Electric quantity distribution and vehicle scheduling optimization method for light storage and charging bus station with priority of green electricity

Abstract

The invention discloses an electric quantity distribution and vehicle scheduling optimization method for a light storage and charging bus station with priority of green electricity, and the method comprises the steps: building a combined optimization model of an electric quantity distribution plan, a bus driving plan and a charging plan of the light storage and charging bus station through obtaining the power generation information and bus travel task information of the light storage and charging bus station; based on the starting time and the ending time of the station travel task, the station travel task is distributed to different electric buses to be executed, and a charging strategy oriented to green electricity priority is decided according to the power consumption of the executed travel and the battery capacity constraint of the electric buses. And according to the regional time-of-use electricity price and the real-time electric quantity of the optical storage and charging bus station, updating a driving plan and a charging plan of the bus, and obtaining a final electric quantity distribution plan of the optical storage and charging bus station. By reasonably deploying the electric buses in the same station, the photovoltaic green electricity is preferentially used by the photovoltaic storage and charging bus station, so that the bus electricity consumption of the photovoltaic electric energy of the station is increased, the electricity load of the power grid in the peak period is reduced, the peak load shifting of the electricity taken from the power grid is realized, and the power consumption of the power grid is reduced. And the daily operation power consumption cost of the electric public transportation system is saved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology and intelligent public transportation dispatching technology, and in particular to a method for optimizing power distribution and vehicle dispatching at a public transportation station with photovoltaic storage and charging with green electricity priority. Background Art

[0002] In recent years, the energy shortage and environmental pollution problems brought about by the development of urban transportation have become increasingly prominent. In order to alleviate the above situation, the urban transportation system has ushered in the rapid development of electrification. The high electrification of the bus system is accompanied by increased energy consumption and electricity demand, which brings challenges to the load and stability of the power grid. Compared with the traditional power grid, photovoltaic power generation is a way to obtain clean energy. Its application in the field of urban transportation, especially in the construction of electric bus charging stations, as an important energy supply point for electric buses, shows great potential to promote green transportation transformation, reduce operating costs, and reduce carbon emissions. The photovoltaic storage and charging bus station integrates photovoltaic power generation system, energy storage system, charging system, and intelligent power dispatching system, which is the key infrastructure for bus electrification. How to combine photovoltaic storage and charging bus stations with bus dispatching and operation to obtain a more efficient operation plan is a key practical problem that needs to be solved urgently. This joint optimization method of power distribution and vehicle dispatching can realize the optimal charging and driving plan of buses, and formulate the power distribution plan of photovoltaic storage and charging bus stations, so as to maximize the economic benefits of the operation of photovoltaic storage and charging bus stations, and realize the reasonable allocation and efficient utilization of photovoltaic green electricity in bus operation.

[0003] Existing solar-storage-charging bus stations mostly use the Internet of Things technology and big data technology to obtain regional daily sunlight information and analyze available light energy data to achieve optimal utilization of solar-storage-charging bus station electricity and efficient charging of electric buses. However, the existing solar-storage-charging bus station power distribution and vehicle dispatch design methods have the following shortcomings:

[0004] 1. In the operation optimization of existing solar-storage-charging bus stations, most of them are based on fixed bus charging plans, and the power supply is completed through the interaction of photovoltaic systems, energy storage systems, power grids and charging terminals through intelligent power dispatching systems. However, it is impossible to flexibly adjust the bus charging plan according to the real-time generated power and remaining power of the solar-storage-charging bus stations, which reduces the optimization space for power distribution of solar-storage-charging bus stations;

[0005] 2. The existing operation and dispatching methods of electric buses are mostly based on an unchanging bus travel plan. The bus cannot flexibly adjust the driving plan according to the time-of-use electricity price and electricity load, resulting in certain limitations in the dispatching optimization of electric buses.

[0006] Therefore, how to provide an efficient photovoltaic storage and charging bus station power allocation strategy so that the bus charging plan and driving plan can be closely integrated and jointly optimized, and the benefits of photovoltaic storage and charging bus station operation can be maximized while giving priority to the use of green electricity is an issue that technical personnel in this field urgently need to solve. Summary of the invention

[0007] The present invention provides a method for optimizing power distribution and vehicle dispatching in a bus station with photovoltaic storage and charging with green electricity priority, so as to overcome the above-mentioned technical problems.

[0008] In order to achieve the above object, the technical solution of the present invention is:

[0009] A method for optimizing power distribution and vehicle dispatching at a bus station with green power priority using photovoltaic storage and charging, specifically comprising the following steps:

[0010] S1: Obtain the daily generated power data and station travel task data of the PV-storage-charging bus station to construct a total objective function that minimizes the departure cost, minimizes the operating cost of the time-of-use electricity price, and maximizes the use of green electricity. Combine the operating experience of the PV-storage-charging bus station with the charging and power consumption characteristics of the electric bus to initialize the parameters in the total objective function;

[0011] S2: obtaining the operation parameters of the electric bus, and combining and allocating the bus trip tasks to be served to different electric buses based on the operation parameters under the condition that the task continuation constraint of the electric bus is satisfied, so as to generate a driving plan of the electric bus;

[0012] S3: according to the driving plan, constructing the electric bus battery capacity constraint and the power consumption constraint of each trip for confirming whether charging is needed, the charging start time and the charging duration after all bus trip tasks in the trip gap and the end cycle of the electric bus;

[0013] According to the battery capacity constraint of the electric bus and the power consumption constraint of each trip, a bus charging plan for each electric bus corresponding to the driving plan is obtained;

[0014] S4: Determine the power distribution mode of the solar-storage-charging bus station under the condition of giving priority to the use of green electricity, and confirm the interaction mode between the photovoltaic system, energy storage system and the power grid in the power distribution mode;

[0015] And according to the bus charging plan, the constraint conditions of the power distribution plan are constructed to be used for deciding the power distribution plan of the solar-storage-charging bus station;

[0016] S5: According to the decided power distribution plan of the solar-storage-charging bus station, the current power distribution plan of the solar-storage-charging bus station is optimized, and the driving plan of the electric bus and the bus charging plan are jointly optimized until the optimal power distribution plan of the solar-storage-charging bus station, the bus driving plan and the bus charging plan that meet the overall objective function are found, thus realizing the joint optimization of power distribution and vehicle scheduling of the solar-storage-charging bus station with green electricity priority.

