Optical storage, charging and conversion integrated station planning method and system considering electricity utilization-traffic demand iteration

Abstract

The invention discloses an optical storage, charging and conversion integrated station planning method and system considering electricity utilization-traffic demand iteration, and the method comprises the steps: firstly constructing an optical storage, charging and conversion integrated station rolling planning model of an electric power-traffic coupling network with the minimum system comprehensive charging and conversion cost as a target, and then solving the optical storage, charging and conversion integrated station rolling planning model in a rolling manner. And obtaining a planning scheme of the optical storage, charging and conversion integrated station including a configuration scheme of charging and conversion, photovoltaic and energy storage facilities, a charging and conversion and traffic demand distribution scheme, and a capacity expansion scheme of a power-traffic coupling network. According to the method, the influence of technical upgrading, user demand change and network capacity expansion in different planning time periods on the supply-demand relationship of the charging and battery swap service is considered, and by rolling optimization of planning and operation schemes of the charging and battery swap station and the electric power-traffic coupling network, on the premise of meeting the time-varying charging and battery swap and traffic demands of the electric vehicle user, the charging and battery swap efficiency is improved. And the comprehensive charging cost of the system is minimized.

Description

Technical Field

[0001] The present invention belongs to the field of power-traffic coupling network planning, and specifically relates to a photovoltaic storage charging and swapping integrated station planning method and system that considers the iteration of power consumption and traffic demand. Background Art

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

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

[0004] At the network level, with the popularization of electric vehicles and charging and swapping facilities, the demand for expansion of transportation networks and power distribution networks has become increasingly urgent. How to optimize the coupling relationship between transportation networks and power networks while meeting user needs has become a key link in rolling planning. Through regular evaluation and dynamic adjustment, this planning method can effectively cope with the uncertainties brought about by technological progress and market changes, and ensure the efficient, safe and sustainable development of charging and swapping services.

[0005] At the same time, in the electric vehicle industry chain, the rapid upgrading of technology has significantly affected the capacity and efficiency of charging and swapping services. The development of battery technology has directly improved the range and charging speed of electric vehicles, while the progress of photovoltaic power generation technology has enhanced the utilization efficiency of renewable energy. These technological advances have not only changed the operation mode of charging and swapping stations, but also put forward new requirements for the configuration of energy systems. Summary of the invention

[0006] The purpose of the present invention is to provide a method and system for planning a photovoltaic storage charging and swapping integrated station taking into account the iteration of electricity consumption and traffic demand in order to solve the above-mentioned problems existing in the prior art.

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

[0008] In a first aspect, the present invention proposes a method for planning a photovoltaic storage charging and swapping integrated station considering the iteration of electricity consumption and traffic demand, comprising:

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

[0010] S2. Rollingly solve the rolling planning model of the integrated photovoltaic, storage and charging / swapping station to obtain a planning scheme for the integrated photovoltaic, storage and charging / swapping station, which includes a configuration scheme for charging / swapping, photovoltaic and energy storage facilities, a charging / swapping and traffic demand allocation scheme, and a capacity expansion scheme for the power-traffic coupling network.

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

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

[0013]

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

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

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

[0017]

[0018]

[0019] In the above formula, is the actual photovoltaic output of the photovoltaic storage and charging-swapping integrated station at node e during a typical day in year y; is the output or input power of the photovoltaic storage charging and swapping station at node e during a typical day in year y; and They are the number of electric vehicles that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; and are the number of electric vehicles in the idle period that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; is the correlation coefficient between path k and traffic node g; is the correlation coefficient between traffic node g and distribution network node e; E U is the charging energy requirement of a single electric vehicle; T U is the unit duration; is the number of batteries that have completed charging in the photovoltaic storage and charging and swapping integrated station at node e during a typical day in year y; The number of electric vehicles performing V2G reverse discharge in the photovoltaic storage charging and swapping integrated station at node e during a typical day in year y; P VG is the power of V2G reverse discharge; The maximum output of the newly added photovoltaic power in the photovoltaic storage and charging and swapping integrated station at the distribution network node e in the yxth year; is the photovoltaic energy conversion efficiency coefficient in the yth year; P EH and P ED They are the maximum discharge power and maximum charging power of a single energy storage unit respectively; is the number of energy storage systems newly added in the photovoltaic storage and charging-swap integrated station at the distribution network node e in year yx; E is the annual capacity decay rate of energy storage; is the output or input power of the charging station at node e during a typical day in year y; L and η H are the lower and upper limits of the energy storage state, respectively; EC E is the installed capacity of a single energy storage unit; EC O is the initial power of the energy storage system; tn is the number of time periods in a typical day; is the number of electric vehicles in the idle period during a typical day in year y that travel to the photovoltaic storage charging and swapping integrated station via path k for V2G reverse discharge; T VG is the average duration of V2G reverse discharge of a single electric vehicle; P UCThe charging power of a single charging pile; and are the number of charged batteries and batteries to be charged stored in the photovoltaic storage charging and swapping integrated station at the distribution network node e during a typical day period t in year y; is the number of batteries that perform battery swapping operations in the PV-storage-charging-swap integrated station at node e during a typical day in year y; and are the upper limits of the number of charging facilities and battery swapping facilities in the integrated photovoltaic storage charging and swapping station at the transportation network node g; δ M is the large M constant; T UC and T US The time consumed for a single battery charging and a single battery replacement operation respectively.

