Charging and battery swapping station energy management system and method based on multi-port energy router

Abstract

The invention relates to the technical field of electric power systems, in particular to an energy management system and method for a charging and swapping station based on a multi-port energy router, and the system comprises the steps: selecting a real-time energy management mode according to the actual photovoltaic power generation power, whether an electric vehicle which is reserved for charging and swapping arrives on time or not, and the states of all power batteries in the charging and swapping station; a real-time energy management strategy is formulated in combination with a rolling energy management strategy, an advanced power electronic technology, a big data technology and an Internet of Vehicles technology are integrated, intelligent scheduling and optimal configuration are carried out on the energy of the charging and battery swapping station at different time scales, the operation efficiency and the service quality of charging and battery swapping facilities are improved, and the energy utilization rate of the charging and battery swapping station is improved. And utilization of renewable energy sources and stable operation of a power grid are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to an energy management system and method for a charging and swapping station based on a multi-port energy router. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] As global climate change and environmental problems become increasingly serious, electric vehicles have received widespread attention and application as an important means to reduce carbon emissions and alleviate the energy crisis. Among them, electric vehicle charging and swapping stations are energy stations that provide charging and rapid replacement of power batteries for electric vehicles. With the rapid popularization of electric vehicles and the rapid growth of the market, how to improve charging and swapping efficiency, reduce operating costs, and ensure the safety and stability of the power grid have become issues that need to be urgently addressed by electric vehicle charging and swapping stations.

[0004] Existing electric vehicle charging and swapping stations only consider a single operating mode, do not fully dispatch the energy of charging stations and swapping stations at the same time, and do not fully utilize the peak-shaving and valley-filling function of power batteries in swapping stations. This not only fails to effectively reduce operating costs, but also fails to consider the impact of the sudden access of electric vehicles to the power grid on the stability of the power grid, and thus cannot effectively ensure the safety and stability of the power grid.

[0005] Based on the above reasons, the present invention designs an energy management system and method for a charging and swapping station based on a multi-port energy router, constructs a multi-time scale energy management strategy, and integrates advanced power electronics technology, big data technology, and Internet of Vehicles technology to intelligently schedule and optimize the energy of the charging and swapping station at different time scales, thereby improving the operating efficiency and service quality of the charging and swapping facilities while promoting the utilization of renewable energy and the stable operation of the power grid. Summary of the invention

[0006] The purpose of the present invention is to overcome the shortcomings of the prior art, provide an energy management system and method for a charging and swapping station based on a multi-port energy router, construct a multi-time scale energy management strategy, and intelligently schedule and optimize the energy of the charging and swapping station at different time scales by integrating advanced power electronics technology, big data technology and Internet of Vehicles technology. While improving the operating efficiency and service quality of the charging and swapping facilities, it also promotes the utilization of renewable energy and the stable operation of the power grid.

[0007] In order to achieve the above-mentioned object, the present invention provides an energy management system for a charging and swapping station based on a multi-port energy router, which is characterized by comprising an information collection and processing module, a rolling energy management module and a real-time energy management module; The information collection and processing module is configured to: the multi-port energy router predicts the photovoltaic power generation power within a future period of time T, detects the status of each power battery at the charging station and the battery swapping station in real time, collects the electric vehicle's scheduled charging and battery swapping information through the Internet of Vehicles, and calculates the remaining power battery capacity of the electric vehicle when it arrives at the charging and battery swapping station based on the current power battery capacity of the electric vehicle and the distance from the charging and battery swapping station; The rolling energy management module is configured to: according to the information collected and processed by the information collection and processing module, with the goal of maximizing the profit of the electric vehicle charging and discharging station, under the condition of meeting the corresponding constraints, every time interval t, the energy management strategy for the future period T is rolling optimized; The real-time energy management module is configured to select the real-time energy management mode based on the actual photovoltaic power generation, whether the electric vehicles scheduled for charging and swapping arrive on time, and the status information of all power batteries in the charging and swapping station, and formulate the real-time energy management strategy in combination with the rolling energy management module.

