Optimization method of power distribution and vehicle dispatching at bus stations with green electricity priority based on photovoltaic storage and charging

Abstract

The present invention discloses a method for optimizing power distribution and vehicle scheduling at a photovoltaic, storage and charging bus station with green electricity priority. By acquiring the power generation information and bus trip task information of the photovoltaic, storage and charging bus station, a joint optimization model of the power distribution plan, bus driving plan and charging plan of the photovoltaic, storage and charging bus station is constructed. Based on the start and end time of the station trip task, it is allocated to different electric buses for execution, and a charging strategy oriented towards green electricity priority is decided based on 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. The present invention realizes the priority use of photovoltaic green electricity by the photovoltaic, storage and charging bus station by rationally allocating electric buses at the same station, thereby increasing the bus power consumption of photovoltaic power at the station, reducing the power load during the peak period of the power grid, and realizing peak shaving and valley filling of power drawn from the power grid, saving the daily operating electricity cost of the electric bus system.

Description

Technical Field

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

[0002] In recent years, the development of urban transportation has led to increasingly severe energy shortages and environmental pollution. To alleviate these challenges, urban transportation systems have seen rapid electrification. However, the increased energy consumption and power demand associated with the high electrification of public transportation systems pose challenges to the load and stability of power grids. Compared to traditional power grids, photovoltaic power generation, as a clean energy source, has great potential for promoting green transportation transitions, reducing operating costs, and mitigating carbon emissions, particularly in the construction of electric bus charging stations. As a key energy supply point for electric buses, photovoltaic (PV) power generation and storage bus stations, integrating photovoltaic power generation systems, energy storage systems, charging systems, and intelligent power dispatching systems, are key infrastructure for public transportation electrification. How to integrate PV power generation and storage bus stations with bus dispatching to achieve more efficient operational solutions is a key practical challenge that urgently needs to be addressed. This combined optimization method for energy distribution and vehicle dispatching can achieve optimal charging and driving plans for buses and formulate power allocation plans for PV power generation and storage bus stations, thereby maximizing the economic benefits of PV power generation and storage bus station operations and achieving the rational allocation and efficient utilization of PV green electricity in public transportation.

[0003] Existing PV-storage bus stations mostly rely on IoT and big data technologies to obtain regional daily sunlight information and analyze available solar energy data to achieve optimal utilization of solar-storage bus station electricity and efficient charging of electric buses. However, the current power distribution and vehicle scheduling design methods for PV-storage bus stations have the following shortcomings:

[0004] 1. Existing PV-storage-charging bus station operation optimization is mostly based on fixed bus charging plans. The power supply is completed through the interaction of photovoltaic systems, energy storage systems, grid terminals, and charging terminals through intelligent power dispatching systems. However, the bus charging plan cannot be flexibly adjusted based on the real-time power generation and remaining power of the PV-storage-charging bus station, which reduces the optimization space for power distribution in the PV-storage-charging bus station.

[0005] 2. Existing electric bus operation and scheduling methods are mostly based on fixed bus travel plans. Buses cannot flexibly adjust their driving plans based on time-of-use electricity prices and electricity loads, resulting in certain limitations in electric bus scheduling optimization.

[0006] Therefore, how to provide an efficient solar-storage-charging bus station power allocation strategy to closely integrate and jointly optimize bus charging plans and driving plans, and maximize the benefits of solar-storage-charging bus station operations while giving priority to the use of green electricity is an urgent problem that technical personnel in this field need to solve. Summary of the Invention

[0007] The present invention provides a method for optimizing power distribution and vehicle dispatching at bus stations with photovoltaic storage and charging that prioritizes green electricity, in order 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 solar-storage charging and green power priority, specifically comprising the following steps:

[0010] S1: Obtain daily electricity generation data and station travel task data for solar-powered bus stations to construct an overall objective function that minimizes departure costs, minimizes operating costs based on time-of-use electricity prices, and maximizes green electricity utilization. The parameters within the overall objective function are initialized by combining the operational experience of solar-powered bus stations with the charging and consumption characteristics of electric buses.