[0020] The electric vehicle user behavior constraints include:

[0021]

[0022]

[0023] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the total number of vehicles that need to be recharged during a typical daytime idle period in year y; is the proportion of electric vehicles with autonomous driving functions in year y; is the number of electric vehicles in the idle period that go to the photovoltaic storage charging and swapping integrated station for V2G reverse discharge via route k during a typical day in year y during period t; is the number of electric vehicles that are idle and fully charged at traffic node g during a typical day in year y; TI y,t is the driving time of the electric vehicle during the vehicle usage period at time t on a typical day in year y; L k is the travel distance of path k; is the congestion coefficient of time period t; v U is the reference speed; TC y,t and TS y,t are the time costs of charging and battery replacement in a typical day period t in year y; TI C and TI S The time taken for a single charge and battery replacement respectively.

[0024] The planning and operation constraints of the power-transportation coupling network include:

[0025]

[0026]

[0027] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the correlation coefficient between path k and road l, is the original traffic capacity of road l; R A To increase traffic capacity after implementing road expansion; and are respectively the active and reactive power on line w in a typical day period t in year y; w represents all lines connected to the distribution network node e; and are the basic active and reactive loads connected to the distribution network node e in a typical day period t in year y, respectively; is the original capacity of the distribution network line w; L A To increase the capacity after the expansion of the distribution network lines; and are the resistance and reactance of the distribution network line w respectively; U N is the rated voltage of the distribution network bus; ΔU t,w is the voltage drop on the distribution network line w in time period t; U t,a and U t,b are the bus voltages of nodes a and b in the distribution network in time period t, and nodes a and b are the two endpoints of the distribution network line w; U m and U M They are the lower and upper limits of the distribution network bus voltage respectively.

[0028] In the second aspect, the present invention proposes a photovoltaic storage charging and swapping integrated station planning system that considers the iteration of electricity consumption and transportation demand, including a model building module and a model solving module; the model building module is used to construct a photovoltaic storage charging and swapping integrated station rolling planning model for the power-traffic coupling network, and the photovoltaic storage charging and swapping integrated station rolling planning model aims to minimize the comprehensive charging and swapping cost of the system, and considers the impact of technology upgrades, user demand changes and network expansion in different planning periods on the supply and demand relationship of charging and swapping services;

[0029] The model solving module is used to rollingly solve the rolling planning model of the photovoltaic storage charging and swapping integrated station to obtain a planning scheme for the photovoltaic storage charging and 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-traffic coupling network.

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

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

[0032]

[0033]

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

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

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

[0037]

[0038]

[0039] In the above formula, is the actual photovoltaic output of the photovoltaic storage and charging-swapping integrated station at node e during a typical day in year y; is the output or input power of the photovoltaic storage charging and swapping station at node e during a typical day in year y; and They are the number of electric vehicles that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; and are the number of electric vehicles in the idle period that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; is the correlation coefficient between path k and traffic node g; is the correlation coefficient between traffic node g and distribution network node e; E U is the charging energy requirement of a single electric vehicle; T U is the unit duration; is the number of batteries that have completed charging in the photovoltaic storage and charging and swapping integrated station at node e during a typical day in year y; The number of electric vehicles performing V2G reverse discharge in the photovoltaic storage charging and swapping integrated station at node e during a typical day in year y; P VG is the power of V2G reverse discharge; The maximum output of the newly added photovoltaic power in the photovoltaic storage and charging and swapping integrated station at the distribution network node e in the yxth year; is the photovoltaic energy conversion efficiency coefficient in the yth year; P EH and P ED They are the maximum discharge power and maximum charging power of a single energy storage unit respectively; is the number of energy storage systems newly added in the photovoltaic storage and charging-swap integrated station at the distribution network node e in year yx; E is the annual capacity decay rate of energy storage; is the output or input power of the charging station at node e during a typical day in year y; L and η H are the lower and upper limits of the energy storage state, respectively; EC E is the installed capacity of a single energy storage unit; EC O is the initial power of the energy storage system; tn is the number of time periods in a typical day; is the number of electric vehicles in the idle period during a typical day in year y that travel to the photovoltaic storage charging and swapping integrated station via path k for V2G reverse discharge; T VG is the average duration of V2G reverse discharge of a single electric vehicle; P UC The charging power of a single charging pile; and are the number of charged batteries and batteries to be charged stored in the photovoltaic storage charging and swapping integrated station at the distribution network node e during a typical day period t in year y; is the number of batteries that perform battery swapping operations in the PV-storage-charging-swap integrated station at node e during a typical day in year y; and are the upper limits of the number of charging facilities and battery swapping facilities in the integrated photovoltaic storage charging and swapping station at the transportation network node g; δ M is the large M constant; T UC and T US The time consumed for a single battery charging and a single battery replacement operation respectively.

[0040] The electric vehicle user behavior constraints include:

[0041]

[0042] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the total number of vehicles that need to be recharged during a typical daytime idle period in year y; is the proportion of electric vehicles with autonomous driving functions in year y; is the number of electric vehicles in the idle period that go to the photovoltaic storage charging and swapping integrated station for V2G reverse discharge via route k during a typical day in year y during period t; is the number of electric vehicles that are idle and fully charged at traffic node g during a typical day in year y; TI y,t is the driving time of the electric vehicle during the vehicle usage period at time t on a typical day in year y; L k is the travel distance of path k; is the congestion coefficient of time period t; v U is the reference speed; TC y,t and TS y,t are the time costs of charging and battery replacement in a typical day period t in year y; TI C and TI S The time taken for a single charge and battery replacement respectively.