[0017] Furthermore, the S1 specifically includes the following steps:

[0018] S11: According to the amount of green electricity generated in each unit time period, the daily electricity generation data of the solar-storage-charging bus station is obtained;

[0019] S12: Obtain the station trip task data of the solar-storage-charging bus station, and according to the set timetable and electric bus schedule, treat a pair of round-trip electric bus schedules as an independent bus trip, and determine the start time and end time of each bus trip;

[0020] S13: Based on steps S11 to S12, construct an overall objective function that minimizes the dispatching cost, minimizes the operating cost of the time-of-use electricity price, and maximizes the use of green electricity;

[0021] The expression of the overall objective function is:

[0022]

[0023] Where: J represents the total objective function; β1 represents the fixed dispatch cost coefficient of the electric bus; β2 represents the charging cost coefficient of the photovoltaic storage charging bus station; β3 represents the green electricity cost coefficient of the photovoltaic storage charging bus station; K represents the set of electric buses, I represents the set of electric bus trips; T represents the set of all-day time and T=T1∪T2∪T3, T1 represents the time set when the photovoltaic system can generate electricity, T2 represents the time set when the photovoltaic system cannot generate electricity and the bus is in operation, and T3 represents the time set when the photovoltaic system cannot generate electricity and the bus is not in operation; α represents the power consumption per unit time period of the bus operation; A k The decision variable indicating whether the electric bus is used; Indicates the amount of electricity purchased from the power grid during period t; λb t represents the time-of-use electricity price per unit of electricity purchased from the power grid during period t; gv and represents the electric energy data generated within a day, and λ gv Indicates the price of self-use electricity generated by the photovoltaic system; represents the self-consumption of electricity generated by the photovoltaic system during period t; λs t It represents the time-of-use electricity price of the unit electricity sold to the power grid during period t; Indicates the amount of electricity sold by the photovoltaic system to the grid during period t; Indicates the amount of electricity sold by the energy storage system to the grid in a unit period; e i represents the starting time of bus trip i; s i Indicates the end time of bus trip i.

[0024] Furthermore, the electric bus task continuation constraints described in S2 specifically include:

[0025] S21: Construct constraints to ensure that a series of travel tasks can only be performed after the electric bus is put into use. The expression is

[0026]

[0027] Where: O represents the departure task set; OO represents the return task set; The decision variable indicating whether bus k performs bus trips i and j consecutively;

[0028] S22: Construct the constraint condition that ensures that the electric bus starts from the charging station and eventually returns to the charging station. Its expression is:

[0029]

[0030] Step 23: Construct the constraint condition to ensure that the bus trip task is only performed once by one electric bus, which is expressed as

[0031]

[0032] Step 24: Construct a constraint condition to ensure that the electric bus can complete at most one more trip task after completing a trip. The expression is:

[0033]

[0034] Step 25: Construct the constraint condition to ensure the balance of electric bus in and out, which is expressed as

[0035]

[0036] Step 26: Construct the constraint condition to ensure the time for the electric bus to continuously perform the bus trip task, which is expressed as

[0037]

[0038] Where: M represents an infinite positive number; s j represents the end time of bus trip j.

[0039] Furthermore, in S3, according to the battery capacity constraint of the electric bus and the power consumption constraint of each trip, a bus charging plan for each electric bus corresponding to the driving plan is obtained, which specifically includes the following steps:

[0040] S31: During the operation period of the electric bus, according to the driving plan, the battery capacity constraint of the electric bus and the power consumption constraint of each bus trip task, a bus charging plan is obtained after the electric bus arrives at the station during the interval of the bus trip task;

[0041] S32: During the non-operating period of the electric bus, a bus charging plan for fully charging the bus is determined according to the power consumption constraints of each bus trip task during the operating period of the electric bus.

[0042] Furthermore, the battery capacity constraint of the electric bus and the power consumption constraint of each bus trip task in S31 specifically include:

[0043] S311: Construct a constraint condition to ensure that when bus k continuously executes bus trip i and bus trip j, whether the electric bus is charged between bus trip i and bus trip j is:

[0044]

[0045] Where: The decision variable indicating whether bus k implements charging operation after executing bus trip i;

[0046] S312: Construct a guarantee that if bus k performs a charging operation after executing bus trip i, the charging operation has a constraint condition of the start time of the bus trip:

[0047]

[0048] Where: represents the decision variable for bus k to start charging at the beginning of time period t after completing bus trip i;

[0049] S313: Construct a guarantee that if bus k performs a charging operation after executing bus trip i, the charging operation has a constraint condition of the end time of the bus trip:

[0050]

[0051] Where: represents the decision variable for bus k to end the charging operation at the beginning time of time period t after executing bus trip i;

[0052] S314: According to the start time and end time of the charging operation after bus k executes bus trip i, a constraint condition is constructed to ensure that bus k executes the charging operation after executing bus trip i:

[0053]

[0054] Where: denoting the decision variable that bus k is implementing charging operation in time period t after executing bus trip i; represents the decision variable for bus k to start charging at the beginning of time period t' after completing bus trip i; represents the decision variable for bus k to end the charging operation at the beginning time of time period t' after executing bus trip i;

[0055] S315: Construct a constraint condition to ensure that the number of buses being charged is not greater than the number of charging piles.

[0056]

[0057] Where: R represents the number of charging piles in the charging station;

[0058] S316: Construct a constraint to ensure that if bus k continuously executes bus trips i and j and performs charging operation during the two trips, the start time of the charging operation shall not be earlier than the end time of trip i and shall not be later than the start time of trip j.

[0059]

[0060] S317: Construct a charging time constraint for bus k to continuously execute bus trips i and j, and perform charging operations during the two trips.

[0061]

[0062] Where: represents the charging time of bus k after executing bus trip i;

[0063] S318: Construct the constraint condition to ensure that the charging end time of bus k completing the task within the cycle during the operation period is not later than the end time of the operation period.

[0064]

[0065] Where: Indicates the start time of the non-operating period;

[0066] Step 319: Construct the constraint condition to ensure that the initial power of the electric bus is fully charged.

[0067]

[0068] Where: s j represents the end time of trip j; The decision variable indicating whether bus k is starting from the departure station O to perform bus trip i for the first time;

[0069]

[0070] Where: represents the remaining power of electric bus k after completing bus trip i; Indicates the maximum acceptable remaining power of the electric bus;

[0071] Step 3110: Obtaining the power of electric bus k after completing bus trip j

[0072] When bus trips i and j are performed consecutively and charging is performed between the two trips, the power consumption constraint is

[0073]

[0074] When bus trips i and j are performed consecutively without charging between the two trips, the power consumption constraint is

[0075]

[0076] When the bus does not leave the station after executing bus trip i, and the charging operation is performed before the end of the operating period, the power consumption constraint is

[0077]

[0078] When the bus does not leave the station after executing bus trip i, and does not charge before the end of the operation period, the power consumption constraint is

[0079]

[0080] Where: θ represents the charging amount of the bus charging unit time period; represents the remaining power of electric bus k after completing bus trip j;

[0081] Step 3111: Construct the constraint conditions to ensure that the maximum and minimum remaining power are met during the operation of the electric bus.

[0082]

[0083] Where: is a non-negative constant, indicating the minimum acceptable remaining power of the electric bus.

[0084] Furthermore, the S32 specifically includes

[0085] S321: Construct the initial constraint of initial power consumption during non-operating period as follows:

[0086]

[0087] Where: represents the initial power of electric bus k during non-operating period;

[0088] S322: Construct the constraint condition that ensures that the bus can be charged during non-operating hours only when it is put into use during operating hours.

