filling integrated stations. New energy vehicles mainly use two clean energy sources, electricity and hydrogen, to replace traditional fuel power, effectively reducing the use of fossil fuels. At the same time, both electricity and hydrogen are secondary energy sources, with a wide range of production methods and no pollution during use. The energy demand of new energy vehicles will not only affect the road traffic of the transportation network, but also affect the operating status of the distribution network. When studying the spatiotemporal distribution prediction of the charging demand of new energy vehicles, it is necessary to consider the "vehicle-road-network" coupling.

[0003] At the same time, hydrogen refueling stations can be divided into hydrogen production outside the energy station and hydrogen production inside the energy station according to the location of the hydrogen production process. Among them, hydrogen production outside the station needs to rely on long-tube trailers to transport hydrogen, which increases transportation costs and safety risks. At the same time, since new energy vehicles are currently dominated by electric vehicles, the market share of hydrogen fuel cell vehicles is small, and the cost of establishing a separate hydrogen refueling station infrastructure is high. Therefore, integrating power grid power supply, electric vehicle charging, in-station production, compression, storage of hydrogen, and fuel cell vehicle hydrogenation to build an integrated electric hydrogen production and filling station can effectively reduce operating costs. The integrated electric hydrogen production and filling station involves three processes: energy production, conversion, and consumption. The power distribution of the distribution system, the energy flow of various equipment inside the integrated station, and the spatial and temporal distribution of electric hydrogen demand for new energy vehicles will affect the site selection and capacity planning of the integrated station, making the site selection and capacity planning of the charging station face great challenges. Summary of the invention

[0004] The purpose of the present invention is to design an integrated electric hydrogen production and filling station and a method for coordinated planning of electricity-hydrogen-road-vehicle.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle, characterized in that: the planning method is as follows:

[0007] S1: Analyze the battery parameters, charging characteristics and driving characteristics of electric and hydrogen new energy vehicles, and analyze and probabilistically model their travel and charging patterns;

[0008] S2: Introduce the time-flow model to analyze the topological structure of traffic roads according to the characteristics of urban road networks, and build models of new energy vehicles, transportation networks and distribution networks;

[0009] S3: Based on the start and destination nodes assigned to the new energy vehicles, the real-time Dijkstra algorithm is used to search for the path with the minimum travel time between the two points to characterize the dynamic driving trajectory of the vehicle;

[0010] S4: Based on the battery parameters and charging characteristics of new energy vehicles, Monte Carlo sampling was used to simulate the travel of new energy vehicles, and a new energy vehicle electric hydrogen demand prediction model considering vehicle-road-network coupling was established;

[0011] S5: Analyze the energy flow relationship between energy production, hydrogen production and filling stations, and energy consumption, and build an operation framework with the three as the main body;

[0012] S6: Considering the whole process of hydrogen production, compression and storage, an energy flow model of the electric hydrogen production and filling station is constructed;

[0013] S7: Establish a regional hydrogen production and filling station planning model with the goal of minimizing economic costs such as investment, operation, and network loss, and impose road-network coupling constraints, distribution network, and hydrogen production and filling station equipment safety operation constraints;

[0014] S8: Aiming at the problem of voltage and current nonlinear constraints in the regional electric hydrogen production and filling integrated station planning model, the second-order cone relaxation method is used to transform the mixed integer nonlinear programming model into a mixed integer second-order cone programming model for solution;

[0015] S9: Taking some main roads in a city as an example, the temporal and spatial distribution of the electric hydrogen demand of new energy vehicles in the area is predicted through examples;

[0016] S10: Determine the optimal site and equipment capacity planning of the integrated hydrogen production and filling station based on the forecast results of the spatiotemporal distribution of regional new energy vehicle hydrogen demand.

[0017] Furthermore, the specific steps in S1 are as follows:

[0018] 1) Analyze the battery parameters of electric and hydrogen new energy vehicles, mainly involving various performance parameters such as capacity, power, energy density, internal resistance, voltage, current, and hydrogen storage capacity;

[0019] 2) Analyze the charging characteristics of electric and hydrogen new energy vehicles. The charging methods of pure electric vehicles mainly include vehicle charging mode and battery replacement mode. Hydrogen fuel cell vehicles are divided into three categories according to the refueling pressure level. The pressure levels of hydrogen refueling stations can be divided into 35MPa, 70MPa and compatible with 35MPa / 70MPa.

[0020] 3) Analyze the driving characteristics of electric and hydrogen new energy vehicles, including initial charge state, charging time, start charging time, etc., and analyze and probabilistically model their travel and charging patterns;

[0021] The charging time can be expressed as:

[0022]

[0023] Where: L EV is the driving distance of the electric vehicle; T c is the charging time; E is the power consumption of the electric vehicle per 100 kilometers; P ch It is the charging power of electric vehicles, which is related to the charging method of electric vehicles; Q c is the rated capacity of the electric vehicle battery; SOC c SOC is the desired state of charge of an electric vehicle. t is the state of charge of the electric vehicle at time t;

[0024] The start charging time can be expressed as:

[0025] t c =t start +Δt (38)

[0026] Where: t c is the charging start time; t start is the start time of travel; Δt is the travel time.

[0027] Furthermore, the specific method of S2 is as follows:

[0028] 1) The topological structure characteristics of traffic roads are described by the principle of graph theory. In view of the complex and changeable characteristics of urban road networks, a time-flow model is introduced; the time-flow model is introduced as a road impedance model, which is composed of a section impedance model and a node impedance model;

[0029] The road section impedance model can be expressed as:

[0030]

[0031] Where: k is the traffic saturation evaluation index of urban road sections; t0 is the zero flow travel time, that is, the road section travel time when the traffic flow is zero; is the impedance of the road section from node i to node j in the road network; α and β are impedance influencing factors respectively;

[0032] The node impedance model can be expressed as:

[0033]

[0034] Where: is the node impedance of node i; c is the signal period; λ is the green-to-signal ratio; q is the vehicle arrival rate of the road section.