[0043] The planning and operation constraints of the power-transportation coupling network include:

[0044]

[0045] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the correlation coefficient between path k and road l, is the original traffic capacity of road l; RA To increase traffic capacity after implementing road expansion; and are respectively the active and reactive power on line w in a typical day period t in year y; w represents all lines connected to the distribution network node e; and are the basic active and reactive loads connected to the distribution network node e in a typical day period t in year y, respectively; is the original capacity of the distribution network line w; L A To increase the capacity after the expansion of the distribution network lines; and are the resistance and reactance of the distribution network line w respectively; U N is the rated voltage of the distribution network bus; ΔU t,w is the voltage drop on the distribution network line w in time period t; U t,a and U t,b are the bus voltages of nodes a and b in the distribution network in time period t, and nodes a and b are the two endpoints of the distribution network line w; U m and U M They are the lower and upper limits of the distribution network bus voltage respectively.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention proposes a method for planning photovoltaic storage charging and swapping integrated stations that takes into account the iteration of electricity consumption and transportation demand. First, a rolling planning model of photovoltaic storage charging and swapping integrated stations of the power-transportation coupling network is constructed with the goal of minimizing the comprehensive charging and swapping cost of the system. Then, the rolling planning model of the photovoltaic storage charging and swapping integrated stations is solved to obtain a planning scheme for the photovoltaic storage charging and swapping integrated stations that includes a configuration scheme for charging and swapping, photovoltaic and energy storage facilities, a charging and swapping and transportation demand allocation scheme, and a capacity expansion scheme for the power-transportation coupling network. The model takes into account the impact of technology upgrades, changes in user demand, and network expansion on the supply and demand relationship of charging and swapping services in different planning periods. By rollingly optimizing the planning and operation schemes of charging and swapping stations and the power-transportation coupling network, the comprehensive charging and swapping cost of the system is minimized while meeting the time-varying charging and swapping and transportation needs of electric vehicle users. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the structure of the power-transportation coupling network described in the present invention.

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

[0050] Figure 3 This is the congestion coefficient time series characteristic curve used in Example 1.

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

[0052] Figure 5 This is the photovoltaic output characteristic curve used in Example 1.

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

[0054] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0055] The present invention proposes a photovoltaic storage charging and swapping integrated station planning method considering the iteration of electricity consumption and traffic demand. Figure 1 The power-transportation coupling network shown in the figure adopts a rolling planning approach, fully considering the impact of technology upgrades, changes in user demand, and network expansion on the supply and demand relationship of charging and swapping related services in different planning periods. Specifically,

[0056] On 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 been improved with the development of technology. In the planning model, the present invention takes into account the impact of the above-mentioned technological upgrades on the service capacity of charging and swapping stations and the utilization rate of renewable energy, and optimizes the configuration of charging and swapping facilities and supporting photovoltaic and energy storage facilities.

[0057] At the user demand level, full consideration is given to the growth in charging and swapping and transportation demand brought about by the increase in the number of electric vehicles. At the same time, the load flexibility brought by multi-mode orderly charging during all periods (owners drive during vehicle use periods and automatic driving during idle periods) and V2G reverse discharge participating in auxiliary services are taken into account to optimize the allocation of charging and swapping and transportation demands.

[0058] At the network level, considering the new demands for transportation and distribution networks caused by the increase in charging and swapping and traffic demand, the roads and distribution network lines of the power-transportation coupling network are optimized and expanded while meeting user needs and network constraints.

[0059] Embodiment 1:

[0060] In this embodiment, the topology structure is as follows Figure 2The 23-node distribution network-19-node transportation network shown (two integrated photovoltaic storage charging and swapping stations are located at P5 (T6) and P10 (T13) respectively, with the following parameters: the investment period is 10 years; the discount rate is 0.05; the unit time is 1 hour; the investment period is 10 years; the typical number of days in a year is 365 days; the unit expansion costs of the distribution network lines and transportation network roads are 1 million yuan and 2 million yuan respectively; the unit configuration costs of charging piles and battery swapping facilities are 10,000 yuan and 200,000 yuan respectively; the unit time cost is 20 yuan / hour; the benchmark driving speed is 40 kilometers / hour; The charging power of a single charging pile is 80 kW; the time for a single charge and battery replacement 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 is 40 kWh; the maximum discharge power and maximum charging power of a single energy storage are 20 kW; the lower and upper limits of the energy state of the energy storage are 0.1 and 0.9 respectively; the annual capacity decay rate of the energy storage is 0.95; the average time for a single electric vehicle V2G reverse discharge is 3 hours; the congestion coefficient timing characteristic curve, time-of-use electricity price and photovoltaic output characteristic curve are as follows: Figure 3 , Figure 4 and Figure 5 As shown in FIG. 1 , the photovoltaic storage charging and swapping integrated station planning method considering the iteration of electricity consumption and traffic demand of the present invention is implemented, including:

[0061] 1. Construct a rolling planning model for photovoltaic storage and charging stations in the power-transportation coupling network

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

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

[0064]

