Optimized scheduling method for integrating electric vehicle charging and discharging into building system

Abstract

The invention discloses an optimal scheduling method for integrating electric vehicle charging and discharging into a building system, which comprises the following steps: carrying out feature extraction on travel data of electric vehicles participating in charging and discharging scheduling in the building system in workdays in a statistical period collected by an intelligent traffic monitoring system in the building system; determining the parking time of the electric vehicles in workdays and the number of the electric vehicles participating in V2G whole-day parking, and obtaining schedulable electric vehicles in each time period and charging and discharging demands thereof; and based on the schedulable electric vehicles in each time period and the charging and discharging requirements thereof, determining the total charging and discharging power of the electric vehicles in different time periods in the building system and the charging and discharging strategy of each electric vehicle by using the built charging and discharging scheduling model of the electric vehicles in the building. According to the invention, the overall schedulability of the electric vehicle is expanded, and the stability requirement of a building for a power grid is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of optimization scheduling, and in particular to an optimization scheduling method for integrating electric vehicle charging and discharging into a building system. Background Art

[0002] As the global energy crisis and environmental pollution become increasingly serious, electric vehicles (EVs) have become an important force in promoting green transportation and sustainable development with their advantages such as zero emissions and low noise. At the same time, as an important part of modern urban energy utilization, the integrated energy building system integrates multiple energy forms such as electricity, gas, and heat, aiming to achieve efficient utilization and optimal allocation of energy. Combining the charging and discharging functions of electric vehicles with the integrated energy building system can not only make full use of the characteristics of electric vehicles as distributed energy storage units to smooth the peak and valley fluctuations of building power load, but also improve the overall efficiency and flexibility of the building energy system through intelligent scheduling strategies.

[0003] However, in actual applications, the integration of electric vehicle charging and discharging with integrated energy building systems faces many challenges: on the one hand, there is uncertainty in the time distribution of electric vehicle charging demand and building power load, and how to accurately predict the parking time and charging demand of electric vehicles has become a prerequisite for formulating effective scheduling strategies. On the other hand, there are complex energy conversion and storage links within the building energy system. How to coordinate the charging and discharging of electric vehicles with the operation of other energy equipment in the building, while ensuring the smoothing of fluctuations in building power load, and taking into account the satisfaction of electric vehicle owners in the charging and discharging process, is an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings and defects of the prior art and to provide an optimization scheduling method for integrating electric vehicle charging and discharging into a building system, aiming to achieve deep integration and efficient coordination of electric vehicle charging and discharging with building energy systems through intelligent optimization scheduling technology.

[0005] An optimization scheduling method for integrating electric vehicle charging and discharging into a building system, comprising:

[0006] Extract features from the electric vehicle travel data participating in charging and discharging scheduling in the building system on weekdays during the statistical period collected by the intelligent traffic monitoring system in the building system, determine the parking time of electric vehicles on weekdays and the number of electric vehicles participating in V2G that stay all day, and obtain the electric vehicles that can be dispatched in each time period and their charging and discharging needs;

[0007] Based on the dispatchable electric vehicles and their charging and discharging needs in each time period, the built charging and discharging scheduling model of electric vehicles in buildings is used to determine the overall charging and discharging power of electric vehicles in different time periods in the building system and the charging and discharging strategy of each electric vehicle:

[0008] The in-building electric vehicle charging and discharging scheduling model includes an in-building electric vehicle charging and discharging scheduling upper model and an in-building electric vehicle charging and discharging scheduling lower model;

[0009] The upper-level model of charging and discharging scheduling of electric vehicles in buildings includes the first objective function established with the goal of minimizing the peak-to-valley fluctuation variance of the building system grid side during a working day;

[0010] The lower-level model of charging and discharging scheduling of electric vehicles in buildings includes a second objective function established with the goal of maximizing the overall charging and discharging satisfaction of owners of electric vehicles participating in charging and discharging in the building system on a weekday; the overall charging and discharging satisfaction of owners includes the overall satisfaction with the charging costs of electric vehicles and the overall satisfaction with the final SOC value of the vehicle battery.

[0011] Among them, the first objective function includes:

[0012] ;

[0013] in, is the basic electrical load of the building system in time period t, is the photovoltaic power generation output value of the building system in time period t; is the total charge and discharge power of the dispatchable electric vehicles in the building system in time period t. When the total charge and discharge power is positive, it means that all dispatchable electric vehicles are charging at this time. When the total charge and discharge power is negative, it means that all dispatchable electric vehicles are discharging. is the average electrical load of the building system, represents the number of time periods t.

[0014] The average electrical load of the building system is calculated by the following formula:

[0015] .

[0016] Among them, the photovoltaic power generation output value of the building system in time period t is calculated and determined by the following formula:

[0017] ;

[0018] ;

[0019] ;

[0020] ;

[0021] In the formula, is the photovoltaic power generation output value; To calculate the maximum solar irradiance within a time step, is the photoelectric conversion efficiency, S is the single-plate area of ​​the photovoltaic cell module, is the probability density distribution function of solar irradiance, g is the solar irradiance at the current moment, is the maximum solar irradiance during the period; p and q are the shape parameters of the Beta distribution, based on the expected value of the light intensity statistics and standard deviation calculate.