[0035] The urban road impedance model is generated by the road section impedance and the node impedance and can be expressed as:

[0036]

[0037] Where: is the road impedance of section ij, i.e., vehicle travel time;

[0038] 2) Analyze the topological structure of traffic roads and build models of new energy vehicles, transportation networks and distribution networks;

[0039] The coupled model of transportation network and distribution network can be expressed as:

[0040]

[0041] Where: j is the coupling node between the transportation network and the distribution network; i is the transportation network node; P j,t , Q j,t are respectively the active power and reactive power of the total load connected at coupling node j; P i,t,HE is the active power generated at node i in the traffic network at time t; P j,t,base , Q j,t,base are the active power and reactive power of the initial load at coupling node j at time t, respectively.

[0042] Furthermore, the real-time Dijkstra algorithm comprises the following steps:

[0043] 1) According to the traffic network matrix and the travel matrix, the starting and ending nodes of the new energy vehicle are obtained and the real-time road resistance function is calculated. The real-time road resistance function here is the road impedance model mentioned above. The two sets X and Y are used to represent all the nodes in the road network respectively. X is used to record the nodes with the minimum road resistance that have been obtained, and Y is used to represent the nodes whose minimum road resistance has not yet been obtained;

[0044] 2) X contains only the starting node v1, and Y contains nodes v except v1 i (i=2,3,…,n), and the road resistance value of the node in Y from the starting point is L(v1,v i )=W(v1,v i ), where W is the road resistance of all roads;

[0045] 3) Calculate the minimum resistance value from node i to the starting point in W by using formula (5), record the other nodes from node i to the starting point as node m, and record the replacement information f(i)=m;

[0046] L(v1,v i )=min{L(v1,νm )+W(v m ,v i ),L(v1,ν i )} (43)

[0047] Where: v1 is the starting node; ν m is the middle node; v i The destination node.

[0048] 4) Select the node ν with the smallest path resistance from W m , the node ν m Add to set X and remove from Y;

[0049] 5) looping step 3) and step 4) until i=n, ​​and finally obtaining the optimal path for the new energy vehicle to travel from the starting point to the destination from f based on the backtracking method.

[0050] Furthermore, the integrated electric hydrogen production and filling station is a comprehensive energy station integrating power distribution, charging, hydrogen production and storage, and hydrogen refueling. At the same time, the integrated electric hydrogen production and filling station serves as a transmission hub to connect the energy production and energy consumption links, realizing the coordinated operation of electricity, hydrogen, road and vehicle.

[0051] Furthermore, the energy flow model in S6 is as follows:

[0052] The electric energy consumption model of the electrolyzer is expressed as:

[0053] P djc,t =H djc,t L h / η djc (44)

[0054] Where: P djc,t is the input power of the electrolytic cell at time t; H djc,t is the hydrogen production power of the electrolyzer at time t; η djc is the hydrogen production efficiency; L h is the calorific value of hydrogen;

[0055] The compressor model is expressed as:

[0056] H ysj,t =(1-α1)H djc,t (45)

[0057]

[0058] Where: P ysj,t is the power consumption of the compressor at time t; H ysj,t is the amount of hydrogen entering the compressor at time t; H djc,t is the amount of hydrogen produced by the electrolyzer at time t; α1 is the dissipation rate of hydrogen transferred from the equipment; is the power consumed by the compressor at the reference working pressure; f ysj , are the pressure of the compressor under normal working pressure and reference working pressure respectively; f ini is standard atmospheric pressure;

[0059] The hydrogen storage tank model is expressed as:

[0060] E cqg,t+1 =E cqg,t -H out,t +H cqg,t (47)

[0061] H cqg,t =(1-α2)H ysj,t (48)

[0062]

[0063] Where: E cqg,t 、E cqg,t+1 are the amount of hydrogen in the hydrogen storage tank at time t and time t+1 respectively; H out,t is the amount of hydrogen required by the hydrogen fuel cell vehicle at time t; H cqg,t is the amount of hydrogen stored in the hydrogen storage tank at time t; α2 is the dissipation rate of hydrogen during transmission from the equipment; E cqg,N is the rated capacity of the hydrogen storage tank; SOC hs,min and SOC hs,max They are the minimum and maximum charge states of hydrogen energy storage respectively.

[0064] Furthermore, the specific process in S7 is as follows:

[0065] 1) Objective function

[0066] Taking the minimum annual comprehensive total cost as the objective function, it is specifically expressed as:

[0067] G=G tz +G yy +G ws (50)

[0068] Where: G tz The annual fixed investment cost for charging station configuration mainly includes equipment investment and land investment; G yy G is the annual operating cost of the charging station, which mainly includes the cost of purchasing electricity and water during equipment operation; ws The annual network loss cost of the charging station operation;

[0069] The annualized fixed investment cost of the integrated hydrogen production and filling station is expressed as:

[0070]

[0071] g n,djc =α djc ·max t [P n,t,djc ] (52)

[0072] g n,ysj =α ysj ·max t [P n,t,ysj ] (53)

[0073] g n,cqg =α cqg ·max t [E n,t,cqg ] (54)

[0074] g n,zqg =α zqg ·N n,zqj (55)

[0075] g n,cdz =α cdz ·N n,cdz (56)

[0076] g n,td =d td,ξ (β3+β4N n,zqj +N n,cdz ),ξ=(1,2,3) (57)