[0065] In the above formula, C N is the expansion cost of the power-transportation coupling network; C P is the configuration cost of charging and swapping facilities; C E is the electricity purchase cost; C T The time cost of charging and replacing batteries for users; and are the expansion decision variables of the distribution network line w and the traffic network road l in year y, respectively. or When it is 1, the capacity is expanded; when it is 0, the capacity is not expanded; PR EP and PR TPare the unit expansion costs of distribution network lines and transportation network roads respectively; y The discount factor for planning investment costs; and are the number of newly added charging piles and battery swapping facilities in the photovoltaic storage charging and swapping integrated station at the transportation network node g in year y; PR CP and PR SF are the unit configuration costs of charging piles and battery swapping facilities respectively; α is the discount rate; γ is the investment period; d is the number of typical days in a year; is the active power output by the distribution network to the PV-storage-charging-swap integrated station on road l at time t on a typical day in year y; is the electricity price in period t; TA y,t PR is the total time consumed by the charging trip during the vehicle use period in period t in year y; T The unit time cost.

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

[0067] (1) Behavior constraints for electric vehicle users

[0068] There are three ways for users to operate electric vehicle batteries: charging mode, battery replacement mode, and V2G mode. In terms of travel, users can choose to go to the photovoltaic storage charging and replacement station during the trip, or they can use the vehicle's automatic driving mode to go to the photovoltaic storage charging and replacement station by themselves during non-use periods. Of the two methods, only the former consumes the user's time cost. Electric vehicles in the travel period must complete charging, battery replacement or V2G reverse discharge during this period, while electric vehicles in the idle period have higher flexibility and can flexibly choose the time period for charging, battery replacement or V2G reverse discharge while meeting the power replenishment needs. Therefore, the specific settings of electric vehicle user behavior constraints are as follows:

[0069]

[0070]

[0071] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the total number of vehicles that need to be recharged during a typical daytime idle period in year y; is the proportion of electric vehicles with autonomous driving functions in year y; is the number of electric vehicles in the idle period that go to the photovoltaic storage charging and swapping integrated station for V2G reverse discharge via route k during a typical day in year y during period t; is the number of electric vehicles that are idle and fully charged at traffic node g during a typical day in year y; TI y,t is the driving time of the electric vehicle during the vehicle usage period at time t on a typical day in year y; L k is the travel distance of path k; is the congestion coefficient of time period t; v U is the reference speed; TC y,t and TS y,t are the time costs of charging and battery replacement in a typical day period t in year y; TI C and TI S The time taken for a single charge and battery replacement respectively.

[0072] In this constraint, equations (7)-(10) are constraints on the number of electric vehicles that use different charging measures in different time periods; equations (11)-(14) are constraints on the time consumption of electric vehicle charging trips during the vehicle use period.

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

[0074]

[0075]

[0076] In the above formula, is the actual photovoltaic output of the photovoltaic storage and charging-swapping integrated station at node e during a typical day in year y; is the output or input power of the photovoltaic storage charging and swapping station at node e during a typical day in year y; and They are the number of electric vehicles that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; and are the number of electric vehicles in the idle period that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; is the correlation coefficient between path k and traffic node g; is the correlation coefficient between traffic node g and distribution network node e; E U is the charging energy requirement of a single electric vehicle; T U is the unit duration; is the number of batteries that have completed charging in the photovoltaic storage and charging and swapping integrated station at node e during a typical day in year y; The number of electric vehicles performing V2G reverse discharge in the photovoltaic storage charging and swapping integrated station at node e during a typical day in year y; P VG is the power of V2G reverse discharge; The maximum output of the newly added photovoltaic power in the photovoltaic storage and charging and swapping integrated station at the distribution network node e in the yxth year; is the photovoltaic energy conversion efficiency coefficient in the yth year; P EH and P ED They are the maximum discharge power and maximum charging power of a single energy storage unit respectively; is the number of energy storage systems newly added in the photovoltaic storage and charging-swap integrated station at the distribution network node e in year yx; E is the annual capacity decay rate of energy storage; is the output or input power of the charging station at node e during a typical day in year y; L and η H are the lower and upper limits of the energy storage state, respectively; EC E is the installed capacity of a single energy storage unit; EC O is the initial power of the energy storage system; tn is the number of time periods in a typical day; is the number of electric vehicles in the idle period during a typical day in year y that travel to the photovoltaic storage charging and swapping integrated station via path k for V2G reverse discharge; T VG is the average duration of V2G reverse discharge of a single electric vehicle; P UC The charging power of a single charging pile; and are the number of charged batteries and batteries to be charged stored in the photovoltaic storage charging and swapping integrated station at the distribution network node e during a typical day period t in year y; is the number of batteries that perform battery swapping operations in the PV-storage-charging-swap integrated station at node e during a typical day in year y; and are the upper limits of the number of charging facilities and battery swapping facilities in the integrated photovoltaic storage charging and swapping station at the transportation network node g; δ M is the large M constant; T UC and T US The time consumed for a single battery charging and a single battery replacement operation respectively.

