Optimal planning method and system for integrated station of photovoltaic power generation, energy storage, charging and power exchange considering electricity-traffic demand iteration

Abstract

A planning method and system for integrated photovoltaic-energy storage-charging-swapping stations considering iterative electricity and transportation demand is presented. This method first constructs a rolling planning model for integrated photovoltaic-energy storage-charging-swapping stations within a power-transportation coupled network, aiming to minimize the overall system charging and swapping cost. Then, the rolling planning model is solved iteratively to obtain a planning scheme for the integrated photovoltaic-energy storage-charging-swapping station that includes configuration schemes for charging and swapping, photovoltaic and energy storage facilities, charging and swapping and transportation demand allocation schemes, and power-transportation coupled network expansion schemes. This invention considers the impact of technological upgrades, changes in user demand, and network expansion on the supply and demand relationship of charging and swapping services during different planning periods. By continuously optimizing the planning and operation schemes of charging and swapping stations and the power-transportation coupled network, it minimizes the overall system charging and swapping cost while meeting the time-varying charging and swapping and transportation needs of electric vehicle users.

Description

Technical Field

[0001] This invention belongs to the field of power-transportation coupled network planning, specifically involving a planning method and system for an integrated photovoltaic, energy storage, charging and swapping station that considers the iterative changes in power consumption and transportation demand. Background Technology

[0002] With the continuous advancement of electric vehicle technology and the rapid changes in market demand, traditional planning methods are no longer able to adapt to the complex and dynamic environment.

[0003] The growth in the number of electric vehicles and changes in user behavior have brought about more complex charging and swapping demands and traffic load management challenges. User charging needs at different times, the introduction of autonomous driving technology, and the interaction between electric vehicles and the power grid all make load flexibility and demand diversity important factors that must be considered in the planning process.

[0004] At the network level, with the increasing prevalence of electric vehicles and charging / swapping infrastructure, the need to expand transportation and power distribution networks has become increasingly urgent. Optimizing the coupling between transportation and power networks while meeting user needs has become a key aspect of rolling planning. Through regular evaluation and dynamic adjustments, this planning approach can effectively address the uncertainties brought about by technological advancements and market changes, ensuring the efficient, safe, and sustainable development of charging / swapping services.

[0005] Meanwhile, in the electric vehicle industry chain, rapid technological upgrades significantly impact the capabilities and efficiency of charging and battery swapping services. Advances in battery technology directly improve the driving range and charging speed of electric vehicles, while progress in photovoltaic power generation enhances the utilization efficiency of renewable energy. These technological advancements not only change the operating model of charging and battery swapping stations but also place new demands on the configuration of energy systems. Summary of the Invention

[0006] The purpose of this invention is to address the aforementioned problems in the existing technology by providing a planning method and system for integrated photovoltaic, energy storage, charging, and swapping stations that considers the iterative changes in electricity and transportation demand.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows:

[0008] In a first aspect, this invention proposes a planning method for integrated photovoltaic, energy storage, charging, and swapping stations that considers the iterative changes in electricity and transportation demand, including:

[0009] S1. Construct a rolling planning model for integrated photovoltaic, energy storage, charging and swapping stations in a power-transportation coupled network. The rolling planning model aims to minimize the overall charging and swapping cost of the system, and considers the impact of technology upgrades, changes in user demand, and network expansion on the supply and demand of charging and swapping services during different planning periods.

[0010] S2. Solve the rolling planning model of the photovoltaic-storage-charging-swapping integrated station to obtain the planning scheme of the photovoltaic-storage-charging-swapping integrated station. The planning scheme includes the configuration scheme of charging and swapping, photovoltaic and energy storage facilities, the allocation scheme of charging and swapping and traffic demand, and the expansion scheme of the power-transportation coupling network.

[0011] The objective function of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station includes:

[0012] min C N +C P +C E +C T ;

[0013]

[0014] In the above formula, C N The cost of expanding the power-transportation coupled network; C P The configuration cost of charging and battery swapping facilities; C E For electricity purchase cost; C T Reduce the time cost of charging and swapping batteries for users; and These are the expansion decision variables for distribution network line w and transportation network road l in year y, respectively; PR EP and PR TP These are the unit expansion costs for power distribution lines and transportation network roads, respectively; y The discount factor for planning investment costs; and These represent the number of newly added charging piles and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at transportation network node g in year y; PR CP and PR SF α represents the unit configuration cost of charging piles and battery swapping facilities, respectively; α is the discount rate; γ is the investment period; and d is the number of typical days within a year. For a typical intraday period t in year y, the active power output by the distribution network to the photovoltaic-storage-charging-swapping integrated station at road l; The electricity price for time period t; TA y,t For year y, the total time consumed by the vehicle during charging trips within time period t; PR T Cost per unit of time;

[0015] The constraints of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station include electric vehicle user behavior constraints, integrated photovoltaic-storage-charging-swapping station planning and operation constraints, and power-transportation coupled network planning and operation constraints.

[0016] The planning and operation constraints for the integrated photovoltaic, energy storage, charging, and swapping station include:

[0017]

[0018]