[0089]

[0090] Where: f k The decision variable indicating whether electric bus k is charged during non-operating hours;

[0091] S323: Construct the constraint condition to ensure that the electric bus can be charged when the initial power is not full during the non-operating period.

[0092]

[0093] S324: Construct the logical constraints to ensure the charging power and charging time of electric buses during non-operating periods.

[0094]

[0095] Where: represents the charging capacity of electric bus k during non-operating hours; represents the charging time of electric bus k during non-operating hours;

[0096] S325: The constraint condition to ensure that the bus battery is fully charged as much as possible after charging during non-operating hours is constructed as follows:

[0097]

[0098] S326: Construct the constraint condition to ensure that the start and end time of charging during non-operating period are in the non-operating period.

[0099]

[0100] Where: The decision variable indicating whether electric bus k starts charging during non-operating period t; The decision variable indicating whether the electric bus k ends charging during the non-operating period t; Indicates the start time of the last period of the non-operating period; Indicates the start time of the first period of non-operating time;

[0101] S327: Calculate and obtain the end time of charging of electric bus k during non-operating period, and its expression is:

[0102]

[0103] Where: The decision variable indicating whether the electric bus k ends charging during the non-operating period t';

[0104] S328: According to the start time and end time of the charging operation during the non-operating period, the period of the charging operation is obtained, and its expression is:

[0105]

[0106] Where: The decision variable indicating whether bus k is charging during night time period t;

[0107] S329: The constraint condition for ensuring that the number of electric buses being charged at the solar-storage-charging bus station is not greater than the number of charging piles is:

[0108]

[0109] Furthermore, the S4 specifically includes the following steps:

[0110] S41: Determine the operation mode of the photovoltaic storage charging bus station during the light period when green electricity is used first, and confirm the interaction mode between the photovoltaic system, energy storage system and the power grid;

[0111] And according to the bus charging plan, the constraint conditions for the daytime electricity distribution plan of the solar-storage-charging bus station are constructed for making decisions on the priority use of green electricity;

[0112] S42: Determine the non-sunlight period operation mode of the solar-storage-charging bus station under the condition of giving priority to the use of green electricity, and confirm the interaction mode between the photovoltaic system, the energy storage system and the power grid;

[0113] And based on the bus charging plan, constraints are constructed for deciding the nighttime electricity distribution plan of the solar-storage charging bus station under the condition of giving priority to the use of green electricity.

[0114] Furthermore, the constraint conditions for constructing a daytime electricity distribution plan for a solar-storage-charging bus station for making a decision on the priority use of green electricity in S41 specifically include:

[0115] S411: Construct a system to ensure that the solar-storage-charging bus station gives priority to the use of green electricity, that is, when there is no need to purchase electricity from the grid, the constraint condition for the energy storage system to sell electricity to the grid is

[0116]

[0117] Where: d t c is the decision variable indicating whether the energy storage system sells electricity to the grid during period t;t The decision variable indicating whether to buy electricity from the power grid during time period t;

[0118] S412: Construct the constraint condition to ensure that during the daytime operation of the photovoltaic system, the energy generated by the photovoltaic system is equal to the energy flowing out of the photovoltaic system.

[0119]

[0120] Where: represents the electric energy generated by the photovoltaic system during time period t; Indicates the amount of electricity flowing from the photovoltaic system to the grid during time period t: Represents the amount of electricity flowing from the photovoltaic system to the energy storage system during time period t;

[0121] S413: Calculate the remaining power at the initial time of each period during the daytime operation of the energy storage system to construct a constraint condition to ensure the power of the energy storage system is

[0122]

[0123] Where: Represents the remaining power in the energy storage system at the initial time of time period t; Indicates the remaining power in the energy storage system at the initial time of time period t+1; Indicates the amount of electricity flowing from the energy storage system to the charging system during time period t; Indicates the minimum acceptable remaining power of the energy storage system; Indicates the maximum remaining power acceptable to the energy storage system;

[0124] S414: Construct the power constraint condition to ensure that the grid receives the solar-storage charging at the bus station:

[0125]

[0126] Where: w max Indicates the maximum amount of electricity that the grid can receive from the solar-storage-charging bus station in a unit period; w max Indicates the minimum amount of electricity that the grid needs to receive if it wants to receive electricity from the station; a t The decision variable indicating whether the power of the photovoltaic system flows directly to the grid during period t;

[0127] S415: Construct the constraint condition to ensure that all the power supplied by the solar-storage charging bus station meets the charging power required during the bus operation period.

[0128]

[0129] S416: Construct the logical constraints to ensure the power flow from the photovoltaic system, energy storage system, and power grid and its auxiliary variables.

[0130]

[0131] Where: SN represents an infinitely small positive number.

[0132] Furthermore, the constraint conditions for constructing a nighttime electricity distribution plan for a solar-storage-charging bus station for making a decision on the priority use of green electricity in S42 specifically include:

[0133] S421: Construct constraints to ensure that the solar-storage-charging bus station gives priority to the use of green electricity, that is, when there is no need to purchase electricity from the grid, the energy storage system will sell electricity to the grid, as follows:

[0134]

[0135] S422: Obtaining the real-time power consumption of the energy storage system during nighttime operation The power constraint condition of the energy storage system is constructed as follows:

[0136]

[0137] S423: Construct the power constraint condition to ensure that the grid receives the solar-storage charging at the bus station:

[0138]

[0139] S424: Construct the constraint condition to ensure that the total power supply of the solar-storage charging bus station meets the charging power required during the bus operation period.

[0140]

[0141] S425: Construct the logical constraints to ensure the energy storage system, the power grid and the auxiliary variables of each flow direction.

[0142]

[0143]

[0144] Furthermore, the S5 specifically includes the following steps:

[0145] S51: Obtaining an initial power distribution plan for the solar-storage-charging bus station;

[0146] S52: Based on step S2, a new driving plan of an electric bus is searched to obtain a new power distribution plan of a solar-storage-charging bus station according to steps S3 to S4;

[0147] The best power distribution plan is selected and updated as the current power distribution plan, thereby optimizing the initial power distribution plan of the solar-storage-charging bus station;

[0148] S53: Based on the bus travel tasks to be served, the driving plan and bus charging plan of the electric bus are searched as a whole until the optimal solar-storage-charging bus station power distribution plan, bus driving plan and charging plan corresponding to the bus travel tasks to be served and satisfying the overall objective function are obtained.