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

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

[0079]

[0080]

[0081] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the correlation coefficient between path k and road l, is the original traffic capacity of road l; R A To increase traffic capacity after implementing road expansion; and are respectively the active and reactive power on line w in a typical day period t in year y; w represents all lines connected to the distribution network node e; and are the basic active and reactive loads connected to the distribution network node e in a typical day period t in year y, respectively; is the original capacity of the distribution network line w; L A To increase the capacity after the expansion of the distribution network lines; and are the resistance and reactance of the distribution network line w respectively; U N is the rated voltage of the distribution network bus; ΔU t,w is the voltage drop on the distribution network line w in time period t; U t,a and U t,b are the bus voltages of nodes a and b in the distribution network in time period t, and nodes a and b are the two endpoints of the distribution network line w; U m and U M They are the lower and upper limits of the distribution network bus voltage respectively.

[0082] In this constraint, equation (30) is the traffic capacity constraint of each road; equation (31) is the road expansion constraint, that is, only one road can be expanded once in one planning cycle; equations (32) and (33) are the active and reactive power balance constraints of the distribution network nodes in each year, respectively; 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 in one planning cycle; equations (36)-(38) are the distribution network node voltage constraints.

[0083] 2. Rollingly solve the rolling planning model of the integrated photovoltaic, storage and charging and swapping station to obtain the planning scheme of the integrated photovoltaic, storage and charging and swapping station, which 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-traffic coupling network.

[0084] In order to verify the effectiveness of the method proposed in the present invention, the method described in Example 1 is used as Method 1, and the traditional planning method of the photovoltaic storage charging and swapping integrated station is used as Method 2 and applied to the 23-node distribution network-19-node transportation network described in Example 1 (Method 2 does not consider the iteration of electricity-traffic demand within the planning period, and does not consider the impact of electric vehicle automatic driving). The economic indicators of the two methods are compared, and the results are shown in Table 1 (wherein the hardware facility cost includes the expansion cost of the power-traffic coupling network and the configuration cost of charging and swapping related facilities):

[0085] Table 1 Comparison of the economic performance of the two methods

[0086]

[0087] As shown in Table 1, the annual comprehensive charging and swapping cost is lower when using method 1. In terms of hardware facility cost, the cost of using method 1 is reduced by 4.95% compared with that of using method 2; in terms of annual electricity purchase cost, the cost of using method 1 is reduced by 8.46% compared with that of using method 2; in terms of annual charging and swapping time cost, the cost of using method 1 is reduced by 21.78% compared with that of using method 2. In terms of annual comprehensive charging and swapping cost, the cost of using method 1 is reduced by 10.06% compared with that of using method 2.

[0088] The above results show that the method proposed in the present invention achieves the effect of minimizing the comprehensive charging and replacement costs of the system while meeting the time-varying charging and replacement and traffic needs of electric vehicle users.

[0089] Embodiment 2:

[0090] like Figure 6 As shown, a photovoltaic storage charging and swapping integrated station planning system considering the iteration of electricity consumption and traffic demand includes a model building module and a model solving module.

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

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

[0093]

[0094] In the above formula, C N is the expansion cost of the power-transportation coupling network; C P is the configuration cost of charging and swapping facilities; C E is the electricity purchase cost; C T The time cost of charging and replacing batteries for users; and are the expansion decision variables of the distribution network line w and the traffic network road l in year y; PR EP and PR TP are the unit expansion costs of distribution network lines and transportation network roads respectively; y The discount factor for the planned investment cost; and are the number of newly added charging piles and battery swapping facilities in the photovoltaic storage charging and swapping integrated station at the transportation network node g in year y; PR CP and PR SF are the unit configuration costs of charging piles and battery swapping facilities respectively; α is the discount rate; γ is the investment period; d is the number of typical days in a year; is the active power output by the distribution network to the PV-storage-charging-swap integrated station on road l at time t on a typical day in year y; is the electricity price in period t; TA y,t PR is the total time consumed by the charging trip during the vehicle use period in period t in year y; T is the unit time cost;

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

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

[0097]

[0098]

[0099] In the above formula, is the actual photovoltaic output of the photovoltaic storage and charging-swapping integrated station at node e during a typical day in year y; is the output or input power of the photovoltaic storage charging and swapping station at node e during a typical day in year y; and They are the number of electric vehicles that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; and are the number of electric vehicles in the idle period that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; is the correlation coefficient between path k and traffic node g; is the correlation coefficient between traffic node g and distribution network node e; E U is the charging energy requirement of a single electric vehicle; T U is the unit duration; is the number of batteries that have completed charging in the photovoltaic storage and charging and swapping integrated station at node e during a typical day in year y; The number of electric vehicles performing V2G reverse discharge in the photovoltaic storage charging and swapping integrated station at node e during a typical day in year y; P VG is the power of V2G reverse discharge; The maximum output of the newly added photovoltaic power in the photovoltaic storage and charging and swapping integrated station at the distribution network node e in the yxth year; is the photovoltaic energy conversion efficiency coefficient in the yth year; P EH and P ED They are the maximum discharge power and maximum charging power of a single energy storage unit respectively; is the number of energy storage systems newly added in the photovoltaic storage and charging-swap integrated station at the distribution network node e in year yx; E is the annual capacity decay rate of energy storage; is the output or input power of the charging station at node e during a typical day in year y; L and η H are the lower and upper limits of the energy storage state, respectively; EC E is the installed capacity of a single energy storage unit; EC O is the initial power of the energy storage system; tn is the number of time periods in a typical day; is the number of electric vehicles in the idle period during a typical day in year y that travel to the photovoltaic storage charging and swapping integrated station via path k for V2G reverse discharge; T VG is the average duration of V2G reverse discharge of a single electric vehicle; P UC The charging power of a single charging pile; and are the number of charged batteries and batteries to be charged stored in the photovoltaic storage charging and swapping integrated station at the distribution network node e during a typical day period t in year y; is the number of batteries that perform battery swapping operations in the PV-storage-charging-swap integrated station at node e during a typical day in year y; and are the upper limits of the number of charging facilities and battery swapping facilities in the integrated photovoltaic storage charging and swapping station at the transportation network node g; δ M is the large M constant; T UC and T US The time consumed for a single battery charging and a single battery replacement operation respectively;