[0011] S2: Obtain the operating parameters of the electric bus, and under the condition that the electric bus task continuation constraint is met, combine and allocate the bus trip tasks that need to be served to different electric buses based on the operating parameters to generate a driving plan for the electric bus;

[0012] S3: Based on the driving plan, constructing the electric bus battery capacity constraint and the power consumption constraint for each trip for all bus trip tasks in the trip interval and end period, and confirming whether charging is required, the charging start time and the charging duration;

[0013] Obtain a bus charging plan for each electric bus corresponding to the driving plan based on the battery capacity constraint of the electric bus and the power consumption constraint of each trip;

[0014] S4: Determine the power distribution model for the PV-storage-charging bus station with green power as the priority, and confirm the interaction between the PV system, energy storage system, and grid in the power distribution model;

[0015] And according to the bus charging plan, the constraints 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: Based on the decided electricity distribution plan for the solar-storage-charging bus station, the current electricity distribution plan for the solar-storage-charging bus station is optimized, and the driving plan and bus charging plan of the electric bus are jointly optimized until the optimal solar-storage-charging bus station electricity distribution plan, bus driving plan and bus charging plan that meet the overall objective function are found, thus achieving the joint optimization of solar-storage-charging bus station electricity distribution and vehicle scheduling with green electricity priority.

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

[0018] S11: Based on the green power generation amount in each unit time period, obtain the daily power generation data of the solar-storage-charging bus station;

[0019] S12: Obtain the bus 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 trips as an independent bus trip, and determine the start time and end time of each bus trip;

[0020] S13: Based on steps S11 and S12, construct an overall objective function that minimizes the dispatch 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 solar-storage-charging bus station; β3 represents the green electricity cost coefficient of the solar-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 periods and T = T1 ∪ T2 ∪ T3, T1 represents the set of time periods when the photovoltaic system can generate electricity, T2 represents the set of time periods when the photovoltaic system cannot generate electricity and the bus is in operation, and T3 represents the set of time periods 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 electric buses are used; represents the amount of electricity purchased from the grid during period t; λb t represents the time-of-use electricity price per unit of electricity purchased from the grid during period t; gv and represents the electric energy data generated within a day, and λ gv Indicates the price of self-consumption of electricity generated by the photovoltaic system; represents the self-consumption of electricity generated by the photovoltaic system during period t; λs t The time-of-use electricity price per unit of electricity sold to the grid during period t; Indicates the amount of electricity sold by the PV system to the grid during period t; Indicates the amount of electricity sold by the energy storage system to the grid during a unit period; e i represents the starting time of bus trip i; s i represents the end time of bus trip i.

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

[0025] S21: Construct the constraint condition that ensures that a series of travel tasks can be executed only after the electric bus is put into use. Its expression is

[0026]

[0027] Where: O represents the set of tasks for leaving the station; OO represents the set of tasks for returning to the station; The decision variable indicating whether bus k performs bus trips i and j consecutively;

[0028] S22: Construct the constraint condition that ensures 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 an electric bus, which is expressed as

[0031]

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

[0033]

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

[0035]

[0036] Step 26: Construct the time constraint to ensure that the electric bus can 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, a bus charging plan for each electric bus corresponding to the driving plan is obtained based on the battery capacity constraint of the electric bus and the power consumption constraint of each trip, which specifically includes the following steps:

[0040] S31: During the electric bus operation period, according to the driving plan, the electric bus battery capacity constraint, and the power consumption constraint of each bus trip task, a bus charging plan is obtained for the electric bus after arriving at the station during the intervals between bus trip tasks.

[0041] S32: During the non-operating period of the electric bus, a bus charging plan for fully charging the bus is determined based on 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 the 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 representing whether bus k performs charging operation after completing bus trip i;

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

[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 constraint to ensure that if bus k performs a charging operation after completing bus trip i, the charging operation has a bus trip end time constraint.

[0050]

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

[0052] S314: Based on the start and end times of the charging operation after bus k completes bus trip i, a constraint condition is constructed to ensure that bus k performs the charging operation after completing bus trip i.

[0053]

[0054] Where: The decision variable representing that bus k is performing charging operation in time period t after completing 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 of time period t' after completing bus trip i;

[0055] S315: Construct the 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 at the charging station;

[0058] S316: Construct the constraint that guarantees that if bus k continuously executes bus trips i and j and performs charging operation during them, 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 period.