[0077] Where: γ is the discount rate; λ is the operation planning period of the electric hydrogen filling station; g n,djc , g n,ysj , g n,cqg , g n,zqg , g n,cdz g are the investment and construction costs of the electrolyzer, compressor, hydrogen storage tank, hydrogen injection machine and charging pile of the nth charging station; n,td is the land area required for the nth charging station; α djc , α ysj , α cqg , α zqj , α cdz are the construction costs of electrolyzer, compressor, hydrogen storage tank, hydrogen injection machine and charging pile per unit capacity or quantity; max t [P n,t,djc ]、max t [P n,t,ysj ]、max t [E n,t,cqg ] are the rated capacities of the electrolyzer, compressor and hydrogen storage tank of the nth electric hydrogen production and filling integrated station; N n,zqj 、N n,cdzare the total number of hydrogen injectors and charging piles in the nth hydrogen production and charging integrated station; d td,ξ is the unit area cost of the ξth type of land, ξ is 1, 2, 3, 1 is residential area, 2 is commercial area, and 3 is office area; β3 and β4 are land cost coefficients;

[0078] The operating cost of the electric hydrogen filling station can be expressed as:

[0079]

[0080] Where: g n,e , g n,w are the electricity cost and water cost of the nth electric hydrogen production and filling integrated station respectively; D is the planned number of days, which is 365; H n,t P is the hydrogen demand of the nth electric hydrogen filling station at time t; n,t,djc , P n,t,ysj They represent the electric power of the electrolyzer and compressor of the nth electric hydrogen production and filling integrated station at time t; P c is the power consumption rate of the cooling system; η h is the efficiency of the cooling system; P n,t,ev is the electric load required for the electric vehicle to arrive at the nth electric hydrogen production and filling station for charging at time t; β1 is the industrial electricity price; β2 is the industrial water price; W n,t,djc , W n,t,ysj The water consumption required by the electrolyzer and compressor of the nth electric hydrogen production and filling integrated station when producing and compressing hydrogen at time t; are the purified water coefficients for electrolyzer and compressor respectively;

[0081] The network loss cost can be expressed as:

[0082]

[0083] Where: c L is the unit network loss cost of the system; P loss,ij,t,n is the active power loss of branch ij in time period t, with T0 as the step length, T0 is 15min, and one day is divided into T time periods, T is 96;

[0084] 2) Constraints

[0085] The distance constraint of the electric hydrogen filling station is expressed as:

[0086] L min <L<L C (65)

[0087] Where: L is the actual distance between two charging stations; L min is the minimum distance between two charging stations; L CThe mileage that a new energy vehicle can travel with the minimum remaining fuel;

[0088] The quantity constraints of hydrogen injection machines and charging piles are expressed as:

[0089] N n,zqj ≥C n,t,hfcv (66)

[0090] N n,cdz ≥C n,t,ev (67)

[0091] Where: N n,zqj 、N n,cdz They represent the number of hydrogen injectors and charging piles built in the nth hydrogen production and charging station; C n,t,hfcv , C n,t,ev are the number of hydrogen fuel cell vehicles and electric vehicles arriving at the nth electric hydrogen production and filling station at time t, respectively;

[0092] Voltage constraints and current constraints can be expressed as:

[0093] U t,i,min ≤U t,i ≤U t,i,max (68)

[0094]

[0095] Where: U t,i,min , U t,i,max are the minimum voltage and maximum voltage allowed at node i at time t; I ij,min ,I ij,max are the minimum current and maximum current allowed for branch ij respectively;

[0096] The upper and lower power constraints and ramp constraints of the electrolyzer at n in the integrated station can be expressed as:

[0097]

[0098] Where: p t,n,djc 、p t-1,n,djc They are respectively represented as the output of the electrolytic cell at location n in the integrated station at time t and t-1; are the upper and lower limits of its output respectively; are the start and stop states of the electrolyzer respectively; is the climbing power of the electrolyzer at location n in the integrated station;

[0099] The power balance constraint can be expressed as:

[0100]

[0101] Where: P i,t,djc , P i,t,ysjRespectively represent the electric power of the electrolyzer and compressor at the traffic node i at time t; P c is the power consumption rate of the cooling system; η h is the efficiency of the cooling system; P i,t,EV is the electric load required by the electric vehicle arriving at traffic node i at time t.

[0102] The following beneficial effects can be obtained through the above technical solution:

[0103] Aiming at the fact that the supply of energy demand for new energy vehicles is affected by the layout planning of basic energy charging facilities, the present invention proposes a planning method for an electric hydrogen production and filling integrated station that considers the coordination of electricity, hydrogen, road and vehicle. Firstly, a time-flow model is established to analyze the topological structure of traffic roads, and the Dijkstra algorithm is used to simulate the driving path of new energy vehicles in real time, so as to establish a prediction model for the electric hydrogen demand of new energy vehicles that considers vehicle-road-network coupling; secondly, the whole process of producing, compressing and storing hydrogen is analyzed, and the operation architecture and energy flow model of the electric hydrogen production and filling integrated station are constructed; then, a regional electric hydrogen production and filling integrated station planning model is established with the goal of minimizing economic costs such as investment, operation and network loss, taking into account the road-network coupling constraints, the distribution network and the electric hydrogen production and filling integrated station equipment safety operation constraints, and using the second-order cone relaxation technology to solve the optimal planning scheme; finally, based on the actual situation of some trunk roads in the urban area of ​​a certain city, the optimal site and equipment capacity planning results of the electric hydrogen production and filling integrated station in the region are obtained, so as to promote the development of new energy vehicles by promoting the use of stations to drive vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] Figure 1 is a flow chart of the method in the present invention;

[0105] Figure 2 Flow chart of the spatiotemporal distribution prediction model for electric hydrogen demand of new energy vehicles;

[0106] Figure 3 It is a vehicle-road-network collaborative operation system;

[0107] Figure 4 This is a topological map of some main roads in a city;

[0108] Figure 5 The number of new energy vehicles that need to be charged at each time point. DETAILED DESCRIPTION