[0019] In the above formula, The actual photovoltaic output of the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; The output or input power of the photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y; and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during a typical intraday period t in year y. and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during the idle period of a typical intraday time t in year y. Let be the correlation coefficient between path k and traffic node g; E represents the correlation coefficient between traffic node g and distribution network node e. U The charging energy requirement for a single electric vehicle; T U Unit duration; The number of batteries that are charged at the integrated photovoltaic, energy storage, charging and swapping station at node e during a typical intraday period in year y. The number of electric vehicles performing V2G reverse discharge at the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; P VG This represents the power of the V2G reverse discharge. This represents the maximum output of newly added photovoltaic power at the integrated photovoltaic-storage-charging-swapping station at distribution network node e in year yx. P represents the photovoltaic energy conversion efficiency coefficient in year y. EH and P ED These are the maximum discharge power and maximum charging power of a single energy storage unit, respectively. This refers to the number of new energy storage systems added within the photovoltaic-storage-charging-swapping integrated station at distribution network node e in year yx; κ E The annual capacity decay rate of energy storage; η represents the output or input power at node e of a charging station during a typical intraday period in year y; L and η H These are the lower and upper limits of the energy state of energy storage, respectively; EC E For the installed capacity of a single energy storage unit; EC O The initial charge of the energy storage system is tn; tn is the number of time periods within a typical day. T represents the number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical day in year y, within the specified time period tx; VG P represents the average duration of V2G reverse discharge for a single electric vehicle. UCThe charging power of a single charging station; and These represent the number of fully charged and uncharged batteries stored in the integrated photovoltaic-storage-charging-swapping station at distribution network node e during a typical intraday period in year y. The number of batteries performing battery swapping operations at the integrated photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y. and These represent the maximum number of charging facilities and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at node g of the transportation network; δ M For large M constants; T UC and T US These represent the time consumed for a single battery charge and a single battery swap operation, respectively.

[0020] The electric vehicle user behavior constraints include:

[0021]

[0022]

[0023] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. The total number of vehicles requiring recharging during a typical daytime off-peak period in year y; The proportion of electric vehicles with autonomous driving capabilities in year y; The number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical intraday period t in year y. This represents the number of electric vehicles with sufficient battery power at traffic node g during a typical intraday period in year y; TI y,t L represents the driving time of an electric vehicle during a typical intraday period t in year y. k Let k be the distance traveled along path k. v is the congestion coefficient for time period t; U The reference speed; TC y,t and TS y,t The charging and battery swapping time costs for a typical intraday period t in year y are respectively; TI C and TI S These represent the time required for a single charge and for battery swapping, respectively.

[0024] The operational constraints for the power-transportation coupled network planning include:

[0025]

[0026]

[0027] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. Let be the correlation coefficient between path k and road l. R represents the original traffic capacity of road l; A To accommodate the increased traffic capacity following road widening; and These represent the active and reactive power on line w during a typical intraday period t in year y; w represents all lines connected to distribution network node e. and These represent the basic active and reactive loads connected at distribution network node e during a typical intraday period in year y; L represents the original capacity of the distribution network line w; A To accommodate the increased capacity following the expansion of the distribution network lines; and These represent the resistance and reactance of the distribution network line w, respectively; U N The rated voltage of the distribution network busbar; ΔU t,w U represents the voltage drop on the distribution network line w during time period t; t,a and U t,b U represents the bus voltages of distribution network nodes a and b during time period t, where nodes a and b are the two endpoints of distribution network line w; m and U M These are the lower and upper limits of the distribution network bus voltage, respectively.

[0028] Secondly, this invention proposes a planning system for integrated photovoltaic, energy storage, charging, and swapping stations that considers the iterative changes in electricity and transportation demand. The system includes a model building module and a model solving module. The model building module is used to construct a rolling planning model for integrated photovoltaic, energy storage, charging, and swapping stations in a power-transportation coupled network. The rolling planning model aims to minimize the overall charging and swapping cost of the system and considers the impact of technological upgrades, changes in user demand, and network expansion on the supply and demand relationship of charging and swapping services during different planning periods.

[0029] The model solving module is used to solve the rolling planning model of the photovoltaic-storage-charging-swapping integrated station in a rolling manner, so as to obtain the planning scheme of the photovoltaic-storage-charging-swapping integrated station. The planning scheme includes the configuration scheme of charging and swapping, photovoltaic and energy storage facilities, the allocation scheme of charging and swapping and traffic demand, and the expansion scheme of the power-transportation coupling network.

[0030] The objective function of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station includes:

[0031] min C N +C P +C E +C T ;

[0032]

[0033]

[0034] In the above formula, C N The cost of expanding the power-transportation coupled network; C P The configuration cost of charging and battery swapping facilities; C E For electricity purchase cost; C T Reduce the time cost of charging and swapping batteries for users; and These are the expansion decision variables for distribution network line w and transportation network road l in year y, respectively; PR EP and PR TP These are the unit expansion costs for power distribution lines and transportation network roads, respectively; y The discount factor for planning investment costs; and These represent the number of newly added charging piles and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at transportation network node g in year y; PR CP and PR SF α represents the unit configuration cost of charging piles and battery swapping facilities, respectively; α is the discount rate; γ is the investment period; and d is the number of typical days within a year. For a typical intraday period t in year y, the active power output by the distribution network to the photovoltaic-storage-charging-swapping integrated station at road l; The electricity price for time period t; TA y,t For year y, the total time consumed by the vehicle during charging trips within time period t; PR T Cost per unit of time;

[0035] The constraints of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station include electric vehicle user behavior constraints, integrated photovoltaic-storage-charging-swapping station planning and operation constraints, and power-transportation coupled network planning and operation constraints.

[0036] The planning and operation constraints for the integrated photovoltaic, energy storage, charging, and swapping station include:

[0037]

[0038]

[0039] In the above formula, The actual photovoltaic output of the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; The output or input power of the photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y; and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during a typical intraday period t in year y. and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during the idle period of a typical intraday time t in year y. Let be the correlation coefficient between path k and traffic node g; E represents the correlation coefficient between traffic node g and distribution network node e. U The charging energy requirement for a single electric vehicle; T U Unit duration; The number of batteries that are charged at the integrated photovoltaic, energy storage, charging and swapping station at node e during a typical intraday period in year y. The number of electric vehicles performing V2G reverse discharge at the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; P VG This represents the power of the V2G reverse discharge. This represents the maximum output of newly added photovoltaic power at the integrated photovoltaic-storage-charging-swapping station at distribution network node e in year yx. P represents the photovoltaic energy conversion efficiency coefficient in year y. EH and P ED These are the maximum discharge power and maximum charging power of a single energy storage unit, respectively. This refers to the number of new energy storage systems added within the photovoltaic-storage-charging-swapping integrated station at distribution network node e in year yx; κ E The annual capacity decay rate of energy storage; η represents the output or input power at node e of a charging station during a typical intraday period in year y; L and η H These are the lower and upper limits of the energy state of energy storage, respectively; EC E For the installed capacity of a single energy storage unit; EC O The initial charge of the energy storage system is tn; tn is the number of time periods within a typical day. T represents the number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical day in year y, within the specified time period tx; VG P represents the average duration of V2G reverse discharge for a single electric vehicle. UC The charging power of a single charging station; and These represent the number of fully charged and uncharged batteries stored in the integrated photovoltaic-storage-charging-swapping station at distribution network node e during a typical intraday period in year y. The number of batteries performing battery swapping operations at the integrated photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y. and These represent the maximum number of charging facilities and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at node g of the transportation network; δ M For large M constants; T UC and T US These represent the time consumed for a single battery charge and a single battery swap operation, respectively.