[0008] The appointment charging and battery swapping information in the information collection and processing module includes: the owner's choice of charging or battery swapping, the charging start and end time, the battery swapping time, the current electric vehicle power battery capacity and the distance to the charging and battery swapping station.

[0009] The energy management method of a charging and swapping station based on a multi-port energy router comprises the following steps: S1, the multi-port energy router predicts the photovoltaic power generation within a period of time T in the future, detects the status of all power batteries in the charging and swapping station in real time, obtains the charging and swapping reservation information of electric vehicle owners through the Internet of Vehicles, and calculates the remaining power battery capacity of the electric vehicle when it arrives at the charging and swapping station based on the current power battery capacity of the electric vehicle and the distance from the charging and swapping station; S2, based on the information collected and processed by the multi-port energy router, with the goal of maximizing the benefits of electric vehicle charging and discharging stations, and under the condition of meeting the corresponding constraints, the rolling energy management module rolls out the energy management strategy for a period of time T in the future at intervals of time t, so as to guide car owners to make reservations in advance, and charge different proportions of service fees according to the time of charging and swapping reservations made in advance by car owners; S3, selects the real-time energy management mode according to the actual photovoltaic power generation, whether the electric vehicles scheduled for charging and swapping arrive on time, and the status information of all power batteries in the charging and swapping station, and formulates the real-time energy management strategy in combination with the rolling energy management strategy.

[0010] The specific calculation method of the remaining capacity of the power battery in S1 is: Formula 1: ; Formula 2: ; Formula 3: ; in, It is the remaining capacity of the power battery when the electric vehicle arrives at the charging and swapping station. is the current electric vehicle power battery capacity, is the speed of the electric car, Is the electric car at speed The power battery discharge power during driving, Is the electric car at speed Driving time, is the power battery discharge efficiency, Is the electric car at speed Distance travelled.

[0011] The energy management strategy for the rolling optimization in S2 within a period of time T in the future is realized through the objective function, and its specific calculation method is: Formula 4: ; Formula 5: ; Formula 6: ; Formula 7: ; in, is the revenue of electric vehicle charging and swapping stations, is the revenue of the charging station, is the revenue from the battery swap station. is the cost of interaction between the multi-port energy router and the grid, and They are the service fee ratio coefficients charged by charging and swapping stations to car owners. yes The total charging power of the charging station at all times, yes The total power exchanged between the power station and the energy router at any time, Positive timing indicates charging at the battery swap station, while negative timing indicates discharging. yes The multi-port energy router interacts with the grid at all times. When it is positive, it means buying electricity from the grid, and vice versa, it means selling electricity to the grid. yes Grid electricity price at the moment.

[0012] The calculation method of the proportional coefficient of the service fee in S2, which is charged at different proportions according to the time of charging and swapping scheduled in advance by the car owner, is: Formula 8: ; in They are the service fee ratio coefficients charged by charging and swapping stations to car owners. It is the time difference between the owner's scheduled charging start time or scheduled battery replacement time and the current time.