[0109] The following is attached Figure 1-Figure 5 The present invention is further described with examples:

[0110] This implementation example provides a method flow for coordinated planning of an electric-hydrogen production and filling integrated station and electric-hydrogen-road-vehicle. Figure 1 As shown, the following steps are included:

[0111] (1) Analyze the battery parameters, charging characteristics, and driving characteristics of electric and hydrogen new energy vehicles, and analyze and probabilistically model their travel and charging patterns;

[0112] Step (1) comprises the following steps:

[0113] 1) Analyze the battery parameters of electric and hydrogen new energy vehicles, mainly involving various performance parameters such as capacity, power, energy density, internal resistance, voltage, current, and hydrogen storage capacity;

[0114] 2) Analyze the charging characteristics of electric and hydrogen new energy vehicles. The charging methods of pure electric vehicles mainly include vehicle charging mode and battery replacement mode. Hydrogen fuel cell vehicles are divided into three categories according to the refueling pressure level. The pressure levels of hydrogen refueling stations can be divided into 35MPa, 70MPa and compatible with 35MPa / 70MPa.

[0115] 3) Analyze the driving characteristics of electric and hydrogen new energy vehicles, including initial charge state, charging time, start charging time, etc., and analyze and probabilistically model their travel and charging patterns;

[0116] The charging time can be expressed as:

[0117]

[0118] Where: L EV is the driving distance of the electric vehicle; T c is the charging time; E is the power consumption of the electric vehicle per 100 kilometers; P ch It is the charging power of electric vehicles, which is related to the charging method of electric vehicles; Q c is the rated capacity of the electric vehicle battery; SOC c SOC is the desired state of charge of an electric vehicle. t is the state of charge of the electric vehicle at time t.

[0119] The start charging time can be expressed as:

[0120] t c =t start +Δt (74)

[0121] Where: t c is the charging start time; t start is the start time of travel; Δt is the travel time.

[0122] (2) In view of the complex and changeable characteristics of urban road networks, a time-flow model is introduced to analyze the topological structure of traffic roads, and models of new energy vehicles, transportation networks, and distribution networks are constructed;

[0123] Step (2) comprises the following steps:

[0124] 1) The topological structure characteristics of traffic roads are described by the principle of graph theory. In view of the complex and changeable characteristics of urban road networks, a time-flow model is introduced; the time-flow model is introduced as a road impedance model, which is composed of a section impedance model and a node impedance model;

[0125] The road section impedance model can be expressed as:

[0126]

[0127] Where: k is the traffic saturation evaluation index of urban road sections; t0 is the zero flow travel time, that is, the road section travel time when the traffic flow is zero; is the impedance of the road section from node i to node j in the road network; α and β are the impedance influencing factors respectively.

[0128] The node impedance model can be expressed as:

[0129]

[0130] Where: is the node impedance of node i; c is the signal period; r is the green-to-signal ratio; q is the vehicle arrival rate of the road section.

[0131] The urban road resistance model is generated by the road section impedance and node impedance and can be expressed as:

[0132]

[0133] Where: is the road impedance of section ij, i.e., the vehicle travel time.

[0134] 2) Analyze the topological structure of traffic roads and build models of new energy vehicles, transportation networks and distribution networks.

[0135] The models of new energy vehicles, transportation networks and distribution networks can be expressed as:

[0136]

[0137] Where: j is the coupling node between the transportation network and the distribution network; i is the transportation network node; P j,t , Q j,t are respectively the active power and reactive power of the total load connected at coupling node j; P i,t,HE is the active power generated at node i in the traffic network at time t; P j,t,base , Q j,t,base are the active power and reactive power of the initial load at coupling node j at time t, respectively.

[0138] (3) According to the start and destination nodes assigned to the new energy vehicle, the real-time Dijkstra algorithm is used to search for the path with the minimum travel time between the two points to characterize the dynamic driving trajectory of the vehicle. The specific real-time Dijkstra algorithm includes the following steps:

[0139] 1) According to the traffic network matrix and the travel matrix, the starting node of the new energy vehicle is obtained and the real-time road resistance function is calculated. The two sets X and Y are used to represent all the nodes in the road network. X is used to record the nodes with the minimum road resistance that have been obtained, and Y is used to represent the nodes whose minimum road resistance has not yet been obtained.

[0140] 2) X contains only the starting node v1, and Y contains nodes v except v1 i (i=2,3,…,n), and the road resistance value of the node in Y from the starting point is L(v1,v i )=W(v1,v i ), where W is the road resistance of all roads.

[0141] 3) The minimum path resistance from node i to the starting point in W is calculated by formula (5), and the other nodes on the path from node i to the starting point are recorded as nodes m, and the replacement information f(i)=m is recorded.

[0142] L(v1,v i )=min{L(v1,ν m )+W(v m ,v i ),L(v1,ν i )} (79)

[0143] Where: v1 is the starting node; ν m is the middle node; v i The destination node.

[0144] 4) Select the node ν with the smallest path resistance from W m , the node ν m Adds to set X and removes it from set Y.

[0145] 5) looping step 3) and step 4) until i=n, ​​and finally obtaining the optimal path for the new energy vehicle to travel from the starting point to the destination from f based on the backtracking method.

[0146] (4) Monte Carlo sampling was used to simulate the travel of new energy vehicles based on the battery parameters and charging characteristics of new energy vehicles, and a new energy vehicle electric hydrogen demand prediction model considering vehicle-road-network coupling was established;

[0147] (5) Analyze the three links of energy production, electric hydrogen production and filling station, and energy consumption, consider the energy flow relationship between electric hydrogen, and build an operation framework with the three as the main body; the electric hydrogen production and filling station is a comprehensive energy station integrating power distribution, charging, hydrogen production and storage, and hydrogen refueling. At the same time, the electric hydrogen production and filling station is used as a transmission hub to connect the energy production and energy consumption links to achieve the coordinated operation of electricity, hydrogen, road and vehicle. Based on this architecture, the distribution network is coupled with the transportation network, and electric energy and hydrogen energy are coupled to realize the conversion of electric hydrogen energy or the direct use of electric energy, thereby meeting the daily charging needs of new energy vehicles.