[0149] Beneficial effects: The present invention provides a method for optimizing power distribution and vehicle dispatching at a photovoltaic and storage charging bus station with green electricity priority. By giving priority to the operation mode of the photovoltaic and storage charging bus station under the condition of green electricity, the different interaction modes of the photovoltaic system, energy storage system and power grid in the light period and non-light period of the photovoltaic and storage charging bus station are considered. For fixed bus trip tasks, the mutual influence of bus scheduling plan, charging strategy and station power distribution plan is considered to form a new optimization mechanism for feedback fusion of bus operation and photovoltaic and storage charging bus station, so as to obtain the optimal photovoltaic and storage charging bus station power distribution plan, bus driving plan and bus charging plan under the corresponding bus trip task. The present invention realizes the priority use of photovoltaic green electricity by photovoltaic and storage charging bus stations through reasonable deployment of electric buses in the same station, thereby increasing the bus power consumption of photovoltaic power in the station, reducing the power load of the power grid during peak hours, and realizing peak shaving and valley filling of power drawn from the power grid, which greatly saves the electricity cost of daily operation of the electric bus system. BRIEF DESCRIPTION OF THE DRAWINGS

[0150] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0151] Figure 1 This is a flow chart of the method for optimizing power distribution and vehicle dispatching at bus stations with green electricity priority using photovoltaic storage and charging according to the present invention. DETAILED DESCRIPTION

[0152] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0153] This embodiment provides a method for optimizing the distribution of electricity and vehicle dispatching at a bus station with solar-storage charging and green electricity priority. Figure 1 As shown, the specific steps include:

[0154] S1: Obtain the daily generated power data and station travel task data of the PV-storage-charging bus station to construct an overall objective function that minimizes the departure cost, minimizes the operating cost of the time-of-use electricity price, and maximizes the use of green electricity. The operating experience of the PV-storage-charging bus station and the charging and power consumption characteristics of the electric bus are combined to initialize the parameters in the overall objective function.

[0155] The specific steps include:

[0156] S11: According to the amount of green electricity generated in each unit time period, the daily electricity generation data of the solar-storage-charging bus station is obtained;

[0157] S12: Obtain the station trip task data of the solar-storage-charging bus station, and according to the set timetable and electric bus schedule, treat a pair of round-trip electric bus schedules as an independent bus trip, and determine the start time and end time of each bus trip;

[0158] S13: Based on steps S11 to S12, construct an overall objective function that minimizes the dispatching cost, minimizes the operating cost of the time-of-use electricity price, and maximizes the use of green electricity;

[0159] The expression of the overall objective function is:

[0160]

[0161] Where: J represents the total objective function, β1 represents the fixed dispatch cost coefficient of electric buses, β2 represents the charging cost coefficient of the photovoltaic storage charging bus station, β3 represents the green electricity cost coefficient of the photovoltaic storage charging bus station, K represents the set of electric buses, I represents the set of electric bus trips, T=T1∪T2∪T3 is the set of all-day time, T1 represents the set of time when the photovoltaic system can generate electricity, T2 represents the set of time when the photovoltaic system cannot generate electricity and the bus is in operation, and T3 represents the set of time when the photovoltaic system cannot generate electricity and the bus is not in operation; α is a non-negative constant, which represents the power consumption per unit time period of bus operation; A k is a variable with a value of 0 or 1, indicating whether the electric bus is used; is a non-negative variable, indicating the amount of electricity purchased from the grid during period t; t is a non-negative variable, indicating the time-of-use electricity price per unit of electricity purchased from the power grid during period t; gv and represents the electric energy data generated within a day, and λ gv is a non-negative variable, representing the self-use electricity price of the electricity generated by the photovoltaic system; is a non-negative variable, representing the self-consumption of electricity generated by the photovoltaic system during period t; λs t is a non-negative variable, indicating the time-of-use electricity price per unit of electricity sold to the grid during period t; is a non-negative variable, indicating the amount of electricity sold by the photovoltaic system to the grid during period t; is a non-negative variable, indicating the amount of electricity sold by the energy storage system to the grid in a unit period; e i is an integer variable, indicating the start time of trip i; s i is an integer variable, indicating the end time of trip i;

[0162] S2: obtaining the operation parameters of the electric bus, and combining and allocating the bus trip tasks to be served to different electric buses based on the operation parameters under the condition of satisfying the task continuation constraint of the electric bus to generate a driving plan of the electric bus. In this embodiment, the driving plans of different electric buses are only acquired according to the condition of the task continuation constraint of the electric bus. The specific process of combining and allocating is not the invention point of this application and will not be described in detail here.

[0163] The electric bus task continuation constraints specifically include:

[0164] S21: Construct constraints to ensure that a series of travel tasks can only be performed after the electric bus is put into use. The expression is

[0165]

[0166] Where: O represents the departure task set; OO represents the return task set; The decision variable indicating whether bus k performs bus trips i and j consecutively, and takes the value of 0 or 1;

[0167] S22: Construct the constraint condition that ensures that the electric bus starts from the charging station and eventually returns to the charging station. Its expression is:

[0168]

[0169] Step 23: Construct the constraint condition to ensure that the bus trip task is only performed once by one electric bus, which is expressed as

[0170]

[0171] Step 24: Construct a constraint condition to ensure that the electric bus can complete at most one more trip task after completing a trip. The expression is:

[0172]

[0173] Step 25: Construct the constraint condition to ensure the balance of electric bus in and out, which is expressed as

[0174]

[0175] Step 26: Construct the constraint condition to ensure the time for the electric bus to continuously perform the bus trip task, which is expressed as

[0176]

[0177] Where: M represents an infinite positive number; s j represents the end time of bus trip j;

[0178] S3: according to the driving plan, constructing the electric bus battery capacity constraint and the power consumption constraint of each trip for confirming whether charging is needed, the charging start time and the charging duration after all bus trip tasks in the trip gap and the end cycle of the electric bus;

[0179] According to the battery capacity constraint of the electric bus and the power consumption constraint of each trip, a bus charging plan for each electric bus corresponding to the driving plan is obtained;

[0180] In a specific embodiment, in S3, according to the battery capacity constraint of the electric bus and the power consumption constraint of each trip, a bus charging plan for each electric bus corresponding to the driving plan is obtained, which specifically includes the following steps:

[0181] S31: During the operation period of the electric bus, according to the driving plan, the battery capacity constraint of the electric bus and the power consumption constraint of each bus trip task, a bus charging plan is obtained after the electric bus arrives at the station during the interval of the bus trip task;

[0182] Specifically, the battery capacity constraint of the electric bus and the power consumption constraint of each bus trip task in S31 include:

[0183] S311: Construct a constraint condition to ensure that when bus k continuously executes bus trip i and bus trip j, whether the electric bus is charged between bus trip i and bus trip j is:

[0184]

[0185] Where: The decision variable indicating whether bus k implements charging operation after executing bus trip i takes the value of 0 or 1;

[0186] S312: Construct a guarantee that if bus k performs a charging operation after executing bus trip i, the charging operation has a constraint condition of the start time of the bus trip:

[0187]

[0188] Where: The decision variable indicating that bus k starts charging at the beginning of time period t after completing bus trip i, and the value is 0 or 1;

[0189] S313: Construct a guarantee that if bus k performs a charging operation after executing bus trip i, the charging operation has a constraint condition of the end time of the bus trip:

[0190]

[0191] Where: The decision variable indicating that bus k ends the charging operation at the beginning of time period t after executing bus trip i, and the value is 0 or 1;

[0192] S314: According to the start time and end time of the charging operation after bus k executes bus trip i, a constraint condition is constructed to ensure that bus k executes the charging operation after executing bus trip i:

[0193]

[0194] Where: The decision variable indicating that bus k is implementing charging operation in time period t after executing bus trip i, and the value is 0 or 1; The decision variable indicating that bus k starts charging at the beginning of time period t' after completing bus trip i, and the value is 0 or 1; The decision variable indicating that bus k ends the charging operation at the beginning of time period t' after executing bus trip i, and the value is 0 or 1;

[0195] S315: Construct a constraint condition to ensure that the number of buses being charged is not greater than the number of charging piles.