[0013] The constraints for the rolling energy management module in S2 to maintain the internal power balance of the multi-port energy router are: The constraints for the rolling energy management module in S2 to maintain the internal power balance of the multi-port energy router are: Formula 9: ; in yes The power generated by the photovoltaic power station at any moment, yes Supercapacitor charging power at all times, When it is positive, the supercapacitor is charged, otherwise, the supercapacitor is discharged; In the charging and swapping station, the charging power constraint condition of the charging station set to meet the port power limit of the multi-port energy router is: Formula 10: ; in, is the maximum total charging power of the charging station; In the charging and swapping station, the interactive power constraint conditions between the charging and swapping station and the multi-port energy router set to meet the port power limit of the multi-port energy router are: Formula 11: ; in, is the maximum total interactive power between the battery swap station and the multi-port energy router; In the charging and swapping station, the interactive power constraint between the supercapacitor and the multi-port energy router set to meet the port power limit of the multi-port energy router is: Formula 12: ; in, is the maximum interaction power between the supercapacitor and the multi-port energy router; It is used to ensure that the electric vehicle that chooses to charge can be fully charged at the agreed time, so as to set the electric vehicle power battery, that is, the constraint condition of SOC is: Formula 13: ; Formula 14: ; in, is the SOC of the i-th electric vehicle at the end of scheduled charging, is the SOC of the i-th electric vehicle at the current moment, is the power battery charging efficiency, is the rated capacity of the power battery; It is used to ensure that when the car owner who has made an appointment for battery replacement arrives at the battery replacement station, there are enough fully charged power batteries for the car owner to replace, so the constraint condition of the power battery SOC of the battery replacement station in the charging and swapping station is set as follows: Formula 15: ; Formula 16: ; in, It is the i-th power battery in the battery swap station SOC at all times, yes The number of vehicles scheduled for battery replacement at any given time, is the total number of power batteries in the battery swap station, is the SOC of the i-th power battery at the current moment of the battery swap station; It is used to ensure that the supercapacitor responds to the power change of the system in real time, so as to set the SOC of the supercapacitor to be maintained at 45% to 55% at the end of each period. The specific constraints are: Formula 17: ; Formula 18: ; in, It is At the end of the period, the SOC of the supercapacitor is and They are the charging and discharging efficiency of the supercapacitor respectively.

[0014] The real-time energy management mode in S3 is divided into on-time arrival and late arrival according to whether the electric vehicle scheduled for charging or swapping arrives on time; S8-1, when the electric vehicle arrives on time, the charging power of the charging station is consistent with that in the rolling energy management module and no modification is made. The supercapacitor balances the error between the actual photovoltaic power generation and the predicted value. When the supercapacitor cannot balance, the power battery in the battery swap station that does not need to participate in the next period of time will absorb it. The specific method is as follows: Formula 19: ; Formula 20: ; Formula 21: ; in, is the deviation between the actual value and the predicted value of photovoltaic power generation. is the actual power generated by the photovoltaic power station at the current moment, is the power generated by the photovoltaic power station at the current moment, is the interaction power between the battery swap station and the multi-port energy router at the current moment in the rolling energy management module; S8-2, when the electric vehicle does not arrive at the charging and swapping station during the scheduled time, the reservation is automatically canceled, and the power that should have been used to charge the power battery is consumed by charging the supercapacitor. If the supercapacitor cannot balance the power deviation, the charging and discharging power of the power battery that does not need to be involved in the battery swapping in the next period of time in the swapping station is adjusted to maintain the internal power balance of the energy router. The specific method is as follows: Formula 22: ; Formula 23: ; Formula 24: ; in, is the power deviation at the current moment, is the interaction power between the multi-port energy router and the grid at the current moment in the rolling energy management module, It is the actual charging power of the charging station at the current moment.

[0015] A computer storage medium stores a computer software program, which, when executed by a processor, implements a charging and swapping station energy management method based on a multi-port energy router.

[0016] An electronic device comprises a housing and a control panel, wherein the control panel comprises a storage medium.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The multi-time scale energy management model of the present invention obtains the reservation information of electric vehicle charging and battery replacement in real time through the Internet of Vehicles, and fully utilizes the capacity of the power battery of the battery replacement station to achieve the function of peak shaving and valley filling. A rolling energy management strategy is formulated with a more reasonable and accurate time scale to reduce operating costs. Different charging strategies are formulated based on the reservation status of electric vehicles to guide car owners to make reservations in advance.

[0018] The present invention formulates real-time energy management strategies respectively through two modes of on-time arrival and late arrival according to the actual arrival situation of the electric vehicle.

[0019] In addition, the present invention maintains the power balance of the system by introducing supercapacitors to smooth out the deviation between the actual power generation of the photovoltaic power station and the predicted value and the disturbance caused by the late arrival of electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The figure is a flow chart of the method of the present invention.

[0021] Figure 2 This is a system model diagram of the present invention.

[0022] Figure 3This is a flow chart of the rolling energy management module in the present invention.

[0023] Figure 4 This is a flow chart of the real-time energy management module in the present invention.