[0148] (6) Considering the entire process of hydrogen production, compression and storage, an energy flow model of the electric hydrogen production and filling station is constructed;

[0149] The electric energy consumption model of the electrolyzer can be expressed as:

[0150] P djc,t =H djc,t L h / η djc (80)

[0151] Where: P djc,t is the input power of the electrolytic cell at time t; H djc,t is the hydrogen production power of the electrolyzer at time t; η djc is the hydrogen production efficiency; L h is the calorific value of hydrogen.

[0152] The compressor model can be expressed as:

[0153] H ysj,t =(1-α1)H djc,t (81)

[0154]

[0155] Where: P ysj,t is the power consumption of the compressor at time t; H ysj,t is the amount of hydrogen entering the compressor at time t; H djc,t is the amount of hydrogen produced by the electrolyzer at time t; α1 is the dissipation rate of hydrogen transferred from the equipment; is the power consumed by the compressor at the reference working pressure; f ysj , are the pressure of the compressor under normal working pressure and reference working pressure respectively; f ini is standard atmospheric pressure.

[0156] The hydrogen storage tank model can be expressed as:

[0157] E cqg,t+1 =E cqg,t -H out,t +Hcqg,t (83)

[0158] H cqg,t =(1-α2)H ysj,t (84)

[0159]

[0160] Where: E cqg,t 、E cqg,t+1 are the amount of hydrogen in the hydrogen storage tank at time t and time t+1 respectively; H out,t is the amount of hydrogen required for the hydrogen fuel cell vehicle at time t; H cqg,t is the amount of hydrogen stored in the hydrogen storage tank at time t; α2 is the dissipation rate of hydrogen during transmission from the equipment; E cqg,N is the rated capacity of the hydrogen storage tank; SOC hs,min and SOC hs,max They are the minimum and maximum charge states of hydrogen energy storage respectively.

[0161] (7) Establish a regional hydrogen production and filling station planning model with the goal of minimizing economic costs such as investment, operation, and network loss, and take into account the road-network coupling constraints, distribution network, and hydrogen production and filling station equipment safety operation constraints. The specific process is as follows:

[0162] 1) Objective function

[0163] Taking the minimum annual comprehensive total cost as the objective function, it can be specifically expressed as:

[0164] G=G tz +G yy +G ws (86)

[0165] Where: G tz The annual fixed investment cost for charging station configuration mainly includes equipment investment and land investment; G yy G is the annual operating cost of the charging station, which mainly includes the cost of purchasing electricity and water during equipment operation; ws It is the annual network loss cost of the charging station operation.

[0166] The annualized fixed investment cost of the integrated hydrogen production and filling station can be expressed as:

[0167]

[0168] g n,djc =α djc ·max t [P n,t,djc ] (88)

[0169] g n,ysj =α ysj ·maxt [P n,t,ysj ] (89)

[0170] g n,cqg =α cqg ·max t [E n,t,cqg ] (90)

[0171] g n,zqg =α zqg ·N n,zqj (91)

[0172] g n,cdz =α cdz ·N n,cdz (92)

[0173] g n,td =d td,ξ (β3+β4N n,zqj +N n,cdz ),ξ=(1,2,3) (93)

[0174] Where: γ is the discount rate; λ is the operation planning period of the electric hydrogen filling station; g n,djc , g n,ysj , g n,cqg , g n,zqg , g n,cdz g are the investment and construction costs of the electrolyzer, compressor, hydrogen storage tank, hydrogen injection machine and charging pile of the nth charging station; n,td is the land area required for the nth charging station; α djc , α ysj , α cqg , α zqj , α cdz are the construction costs of electrolyzer, compressor, hydrogen storage tank, hydrogen injection machine and charging pile per unit capacity or quantity; max t [P n,t,djc ]、max t [P n,t,ysj ]、max t [E n,t,cqg ] are the rated capacities of the electrolyzer, compressor and hydrogen storage tank of the nth electric hydrogen production and filling integrated station; N n,zqj 、N n,cdz are the total number of hydrogen injectors and charging piles in the nth hydrogen production and charging integrated station; d td,ξ is the unit area cost of the ξth type of land, ξ takes 1, 2, or 3, 1 is the residential area, 2 is the commercial area, and 3 is the office area; β3 and β4 are the land cost coefficients.

[0175] The operating cost of the electric hydrogen filling station can be expressed as:

[0176]

[0177] Where: g n,e , g n,w are the electricity cost and water cost of the nth electric hydrogen production and filling integrated station respectively; D is the planned number of days, which is 365; H n,t P is the hydrogen demand of the nth electric hydrogen filling station at time t; n,t,djc , P n,t,ysj They represent the electric power of the electrolyzer and compressor of the nth electric hydrogen production and filling integrated station at time t; P c is the power consumption rate of the cooling system; η h is the efficiency of the cooling system; P n,t,ev is the electric load required for the electric vehicle to arrive at the nth electric hydrogen production and filling station for charging at time t; β1 is the industrial electricity price; β2 is the industrial water price; W n,t,djc , W n,t,ysj The water consumption required by the electrolyzer and compressor of the nth electric hydrogen production and filling integrated station when producing and compressing hydrogen at time t; are the purified water coefficients for electrolyzer and compressor respectively.

[0178] The network loss cost can be expressed as:

[0179]

[0180]

[0181] Where: c L is the unit network loss cost of the system; P loss,ij,t,n is the active power loss of branch ij in time period t, with T0 as the step length, T0 is 15 minutes, and a day is divided into T time periods, T is 96.