[0040] The electric vehicle user behavior constraints include:

[0041]

[0042] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. The total number of vehicles requiring recharging during a typical daytime off-peak period in year y; The proportion of electric vehicles with autonomous driving capabilities in year y; The number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical intraday period t in year y. This represents the number of electric vehicles with sufficient battery power at traffic node g during a typical intraday period in year y; TI y,t L represents the driving time of an electric vehicle during a typical intraday period t in year y. k Let k be the distance traveled along path k. v is the congestion coefficient for time period t; U The reference speed; TC y,t and TS y,t The charging and battery swapping time costs for a typical intraday period t in year y are respectively; TI C and TI S These represent the time required for a single charge and for battery swapping, respectively.

[0043] The operational constraints for the power-transportation coupled network planning include:

[0044]

[0045] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. Let be the correlation coefficient between path k and road l. R represents the original traffic capacity of road l;A To accommodate the increased traffic capacity following road widening; and These represent the active and reactive power on line w during a typical intraday period t in year y; w represents all lines connected to distribution network node e. and These represent the basic active and reactive loads connected at distribution network node e during a typical intraday period in year y; L represents the original capacity of the distribution network line w; A To accommodate the increased capacity following the expansion of the distribution network lines; and These represent the resistance and reactance of the distribution network line w, respectively; U N The rated voltage of the distribution network busbar; ΔU t,w U represents the voltage drop on the distribution network line w during time period t; t,a and U t,b U represents the bus voltages of distribution network nodes a and b during time period t, where nodes a and b are the two endpoints of distribution network line w; m and U M These are the lower and upper limits of the distribution network bus voltage, respectively.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] This invention proposes a planning method for integrated photovoltaic-energy storage-charging-swapping stations that considers iterative electricity and transportation demand. First, a rolling planning model for integrated photovoltaic-energy storage-charging-swapping stations within a power-transportation coupled network is constructed with the goal of minimizing the overall system charging and swapping cost. Then, the rolling planning model is solved in a rolling manner to obtain a planning scheme for the integrated photovoltaic-energy storage-charging-swapping station that includes configuration schemes for charging and swapping, photovoltaic and energy storage facilities, allocation schemes for charging and swapping and transportation demand, and expansion schemes for the power-transportation coupled network. This model considers the impact of technological upgrades, changes in user demand, and network expansion on the supply and demand relationship of charging and swapping services during different planning periods. By continuously optimizing the planning and operation schemes of charging and swapping stations and the power-transportation coupled network, the overall system charging and swapping cost is minimized while meeting the time-varying charging and swapping and transportation needs of electric vehicle users. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the power-transportation coupled network described in this invention.

[0049] Figure 2 This is a topology diagram of the 23-node distribution network and 19-node transportation network used in Example 1.

[0050] Figure 3 The congestion coefficient time-series characteristic curve used in Example 1 is shown.

[0051] Figure 4 This is a schematic diagram of the time-of-use electricity pricing used in Example 1.

[0052] Figure 5 The photovoltaic output characteristic curve used in Example 1 is shown.

[0053] Figure 6 This is a structural diagram of the system described in Example 2. Detailed Implementation

[0054] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings.

[0055] This invention proposes a planning method for integrated photovoltaic, energy storage, charging, and swapping stations that considers the iterative changes in electricity and transportation demand. This method is specifically designed for... Figure 1 The power-transportation coupled network shown employs a rolling planning approach, fully considering the impact of technological upgrades, changes in user demand, and network expansion on the supply and demand of charging and swapping services during different planning periods. Specifically, this is reflected in...

[0056] At the technical level, the cycle life of electric vehicle batteries, the charging speed of electric vehicles, and the photoelectric conversion efficiency of photovoltaic cells have all improved with technological advancements. This invention considers the impact of these technological upgrades on the service capacity of charging and battery swapping stations and the utilization rate of renewable energy in its planning model, and optimizes the configuration of charging and battery swapping facilities and supporting photovoltaic and energy storage facilities.

[0057] At the user demand level, the increased demand for charging and swapping and transportation brought about by the growth in the number of electric vehicles is fully considered. At the same time, the load flexibility brought about by orderly charging in multiple modes at all times (drivers drive during usage hours and autonomous driving during idle hours) and V2G reverse discharge participating in auxiliary services is also considered, and the charging and swapping demand and transportation demand are optimized and allocated.

[0058] At the network level, considering the new demands on the transportation network and distribution network from charging and swapping and increased traffic demand, the road and distribution network lines of the power-transportation coupled network are optimized and expanded while meeting user needs and network constraints.