[0196]

[0197] Where: R is a non-negative constant, indicating the number of charging piles in the charging station;

[0198] S316: Construct a constraint to ensure that if bus k continuously executes bus trips i and j and performs charging operation during the two trips, the start time of the charging operation shall not be earlier than the end time of trip i and shall not be later than the start time of trip j.

[0199]

[0200] S317: Construct a charging time constraint for bus k to continuously execute bus trips i and j, and perform charging operations during the two trips.

[0201]

[0202] Where: is a non-negative constant, which indicates the charging time of bus k after executing bus trip i;

[0203] S318: Construct the constraint condition to ensure that the charging end time of bus k completing the task within the cycle during the operation period is not later than the end time of the operation period.

[0204]

[0205] Where: is a non-negative constant, indicating the start time of the non-operating period;

[0206] Step 319: Construct the constraint condition to ensure that the initial power of the electric bus is fully charged.

[0207]

[0208] Where: s j represents the end time of trip j; The decision variable indicating whether bus k is starting from the departure station O to perform bus trip i for the first time;

[0209]

[0210] Where: is a non-negative variable, indicating the remaining power of electric bus k after completing bus trip i; is a non-negative constant, indicating the maximum acceptable remaining power of the electric bus;

[0211] Step 3110: Obtaining the power of electric bus k after completing bus trip j

[0212] When bus trips i and j are performed consecutively and charging is performed between the two trips, the power consumption constraint is

[0213]

[0214] When bus trips i and j are performed consecutively without charging between the two trips, the power consumption constraint is

[0215]

[0216] When the bus does not leave the station after executing bus trip i, and the charging operation is performed before the end of the operating period, the power consumption constraint is

[0217]

[0218] When the bus does not leave the station after executing bus trip i, and does not charge before the end of the operation period, the power consumption constraint is

[0219]

[0220] Where: θ is a non-negative constant, which represents the charging amount of the bus charging unit time period; is a non-negative variable, indicating the remaining power of electric bus k after completing bus trip j;

[0221] Step 3111: Construct the constraint conditions to ensure that the maximum and minimum remaining power are met during the operation of the electric bus.

[0222]

[0223] Where: is a non-negative constant, indicating the minimum acceptable remaining power of the electric bus.

[0224] S32: during the non-operating period of the electric bus, according to the power consumption constraints of each bus trip task during the operating period of the electric bus, a bus charging plan for fully charging the bus is determined;

[0225] Specifically, the power consumption constraints of each bus trip task during the electric bus operation period include:

[0226] S321: Construct the initial constraint of initial power consumption during non-operating period as follows:

[0227]

[0228] Where: represents the initial power of electric bus k during non-operating period;

[0229] S322: Construct the constraint condition that ensures that the bus can be charged during non-operating hours only when it is put into use during operating hours.

[0230]

[0231] Where: f k The decision variable indicating whether the electric bus k is charged during non-operating hours takes the value 0 or 1;

[0232] S323: Construct the constraint condition to ensure that the electric bus can be charged when the initial power is not full during the non-operating period.

[0233]

[0234] S324: Construct the logical constraints to ensure the charging power and charging time of electric buses during non-operating periods.

[0235]

[0236] Where: is a non-negative variable, representing the charging power of electric bus k during the non-operating period; is a non-negative variable, indicating the charging time of electric bus k during the non-operating period;

[0237] S325: The constraint condition to ensure that the bus battery is fully charged as much as possible after charging during non-operating hours is constructed as follows:

[0238]

[0239] S326: Construct the constraint condition to ensure that the start and end time of charging during non-operating period are in the non-operating period.

[0240]

[0241] Where: The decision variable indicating whether the electric bus k starts charging during the non-operating period t takes the value 0 or 1; The decision variable indicating whether the electric bus k ends charging during the non-operating period t takes the value 0 or 1; is a non-negative constant, indicating the start time of the last period of the non-operating period; is a non-negative constant, indicating the start time of the first period of the non-operating period;

[0242] S327: Calculate and obtain the end time of charging of electric bus k during non-operating period, and its expression is:

[0243]

[0244] Where: The decision variable indicating whether the electric bus k ends charging during the non-operating period t' takes the value of 0 or 1;

[0245] S328: According to the start time and end time of the charging operation during the non-operating period, the period of the charging operation is obtained, and its expression is:

[0246]

[0247] Where: The decision variable indicating whether bus k is charging during night time period t takes the value of 0 or 1;

[0248] S329: The constraint condition for ensuring that the number of electric buses being charged at the solar-storage-charging bus station is not greater than the number of charging piles is:

[0249]

[0250] S4: Determine the power distribution mode of the solar-storage-charging bus station under the condition of giving priority to the use of green electricity, and confirm the interaction mode between the photovoltaic system, energy storage system and the power grid in the power distribution mode;

[0251] And according to the bus charging plan, the constraint conditions of the power distribution plan are constructed to be used for deciding the power distribution plan of the solar-storage-charging bus station;

[0252] The specific steps include:

[0253] S41: Determine the operation mode of the photovoltaic storage charging bus station during the light period when green electricity is used first, and confirm the interaction mode between the photovoltaic system, energy storage system and the power grid;

[0254] And according to the bus charging plan, the constraint conditions for the daytime electricity distribution plan of the solar-storage-charging bus station are constructed for making decisions on the priority use of green electricity;

[0255] Specifically, the constraint conditions for constructing a daytime electricity distribution plan for a solar-storage-charging bus station for making a decision to give priority to the use of green electricity in S41 include:

[0256] S411: Construct a system to ensure that the solar-storage-charging bus station gives priority to the use of green electricity, that is, when there is no need to purchase electricity from the grid, the constraint condition for the energy storage system to sell electricity to the grid is

[0257]

[0258] Where: d t c is the decision variable indicating whether the energy storage system sells electricity to the grid during period t, and its value is 0 or 1; t The decision variable indicating whether to buy electricity from the power grid during time period t takes the value of 0 or 1;

[0259] S412: Construct the constraint condition to ensure that during the daytime operation of the photovoltaic system, the energy generated by the photovoltaic system is equal to the energy flowing out of the photovoltaic system.