[0182] 2) Constraints

[0183] The distance constraint of the electric hydrogen filling station is expressed as:

[0184] L min <L<L C (101)

[0185] Where: L is the actual distance between two charging stations; L min is the minimum distance between two charging stations; L C It is the mileage that new energy vehicles can travel with the minimum remaining fuel.

[0186] The quantity constraints of hydrogen injection machines and charging piles are expressed as:

[0187] N n,zqj ≥C n,t,hfcv (102)

[0188] N n,cdz ≥C n,t,ev (103)

[0189] Where: N n,zqj 、N n,cdz They represent the number of hydrogen injectors and charging piles built in the nth hydrogen production and charging station; C n,t,hfcv , C n,t,ev They are the number of hydrogen fuel vehicles and electric vehicles arriving at the nth electric hydrogen production and filling station at time t respectively.

[0190] Voltage constraints and current constraints can be expressed as:

[0191] U t,i,min ≤U t,i ≤U t,i,max (104)

[0192]

[0193] Where: U t,i,min , U t,i,max are the minimum voltage and maximum voltage allowed at node i at time t; I ij,min ,I ij,max are the minimum and maximum currents allowed in branch ij respectively.

[0194] The upper and lower power constraints and ramp constraints of the electrolyzer at n in the integrated station can be expressed as:

[0195]

[0196] Where: p t,n,djc 、p t-1,n,djc They are respectively represented as the output of the electrolytic cell at location n in the integrated station at time t and t-1; are the upper and lower limits of its output respectively; are the start and stop states of the electrolyzer respectively; It is the climbing power of the electrolytic cell at location n in the integrated station.

[0197] The power balance constraint can be expressed as:

[0198]

[0199] Where: P i,t,djc , P i,t,ysj Respectively represent the electric power of the electrolyzer and compressor at the traffic node i at time t; P c is the power consumption rate of the cooling system; η h is the efficiency of the cooling system; P i,t,EV is the electric load required by the electric vehicle arriving at traffic node i at time t.

[0200] (8) In order to solve the nonlinear constraints in the model, the mixed integer nonlinear programming model is transformed into a mixed integer second-order cone programming model using the second-order cone relaxation method;

[0201] (9) Taking some main roads in a certain city as an example, the model is used to predict the spatiotemporal distribution of the electric hydrogen demand of new energy vehicles in the area;

[0202] (10) Determine the optimal site and equipment capacity planning of the hydrogen production and filling station based on the forecast results of the temporal and spatial distribution of regional new energy vehicle hydrogen demand.

[0203] Based on the coupling of new energy vehicles, transportation network and distribution network, taking economic factors as indicators, the annual comprehensive total cost of related annual investment and construction cost, operation cost and network loss cost in the process of optimizing the configuration of the electric hydrogen production and filling station is minimized as the objective function, and the electric hydrogen production and filling station is planned. In order to simplify the analysis, three typical schemes are selected from the candidate schemes for comparison with the optimal scheme. The site selection results of the electric hydrogen production and filling station in the transportation network and distribution network are shown in Table 1.

[0204] Table 1 Annual economic cost of electric hydrogen filling station at different nodes

[0205]

[0206] Based on the above site selection plan, charging stations are connected at nodes T8, T14, and T24, and the capacity of the electric hydrogen production and filling integrated station equipment is planned according to the electric hydrogen energy demand. The capacity planning results of each device at different nodes are shown in Table 2.

[0207] Table 2 Capacity planning of each device under different nodes

[0208]

[0209] The above implementation scheme is only used to illustrate the present invention, and is not intended to limit the present invention. Ordinary technicians in the relevant technical field may make various changes and modifications without departing from the essence and scope of the present invention. Therefore, all equivalent technical solutions also fall within the protection scope of the present invention.

Claims

1. A method for coordinated planning of an electric-hydrogen production and filling station and electric-hydrogen-road-vehicle, Features: The planning method is as follows: S1: Analyze the battery parameters, charging characteristics and driving characteristics of electric and hydrogen new energy vehicles, and analyze and probabilistically model their travel and charging patterns; S2: Introduce the time-flow model to analyze the topological structure of traffic roads according to the characteristics of urban road networks, and build models of new energy vehicles, transportation networks and distribution networks; S3: Based on the start and destination nodes assigned to the new energy vehicles, the real-time Dijkstra algorithm is used to search for the path with the minimum travel time between the two points to characterize the dynamic driving trajectory of the vehicle; S4: Based on the battery parameters and charging characteristics of new energy vehicles, Monte Carlo sampling is used to simulate the travel of new energy vehicles, and a new energy vehicle electric hydrogen demand prediction model considering vehicle-road-network coupling is established; S5: Analyze the energy flow relationship between energy production, hydrogen production and filling stations, and energy consumption, and build an operation framework with the three as the main body; S6: Considering the whole process of hydrogen production, compression and storage, an energy flow model of the electric hydrogen production and filling station is constructed; S7: Establish a regional hydrogen production and filling station planning model with the goal of minimizing economic costs such as investment, operation, and network loss, and impose road-network coupling constraints, distribution network, and hydrogen production and filling station equipment safety operation constraints; S8: Aiming at the problem of voltage and current nonlinear constraints in the regional electric hydrogen production and filling integrated station planning model, the second-order cone relaxation method is used to transform the mixed integer nonlinear programming model into a mixed integer second-order cone programming model for solution; S9: Predict the spatiotemporal distribution of the electric hydrogen demand of new energy vehicles in the region through the new energy vehicle electric hydrogen demand prediction model; S10: Determine the optimal site and equipment capacity planning of the integrated hydrogen production and filling station based on the forecast results of the spatiotemporal distribution of regional new energy vehicle hydrogen demand.