[0100] Behavior constraints for electric vehicle users

[0101]

[0102] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the total number of vehicles that need to be recharged during a typical daytime idle period in year y; is the proportion of electric vehicles with autonomous driving functions in year y; is the number of electric vehicles in the idle period that go to the photovoltaic storage charging and swapping integrated station for V2G reverse discharge via route k during a typical day in year y during period t; is the number of electric vehicles that are idle and fully charged at traffic node g during a typical day in year y; TI y,t is the driving time of the electric vehicle during the vehicle usage period at time t on a typical day in year y; L k is the travel distance of path k; is the congestion coefficient of time period t; v U is the reference speed; TC y,t and TS y,t are the time costs of charging and battery replacement in a typical day period t in year y; TI C and TI S The time taken for a single charge and battery replacement respectively;

[0103] Planning and operation constraints of power-transportation coupling network

[0104]

[0105] In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the correlation coefficient between path k and road l, is the original traffic capacity of road l; RA To increase traffic capacity after implementing road expansion; and are respectively the active and reactive power on line w in a typical day period t in year y; w represents all lines connected to the distribution network node e; and are the basic active and reactive loads connected to the distribution network node e in a typical day period t in year y, respectively; is the original capacity of the distribution network line w; L A To increase the capacity after the expansion of the distribution network lines; and are the resistance and reactance of the distribution network line w respectively; U N is the rated voltage of the distribution network bus; ΔU t,w is the voltage drop on the distribution network line w in time period t; U t,a and U t,b are the bus voltages of nodes a and b in the distribution network in time period t, and nodes a and b are the two endpoints of the distribution network line w; U m and U M They are the lower and upper limits of the distribution network bus voltage respectively.

[0106] The model solving module is used to rollingly solve the rolling planning model of the photovoltaic storage charging and swapping integrated station to obtain a planning scheme for the photovoltaic storage charging and 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-traffic coupling network.

Claims

1. A method for planning a photovoltaic storage charging and swapping integrated station considering the iteration of electricity consumption and traffic demand, characterized in that: The method comprises: S1. Construct a rolling planning model for integrated photovoltaic storage and charging stations in the power-transportation coupling network. The rolling planning model for integrated photovoltaic storage and charging stations aims to minimize the comprehensive charging and swapping cost of the system, and considers the impact of technology upgrades, changes in user demand, and network expansion in different planning periods on the supply and demand relationship of charging and swapping services; S2. Rollingly solve the rolling planning model of the integrated photovoltaic, storage and charging / swapping station to obtain a planning scheme for the integrated photovoltaic, storage and charging / swapping station, which includes a configuration scheme for charging / swapping, photovoltaic and energy storage facilities, a charging / swapping and traffic demand allocation scheme, and a capacity expansion scheme for the power-traffic coupling network.

2. According to claim 1, a method for planning a photovoltaic storage charging and swapping integrated station considering the iteration of electricity consumption and traffic demand is characterized in that: The objective function of the rolling planning model of the photovoltaic storage charging and swapping integrated station includes: my C N +C P +C E +C T ; In the above formula, C N is the expansion cost of the power-transportation coupling network; C P is the configuration cost of charging and swapping facilities; C E is the electricity purchase cost; C T The time cost of charging and replacing batteries for users; and are the expansion decision variables of the distribution network line w and the traffic network road l in year y; PR EP and PR TP are the unit expansion costs of distribution network lines and transportation network roads respectively; y The discount factor for the planned investment cost; and are the number of newly added charging piles and battery swapping facilities in the photovoltaic storage charging and swapping integrated station at the transportation network node g in year y; PR CP and PR SF are the unit configuration costs of charging piles and battery swapping facilities respectively; α is the discount rate; γ is the investment period; d is the number of typical days in a year; is the active power output by the distribution network to the PV-storage-charging-swap integrated station on road l at time t on a typical day in year y; is the electricity price in period t; TA y,t PR is the total time consumed by the charging trip during the vehicle use period in period t in year y; T is the unit time cost; The constraints of the photovoltaic storage charging and swapping integrated station rolling planning model include electric vehicle user behavior constraints, photovoltaic storage charging and swapping integrated station planning and operation constraints, and power-transportation coupling network planning and operation constraints.