[0260]

[0261] Where: is a non-negative variable, representing the electrical energy generated by the photovoltaic system during period t; is a non-negative variable, indicating the amount of electricity flowing from the photovoltaic system to the grid during period t: is a non-negative variable, representing the amount of electricity flowing from the photovoltaic system to the energy storage system during time period t;

[0262] S413: Calculate the remaining power at the initial time of each period during the daytime operation of the energy storage system to construct a constraint condition to ensure the power of the energy storage system is

[0263]

[0264] Where: is a non-negative variable, indicating the remaining power in the energy storage system at the initial time of period t; is a non-negative variable, indicating the remaining power in the energy storage system at the initial time of period t+1; is a non-negative variable, indicating the amount of electricity flowing from the energy storage system to the charging system during time period t; is a non-negative constant, indicating the minimum acceptable remaining power of the energy storage system; is a non-negative constant, indicating the maximum remaining power acceptable to the energy storage system;

[0265] S414: Construct the power constraint condition to ensure that the grid receives the solar-storage charging at the bus station:

[0266]

[0267] Where: w max is a non-negative constant, indicating the maximum amount of electricity that the grid can receive from the solar-storage charging bus station in a unit period; max is a non-negative constant, indicating the minimum amount of electricity that the grid needs to receive if it wants to receive electricity from the station; a t The decision variable indicating whether the power of the photovoltaic system flows directly to the grid during period t takes the value of 0 or 1;

[0268] S415: Construct the constraint condition to ensure that all the power supplied by the solar-storage charging bus station meets the charging power required during the bus operation period.

[0269]

[0270] S416: Construct the logical constraints to ensure the power flow from the photovoltaic system, energy storage system, and power grid and its auxiliary variables.

[0271]

[0272] Where: SN represents an infinitesimal positive number;

[0273] S42: Determine the non-sunlight period operation mode of the solar-storage-charging bus station under the condition of giving priority to the use of green electricity, and confirm the interaction mode between the photovoltaic system, the energy storage system and the power grid;

[0274] And according to the bus charging plan, the constraint conditions for the nighttime electricity distribution plan of the solar-storage charging bus station are constructed for making decisions on the priority use of green electricity;

[0275] Specifically, the constraint conditions for constructing a nighttime electricity distribution plan for a solar-storage-charging bus station for making a decision on the priority use of green electricity in S42 include:

[0276] S421: Construct constraints to ensure that the solar-storage-charging bus station gives priority to the use of green electricity, that is, when there is no need to purchase electricity from the grid, the energy storage system will sell electricity to the grid, as follows:

[0277]

[0278] S422: Obtaining the real-time power consumption of the energy storage system during nighttime operation The power constraint condition of the energy storage system is constructed as follows:

[0279]

[0280] S423: Construct the power constraint condition to ensure that the grid receives the solar-storage charging at the bus station:

[0281]

[0282] S424: Construct the constraint condition to ensure that the total power supply of the solar-storage charging bus station meets the charging power required during the bus operation period.

[0283]

[0284] S425: Construct the logical constraints to ensure the energy storage system, the power grid and the auxiliary variables of each flow direction.

[0285]

[0286]

[0287] S5: According to the decided solar-storage-charging bus station power distribution plan, the current solar-storage-charging bus station power distribution plan is optimized, and the driving plan of the electric bus and the bus charging plan are jointly optimized until the optimal solar-storage-charging bus station power distribution plan, bus driving plan and bus charging plan that meet the total objective function are found, that is, the joint optimization of solar-storage-charging bus station power distribution and vehicle scheduling with green electricity priority is realized;

[0288] The specific steps include:

[0289] S51: Obtaining an initial power distribution plan for the solar-storage-charging bus station;

[0290] S52: Based on step S2, a new driving plan of an electric bus is searched to obtain a new power distribution plan of a solar-storage-charging bus station according to steps S3 to S4;

[0291] The best power distribution plan is selected and updated as the current power distribution plan, thereby optimizing the initial power distribution plan of the solar-storage-charging bus station;

[0292] S53: Based on the bus travel tasks to be served, the driving plan and bus charging plan of the electric bus are searched as a whole until the optimal solar-storage-charging bus station power distribution plan, bus driving plan and charging plan corresponding to the bus travel tasks to be served and satisfying the overall objective function are obtained.

[0293] Compared with the prior art, this embodiment discloses a joint optimization method for the distribution of electricity and vehicle scheduling of photovoltaic storage and charging bus stations with green electricity priority. By collecting the power generation information and bus trip task information of a photovoltaic storage and charging bus station, a joint optimization model (total objective function) of the photovoltaic storage and charging bus station power distribution plan, bus driving plan and charging plan is constructed; based on the start and end time of the station trip task, it is allocated to different electric buses for execution, and the charging strategy for green electricity priority is decided according to the power consumption of the execution trip and the battery capacity constraint of the electric bus. According to the regional time-of-use electricity price and the real-time power of the photovoltaic storage and charging bus station, the driving plan and charging plan of the bus are updated to obtain the final power distribution plan of the photovoltaic storage and charging bus station. In this embodiment, by reasonably allocating the electric buses in the same station, the photovoltaic storage and charging bus station has realized the priority use of photovoltaic green electricity, thereby increasing the bus power consumption of the photovoltaic power of the station, reducing the power load during the peak period of the power grid, and realizing the peak shaving and valley filling of the power taken from the power grid, saving electricity costs for the daily operation of the bus system.

[0294] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing power distribution and vehicle dispatching at bus stations with green power priority using photovoltaic storage and charging, characterized in that: The specific steps include: S1: Obtain the daily generated power data and station travel task data of the PV-storage-charging bus station to construct a total objective function that minimizes the departure cost, minimizes the operating cost of the time-of-use electricity price, and maximizes the use of green electricity. Combine the operating experience of the PV-storage-charging bus station with the charging and power consumption characteristics of the electric bus to initialize the parameters in the total objective function; S2: obtaining the operation parameters of the electric bus, and combining and allocating the bus trip tasks to be served to different electric buses based on the operation parameters under the condition that the task continuation constraint of the electric bus is satisfied, so as to generate a driving plan of the electric bus; S3: according to the driving plan, constructing the electric bus battery capacity constraint and the power consumption constraint of each trip for confirming whether charging is needed, the charging start time and the charging duration after all bus trip tasks in the trip gap and the end cycle of the electric bus; According to the battery capacity constraint of the electric bus and the power consumption constraint of each trip, a bus charging plan for each electric bus corresponding to the driving plan is obtained; S4: Determine the power distribution mode of the solar-storage-charging bus station under the condition of giving priority to the use of green electricity, and confirm the interaction mode between the photovoltaic system, energy storage system and the power grid in the power distribution mode; And according to the bus charging plan, the constraint conditions of the power distribution plan are constructed to be used for deciding the power distribution plan of the solar-storage-charging bus station; S5: According to the decided power distribution plan of the solar-storage-charging bus station, the current power distribution plan of the solar-storage-charging bus station is optimized, and the driving plan of the electric bus and the bus charging plan are jointly optimized until the optimal power distribution plan of the solar-storage-charging bus station, the bus driving plan and the bus charging plan that meet the overall objective function are found, thus realizing the joint optimization of power distribution and vehicle scheduling of the solar-storage-charging bus station with green electricity priority.