[0024] Figure 5 It is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0025] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0026] The present invention will now be further described with reference to the accompanying drawings. Example

[0027] This embodiment provides a charging and swapping station energy management system based on a multi-port energy router, such as Figure 5 As shown, it includes: an information collection and processing module, a rolling energy management module and a real-time energy management module.

[0028] The information collection and processing module is configured as follows: the multi-port energy router predicts the photovoltaic power generation power in the future T period, detects the status of each power battery in the charging station and the battery swapping station in real time, and collects the electric vehicle charging and battery swapping reservation information through the Internet of Vehicles. The electric vehicle charging and battery swapping reservation information collected through the Internet of Vehicles includes: the electric vehicle owner chooses to charge or swap, the charging start and end time, the battery swapping time, the current electric vehicle power battery capacity and the distance from the charging and swapping station. And the remaining power battery capacity of the electric vehicle when it arrives at the charging and swapping station is calculated based on the current electric vehicle power battery capacity and the distance from the charging and swapping station.

[0029] The rolling energy management module is configured to: according to the information collected and processed by the multi-port energy router, with the goal of maximizing the profit of the electric vehicle charging and discharging station, under the condition of meeting the corresponding constraints, every t time period rolling optimize the energy management strategy for the future time T.

[0030] The real-time energy management module is configured to select the real-time energy management mode based on the actual photovoltaic power generation, whether the electric vehicles scheduled for charging and swapping arrive on time, the status of all power batteries in the charging and swapping station, and formulate the real-time energy management strategy in combination with the rolling energy management strategy. Example

[0031] This embodiment provides a charging and swapping station energy method based on a multi-port energy router, such as Figure 1 As shown, the following steps are included: The power station energy management method comprises the following steps: (1) The multi-port energy router predicts the photovoltaic power generation power in the future T period, detects the status of all power batteries in the charging and swapping station in real time, and obtains the charging and swapping appointment information of electric vehicle owners through the Internet of Vehicles and performs corresponding processing.

[0032] (2) Based on the information collected and processed by the multi-port energy router, the energy management strategy for the future T periods is optimized at rolling intervals every time t, with the goal of maximizing the profit of the electric vehicle charging and discharging station and subject to the corresponding constraints.

[0033] (3) Based on the actual photovoltaic power generation, whether the electric vehicles scheduled for charging and swapping arrive on time, the status of all power batteries in the charging and swapping station, etc., select the real-time energy management mode and formulate a real-time energy management strategy in combination with the rolling energy management strategy.

[0034] The architecture of the above method is as follows Figure 2 As shown, the multi-port energy router is connected to the power grid, photovoltaic power stations, charging stations, battery swap stations, and supercapacitors, wherein the supercapacitors are used to buffer the impact on the stability of the multi-port energy router caused by the deviation of photovoltaic power generation and the sudden charging of electric vehicles not at the scheduled time.

[0035] The method of the embodiment of the present invention is further described below from the three steps of "information collection and processing, formulating a rolling energy management strategy, and formulating a real-time energy management strategy": It should be pointed out here that information collection and processing are implemented by the information collection and processing module, rolling energy management strategy is implemented by the rolling energy management module, and real-time energy management strategy is implemented by the real-time energy management module.

[0036] S1: Information Collection and Processing The multi-port energy router predicts the photovoltaic power generation power in the future T period, detects the status of each power battery in the charging station and the battery swap station in real time, and collects the electric vehicle charging and battery swap appointment information through the Internet of Vehicles. The electric vehicle charging and battery swap appointment information collected through the Internet of Vehicles includes: the electric vehicle owner's choice of charging or battery swapping, the charging start and end time, the battery swap time, the current electric vehicle power battery capacity and the distance from the charging and battery swap station.