2. A method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 1, Features: The specific steps in S1 are as follows: 1) Analyze the battery parameters of electric and hydrogen new energy vehicles, mainly involving various performance parameters such as capacity, power, energy density, internal resistance, voltage, current, and hydrogen storage capacity; 2) Analyze the charging characteristics of electric and hydrogen new energy vehicles. The charging methods of pure electric vehicles mainly include vehicle charging mode and battery replacement mode. Hydrogen fuel cell vehicles are divided into three categories according to the refueling pressure level. The pressure levels of hydrogen refueling stations can be divided into 35MPa, 70MPa and compatible with 35MPa / 70MPa. 3) Analyze the driving characteristics of electric and hydrogen new energy vehicles, including initial charge state, charging time, start charging time, etc., and analyze and probabilistically model their travel and charging patterns.

3. A method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 2, Features: The charging time can be expressed as: Where: L EV is the driving distance of the electric vehicle; T c is the charging time; E is the power consumption of the electric vehicle per 100 kilometers; P ch It is the charging power of electric vehicles, which is related to the charging method of electric vehicles; Q c is the rated capacity of the electric vehicle battery; SOC c SOC is the desired state of charge of an electric vehicle. t is the state of charge of the electric vehicle at time t; The start charging time can be expressed as: t c =t start +Δt (2) Where: t c is the charging start time; t start is the start time of travel; Δt is the travel time.

4. The method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 1, Features: The specific method of S2 is as follows: 1) The topological structure characteristics of traffic roads are described by using the principles of graph theory, and the time-flow model is introduced according to the characteristics of urban road networks; 2) Analyze the topological structure of traffic roads and build models of new energy vehicles, transportation networks and distribution networks.

5. A method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 4, Features: The time-flow model introduced in 1) is a road impedance model, which is composed of a section impedance model and a node impedance model. The road section impedance model can be expressed as: Where: k is the traffic saturation evaluation index of urban road sections; t 0 is the zero-flow travel time, i.e., the travel time on a road section when the traffic flow is zero; is the impedance of the road section from node i to node j in the road network; α and β are impedance influencing factors, which are set to 0.15 and 4 respectively; The node impedance model can be expressed as: Where: is the node impedance of node i; c is the signal period; λ is the green-to-signal ratio; q is the vehicle arrival rate of the road section. The urban road impedance model is generated by the road section impedance and the node impedance and can be expressed as: Where: is the road impedance of section ij, i.e., the vehicle travel time.

6. A method for coordinated planning of an electric-hydrogen-filling integrated station and electric-hydrogen-road-vehicle according to claim 4, Features: The models of new energy vehicles, transportation networks and distribution networks in 2) can be expressed as: Where: j is the coupling node between the transportation network and the distribution network; i is the transportation network node; P j,t , Q j,t are respectively the active power and reactive power of the total load connected at coupling node j; P i,t,HE is the active power generated at node i in the traffic network at time t; P j,t,base , Q j,t,base are respectively the active power and reactive power of the initial load at coupling node j at time t, where t is a certain time.

7. The method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 1, Features: The real-time Dijkstra algorithm comprises the following steps: 1) According to the traffic network matrix and the travel matrix, the starting node of the new energy vehicle is obtained and the real-time road resistance function is calculated. The two sets X and Y are used to represent all the nodes in the road network. X is used to record the nodes with the minimum road resistance that have been obtained, and Y is used to represent the nodes whose minimum road resistance has not yet been obtained; 2) X contains only the starting node v 1 , Y contains all the numbers except v 1 Node v outside i (i=2,3,…,n), and the road resistance value L(v 1 , v i )=W(v 1 , v i ), where W is the road resistance of all roads; 3) Calculate the minimum resistance value from node i to the starting point in W by using formula (5), record the other nodes from node i to the starting point as node m, and record the replacement information f(i)=m; L(v 1 ,v i )=min{L(v 1 ,ν m )+W(v m ,v i ),L(v 1 ,ν i )} (7) Where: v 1 is the starting node; m is the middle node; v i is the destination node; 4) Select the node ν with the smallest path resistance from W m , the node ν m Add to set X and remove from Y; 5) looping step 3) and step 4) until i=n, ​​and finally obtaining the optimal path for the new energy vehicle to travel from the starting point to the destination from f based on the backtracking method.

8. The method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 1, Features: The integrated electric hydrogen production and filling station is a comprehensive energy station integrating power distribution, charging, hydrogen production and storage, and hydrogen refueling. At the same time, the integrated electric hydrogen production and filling station serves as a transmission hub to connect the energy production and energy consumption links, realizing the coordinated operation of electricity, hydrogen, road and vehicle.

9. The method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 1, Features: The energy flow model in S6 includes the power consumption model of the electrolyzer, the compressor model, and the hydrogen storage tank model. Among them, the power consumption model of the electrolytic cell is expressed as: P djc,t =H djc,t L h / η djc (8) Where: P djc,t is the input power of the electrolytic cell at time t; H djc,t is the hydrogen production power of the electrolyzer at time t; η djc is the hydrogen production efficiency; L h is the calorific value of hydrogen.

10. A method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 9, Features: The compressor model is expressed as: H ysj,t =(1-a 1 )H djc,t (9) Where: P ysj,t is the power consumption of the compressor at time t; H ysj,t is the amount of hydrogen entering the compressor at time t; H djc,t is the amount of hydrogen produced by the electrolyzer at time t; α 1 is the dissipation rate of hydrogen transferred from the equipment; is the power consumed by the compressor at the reference working pressure; f ysj , are the pressure of the compressor under normal working pressure and reference working pressure respectively; f ini is standard atmospheric pressure.