2. According to the green electricity priority photovoltaic storage and charging bus station power distribution and vehicle scheduling optimization method of claim 1, it is characterized in that: The S1 specifically includes the following steps: S11: According to the amount of green electricity generated in each unit time period, the daily electricity generation data of the solar-storage-charging bus station is obtained; S12: Obtain the station trip task data of the solar-storage-charging bus station, and according to the set timetable and electric bus schedule, treat a pair of round-trip electric bus schedules as an independent bus trip, and determine the start time and end time of each bus trip; S13: Based on steps S11 to S12, construct an overall objective function that minimizes the dispatching cost, minimizes the operating cost of the time-of-use electricity price, and maximizes the use of green electricity; The expression of the overall objective function is: Where: J represents the total objective function; β1 represents the fixed dispatch cost coefficient of the electric bus; β2 represents the charging cost coefficient of the photovoltaic storage charging bus station; β3 represents the green electricity cost coefficient of the photovoltaic storage charging bus station; K represents the set of electric buses, I represents the set of electric bus trips; T represents the set of all-day time and T=T1∪T2∪T3, T1 represents the time set when the photovoltaic system can generate electricity, T2 represents the time set when the photovoltaic system cannot generate electricity and the bus is in operation, and T3 represents the time set when the photovoltaic system cannot generate electricity and the bus is not in operation; α represents the power consumption per unit time period of the bus operation; A k The decision variable indicating whether the electric bus is used; Indicates the amount of electricity purchased from the power grid during period t; λb t represents the time-of-use electricity price per unit of electricity purchased from the power grid during period t; gv and represents the electric energy data generated within a day, and λ gv Indicates the price of self-use electricity generated by the photovoltaic system; represents the self-consumption of electricity generated by the photovoltaic system during period t; λs t It represents the time-of-use electricity price of the unit electricity sold to the power grid during period t; Indicates the amount of electricity sold by the photovoltaic system to the grid during period t; Indicates the amount of electricity sold by the energy storage system to the grid in a unit period; e i represents the starting time of bus trip i; s i Indicates the end time of bus trip i.

3. According to claim 2, a method for optimizing power distribution and vehicle dispatching at bus stations with green power priority using photovoltaic storage and charging, characterized in that: The constraints on the continuation of the electric bus mission described in S2 include: S21: Construct constraints to ensure that a series of travel tasks can only be performed after the electric bus is put into use. The expression is Where: O represents the departure task set; OO represents the return task set; The decision variable indicating whether bus k performs bus trips i and j consecutively; S22: Construct the constraint condition that ensures that the electric bus starts from the charging station and eventually returns to the charging station. Its expression is: Step 23: Construct the constraint condition to ensure that the bus trip task is only performed once by one electric bus, which is expressed as Step 24: Construct a constraint condition to ensure that the electric bus can complete at most one more trip task after completing a trip. The expression is: Step 25: Construct the constraint condition to ensure the balance of electric bus in and out, which is expressed as Step 26: Construct the constraint condition to ensure the time for the electric bus to continuously perform the bus trip task, which is expressed as Where: M represents an infinite positive number; s j represents the end time of bus trip j.

4. According to the green electricity priority photovoltaic storage and charging bus station power distribution and vehicle scheduling optimization method of claim 3, it is characterized in that: In S3, according to the battery capacity constraint of the electric bus and the power consumption constraint of each trip, a bus charging plan for each electric bus corresponding to the driving plan is obtained, which specifically includes the following steps: S31: During the operation period of the electric bus, according to the driving plan, the battery capacity constraint of the electric bus and the power consumption constraint of each bus trip task, a bus charging plan is obtained after the electric bus arrives at the station during the interval of the bus trip task; S32: During the non-operating period of the electric bus, a bus charging plan for fully charging the bus is determined according to the power consumption constraints of each bus trip task during the operating period of the electric bus.

5. According to claim 4, a method for optimizing power distribution and vehicle dispatching at bus stations with green power priority using photovoltaic storage and charging, characterized in that: The battery capacity constraint of the electric bus and the power consumption constraint of each bus trip task in S31 specifically include: S311: Construct a constraint condition to ensure that when bus k continuously executes bus trip i and bus trip j, whether the electric bus is charged between bus trip i and bus trip j is: Where: The decision variable indicating whether bus k implements charging operation after executing bus trip i; S312: Construct a guarantee that if bus k performs a charging operation after executing bus trip i, the charging operation has a constraint condition of the start time of the bus trip: Where: represents the decision variable for bus k to start charging at the beginning of time period t after completing bus trip i; S313: Construct a guarantee that if bus k performs a charging operation after executing bus trip i, the charging operation has a constraint condition of the end time of the bus trip: Where: represents the decision variable for bus k to end the charging operation at the beginning time of time period t after executing bus trip i; S314: According to the start time and end time of the charging operation after bus k executes bus trip i, a constraint condition is constructed to ensure that bus k executes the charging operation after executing bus trip i: Where: denoting the decision variable that bus k is implementing charging operation in time period t after executing bus trip i; represents the decision variable for bus k to start charging at the beginning of time period t' after completing bus trip i; represents the decision variable for bus k to end the charging operation at the beginning time of time period t' after executing bus trip i; S315: Construct a constraint condition to ensure that the number of buses being charged is not greater than the number of charging piles. Where: R represents the number of charging piles in the charging station; S316: Construct a constraint to ensure that if bus k continuously executes bus trips i and j and performs charging operation during the two trips, the start time of the charging operation shall not be earlier than the end time of trip i and shall not be later than the start time of trip j. S317: Construct a charging time constraint for bus k to continuously execute bus trips i and j, and perform charging operations during the two trips. Where: represents the charging time of bus k after executing bus trip i; S318: Construct the constraint condition to ensure that the charging end time of bus k completing the task within the cycle during the operation period is not later than the end time of the operation period. Where: Indicates the start time of the non-operating period; Step 319: Construct the constraint condition to ensure that the initial power of the electric bus is fully charged. Where: s j represents the end time of trip j; The decision variable indicating whether bus k is starting from the departure station O to perform bus trip i for the first time; Where: represents the remaining power of electric bus k after completing bus trip i; Indicates the maximum acceptable remaining power of the electric bus; Step 3110: Obtaining the power of electric bus k after completing bus trip j When bus trips i and j are performed consecutively and charging is performed between the two trips, the power consumption constraint is When bus trips i and j are performed consecutively without charging between the two trips, the power consumption constraint is When the bus does not leave the station after executing bus trip i, and the charging operation is performed before the end of the operating period, the power consumption constraint is When the bus does not leave the station after executing bus trip i, and does not charge before the end of the operation period, the power consumption constraint is Where: θ represents the charging amount of the bus charging unit time period; represents the remaining power of electric bus k after completing bus trip j; Step 3111: Construct the constraint conditions to ensure that the maximum and minimum remaining power are met during the operation of the electric bus. Where: is a non-negative constant, indicating the minimum acceptable remaining power of the electric bus.