[0037] Furthermore, the remaining capacity of the power battery of the electric vehicle when it arrives at the charging and swapping station is calculated based on the current power battery capacity of the electric vehicle and the distance to the charging and swapping station. Specifically, Formula 1: ; Formula 2: ; Formula 3: ; in, It is the remaining capacity of the power battery when the electric vehicle arrives at the charging and swapping station. is the current electric vehicle power battery capacity, is the speed of the electric car, Is the electric car at speed The power battery discharge power during driving, Is the electric car at speed Driving time, is the power battery discharge efficiency, Is the electric car at speed Distance travelled.

[0038] S2: Develop rolling energy management strategies, such as Figure 3 As shown: Based on the information collected and processed by the multi-port energy router, the energy management strategy for the future T period is optimized at intervals of t, with the goal of maximizing the profit of the electric vehicle charging and swapping station.

[0039] The rolling energy management model is established, and the objective function is as follows: Formula 4: ; Formula 5: ; Formula 6: ; Formula 7: ; in, is the revenue of electric vehicle charging and swapping stations, is the revenue of the charging station, is the revenue from the battery swap station. is the cost of interaction between the multi-port energy router and the grid, and They are the service fee ratio coefficients charged by charging and swapping stations to car owners. yes The total charging power of the charging station at all times, yes The total power exchanged between the power station and the energy router at any time, Positive timing indicates charging at the battery swap station, while negative timing indicates discharging. yes The multi-port energy router interacts with the grid at all times. When it is positive, it means buying electricity from the grid, and vice versa, it means selling electricity to the grid. yes Grid electricity price at the moment.

[0040] In order to guide car owners to make reservations in advance, different proportions of service fees are charged according to the time of charging and battery replacement reservation made in advance by the car owners. The service fee coefficients are formulated as follows: Formula 8: ; in They are the service fee ratio coefficients charged by charging and swapping stations to car owners. It is the time difference between the owner's scheduled charging start time or scheduled battery replacement time and the current time.

[0041] In order to maintain the internal power balance of the multi-port energy router, the rolling energy management model should satisfy the power balance constraint, specifically: Formula 9: ; in yes The power generated by the photovoltaic power station at any moment, yes Supercapacitor charging power at all times, When it is positive, the supercapacitor is charged, otherwise, the supercapacitor is discharged; In the charging and swapping station, the charging power constraint of the charging station set to avoid the port power limitation of the multi-port energy router is: Formula 10: ; in, is the maximum total charging power of the charging station; In the charging and swapping station, the interactive power constraint between the charging and swapping station and the multi-port energy router set to avoid the port power limitation of the multi-port energy router is: Formula 11: ; in, is the maximum total interactive power between the battery swap station and the multi-port energy router; In the charging and swapping station, the interaction power constraint between the supercapacitor and the multi-port energy router set to avoid the port power limitation of the multi-port energy router is: Formula 12: ; in, is the maximum interaction power between the supercapacitor and the multi-port energy router; It is used to ensure that the electric vehicle that chooses to charge can be fully charged at the agreed time, so as to set the electric vehicle power battery, that is, the constraint condition of SOC is: Formula 13: ; Formula 14: ; in, is the SOC of the i-th electric vehicle at the end of scheduled charging, is the SOC of the i-th electric vehicle at the current moment, is the power battery charging efficiency, is the rated capacity of the power battery; It is used to ensure that when the car owner who has made an appointment for battery replacement arrives at the battery replacement station, there are enough fully charged power batteries for the car owner to replace, so the constraint condition of the power battery SOC of the battery replacement station in the charging and swapping station is set as follows: Formula 15: ; Formula 16: ; in, It is the i-th power battery in the battery swap station SOC at all times, yes The number of vehicles scheduled for battery replacement at any given time, is the total number of power batteries in the battery swap station, is the SOC of the i-th power battery at the current moment of the battery swap station; It is used to ensure that the supercapacitor responds to the power change of the system in real time, so as to set the SOC of the supercapacitor to be maintained at 45% to 55% at the end of each period. The specific constraints are: Formula 17: ; Formula 18: ; in, It is At the end of the period, the SOC of the supercapacitor is and They are the charging and discharging efficiency of the supercapacitor respectively.