[0059] Example 1:

[0060] This embodiment uses a topological structure such as Figure 2The diagram shows a 23-node distribution network and a 19-node transportation network (with two integrated photovoltaic, energy storage, charging, and battery swapping stations located at P5(T6) and P10(T13) respectively). The parameters are as follows: investment period is 10 years; discount rate is 0.05; unit time is 1 hour; investment term is 10 years; typical number of days in a year is 365; unit expansion costs for distribution network lines and transportation network roads are 1 million yuan and 2 million yuan respectively; unit configuration costs for charging piles and battery swapping facilities are 10,000 yuan and 200,000 yuan respectively; unit time cost is 20 yuan / hour; base driving speed is 40 km / h. The charging power of a single charging pile is 80 kW; the time for a single charge and battery swap is 0.5 hours and 0.3 hours, respectively; the charging energy demand of a single electric vehicle is 40 kWh; the installed capacity of a single energy storage unit is 40 kWh; the maximum discharge power and maximum charging power of a single energy storage unit are 20 kW; the lower and upper limits of the energy storage state of being are 0.1 and 0.9, respectively; the annual capacity decay rate of the energy storage is 0.95; the average duration of V2G reverse discharge for a single electric vehicle is 3 hours; the congestion coefficient time-series characteristic curve, time-of-use pricing, and photovoltaic output characteristic curves are as follows: Figure 3 , Figure 4 and Figure 5 As shown in the figure, the planning method for integrated photovoltaic, energy storage, charging and swapping stations considering the iterative electricity and transportation demand described in this invention is implemented, including:

[0061] 1. Construct a rolling planning model for integrated photovoltaic, energy storage, charging, and swapping stations in a power-transportation coupled network.

[0062] The rolling planning model for the integrated photovoltaic-storage-charging-swapping station aims to minimize the overall charging and swapping cost of the system. Its objective function is shown in equations (1)-(6):

[0063] min C N +C P +C E +C T Equation (1)

[0064]

[0065] In the above formula, C N The cost of expanding the power-transportation coupled network; C P The configuration cost of charging and battery swapping facilities; C E For electricity purchase cost; C T Reduce the time cost of charging and swapping batteries for users; and These are the expansion decision variables for the distribution network line w and the transportation network road l in year y, respectively. or Expansion is performed when the value is 1, and not when the value is 0; PR EP and PR TPThese are the unit expansion costs for power distribution lines and transportation network roads, respectively; y The discount factor for planning investment costs; and These represent the number of newly added charging piles and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at transportation network node g in year y; PR CP and PR SF α represents the unit configuration cost of charging piles and battery swapping facilities, respectively; α is the discount rate; γ is the investment period; and d is the number of typical days within a year. For a typical intraday period t in year y, the active power output by the distribution network to the photovoltaic-storage-charging-swapping integrated station at road l; The electricity price for time period t; TA y,t For year y, the total time consumed by the vehicle during charging trips within time period t; PR T Cost per unit of time.

[0066] The constraints of the rolling planning model for the integrated photovoltaic, energy storage, charging, and swapping station include:

[0067] (1) Constraints on electric vehicle user behavior

[0068] There are three ways for users to operate electric vehicle batteries: charging mode, battery swapping mode, and V2G mode. Regarding travel, users can choose to visit a photovoltaic-storage-charging-swapping integrated station during their trip, or they can use the vehicle's autonomous driving mode to travel to the station during off-peak hours. Of these two methods, only the former incurs a time cost for the user. Electric vehicles traveling during their trip must complete charging, battery swapping, or V2G reverse discharge during that time. Electric vehicles in idle periods have greater flexibility, allowing them to choose charging, battery swapping, or V2G reverse discharge times while meeting their charging needs. Therefore, the specific behavioral constraints for electric vehicle users are set as follows:

[0069]

[0070]

[0071] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. The total number of vehicles requiring recharging during a typical daytime off-peak period in year y; The proportion of electric vehicles with autonomous driving capabilities in year y; The number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical intraday period t in year y. This represents the number of electric vehicles with sufficient battery power at traffic node g during a typical intraday period in year y; TI y,t L represents the driving time of an electric vehicle during a typical intraday period t in year y. k Let k be the distance traveled along path k. v is the congestion coefficient for time period t; U The reference speed; TC y,t and TS y,t The charging and battery swapping time costs for a typical intraday period t in year y are respectively; TI C and TI S These represent the time required for a single charge and for battery swapping, respectively.

[0072] In this constraint, equations (7)-(10) represent the number of electric vehicles using different charging measures in each time period; equations (11)-(14) represent the time constraints for the charging trip of electric vehicles during the usage period.

[0073] (2) Planning and operation constraints of integrated photovoltaic, energy storage, charging and swapping stations

[0074]

[0075]

[0076] In the above formula, The actual photovoltaic output of the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; The output or input power of the photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y; and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during a typical intraday period t in year y. and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during the idle period of a typical intraday time t in year y. Let be the correlation coefficient between path k and traffic node g; E represents the correlation coefficient between traffic node g and distribution network node e. U The charging energy requirement for a single electric vehicle; T U Unit duration; The number of batteries that are charged at the integrated photovoltaic, energy storage, charging and swapping station at node e during a typical intraday period in year y. The number of electric vehicles performing V2G reverse discharge at the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; P VG This represents the power of the V2G reverse discharge. This represents the maximum output of newly added photovoltaic power at the integrated photovoltaic-storage-charging-swapping station at distribution network node e in year yx. P represents the photovoltaic energy conversion efficiency coefficient in year y. EH and P ED These are the maximum discharge power and maximum charging power of a single energy storage unit, respectively. This refers to the number of new energy storage systems added within the photovoltaic-storage-charging-swapping integrated station at distribution network node e in year yx; κ E The annual capacity decay rate of energy storage; η represents the output or input power at node e of a charging station during a typical intraday period in year y; L and η H These are the lower and upper limits of the energy state of energy storage, respectively; EC E For the installed capacity of a single energy storage unit; EC O The initial charge of the energy storage system is tn; tn is the number of time periods within a typical day. T represents the number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical day in year y, within the specified time period tx; VG P represents the average duration of V2G reverse discharge for a single electric vehicle. UC The charging power of a single charging station; and These represent the number of fully charged and uncharged batteries stored in the integrated photovoltaic-storage-charging-swapping station at distribution network node e during a typical intraday period in year y. The number of batteries performing battery swapping operations at the integrated photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y. and These represent the maximum number of charging facilities and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at node g of the transportation network; δ M For large M constants; T UC and T US These represent the time consumed for a single battery charge and a single battery swap operation, respectively.