6. According to the green electricity priority photovoltaic storage and charging bus station power distribution and vehicle scheduling optimization method of claim 4, it is characterized in that: The S32 specifically includes S321: Construct the initial constraint of initial power consumption during non-operating period as follows: Where: represents the initial power of electric bus k during non-operating period; S322: Construct the constraint condition that ensures that the bus can be charged during non-operating hours only when it is put into use during operating hours. Where: f k The decision variable indicating whether electric bus k is charged during non-operating hours; S323: Construct the constraint condition to ensure that the electric bus can be charged when the initial power is not full during the non-operating period. S324: Construct the logical constraints to ensure the charging power and charging time of electric buses during non-operating periods. Where: represents the charging capacity of electric bus k during non-operating hours; represents the charging time of electric bus k during non-operating hours; S325: The constraint condition to ensure that the bus battery is fully charged during non-operating hours is constructed as follows: S326: Construct the constraint condition to ensure that the start and end time of charging during non-operating period are in the non-operating period. Where: The decision variable indicating whether electric bus k starts charging during non-operating period t; The decision variable indicating whether the electric bus k ends charging during the non-operating period t; Indicates the start time of the last period of the non-operating period; Indicates the start time of the first period of non-operating time; S327: Calculate and obtain the end time of charging of electric bus k during non-operating period, and its expression is: Where: The decision variable indicating whether the electric bus k ends charging during the non-operating period t'; S328: According to the start time and end time of the charging operation during the non-operating period, the period of the charging operation is obtained, and its expression is: Where: The decision variable indicating whether bus k is charging during night time period t; S329: The constraint condition for ensuring that the number of electric buses being charged at the solar-storage-charging bus station is not greater than the number of charging piles is:

7. According to claim 4, a method for optimizing power distribution and vehicle dispatching at bus stations with green power priority based on photovoltaic storage and charging is characterized in that: The S4 specifically includes the following steps S41: Determine the operation mode of the photovoltaic storage charging bus station during the light period when green electricity is used first, and confirm the interaction mode between the photovoltaic system, energy storage system and the power grid; And according to the bus charging plan, the constraint conditions for the daytime electricity distribution plan of the solar-storage charging bus station are constructed for making decisions on the priority use of green electricity; S42: Determine the non-sunlight period operation mode of the solar-storage-charging bus station under the condition of giving priority to the use of green electricity, and confirm the interaction mode between the photovoltaic system, the energy storage system and the power grid; And based on the bus charging plan, constraints are constructed for deciding the nighttime electricity distribution plan of the solar-storage charging bus station under the condition of giving priority to the use of green electricity.

8. The method for optimizing power distribution and vehicle dispatching at bus stations with green power priority based on photovoltaic storage and charging according to claim 7 is characterized in that: The constraints for constructing a daytime electricity distribution plan for solar-storage-charging bus stations in S41 for making decisions on the priority use of green electricity include: S411: Construct a system to ensure that the solar-storage-charging bus station gives priority to the use of green electricity, that is, when there is no need to purchase electricity from the grid, the constraint condition for the energy storage system to sell electricity to the grid is Where: d t c is the decision variable indicating whether the energy storage system sells electricity to the grid during period t; t The decision variable indicating whether to buy electricity from the power grid during time period t; S412: Construct the constraint condition to ensure that the energy generated by the photovoltaic system is equal to the energy flowing out of the photovoltaic system during the daytime operation. Where: represents the electric energy generated by the photovoltaic system during time period t; Indicates the amount of electricity flowing from the photovoltaic system to the grid during time period t: Represents the amount of electricity flowing from the photovoltaic system to the energy storage system during time period t; S413: Calculate the remaining power at the initial time of each period during the daytime operation of the energy storage system to construct a constraint condition to ensure the power of the energy storage system is Where: Represents the remaining power in the energy storage system at the initial time of time period t; Indicates the remaining power in the energy storage system at the initial time of time period t+1; Indicates the amount of electricity flowing from the energy storage system to the charging system during time period t; Indicates the minimum acceptable remaining power of the energy storage system; Indicates the maximum remaining power acceptable to the energy storage system; S414: Construct the power constraint condition to ensure that the grid receives the solar-storage charging at the bus station: Where: w max Indicates the maximum amount of electricity that the grid can receive from the solar-storage-charging bus station in a unit period; w max Indicates the minimum amount of electricity that the grid needs to receive if it wants to receive electricity from the station; a t The decision variable indicating whether the power of the photovoltaic system flows directly to the grid during period t; S415: Construct the constraint condition to ensure that all the power supplied by the solar-storage charging bus station meets the charging power required during the bus operation period. S416: Construct the logical constraints to ensure the power flow from the photovoltaic system, energy storage system, and power grid and its auxiliary variables. Where: SN represents an infinitely small positive number.

9. The method for optimizing power distribution and vehicle dispatching at bus stations with green power priority based on photovoltaic storage and charging according to claim 7 is characterized in that: The constraint conditions for constructing a nighttime electricity distribution plan for solar-storage-charging bus stations in S42 for making decisions on the priority use of green electricity include: S421: Construct constraints to ensure that the solar-storage-charging bus station gives priority to the use of green electricity, that is, when there is no need to purchase electricity from the grid, the energy storage system will sell electricity to the grid, as follows: S422: Obtaining the real-time power consumption of the energy storage system during nighttime operation The power constraint condition of the energy storage system is constructed as follows: S423: Construct the power constraint condition to ensure that the grid receives the power of the solar-storage charging bus station: S424: Construct the constraint condition to ensure that the total power supply of the solar-storage charging bus station meets the charging power required during the bus operation period. S425: Construct the logical constraints to ensure the energy storage system, the power grid and the auxiliary variables of each flow direction.

10. The method for optimizing power distribution and vehicle dispatching at bus stations with green power priority based on photovoltaic storage and charging according to claim 1 is characterized in that: The S5 specifically includes the following steps: S51: Obtaining an initial power distribution plan for the solar-storage-charging bus station; S52: Based on step S2, a new driving plan of an electric bus is searched to obtain a new power distribution plan of a solar-storage-charging bus station according to steps S3 to S4; The best power distribution plan is selected and updated as the current power distribution plan, thereby optimizing the initial power distribution plan of the solar-storage-charging bus station; S53: Based on the bus travel tasks to be served, the driving plan and bus charging plan of the electric bus are searched as a whole until the optimal solar-storage-charging bus station power distribution plan, bus driving plan and charging plan corresponding to the bus travel tasks to be served and satisfying the overall objective function are obtained.

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