3. According to claim 2, a method for planning a photovoltaic storage charging and swapping integrated station considering the iteration of electricity consumption and traffic demand is characterized in that: The planning and operation constraints of the integrated photovoltaic storage and charging and swapping station include: In the above formula, is the actual photovoltaic output of the photovoltaic storage and charging-swapping integrated station at node e during a typical day in year y; is the output or input power of the photovoltaic storage charging and swapping station at node e during a typical day in year y; and They are the number of electric vehicles that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; and are the number of electric vehicles in the idle period that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; is the correlation coefficient between path k and traffic node g; is the correlation coefficient between traffic node g and distribution network node e; E U is the charging energy requirement of a single electric vehicle; T U is the unit duration; is the number of batteries that have completed charging in the photovoltaic storage and charging and swapping integrated station at node e during a typical day in year y; The number of electric vehicles performing V2G reverse discharge in the photovoltaic storage charging and swapping integrated station at node e during a typical day in year y; P VG is the power of V2G reverse discharge; The maximum output of the newly added photovoltaic power in the photovoltaic storage and charging and swapping integrated station at the distribution network node e in the yxth year; is the photovoltaic energy conversion efficiency coefficient in the yth year; P EH and P ED They are the maximum discharge power and maximum charging power of a single energy storage unit respectively; is the number of energy storage systems newly added in the photovoltaic storage and charging-swap integrated station at the distribution network node e in year yx; E is the annual capacity decay rate of energy storage; is the output or input power of the charging station at node e during a typical day in year y; L and η H are the lower and upper limits of the energy storage state, respectively; EC E is the installed capacity of a single energy storage unit; EC O is the initial power of the energy storage system; tn is the number of time periods in a typical day; is the number of electric vehicles in the idle period during a typical day in year y that travel to the photovoltaic storage charging and swapping integrated station via path k for V2G reverse discharge; T VG is the average duration of V2G reverse discharge of a single electric vehicle; P UC The charging power of a single charging pile; and are the number of charged batteries and batteries to be charged stored in the photovoltaic storage charging and swapping integrated station at the distribution network node e during a typical day period t in year y; is the number of batteries that perform battery swapping operations in the PV-storage-charging-swap integrated station at node e during a typical day in year y; and are the upper limits of the number of charging facilities and battery swapping facilities in the integrated photovoltaic storage charging and swapping station at the transportation network node g; δ M is the large M constant; T UC and T US The time consumed for a single battery charging and a single battery replacement operation respectively.

4. A method for planning a photovoltaic storage charging and swapping integrated station considering the iteration of electricity consumption and traffic demand according to claim 3, characterized in that: The electric vehicle user behavior constraints include: In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the total number of vehicles that need to be recharged during a typical daytime idle period in year y; is the proportion of electric vehicles with autonomous driving functions in year y; is the number of electric vehicles in the idle period that go to the photovoltaic storage charging and swapping integrated station for V2G reverse discharge via route k during a typical day in year y during period t; is the number of electric vehicles that are idle and fully charged at traffic node g during a typical day in year y; TI y,t is the driving time of the electric vehicle during the vehicle usage period at time t on a typical day in year y; L k is the travel distance of path k; is the congestion coefficient of time period t; v U is the reference speed; TC y,t and TS y,t are the time costs of charging and battery replacement in a typical day period t in year y; TI C and TI S The time taken for a single charge and battery replacement respectively.

5. A method for planning a photovoltaic storage charging and swapping integrated station considering the iteration of electricity consumption and traffic demand according to any one of claims 2 to 4, characterized in that: The planning and operation constraints of the power-transportation coupling network include: In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the correlation coefficient between path k and road l, is the original traffic capacity of road l; R A To increase traffic capacity after implementing road expansion; and are respectively the active and reactive power on line w in a typical day period t in year y; w represents all lines connected to the distribution network node e; and are the basic active and reactive loads connected to the distribution network node e in a typical day period t in year y, respectively; is the original capacity of the distribution network line w; L A To increase the capacity after the expansion of the distribution network lines; and are the resistance and reactance of the distribution network line w respectively; U N is the rated voltage of the distribution network bus; ΔU t,w is the voltage drop on the distribution network line w in time period t; U t,a and U t,b are the bus voltages of nodes a and b in the distribution network in time period t, and nodes a and b are the two endpoints of the distribution network line w; U m and U M They are the lower and upper limits of the distribution network bus voltage respectively.

6. A photovoltaic storage charging and swapping integrated station planning system considering the iteration of electricity consumption and traffic demand, characterized in that: The system includes a model building module and a model solving module; the model building module is used to build a rolling planning model for photovoltaic storage charging and swapping integrated stations of the power-traffic coupling network, the photovoltaic storage charging and swapping integrated station rolling planning model aims to minimize the comprehensive charging and swapping cost of the system, and considers the impact of technology upgrades, user demand changes and network expansion in different planning periods on the supply and demand relationship of charging and swapping services; The model solving module is used to rollingly solve the rolling planning model of the photovoltaic storage charging and swapping integrated station to obtain a planning scheme for the photovoltaic storage charging and 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-traffic coupling network.

7. A photovoltaic storage charging and swapping integrated station planning system considering the iteration of electricity consumption and traffic demand according to claim 6, characterized in that: The objective function of the rolling planning model of the photovoltaic storage charging and swapping integrated station includes: my C N +C P +C E +C T ; In the above formula, C N is the expansion cost of the power-transportation coupling network; C P is the configuration cost of charging and swapping facilities; C E is the electricity purchase cost; C T The time cost of charging and replacing batteries for users; and are the expansion decision variables of the distribution network line w and the traffic network road l in year y; PR EP and PR TP are the unit expansion costs of distribution network lines and transportation network roads respectively; y The discount factor for planning investment costs; and are the number of newly added charging piles and battery swapping facilities in the photovoltaic storage charging and swapping integrated station at the transportation network node g in year y; PR CP and PR SF are the unit configuration costs of charging piles and battery swapping facilities respectively; α is the discount rate; γ is the investment period; d is the number of typical days in a year; is the active power output by the distribution network to the PV-storage-charging-swap integrated station on road l at time t on a typical day in year y; is the electricity price in period t; TA y,t PR is the total time consumed by the charging trip during the vehicle use period in period t in year y; T is the unit time cost; The constraints of the photovoltaic storage charging and swapping integrated station rolling planning model include electric vehicle user behavior constraints, photovoltaic storage charging and swapping integrated station planning and operation constraints, and power-transportation coupling network planning and operation constraints.