[0077] In this constraint, equations (15)-(16) are the planning and operation constraints of the photovoltaic-storage-charging-swapping integrated station in this invention, wherein equation (15) is the power balance constraint of the photovoltaic-storage-charging-swapping integrated station, equation (16) is the photovoltaic output constraint; equations (17)-(18) are the energy storage operation constraints; equation (19) is the V2G reverse discharge constraint; equation (20) is the charging pile quantity constraint, since electric vehicle charging, V2G reverse discharge and battery charging all use charging piles, it is subject to the constraint of the number of charging piles; equations (21)-(22) are the quantity constraints of the completed charging and waiting-to-be-charged batteries stored in the photovoltaic-storage-charging-swapping integrated station; equations (23)-(24) are the electric vehicle battery state change constraints; equations (25)-(26) are the quantity constraints of the charging and swapping facilities in the photovoltaic-storage-charging-swapping integrated station; and equations (27)-(29) are the service capacity constraints of the photovoltaic-storage-charging-swapping integrated station.

[0078] (3) Planning and operation constraints of the power-transportation coupled network

[0079]

[0080]

[0081] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. Let be the correlation coefficient between path k and road l. R represents the original traffic capacity of road l; A To accommodate the increased traffic capacity following road widening; and These represent the active and reactive power on line w during a typical intraday period t in year y; w represents all lines connected to distribution network node e. and These represent the basic active and reactive loads connected at distribution network node e during a typical intraday period in year y; L represents the original capacity of the distribution network line w; A To accommodate the increased capacity following the expansion of the distribution network lines; and These represent the resistance and reactance of the distribution network line w, respectively; U N The rated voltage of the distribution network busbar; ΔU t,w U represents the voltage drop on the distribution network line w during time period t; t,a and U t,b U represents the bus voltages of distribution network nodes a and b during time period t, where nodes a and b are the two endpoints of distribution network line w; m and U M These are the lower and upper limits of the distribution network bus voltage, respectively.

[0082] In this constraint, Equation (30) is the traffic capacity constraint for each road; Equation (31) is the road expansion constraint, that is, only one road can be expanded once within a planning period; Equations (32) and (33) are the active and reactive power balance constraints of the distribution network nodes in each year; Equation (34) is the distribution network line capacity constraint; Equation (35) is the line expansion constraint, that is, only one line can be expanded once within a planning period; Equations (36)-(38) are the distribution network node voltage constraints.

[0083] 2. The rolling planning model of the photovoltaic-storage-charging-swapping integrated station is solved in a rolling manner to obtain the planning scheme of the integrated station. The planning scheme includes the configuration scheme of charging and swapping, photovoltaic and energy storage facilities, the allocation scheme of charging and swapping and traffic demand, and the expansion scheme of the power-transportation coupling network.

[0084] To verify the effectiveness of the method proposed in this invention, the method described in Example 1 was used as Method 1, and the traditional planning method for integrated photovoltaic-storage-charging-swapping stations was used as Method 2. This method was applied to the 23-node distribution network and 19-node transportation network described in Example 1 (Method 2 does not consider the iterative power-transportation demand within the planning period, nor does it consider the impact of autonomous driving of electric vehicles). The economic indicators of the two methods were compared, and the results are shown in Table 1 (where hardware costs include the expansion cost of the power-transportation coupled network and the configuration cost of charging and swapping related facilities):

[0085] Table 1. Comparison of economic results between the two methods

[0086]

[0087] As shown in Table 1, Method 1 offers the lowest overall annual charging and battery swapping cost. In terms of hardware infrastructure costs, Method 1 reduces costs by 4.95% compared to Method 2; in terms of annual electricity purchase costs, Method 1 reduces costs by 8.46% compared to Method 2; and in terms of annual charging and battery swapping time costs, Method 1 reduces costs by 21.78% compared to Method 2. Overall, the annual comprehensive charging and battery swapping cost is 10.06% lower using Method 1 compared to Method 2.

[0088] The above results demonstrate that the method proposed in this invention achieves the effect of minimizing the overall charging and swapping cost of the system while meeting the time-varying charging and swapping needs of electric vehicle users and traffic requirements.

[0089] Example 2:

[0090] like Figure 6 As shown, a planning system for an integrated photovoltaic, energy storage, charging, and swapping station that considers the iterative changes in electricity and transportation demand includes a model building module and a model solving module.

[0091] The model building module is used to construct a rolling planning model for integrated photovoltaic, energy storage, charging, and swapping stations in a power-transportation coupled network. The objective function of the rolling planning model for integrated photovoltaic, energy storage, charging, and swapping stations includes:

[0092] min C N +C P +C E +C T ;

[0093]

[0094] In the above formula, C N The cost of expanding the power-transportation coupled network; C P The configuration cost of charging and battery swapping facilities; C E For electricity purchase cost; C T Reduce the time cost of charging and swapping batteries for users; and These are the expansion decision variables for distribution network line w and transportation network road l in year y, respectively; PR EP and PR TP These are the unit expansion costs for power distribution lines and transportation network roads, respectively; y The discount factor for planning investment costs; and These represent the number of newly added charging piles and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at transportation network node g in year y; PR CP and PR SF α represents the unit configuration cost of charging piles and battery swapping facilities, respectively; α is the discount rate; γ is the investment period; and d is the number of typical days within a year. For a typical intraday period t in year y, the active power output by the distribution network to the photovoltaic-storage-charging-swapping integrated station at road l; The electricity price for time period t; TA y,t For year y, the total time consumed by the vehicle during charging trips within time period t; PR T Cost per unit of time;

[0095] The constraints of the rolling planning model for the integrated photovoltaic, energy storage, charging, and swapping station include:

[0096] Planning and operation constraints of integrated photovoltaic, energy storage, charging and swapping stations

[0097]

[0098]