[0061]

[0062] Where: represents the charging time of bus k after completing 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 and charging during the operation period is no 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: Obtain 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 is charged before the end of the operating period, the power consumption constraint is

[0077]

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

[0079]

[0080] Where: θ represents the charging capacity of the bus in a 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, representing the minimum acceptable remaining power of the electric bus.

[0084] Furthermore, the S32 specifically includes

[0085] S321: Construct the initial constraint of the initial power consumption during the 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 representing 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: Construct the constraint condition to ensure that the bus battery is fully charged after charging during non-operating hours.

[0097]

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

[0099]

[0100] Where: The decision variable representing whether electric bus k starts charging during the non-operating period t; The decision variable representing whether 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 period;

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

[0102]

[0103] Where: The decision variable indicating whether 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 representing 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 operating mode of the solar-storage-charging bus station during the daylight period when green electricity is given priority, and confirm the interaction between the photovoltaic system, energy storage system and the grid end;

[0111] Based on the bus charging plan, constraints are constructed for deciding the daytime power allocation plan for solar-storage charging at bus stations, with green electricity being the priority.

[0112] S42: Determine the non-sunny period operation mode of the PV-storage bus station with green electricity as the priority, and confirm the interaction mode between the PV system, energy storage system and the grid.

[0113] Based on the bus charging plan, constraints are constructed for deciding the nighttime electricity distribution plan for solar-storage charging bus stations 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 solar-storage-charging bus stations for making decisions 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 prioritizes the use of green electricity. That is, when there is no need to purchase electricity from the grid, the energy storage system can sell electricity to the grid under the following constraints:

[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 purchase electricity from the grid during period t;

[0118] 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.

[0119]

[0120] Where: represents the electrical energy generated by the photovoltaic system during time period t; Indicates the amount of electricity flowing from the photovoltaic system to the grid during 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 of the energy storage system at the initial moment of each period during the daytime operation to establish the 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 moment of time period t; Indicates the remaining power in the energy storage system at the initial moment 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 that the energy storage system can accept;

[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 time 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 PV 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 outflow of electricity from the photovoltaic system, energy storage system, and grid end and their auxiliary variables.

[0130]

[0131] Where: SN represents an infinitesimal positive number.

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

[0133] S421: Establish constraints to ensure that solar-storage-charging bus stations prioritize the use of green electricity. That is, when there is no need to purchase electricity from the grid, the energy storage system can sell electricity to the grid. The following are the constraints:

[0134]

[0135] S422: Obtaining the real-time power consumption of the energy storage system during nighttime operation The power constraint condition for 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 flow out of the grid and its auxiliary variables.

[0142]

[0143]

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

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

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

[0147] The optimal 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 electric bus driving plan and bus charging plan 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 bus station with green electricity priority. By giving priority to the operation mode of the photovoltaic and storage 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 bus station are considered. For fixed bus travel 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 bus station, so as to obtain the optimal photovoltaic and storage bus station power distribution plan, bus driving plan and bus charging plan under the corresponding bus travel task. The present invention realizes the priority use of photovoltaic green electricity at the photovoltaic and storage bus station by rationally allocating electric buses at the same station, thereby increasing the bus power consumption of photovoltaic power at 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 the 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 is a brief introduction to 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 any creative labor.

[0151] Figure 1 This is a flow chart of the green electricity-prioritized solar-storage-charging bus station power distribution and vehicle scheduling optimization method of the present invention. DETAILED DESCRIPTION

[0152] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall 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 bus stations with solar-storage charging and green electricity priority. Figure 1 As shown, the specific steps include:

[0154] S1: Obtain daily electricity generation data and station travel task data for solar-powered bus stations to construct an overall objective function that minimizes departure costs, minimizes operating costs of time-of-use electricity prices, and maximizes green electricity utilization. The operational experience of solar-powered bus stations and the charging and consumption characteristics of electric buses are combined to initialize the parameters within the overall objective function.