8. A photovoltaic storage charging and swapping integrated station planning system considering the iteration of electricity consumption and traffic demand according to claim 7, characterized in that: The planning and operation constraints of the integrated photovoltaic storage and charging and swapping station include: In the above formula, is the actual photovoltaic output of the photovoltaic storage and charging-swapping integrated station at node e during a typical day in year y; is the output or input power of the photovoltaic storage charging and swapping station at node e during a typical day in year y; and They are the number of electric vehicles that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; and are the number of electric vehicles in the idle period that go to the photovoltaic storage charging and battery swapping integrated station via route k during a typical day in year y during period t; is the correlation coefficient between path k and traffic node g; is the correlation coefficient between traffic node g and distribution network node e; E U is the charging energy requirement of a single electric vehicle; T U is the unit duration; is the number of batteries that have completed charging in the photovoltaic storage and charging and swapping integrated station at node e during a typical day in year y; The number of electric vehicles performing V2G reverse discharge in the photovoltaic storage charging and swapping integrated station at node e during a typical day in year y; P VG is the power of V2G reverse discharge; The maximum output of the newly added photovoltaic power in the photovoltaic storage and charging and swapping integrated station at the distribution network node e in the yxth year; is the photovoltaic energy conversion efficiency coefficient in the yth year; P EH and P ED They are the maximum discharge power and maximum charging power of a single energy storage unit respectively; is the number of energy storage systems newly added in the photovoltaic storage and charging-swap integrated station at the distribution network node e in year yx; E is the annual capacity decay rate of energy storage; is the output or input power of the charging station at node e during a typical day in year y; L and η H are the lower and upper limits of the energy storage state, respectively; EC E is the installed capacity of a single energy storage unit; EC O is the initial power of the energy storage system; tn is the number of time periods in a typical day; is the number of electric vehicles in the idle period during a typical day in year y that travel to the photovoltaic storage charging and swapping integrated station via path k for V2G reverse discharge; T VG is the average duration of V2G reverse discharge of a single electric vehicle; P UC The charging power of a single charging pile; and are the number of charged batteries and batteries to be charged stored in the photovoltaic storage charging and swapping integrated station at the distribution network node e during a typical day period t in year y; is the number of batteries that perform battery swapping operations in the PV-storage-charging-swap integrated station at node e during a typical day in year y; and are the upper limits of the number of charging facilities and battery swapping facilities in the integrated photovoltaic storage charging and swapping station at the transportation network node g; δ M is the large M constant; T UC and T US The time consumed for a single battery charging and a single battery replacement operation respectively.

9. A photovoltaic storage charging and swapping integrated station planning system considering the iteration of electricity consumption and traffic demand according to claim 6, characterized in that: The electric vehicle user behavior constraints include: In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the total number of vehicles that need to be recharged during a typical daytime idle period in year y; is the proportion of electric vehicles with autonomous driving functions in year y; is the number of electric vehicles in the idle period that go to the photovoltaic storage charging and swapping integrated station for V2G reverse discharge via route k during a typical day in year y during period t; is the number of electric vehicles that are idle and fully charged at traffic node g during a typical day in year y; TI y,t is the driving time of the electric vehicle during the vehicle usage period at time t on a typical day in year y; L k is the travel distance of path k; is the congestion coefficient of time period t; v U is the reference speed; TC y,t and TS y,t are the charging and battery replacement time costs in a typical day period t in year y; TI C and TI S The time taken for a single charge and battery replacement respectively.

10. A photovoltaic storage charging and swapping integrated station planning system considering the iteration of electricity consumption and traffic demand according to any one of claims 7 to 9, characterized in that: The planning and operation constraints of the power-transportation coupling network include: In the above formula, and They are the number of electric vehicles during the use period and the number of electric vehicles during the idle period that go to the photovoltaic storage charging and swapping integrated station for charging via route k in a typical day in year y during time period t; is the correlation coefficient between path k and road l, is the original traffic capacity of road l; R A To increase traffic capacity after implementing road expansion; and are respectively the active and reactive power on line w in a typical day period t in year y; w represents all lines connected to the distribution network node e; and are the basic active and reactive loads connected to the distribution network node e in a typical day period t in year y, respectively; is the original capacity of the distribution network line w; L A To increase the capacity after the expansion of the distribution network lines; and are the resistance and reactance of the distribution network line w respectively; U N is the rated voltage of the distribution network bus; ΔU t,w is the voltage drop on the distribution network line w in time period t; U t,a and U t,b are the bus voltages of nodes a and b in the distribution network in time period t, and nodes a and b are the two endpoints of the distribution network line w; U m and U M They are the lower and upper limits of the distribution network bus voltage respectively.

Images