[0099] In the above formula, The actual photovoltaic output of the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; The output or input power of the photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y; and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during a typical intraday period t in year y. and The numbers of electric vehicles traveling to the integrated photovoltaic-storage-charging-swapping station for charging and battery swapping via path k during a typical intraday period t in year y are respectively the number of electric vehicles during the idle period of a typical intraday time t in year y. Let be the correlation coefficient between path k and traffic node g; E represents the correlation coefficient between traffic node g and distribution network node e. U The charging energy requirement for a single electric vehicle; T U Unit duration; The number of batteries that are charged at the integrated photovoltaic, energy storage, charging and swapping station at node e during a typical intraday period in year y. The number of electric vehicles performing V2G reverse discharge at the photovoltaic-storage-charging-swapping integrated station at node e during a typical intraday period in year y; P VG This represents the power of the V2G reverse discharge. This represents the maximum output of newly added photovoltaic power at the integrated photovoltaic-storage-charging-swapping station at distribution network node e in year yx. P represents the photovoltaic energy conversion efficiency coefficient in year y. EH and P ED These are the maximum discharge power and maximum charging power of a single energy storage unit, respectively. This refers to the number of new energy storage systems added within the photovoltaic-storage-charging-swapping integrated station at distribution network node e in year yx; κ E The annual capacity decay rate of energy storage; η represents the output or input power at node e of a charging station during a typical intraday period in year y; L and η H These are the lower and upper limits of the energy state of energy storage, respectively; EC E For the installed capacity of a single energy storage unit; EC O The initial charge of the energy storage system is tn; tn is the number of time periods within a typical day. T represents the number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical day in year y, within the specified time period tx; VG P represents the average duration of V2G reverse discharge for a single electric vehicle. UC The charging power of a single charging station; and These represent the number of fully charged and uncharged batteries stored in the integrated photovoltaic-storage-charging-swapping station at distribution network node e during a typical intraday period in year y. The number of batteries performing battery swapping operations at the integrated photovoltaic-storage-charging-swapping station at node e during a typical intraday period in year y. and These represent the maximum number of charging facilities and battery swapping facilities within the integrated photovoltaic-storage-charging-swapping station at node g of the transportation network; δ M For large M constants; T UC and T US These represent the time consumed for a single battery charge and a single battery swap operation, respectively.

[0100] Electric vehicle user behavior constraints

[0101]

[0102] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. The total number of vehicles requiring recharging during a typical daytime off-peak period in year y; The proportion of electric vehicles with autonomous driving capabilities in year y; The number of electric vehicles traveling via path k to the integrated photovoltaic-storage-charging-swapping station for V2G reverse discharge during a typical intraday period t in year y. This represents the number of electric vehicles with sufficient battery power at traffic node g during a typical intraday period in year y; TI y,t L represents the driving time of an electric vehicle during a typical intraday period t in year y. k Let k be the distance traveled along path k. v is the congestion coefficient for time period t; U The reference speed; TC y,t and TS y,t The charging and battery swapping time costs for a typical intraday period t in year y are respectively; TI C and TI S These are the times for a single charge and for battery swapping, respectively.

[0103] Power-transportation coupled network planning and operation constraints

[0104]

[0105] In the above formula, and The numbers of electric vehicles during a typical intraday period t in year y, traveling via path k to the integrated photovoltaic-storage-charging-swapping station for recharging during the usage period and the idle period, are respectively the number of electric vehicles during the usage period and the idle period during a typical intraday period t in year y. Let be the correlation coefficient between path k and road l. R represents the original traffic capacity of road l;A To accommodate the increased traffic capacity following road widening; and These represent the active and reactive power on line w during a typical intraday period t in year y; w represents all lines connected to distribution network node e. and These represent the basic active and reactive loads connected at distribution network node e during a typical intraday period in year y; L represents the original capacity of the distribution network line w; A To accommodate the increased capacity following the expansion of the distribution network lines; and These represent the resistance and reactance of the distribution network line w, respectively; U N The rated voltage of the distribution network busbar; ΔU t,w U represents the voltage drop on the distribution network line w during time period t; t,a and U t,b U represents the bus voltages of distribution network nodes a and b during time period t, where nodes a and b are the two endpoints of distribution network line w; m and U M These are the lower and upper limits of the distribution network bus voltage, respectively.

[0106] The model solving module is used to solve the rolling planning model of the photovoltaic-storage-charging-swapping integrated station in a rolling manner, so as to obtain the planning scheme of the photovoltaic-storage-charging-swapping integrated station. The planning scheme includes the configuration scheme of charging and swapping, photovoltaic and energy storage facilities, the allocation scheme of charging and swapping and traffic demand, and the expansion scheme of the power-transportation coupling network.