[0155] The specific steps include:

[0156] S11: Based on the green power generation amount in each unit time period, obtain the daily power generation data of the solar-storage-charging bus station;

[0157] S12: Obtain the bus 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 trips as an independent bus trip, and determine the start time and end time of each bus trip;

[0158] S13: Based on steps S11 and S12, construct an overall objective function that minimizes the dispatch 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 the electric bus, β2 represents the charging cost coefficient of the solar-storage-charging bus station, β3 represents the green electricity cost coefficient of the solar-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 representing the power consumption per unit time period of the 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, which represents the time-of-use electricity price per unit of electricity purchased from the 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 price of self-use 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, representing the time-of-use electricity price per unit of electricity sold to the grid during period t; is a non-negative variable, representing 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 during a unit period; e i is an integer variable, indicating the starting time of trip i; s i is an integer variable, indicating the end time of trip i;

[0162] S2: Obtaining operating parameters of the electric bus and, subject to the electric bus task continuation constraint, combining and allocating bus trip tasks to be served to different electric buses based on the operating parameters to generate a driving plan for the electric bus. In this embodiment, only the driving plans of different electric buses are obtained based on the electric bus task continuation constraint. The specific process of combining and allocating is not the inventive point of this application and will not be described in detail here.

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

[0164] S21: Construct the constraint condition that ensures that a series of travel tasks can be executed only after the electric bus is put into use. Its expression is

[0165]

[0166] Where: O represents the set of tasks for leaving the station; OO represents the set of tasks for returning to the station; The decision variable representing whether bus k performs bus trips i and j consecutively takes the value 0 or 1;

[0167] S22: Construct the constraint condition that ensures 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 an electric bus, which is expressed as

[0170]

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

[0172]

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

[0174]

[0175] Step 26: Construct the time constraint to ensure that the electric bus can 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: Based on the driving plan, constructing the electric bus battery capacity constraint and the power consumption constraint for each trip for all bus trip tasks in the trip interval and end period, and confirming whether charging is required, the charging start time and the charging duration;

[0179] Obtain a bus charging plan for each electric bus corresponding to the driving plan based on the battery capacity constraint of the electric bus and the power consumption constraint of each trip;

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

[0181] S31: During the electric bus operation period, according to the driving plan, the electric bus battery capacity constraint, and the power consumption constraint of each bus trip task, a bus charging plan is obtained for the electric bus after arriving at the station during the intervals between bus trip tasks.

[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 the 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 representing whether bus k performs charging operation after completing bus trip i takes the value of 0 or 1;

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

[0187]

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

[0189] S313: Construct a constraint to ensure that if bus k performs a charging operation after completing bus trip i, the charging operation has a bus trip end time constraint.

[0190]

[0191] Where: The decision variable representing whether bus k ends charging at the beginning of time period t after completing bus trip i is 0 or 1;

[0192] S314: Based on the start and end times of the charging operation after bus k completes bus trip i, a constraint condition is constructed to ensure that bus k performs the charging operation after completing bus trip i.

[0193]

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

[0195] S315: Construct the 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, representing the number of charging piles in the charging station;

[0198] S316: Construct the constraint that guarantees that if bus k continuously executes bus trips i and j and performs charging operation during them, 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 period.

[0201]

[0202] Where: is a non-negative constant, representing the charging time of bus k after completing 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 and charging during the operation period is no 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, which represents 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: Obtain 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 is charged before the end of the operating period, the power consumption constraint is

[0217]

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

[0219]

[0220] Where: θ is a non-negative constant, representing the amount of charge per unit time period for bus charging; is a non-negative variable, which represents 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, representing the minimum acceptable remaining power of the electric bus.

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

[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 the initial power consumption during the 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 representing whether 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, representing the charging time of electric bus k during the non-operating period;

[0237] S325: Construct the constraint condition to ensure that the bus battery is fully charged after charging during non-operating hours.

[0238]

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

[0240]

[0241] Where: The decision variable indicating whether electric bus k starts charging during the non-operating period t takes the value 0 or 1; The decision variable indicating whether 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, the expression is:

[0243]

[0244] Where: The decision variable indicating whether 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 model for the PV-storage-charging bus station with green power as the priority, and confirm the interaction between the PV system, energy storage system, and grid in the power distribution model;

[0251] And according to the bus charging plan, the constraints 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 operating mode of the solar-storage-charging bus station during the daylight period when green electricity is given priority, and confirm the interaction between the photovoltaic system, energy storage system and the grid end;

[0254] Based on the bus charging plan, constraints are constructed for deciding the daytime power allocation plan for solar-storage charging at bus stations, with green electricity being the priority.