[0042] By solving the above rolling energy management model, a rolling energy management strategy is formulated, including: the charging power of the charging station in each period, the interaction power between the battery swap station and the energy router, and the interaction power between the energy router and the power grid.

[0043] S3: Develop real-time energy management strategies, such as Figure 4 As shown: Since charging and swapping stations adopt an appointment system, car owners need to make an appointment in advance before charging or swapping. Depending on whether the electric car scheduled for charging and swapping arrives on time, there are two situations: on-time arrival and late arrival. For these two modes, real-time energy management models are established in combination with the actual photovoltaic power generation and rolling energy management strategy, specifically: Mode 1: Arrive on time.

[0044] If the electric vehicle arrives at the charging and swapping station at the scheduled time for charging or battery swapping, the charging power of the charging station is consistent with the rolling energy management method and is not modified. The supercapacitor balances the error between the actual photovoltaic power generation and the predicted value. When the supercapacitor cannot balance, the power battery in the swapping station that does not need to participate in the battery swapping in the next period will absorb it. Specifically: Formula 19: ; Formula 20: ; Formula 21: ; in, is the deviation between the actual value and the predicted value of photovoltaic power generation. is the actual power generated by the photovoltaic power station at the current moment, is the power generated by the photovoltaic power station at the current moment, It is the interaction power between the battery swap station and the multi-port energy router in the rolling energy management module at the current moment.

[0045] Mode 2: Late or not arriving.

[0046] If the electric vehicle does not arrive at the charging and swapping station during the scheduled time, the reservation will be automatically canceled, and the power that should have been used to charge the power battery will be consumed by charging the supercapacitor. If the supercapacitor cannot balance the power deviation, the charging and discharging power of the power battery that does not need to be swapped in the next period of time in the swapping station will be adjusted to maintain the internal power balance of the energy router. Specifically: Formula 22: ; Formula 23: ; Formula 24: ; in, is the power deviation at the current moment, is the interaction power between the multi-port energy router and the grid at the current moment in the rolling energy management module, It is the actual charging power of the charging station at the current moment.

[0047] By solving the above real-time energy management model, a real-time energy management strategy is formulated, including: the charging power of the charging station in the current period, the interaction power between the supercapacitor and the energy router, the interaction power between the battery swap station and the energy router, and the interaction power between the energy router and the power grid.

[0048] Embodiment 3: This embodiment also provides a computer-readable storage medium and an electronic device, wherein the computer-readable storage medium stores a computer program, and when the program is executed by a processor, the steps in the energy method of a charging and swapping station based on a multi-port energy router as described in Embodiment 2 of the present disclosure are implemented.

[0049] The electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the energy method of a charging and swapping station based on a multi-port energy router in the second embodiment of the present disclosure are implemented.

[0050] The above are only preferred embodiments of the present invention, which are only used to help understand the method and core ideas of the present application. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

[0051] The present invention solves the shortcomings of the prior art, such as the high operating cost caused by the single operation mode of the electric vehicle charging and swapping station, and the impact of the sudden access of electric vehicles on the stability of the power grid. Through a multi-time scale energy management strategy, the present invention integrates advanced power electronics technology, big data technology and Internet of Vehicles technology, and intelligently dispatches and optimizes the energy of the charging and swapping station at different time scales, thereby improving the operating efficiency and service quality of the charging and swapping facilities, and promoting the utilization of renewable energy and the stable operation of the power grid.

Claims

1. The energy management system of a charging and swapping station based on a multi-port energy router is characterized by: It includes information collection and processing module, rolling energy management module and real-time energy management module; The information collection and processing module is configured to: the multi-port energy router predicts the photovoltaic power generation power within a future period of time T, detects the status of each power battery at the charging station and the battery swapping station in real time, collects the electric vehicle's scheduled charging and battery swapping information through the Internet of Vehicles, and calculates the remaining power battery capacity of the electric vehicle when it arrives at the charging and battery swapping station based on the current power battery capacity of the electric vehicle and the distance from the charging and battery swapping station; The rolling energy management module is configured to: according to the information collected and processed by the information collection and processing module, with the goal of maximizing the profit of the electric vehicle charging and discharging station, under the condition of meeting the corresponding constraints, every time interval t, the energy management strategy for the future period T is rolling optimized; The real-time energy management module is configured to: select the real-time energy management mode according to the actual photovoltaic power generation, whether the electric vehicles scheduled for charging and swapping arrive on time, and the status information of all power batteries in the charging and swapping station, and formulate the real-time energy management strategy in combination with the rolling energy management module.