Claims

1. A planning method for integrated photovoltaic, energy storage, charging, and swapping stations considering the iterative changes in electricity and transportation demand, characterized in that, The method includes: S1. Construct a rolling planning model for integrated photovoltaic, energy storage, charging and swapping stations in a power-transportation coupled network. The rolling planning model aims to minimize the overall charging and swapping cost of the system, and considers the impact of technology upgrades, changes in user demand, and network expansion on the supply and demand of charging and swapping services during different planning periods. The objective function of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station includes: ； ； ； ； ； ； In the above formula, The cost of expanding the power-transportation coupled network; The configuration cost of charging and battery swapping facilities; For electricity purchase costs; Reduce the time cost of charging and swapping batteries for users; and The first Annual distribution network lines and transportation network roads Expanding decision variables; and These are the unit expansion costs for power distribution network lines and transportation network roads, respectively. The discount factor for planning investment costs; and The first Annual transportation network nodes The number of newly added charging piles and battery swapping facilities in the integrated photovoltaic, energy storage, charging and swapping station; and These are the unit configuration costs for charging piles and battery swapping facilities, respectively. The discount rate; For the investment cycle; The number of typical days in a year; For the first A typical intraday period of the year At that time, the power distribution network supplies power to the road. The active power output of the integrated photovoltaic, energy storage, charging and swapping station at the location; For time period The electricity price; For the first Year, Time Period The total time consumed during the recharging trip in the internal driving period; Cost per unit of time; The constraints of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station include electric vehicle user behavior constraints, integrated photovoltaic-storage-charging-swapping station planning and operation constraints, and power-transportation coupled network planning and operation constraints. The planning and operation constraints for the integrated photovoltaic, energy storage, charging, and swapping station include: ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； In the above formula, For the first A typical intraday period of the year node The actual photovoltaic output of the integrated photovoltaic, energy storage, charging and swapping station; For the first A typical intraday period of the year node The output or input power within the photovoltaic, energy storage, charging, and battery swapping station; and The first A typical intraday period of the year By path Number of electric vehicles during the time period when they go to the photovoltaic-storage-charging-swapping integrated station for charging and battery swapping. and The first A typical intraday period of the year By path The number of electric vehicles going to the photovoltaic-storage-charging-swapping integrated station for charging and battery swapping during off-peak hours; For path With traffic nodes The correlation coefficient; For traffic nodes With distribution network nodes The correlation coefficient; The energy requirements for charging a single electric vehicle; Unit duration; For the first A typical intraday period of the year node The number of batteries that have completed charging within the integrated photovoltaic, energy storage, charging, and swapping station; No. A typical intraday period of the year node The number of electric vehicles performing V2G reverse discharge within the integrated photovoltaic, energy storage, charging, and swapping station. This represents the power of the V2G reverse discharge. For the first Annual distribution network nodes The maximum output of newly added photovoltaic power generation within the integrated photovoltaic, energy storage, charging, and swapping station; For the first Annual photovoltaic energy conversion efficiency coefficient; and These are the maximum discharge power and maximum charging power of a single energy storage unit, respectively. For the first Annual distribution network nodes The number of newly added energy storage systems within the integrated photovoltaic, energy storage, charging, and swapping station; The annual capacity decay rate of energy storage; For the first A typical intraday period of the year node The output or input power within the charging station; and These are the lower and upper limits of the energy state of the stored energy, respectively. The installed capacity of a single energy storage unit; This is the initial charge of the energy storage system; This represents the number of time periods within a typical day; For the first A typical intraday period of the year By path The number of electric vehicles going to the photovoltaic-storage-charging-swapping integrated station for V2G reverse discharge during idle periods; The average duration of V2G reverse discharge for a single electric vehicle; The charging power of a single charging station; and The first A typical intraday period of the year Distribution network nodes The number of batteries that have been charged and batteries that are yet to be charged stored in the integrated photovoltaic, energy storage, charging and swapping station; For the first A typical intraday period of the year node The number of batteries performing battery swapping operations within the integrated photovoltaic, energy storage, charging, and swapping station; and They are traffic network nodes The upper limit on the number of charging facilities and battery swapping facilities within an integrated photovoltaic, energy storage, charging, and swapping station; It is a large M constant; and These represent the time consumed for a single battery charge and a single battery swap operation, respectively. The electric vehicle user behavior constraints include: ； ； ； ； ； ； ； ； In the above formula, and The first A typical intraday period of the year By path The number of electric vehicles during peak hours and off-peak hours when they go to the photovoltaic-storage-charging-swapping integrated station for power replenishment. For the first The total number of vehicles requiring recharging during a typical midday off-peak period in a year; For the first The proportion of electric vehicles with autonomous driving capabilities in a given year; For the first A typical intraday period of the year By path The number of electric vehicles going to the photovoltaic-storage-charging-swapping integrated station for V2G reverse discharge during idle periods; For the first A typical intraday period of the year Traffic nodes The number of electric vehicles that are in idle periods and have sufficient power; For the first A typical intraday period of the year The driving time of electric vehicles during the designated usage period; For path The driving distance; For time period The congestion coefficient; The base driving speed; and The first A typical intraday period of the year The time and cost of charging and battery swapping; and These are the times for a single charge and for battery swapping, respectively. The operational constraints for the power-transportation coupled network planning include: ； ； ； ； ； ； ； ； ； In the above formula, and The first A typical intraday period of the year By path The number of electric vehicles during peak hours and off-peak hours when they go to the photovoltaic-storage-charging-swapping integrated station for power replenishment. For path With roads The correlation coefficient, For roads The original traffic capacity; To accommodate the increased traffic capacity resulting from road widening; and The first A typical intraday period of the year line Active and reactive power; To connect with distribution network nodes All connected lines; and The first A typical intraday period of the year Distribution network nodes The basic active and reactive loads connected at the point; For distribution network lines The original capacity; To accommodate the increased capacity following the expansion of the distribution network lines; and Distribution network lines Resistance and reactance; This refers to the rated voltage of the distribution network busbar. For time period Internal power distribution network lines Voltage drop on; and Time periods Internal distribution network nodes and Bus voltage, node and Distribution network lines The two endpoints; and These are the lower and upper limits of the distribution network bus voltage, respectively. S2. Solve the rolling planning model of the photovoltaic-storage-charging-swapping integrated station to obtain the planning scheme of the photovoltaic-storage-charging-swapping integrated station. The planning scheme includes the configuration scheme of charging and swapping, photovoltaic and energy storage facilities, the allocation scheme of charging and swapping and traffic demand, and the expansion scheme of the power-transportation coupling network.