11. The method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 9, Features: The hydrogen storage tank model is expressed as: E cqg,t+1 =E cqg,t -H out,t +H cqg,t (11) H cqg,t =(1-a 2 )H ysj,t (12) Where: E cqg,t 、E cqg,t+1 are the amount of hydrogen in the hydrogen storage tank at time t and time t+1 respectively; H out,t is the amount of hydrogen required by the hydrogen fuel cell vehicle at time t; H cqg,t is the amount of hydrogen stored in the hydrogen storage tank at time t; α 2 E is the dissipation rate of hydrogen during transmission from the equipment; cqg,N is the rated capacity of the hydrogen storage tank; SOC hs,min and SOC hs,max They are the minimum and maximum charge states of hydrogen energy storage respectively.

12. The method for coordinated planning of an electric hydrogen production and filling integrated station and electric-hydrogen-road-vehicle according to claim 1, Features: The specific process in S7 is as follows: 1) Objective function Taking the minimum annual comprehensive total cost as the objective function, it is specifically expressed as: G=G tz +G yy +G ws (14) Where: G tz The annual fixed investment cost for charging station configuration mainly includes equipment investment and land investment; G yy G is the annual operating cost of the charging station, which mainly includes the cost of purchasing electricity and water during equipment operation; ws The annual network loss cost of the charging station operation; The annualized fixed investment cost of the integrated hydrogen production and filling station is expressed as: g n,djc =a djc ·max t [P n,t,djc ] (16) g n,ysj =a ysj ·max t [P n,t,ysj ] (17) g n,cqg =a cqg ·max t [E n,t,cqg ] (18) g n,zqg =a zqg ·N n,zqj (19) g n,cdz =a cdz ·N n,cdz (20) g n,td =d td,ξ (b 3 +b 4 N n,zqj +N n,cdz ),ξ=(1,2,3) (21) Where: γ is the discount rate; λ is the operation planning period of the electric hydrogen filling station; g n,djc , g n,ysj , g n,cqg , g n,zqg , g n,cdz g are the investment and construction costs of the electrolyzer, compressor, hydrogen storage tank, hydrogen injection machine and charging pile of the nth charging station; n,td is the land area required for the nth charging station; α djc , α ysj , α cqg , α zqj , α cdz are the construction costs of electrolyzer, compressor, hydrogen storage tank, hydrogen injection machine and charging pile per unit capacity or quantity; max t [P n,t,djc ]、max t [P n,t,ysj ]、max t [E n,t,cqg ] are the rated capacities of the electrolyzer, compressor and hydrogen storage tank of the nth electric hydrogen production and filling integrated station; N n,zqj 、N n,cdz are the total number of hydrogen injectors and charging piles in the nth hydrogen production and charging integrated station; d td,ξ is the unit area cost of the ξth type of land, ξ is 1, 2, 3, 1 is the residential area, 2 is the commercial area, and 3 is the office area; β 3 , β 4 is the land cost coefficient, which is a fixed value and takes values ​​of 50.71 and 20.5 respectively; N is the number of charging stations. The operating cost of the electric hydrogen filling station can be expressed as: Where: g n,e , g n,w are the electricity cost and water cost of the nth electric hydrogen production and filling integrated station respectively; D is the planned number of days, which is 365; H n,t P is the hydrogen demand of the nth electric hydrogen filling station at time t; n,t,djc , P n,t,ysj They represent the electric power of the electrolyzer and compressor of the nth electric hydrogen production and filling integrated station at time t; P c is the power consumption rate of the cooling system; η h is the efficiency of the cooling system; P n,t,ev The electric load required for the electric vehicle to arrive at the nth electric hydrogen production and filling station for charging at time t; β 1 is the industrial electricity price; β 2 is the industrial water price; W n,t,djc , W n,t,ysj The water consumption required by the electrolyzer and compressor of the nth electric hydrogen production and filling integrated station when producing and compressing hydrogen at time t; are the purified water coefficients for electrolyzer and compressor respectively; The network loss cost can be expressed as: Where: c L is the unit network loss cost of the system; P loss,ij,t is the active power loss of branch ij in time period t, with T 0 is the step length, T 0 is 15 minutes, and a day is divided into T time periods, T is 96; 2) Constraints The distance constraint of the electric hydrogen filling station is expressed as: L min <L<L C (29) Where: L is the actual distance between two charging stations; L min is the minimum distance between two charging stations; L C The mileage that a new energy vehicle can travel with the minimum remaining fuel; The quantity constraints of hydrogen injection machines and charging piles are expressed as: N n,zqj ≥C n,t,hfcv (30) N n,cdz ≥C n,t,ev (31) Where: N n,zqj 、N n,cdz They represent the number of hydrogen injectors and charging piles built in the nth hydrogen production and charging station; C n,t,hfcv , C n,t,ev are the number of hydrogen fuel cell vehicles and electric vehicles arriving at the nth electric hydrogen production and filling station at time t, respectively; Voltage constraints and current constraints can be expressed as: IN t,i,min ≤U t,i ≤U t,i,max (32) Where: U t,i,min , U t,i,max are the minimum voltage and maximum voltage allowed at node i at time t; I ij,min ,I ij,max are the minimum current and maximum current allowed for branch ij respectively; The upper and lower power constraints and ramp constraints of the electrolyzer at n in the integrated station can be expressed as: Where: p t,n,djc 、p t-1,n,djc They are respectively represented as the output of the electrolytic cell at location n of the integrated station at time t and t-1; are the upper and lower limits of its output respectively; are the start and stop states of the electrolyzer respectively; is the climbing power of the electrolyzer at location n in the integrated station; The power balance constraint can be expressed as: Where: P i,t,djc , P i,t,ysj Respectively represent the electric power of the electrolyzer and compressor at the traffic node i at time t; P c is the power consumption rate of the cooling system; η h is the efficiency of the cooling system; P i,t,EV is the electric load required by the electric vehicle arriving at traffic node i at time t.

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