[0255] Specifically, the constraints for constructing a daytime electricity distribution plan for solar-storage-charging bus stations in S41 for deciding on the priority use of green electricity include:

[0256] S411: Construct a system to ensure that the solar-storage-charging bus station prioritizes the use of green electricity. That is, when there is no need to purchase electricity from the grid, the energy storage system can sell electricity to the grid under the following constraints:

[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 purchase electricity from the grid during period t takes the value of 0 or 1;

[0259] 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.

[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, representing 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 of the energy storage system at the initial moment of each period during the daytime operation to establish the constraint condition to ensure the power of the energy storage system is

[0263]

[0264] Where: is a non-negative variable, representing the remaining power in the energy storage system at the initial moment of time period t; is a non-negative variable, representing the remaining power in the energy storage system at the initial moment of time period t+1; is a non-negative variable, representing the amount of electricity flowing from the energy storage system to the charging system during period t; is a non-negative constant, indicating the minimum remaining capacity acceptable to the energy storage system; is a non-negative constant, indicating the maximum remaining capacity 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 outflow of electricity from the photovoltaic system, energy storage system, and grid end and their auxiliary variables.

[0271]

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

[0273] S42: Determine the non-sunny period operation mode of the PV-storage bus station with green electricity as the priority, and confirm the interaction mode between the PV system, energy storage system and the grid.

[0274] Based on the bus charging plan, constraints are constructed for deciding the nighttime power allocation plan for solar-storage-charging bus stations, with green electricity being the priority.

[0275] Specifically, the constraints for constructing a nighttime electricity distribution plan for solar-storage-charging bus stations in S42 for deciding on the priority use of green electricity include:

[0276] S421: Establish constraints to ensure that solar-storage-charging bus stations prioritize the use of green electricity. That is, when there is no need to purchase electricity from the grid, the energy storage system can sell electricity to the grid. The following are the constraints:

[0277]

[0278] S422: Obtaining the real-time power consumption of the energy storage system during nighttime operation The power constraint condition for 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 flow out of the grid and its auxiliary variables.

[0285]

[0286]

[0287] S5: Based on the decided solar-storage-charging bus station power allocation plan, the current solar-storage-charging bus station power allocation plan is optimized, and the electric bus driving plan and bus charging plan are jointly optimized until the optimal solar-storage-charging bus station power allocation plan, bus driving plan, and bus charging plan that meet the overall objective function are found. This achieves the joint optimization of solar-storage-charging bus station power allocation and vehicle scheduling with green electricity priority.

[0288] The specific steps include:

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

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

[0291] The optimal 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 electric bus driving plan and bus charging plan 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 energy allocation and vehicle scheduling of a photovoltaic storage and charging bus station 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 energy allocation 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 a charging strategy for green electricity priority is decided based on the energy 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 energy consumption of the photovoltaic storage and charging bus station, the bus driving plan and charging plan are updated to obtain the final energy allocation plan for the photovoltaic storage and charging bus station. In this embodiment, by rationally allocating electric buses at the same station, the photovoltaic storage and charging bus station achieves the priority use of photovoltaic green electricity, thereby increasing the bus power consumption of the photovoltaic power at the station, reducing the power load during the peak period of the power grid, and achieving peak shaving and valley filling of power drawn 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 above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above 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 solar-storage charging and green electricity priority, characterized by: The specific steps include: S1: Obtain daily electricity generation data and station travel task data for solar-powered bus stations to construct an overall objective function that minimizes departure costs, minimizes operating costs based on time-of-use electricity prices, and maximizes green electricity utilization. The parameters within the overall objective function are initialized by combining the operational experience of solar-powered bus stations with the charging and consumption characteristics of electric buses. The specific steps include: S11: Based on the green power generation amount in each unit time period, obtain the daily power generation data of the solar-storage-charging bus station; S12: Obtain the bus 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 trips as an independent bus trip, and determine the start time and end time of each bus trip; S13: Based on steps S11 and S12, construct an overall objective function that minimizes the dispatch 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 solar-storage-charging bus station; β3 represents the green electricity cost coefficient of the solar-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 periods and T = T1 ∪ T2 ∪ T3, T1 represents the set of time periods when the photovoltaic system can generate electricity, T2 represents the set of time periods when the photovoltaic system cannot generate electricity and the bus is in operation, and T3 represents the set of time periods 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 electric buses are used; represents the amount of electricity purchased from the grid during period t; λb t represents the time-of-use electricity price per unit of electricity purchased from the grid during period t; gv and represents the electric energy data generated within a day, and λ gv Indicates the price of self-consumption of electricity generated by the photovoltaic system; represents the self-consumption of electricity generated by the photovoltaic system during period t; λs t The time-of-use electricity price per unit of electricity sold to the grid during period t; Indicates the amount of electricity sold by the PV system to the grid during period t; Indicates the amount of electricity sold by the energy storage system to the grid during a unit period; e i represents the starting time of bus trip i; s i represents the end time of bus trip i; S2: Obtain the operating parameters of the electric bus, and under the condition that the electric bus task continuation constraint is met, combine and allocate the bus trip tasks that need to be served to different electric buses based on the operating parameters to generate a driving plan for the electric bus; S3: Based on the driving plan, constructing the electric bus battery capacity constraint and the power consumption constraint for each trip for all bus trip tasks in the trip interval and end period, and confirming whether charging is required, the charging start time and the charging duration; Obtain a bus charging plan for each electric bus corresponding to the driving plan based on the battery capacity constraint of the electric bus and the power consumption constraint of each trip; S4: Determine the power distribution model for the PV-storage-charging bus station with green power as the priority, and confirm the interaction between the PV system, energy storage system, and grid in the power distribution model; And according to the bus charging plan, the constraints of the power distribution plan are constructed to be used for deciding the power distribution plan of the solar-storage-charging bus station; S5: Based on the decided electricity distribution plan for the solar-storage-charging bus station, the current electricity distribution plan for the solar-storage-charging bus station is optimized, and the driving plan and bus charging plan of the electric bus are jointly optimized until the optimal solar-storage-charging bus station electricity distribution plan, bus driving plan and bus charging plan that meet the overall objective function are found, thus achieving the joint optimization of solar-storage-charging bus station electricity distribution and vehicle scheduling with green electricity priority.

2. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green power priority according to claim 1 is characterized in that: The constraints on the continuation of the electric bus mission described in S2 include: S21: Construct the constraint condition that ensures that a series of travel tasks can be executed only after the electric bus is put into use. Its expression is Where: O represents the set of tasks for leaving the station; OO represents the set of tasks for returning to the station; The decision variable indicating whether bus k performs bus trips i and j consecutively; S22: Construct the constraint condition that ensures 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 an electric bus, which is expressed as Step 24: Construct the constraint condition to ensure that the electric bus can complete at most one more trip task after completing one trip. The expression is: Step 25: Construct the constraint condition to ensure the balance of electric bus inflow and outflow, which is expressed as Step 26: Construct the time constraint to ensure that the electric bus can 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.

3. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green-power priority according to claim 2 is characterized in that: In S3, a bus charging plan for each electric bus corresponding to the driving plan is obtained based on the battery capacity constraint of the electric bus and the power consumption constraint of each trip. Specifically, the following steps are included: S31: During the electric bus operation period, according to the driving plan, the electric bus battery capacity constraint, and the power consumption constraint of each bus trip task, a bus charging plan is obtained for the electric bus after arriving at the station during the intervals between bus trip tasks. S32: During the non-operating period of the electric bus, a bus charging plan for fully charging the bus is determined based on the power consumption constraints of each bus trip task during the operating period of the electric bus.

4. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green-power priority according to claim 3 is 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 the 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 representing whether bus k performs charging operation after completing bus trip i; S312: Construct a constraint to ensure that if bus k performs a charging operation after completing bus trip i, the charging operation has a bus trip start time constraint condition: 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 constraint to ensure that if bus k performs a charging operation after completing bus trip i, the charging operation has a bus trip end time constraint. Where: represents the decision variable for bus k to end the charging operation at the beginning of time period t after completing bus trip i; S314: Based on the start and end times of the charging operation after bus k completes bus trip i, a constraint condition is constructed to ensure that bus k performs the charging operation after completing bus trip i. Where: The decision variable representing that bus k is performing charging operation in time period t after completing bus trip i; Indicates that bus k completes bus trip i in time period t ' The decision variables for starting the charging operation at the start time; Indicates that bus k completes bus trip i in time period t ′ The decision variables for implementing the charging operation at the start and end time; S315: Construct the 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 at the charging station; S316: Construct the constraint that guarantees that if bus k continuously executes bus trips i and j and performs charging operation during them, 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 period. Where: represents the charging time of bus k after completing bus trip i; S318: Construct the constraint condition to ensure that the charging end time of bus k completing the task within the cycle and charging during the operation period is no 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: Obtain 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 is charged before the end of the operating period, the power consumption constraint is When the bus does not leave the station after executing the bus trip i and does not charge before the end of the operating period, the power consumption constraint is Where: θ represents the charging capacity of the bus in a 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, representing the minimum acceptable remaining power of the electric bus.

5. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green power priority according to claim 4 is characterized in that: The S32 specifically includes S321: Construct the initial constraint of the initial power consumption during the 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 representing 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: Construct the constraint condition to ensure that the bus battery is fully charged after charging during non-operating hours. S326: Construct the constraint condition to ensure that the start and end time of charging during non-operating period are in non-operating period. Where: The decision variable representing whether electric bus k starts charging during the non-operating period t; The decision variable representing whether 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 period; S327: Calculate and obtain the end time of charging of electric bus k during non-operating period, the expression is: Where: Indicates whether electric bus k is in non-operating period t ′ The decision variable for ending charging; 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 representing 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:

6. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green power priority according to claim 5 is characterized in that: Said S4 specifically comprises the following steps S41: Determine the operating mode of the solar-storage-charging bus station during the daylight period when green electricity is given priority, and confirm the interaction between the photovoltaic system, energy storage system and the grid end; Based on the bus charging plan, constraints are constructed for deciding the daytime power allocation plan for solar-storage charging at bus stations, with green electricity being the priority. S42: Determine the non-sunny period operation mode of the PV-storage bus station with green electricity as the priority, and confirm the interaction mode between the PV system, energy storage system and the grid. Based on the bus charging plan, constraints are constructed for deciding the nighttime electricity distribution plan for solar-storage charging bus stations under the condition of giving priority to the use of green electricity.

7. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green power priority according to claim 6 is characterized in that: The constraints for the daytime electricity allocation plan for solar-storage-charging bus stations, which are used to make decisions on the priority use of green electricity, as described in S41, specifically include: S411: Construct a system to ensure that the solar-storage-charging bus station prioritizes the use of green electricity. That is, when there is no need to purchase electricity from the grid, the energy storage system can sell electricity to the grid under the following constraints: 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 purchase electricity from the grid during 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 electrical energy generated by the photovoltaic system during time period t; Indicates the amount of electricity flowing from the photovoltaic system to the grid during 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 of the energy storage system at the initial moment of each period during the daytime operation to establish the 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 moment of time period t; Indicates the remaining power in the energy storage system at the initial moment 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 that the energy storage system can accept; 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 time 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 PV 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 outflow of electricity from the photovoltaic system, energy storage system, and grid end and their auxiliary variables. Where: SN represents an infinitesimal positive number.

8. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green power priority according to claim 6 is characterized in that: The constraints for constructing a nighttime electricity allocation plan for solar-storage-charging bus stations in S42, which is used to make decisions on the priority use of green electricity, specifically include: S421: Establish constraints to ensure that solar-storage-charging bus stations prioritize the use of green electricity. That is, when there is no need to purchase electricity from the grid, the energy storage system can sell electricity to the grid. The following are the constraints: S422: Obtaining the real-time power consumption of the energy storage system during nighttime operation The power constraint condition for the energy storage system is constructed as follows: S423: Construct the power constraint condition to ensure that the grid receives the solar-storage charging at the 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 flow out of the grid and its auxiliary variables.

9. The method for optimizing power distribution and vehicle dispatching at bus stations with solar-storage-charging and green power priority according to claim 1 is characterized in that: The S5 specifically includes the following steps: S51: Obtaining the initial power distribution plan for the solar-storage-charging bus station; S52: Based on step S2, a new electric bus driving plan is searched to obtain a new power distribution plan for the solar-storage-charging bus station according to steps S3 to S4; The optimal 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 electric bus driving plan and bus charging plan 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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