2. The energy management system for a charging and swapping station based on a multi-port energy router according to claim 1 is characterized in that: The scheduled charging and battery swapping information in the information collection and processing module includes: the owner's choice of charging or battery swapping, the charging start and end time, the battery swapping time, the current electric vehicle power battery capacity and the distance to the charging and battery swapping station.

3. A charging and swapping station energy management method based on a multi-port energy router according to the system of claim 1, characterized in that: The following steps are involved: S1, the multi-port energy router predicts the photovoltaic power generation within a period of time T in the future, detects the status of all power batteries in the charging and swapping station in real time, obtains the charging and swapping reservation information of electric vehicle owners through the Internet of Vehicles, and calculates the remaining power battery capacity of the electric vehicle when it arrives at the charging and swapping station based on the current power battery capacity of the electric vehicle and the distance from the charging and swapping station; S2, based on the information collected and processed by the multi-port energy router, with the goal of maximizing the revenue of the electric vehicle charging and discharging station, under the condition of meeting the corresponding constraints, the rolling energy management module rolls out the energy management strategy for a period of time T in the future at intervals of time t, so as to guide the car owner to make an appointment in advance, and charge different proportions of service fees according to the car owner's advance appointment time for charging and swapping; S3, selects the real-time energy management mode according to the actual photovoltaic power generation, whether the electric vehicles scheduled for charging and swapping arrive on time, and the status information of all power batteries in the charging and swapping station, and formulates the real-time energy management strategy in combination with the rolling energy management strategy.

4. The energy management method for a charging and swapping station based on a multi-port energy router according to claim 3 is characterized in that: The specific calculation method of the remaining capacity of the power battery in S1 is: Formula 1: ; Formula 2: ; Formula 3: ; in, It is the remaining capacity of the power battery when the electric vehicle arrives at the charging and swapping station. is the current electric vehicle power battery capacity, is the speed of the electric car, Is the electric car at speed The power battery discharge power during driving, Is the electric car at speed Driving time, is the power battery discharge efficiency, Is the electric car at speed Distance travelled.

5. The energy management method for a charging and swapping station based on a multi-port energy router according to claim 3 is characterized in that: The energy management strategy for the rolling optimization in the future period T in S2 is realized by the objective function, and its specific calculation method is: Formula 4: ; Formula 5: ; Formula 6: ; Formula 7: ; in, is the revenue of electric vehicle charging and swapping stations, is the revenue of the charging station, is the revenue from the battery swap station. is the cost of interaction between the multi-port energy router and the grid, and They are the service fee ratio coefficients charged by charging and swapping stations to car owners. yes The total charging power of the charging station at all times, yes The total power exchanged between the power station and the energy router at the moment, Positive timing indicates charging at the battery swap station, while negative timing indicates discharging. yes At the moment the multi-port energy router interacts with the grid, the When it is positive, it means buying electricity from the grid, and vice versa, it means selling electricity to the grid. yes Grid electricity price at the moment.

6. The energy management method for a charging and swapping station based on a multi-port energy router according to claim 3 is characterized in that: The calculation method of the proportional coefficient of the service fee charged at different proportions according to the time of charging and swapping scheduled in advance by the car owner in S2 is: Formula 8: ; in They are the service fee ratio coefficients charged by charging and swapping stations to car owners. It is the time difference between the owner's scheduled charging start time or scheduled battery replacement time and the current time.