2. A planning system for an integrated photovoltaic, energy storage, charging, and swapping station that considers the iterative changes in electricity and transportation demand, characterized in that: The system includes a model building module and a model solving module; The model building module is used to construct a rolling planning model for integrated photovoltaic-storage-charging-swapping stations in a power-transportation coupled network. This rolling planning model aims to minimize the overall system cost of charging and swapping, and considers the impact of technological upgrades, changes in user demand, and network expansion on the supply and demand of charging and swapping services during different planning periods. The objective function of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station includes: ； ； ； ； ； ； In the above formula, The cost of expanding the power-transportation coupled network; The configuration cost of charging and battery swapping facilities; For electricity purchase costs; Reduce the time cost of charging and swapping batteries for users; and The first Annual distribution network lines and transportation network roads Expanding decision variables; and These are the unit expansion costs for power distribution network lines and transportation network roads, respectively. The discount factor for planning investment costs; and The first Annual transportation network nodes The number of newly added charging piles and battery swapping facilities in the integrated photovoltaic, energy storage, charging and swapping station; and These are the unit configuration costs for charging piles and battery swapping facilities, respectively. The discount rate; For the investment cycle; The number of typical days in a year; For the first A typical intraday period of the year At that time, the power distribution network supplies power to the road. The active power output of the integrated photovoltaic, energy storage, charging and swapping station at the location; For time period The electricity price; For the first Year, Time Period The total time consumed during the recharging trip in the internal driving period; Cost per unit of time; The constraints of the rolling planning model for the integrated photovoltaic-storage-charging-swapping station include electric vehicle user behavior constraints, integrated photovoltaic-storage-charging-swapping station planning and operation constraints, and power-transportation coupled network planning and operation constraints. The planning and operation constraints for the integrated photovoltaic, energy storage, charging, and swapping station include: ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； In the above formula, For the first A typical intraday period of the year node The actual photovoltaic output of the integrated photovoltaic, energy storage, charging and swapping station; For the first A typical intraday period of the year node The output or input power within the photovoltaic, energy storage, charging, and battery swapping station; and The first A typical intraday period of the year By path Number of electric vehicles during the time period when they go to the photovoltaic-storage-charging-swapping integrated station for charging and battery swapping. and The first A typical intraday period of the year By path The number of electric vehicles going to the photovoltaic-storage-charging-swapping integrated station for charging and battery swapping during off-peak hours; For path With traffic nodes The correlation coefficient; For traffic nodes With distribution network nodes The correlation coefficient; The energy requirements for charging a single electric vehicle; Unit duration; For the first A typical intraday period of the year node The number of batteries that have completed charging within the integrated photovoltaic, energy storage, charging, and swapping station; No. A typical intraday period of the year node The number of electric vehicles performing V2G reverse discharge within the integrated photovoltaic, energy storage, charging, and swapping station. This represents the power of the V2G reverse discharge. For the first Annual distribution network nodes The maximum output of newly added photovoltaic power generation within the integrated photovoltaic, energy storage, charging, and swapping station; For the first Annual photovoltaic energy conversion efficiency coefficient; and These are the maximum discharge power and maximum charging power of a single energy storage unit, respectively. For the first Annual distribution network nodes The number of newly added energy storage systems within the integrated photovoltaic, energy storage, charging, and swapping station; The annual capacity decay rate of energy storage; For the first A typical intraday period of the year node The output or input power within the charging station; and These are the lower and upper limits of the energy state of the stored energy, respectively. The installed capacity of a single energy storage unit; This is the initial charge of the energy storage system; This represents the number of time periods within a typical day; For the first A typical intraday period of the year By path The number of electric vehicles going to the photovoltaic-storage-charging-swapping integrated station for V2G reverse discharge during idle periods; The average duration of V2G reverse discharge for a single electric vehicle; The charging power of a single charging station; and The first A typical intraday period of the year Distribution network nodes The number of batteries that have been charged and batteries that are yet to be charged stored in the integrated photovoltaic, energy storage, charging and swapping station; For the first A typical intraday period of the year node The number of batteries performing battery swapping operations within the integrated photovoltaic, energy storage, charging, and swapping station; and They are traffic network nodes The upper limit on the number of charging facilities and battery swapping facilities within an integrated photovoltaic, energy storage, charging, and swapping station; It is a large M constant; and These represent the time consumed for a single battery charge and a single battery swap operation, respectively. The electric vehicle user behavior constraints include: ； ； ； ； ； ； ； ； In the above formula, and The first A typical intraday period of the year By path The number of electric vehicles during peak hours and off-peak hours when they go to the photovoltaic-storage-charging-swapping integrated station for power replenishment. For the first The total number of vehicles requiring recharging during a typical midday off-peak period in a year; For the first The proportion of electric vehicles with autonomous driving capabilities in a given year; For the first A typical intraday period of the year By path The number of electric vehicles going to the photovoltaic-storage-charging-swapping integrated station for V2G reverse discharge during idle periods; For the first A typical intraday period of the year Traffic nodes The number of electric vehicles that are in idle periods and have sufficient power; For the first A typical intraday period of the year The driving time of electric vehicles during the designated usage period; For path The driving distance; For time period The congestion coefficient; The base driving speed; and The first A typical intraday period of the year The time and cost of charging and battery swapping; and These are the times for a single charge and for battery swapping, respectively. The operational constraints for the power-transportation coupled network planning include: ； ； ； ； ； ； ； ； ； In the above formula, and The first A typical intraday period of the year By path The number of electric vehicles during peak hours and off-peak hours when they go to the photovoltaic-storage-charging-swapping integrated station for power replenishment. For path With roads The correlation coefficient, For roads The original traffic capacity; To accommodate the increased traffic capacity resulting from road widening; and The first A typical intraday period of the year line Active and reactive power; To connect with distribution network nodes All connected lines; and The first A typical intraday period of the year Distribution network nodes The basic active and reactive loads connected at the point; For distribution network lines The original capacity; To accommodate the increased capacity following the expansion of the distribution network lines; and Distribution network lines Resistance and reactance; This refers to the rated voltage of the distribution network busbar. For time period Internal power distribution network lines Voltage drop on; and Time periods Internal distribution network nodes and Bus voltage, node and Distribution network lines The two endpoints; and These are the lower and upper limits of the distribution network bus voltage, respectively. The model solving module is used to solve the rolling planning model of the photovoltaic-storage-charging-swapping integrated station in a rolling manner, so as to obtain the planning scheme of the photovoltaic-storage-charging-swapping integrated station. The planning scheme includes the configuration scheme of charging and swapping, photovoltaic and energy storage facilities, the allocation scheme of charging and swapping and traffic demand, and the expansion scheme of the power-transportation coupling network.

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