7. The energy management method for a charging and swapping station based on a multi-port energy router according to claim 3 is characterized in that: The constraints for the rolling energy management module in S2 to maintain the internal power balance of the multi-port energy router are: Formula 9: ; in yes The power generated by the photovoltaic power station at any moment, yes The supercapacitor charging power at the moment, When it is positive, the supercapacitor is charged, otherwise, the supercapacitor is discharged; In the charging and swapping station, the charging power constraint condition of the charging station set to meet the port power limit of the multi-port energy router is: Formula 10: ; in, is the maximum total charging power of the charging station; In the charging and discharging station, the power constraint condition for interaction between the battery swap station and the multi-port energy router set to meet the port power limit of the multi-port energy router is: Formula 11: ; in, is the maximum total interactive power between the battery swap station and the multi-port energy router; In the charging and swapping station, the interactive power constraint condition between the supercapacitor and the multi-port energy router set to meet the port power limit of the multi-port energy router is: Formula Twelve: ; in, is the maximum interaction power between the supercapacitor and the multi-port energy router; It is used to ensure that the electric vehicle that chooses to charge can be fully charged at the agreed time, so as to set the electric vehicle power battery, that is, the constraint condition of SOC is: Formula 13: ; Formula 14: ; in, is the SOC of the i-th electric vehicle at the end of scheduled charging, is the SOC of the i-th electric vehicle at the current moment, is the power battery charging efficiency, is the rated capacity of the power battery; To ensure that when the car owner who has made an appointment for battery replacement arrives at the battery replacement station, there are enough fully charged power batteries for the car owner to replace, so the constraint condition of the power battery SOC of the battery replacement station in the charging and swapping station is set as follows: Formula 15: ; Formula 16: ; in, It is the i-th power battery in the battery swap station SOC at all times, yes The number of vehicles scheduled for battery replacement at any given time, is the total number of power batteries in the battery swap station, is the SOC of the i-th power battery at the current moment of the battery swap station; It is used to ensure that the supercapacitor responds to the system power change in real time, so as to control the SOC of the supercapacitor to be maintained at 45% to 55% at the end of each period. The specific constraints are: Formula 17: ; Formula 18: ; in, It is At the end of the period, the SOC of the supercapacitor is and They are the charging and discharging efficiency of the supercapacitor respectively.

8. The energy management method for a charging and swapping station based on a multi-port energy router according to claim 3 is characterized in that: The real-time energy management mode in S3 is divided into on-time arrival and late arrival according to whether the electric vehicle scheduled for charging or swapping arrives on time; S8-1, when the electric vehicle arrives on time, the charging power of the charging station is consistent with that in the rolling energy management module and is not modified. The supercapacitor balances the error between the actual photovoltaic power generation and the predicted value. When the supercapacitor cannot balance, the power battery in the battery swap station that does not need to participate in the next period of time will absorb it. The specific method is: Formula 19: ; Formula 20: ; Formula 21: ; in, is the deviation between the actual value and the predicted value of photovoltaic power generation. is the actual power generated by the photovoltaic power station at the current moment, is the power generated by the photovoltaic power station at the current moment, is the interaction power between the battery swap station and the multi-port energy router in the rolling energy management module at the current moment; S8-2, when the electric vehicle does not arrive at the charging and swapping station during the scheduled time, the reservation is automatically canceled, and the power that should have been used to charge the power battery is consumed by charging the supercapacitor. If the supercapacitor cannot balance the power deviation, the charging and discharging power of the power battery that does not need to be involved in the battery swapping in the next period of time in the swapping station is adjusted to maintain the internal power balance of the energy router. The specific method is as follows: Formula 22: ; Formula 23: ; Formula 24: ; in, is the power deviation at the current moment, is the interaction power between the multi-port energy router and the power grid at the current moment in the rolling energy management module, It is the actual charging power of the charging station at the current moment.

9. A computer storage medium, characterized in that: The storage medium stores a computer software program, and when the computer software program is executed by the processor, the energy management method for a charging and swapping station based on a multi-port energy router as described in any one of claims 3 to 8 is implemented.

10. An electronic device, comprising a housing and a control panel, characterized in that: The control board includes the storage medium as claimed in claim 9.

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