[0022] Among them, the second objective function includes:

[0023] ;

[0024] ;

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] in, The overall charging and discharging satisfaction of electric vehicle owners. are the weight coefficients, Overall satisfaction with charging costs for all electric vehicles, The overall satisfaction of all EV owners with the final SOC value; The total charging cost of all electric vehicle owners who do not participate in the charging and discharging scheduling, The total charging cost for all electric vehicle owners participating in the charging and discharging scheduling; For the The final SOC value of an electric vehicle when it leaves the building system. For the The SOC target value after the electric vehicles participate in the charging and discharging scheduling, N is all the electric vehicles participating in the charging and discharging scheduling; r is the electricity price provided by the power grid that does not participate in the charging and discharging scheduling; is the discharge compensation price for electric vehicle owners; is the charging price for electric car owners; is the discharge power of all dispatchable electric vehicles in the building system during period t; It is represented by the charging power of all dispatchable electric vehicles in the building system during period t; During peak hours, is the electricity price during peak hours, For normal period, The electricity price during normal times is The valley period, The electricity price during peak hours.

[0032] Among them, the constraints of the second objective function include:

[0033] , ;

[0034] , ;

[0035] ;

[0036] in, is the charging and discharging power of electric vehicles in the building system, is the number of electric vehicles that can be dispatched in the building system at different time periods t, For the The charging and discharging power of electric vehicles; M is the number of electric vehicles involved in charging and discharging in a single scheduling period;

[0037] in, is the difference generally accepted by electric car owners; during the dispatch process, each electric car The value cannot exceed the upper and lower limits. is the minimum allowed SOC value of electric vehicles; is the maximum allowable SOC value of an electric vehicle;

[0038] in, For the The maximum number of charge-discharge switching times allowed for an electric vehicle during the dispatchable period.

[0039] Among them, the building system includes:

[0040] The above-ground floors are constructed based on the photovoltaic building integrated BIPV technology, using the building's facade resources to arrange photovoltaic cell components to form a distributed photovoltaic power generation system;

[0041] The underground parking lot is connected to the transportation network, equipped with an intelligent traffic monitoring system, and deployed with smart charging piles for electric vehicles. It is also equipped with an energy management center to schedule the charging and discharging of battery vehicles on the smart charging piles at different times of the day.

[0042] The underground parking lot includes:

[0043] The vehicle identification device is used to identify the parked vehicles in the underground parking lot when the parked vehicles enter or exit the underground parking lot.

[0044] Wherein, the underground parking lot is provided with:

[0045] The navigation device is used to provide parking navigation guidance for the identified vehicles based on networking technology, and is used to guide electric vehicles without charging and discharging requirements to non-intelligent charging parking spaces, and guide electric vehicles with charging and discharging requirements to intelligent charging parking spaces for charging and discharging.

[0046] Among them, the importance random sampling method is used to sample the time data of N electric vehicles entering / exiting the building system, and the time distribution of electric vehicles entering / exiting is quantified. The number of electric vehicles entering / exiting the building system in each time period is converted into the probability value of the electric vehicle arriving at the building system in the time period. Finally, the standard normal distribution curve is used for fitting, and then the time of each electric vehicle entering / exiting the building system on weekdays is determined by sampling;

[0047] The collected data of electric vehicles participating in V2G staying all day are calculated using the arithmetic mean method to determine the number of electric vehicles staying in V2G all day.

[0048] The technology of the present invention takes into account the dispatchable capacity of electric vehicle owners in different travel modes in the building and comprehensively determines the charging and discharging satisfaction of electric vehicle users based on multiple factors, further expanding the overall dispatchable capacity of electric vehicles. At the same time, this technology comprehensively considers the satisfaction of electric vehicle owners in participating in charging and discharging based on multiple factors, ensures the building's demand for the stability of the power grid, and takes into account the satisfaction of electric vehicle owners in the dispatching process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flow chart of an optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0051] The optimized scheduling method for integrating electric vehicle charging and discharging into a building system in an embodiment of the present invention is proposed by taking into account the dispatchable capacity of electric vehicle owners in different travel modes in a building and determining the charging and discharging satisfaction of electric vehicle users based on a comprehensive consideration of multiple factors. It can further expand the overall dispatchable capacity of electric vehicles, and comprehensively consider the satisfaction of electric vehicle owners in participating in charging and discharging based on multiple factors, thereby ensuring the building's demand for the stability of the power grid and taking into account the satisfaction of electric vehicle owners in the scheduling process.

[0052] See attached Figure 1 As shown, the optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to an embodiment of the present invention comprises the following steps:

[0053] Extract features from the electric vehicle travel data participating in charging and discharging scheduling in the building system on weekdays during the statistical period collected by the intelligent traffic monitoring system in the building system, determine the parking time of electric vehicles on weekdays and the number of electric vehicles participating in V2G that stay all day, and obtain the electric vehicles that can be dispatched in each time period and their charging and discharging needs;

[0054] Based on the dispatchable electric vehicles and their charging and discharging needs in each time period, the constructed in-building electric vehicle charging and discharging scheduling model is used to determine the overall charging and discharging power of electric vehicles in different time periods in the building system and the charging and discharging strategy of each electric vehicle.

[0055] In an embodiment of the present application, the in-building electric vehicle charging and discharging scheduling model includes an in-building electric vehicle charging and discharging scheduling upper model and an in-building electric vehicle charging and discharging scheduling lower model; the in-building electric vehicle charging and discharging scheduling upper model includes a first objective function established with the goal of minimizing the peak-to-valley fluctuation variance of the building system on a working day; the in-building electric vehicle charging and discharging scheduling lower model includes a second objective function established with the goal of maximizing the overall charging and discharging satisfaction of the owners of electric vehicles participating in charging and discharging in the building system on a working day; the overall charging and discharging satisfaction of the owners includes the overall satisfaction with the electric vehicle charging fee and the overall satisfaction with the final SOC value of the vehicle battery.

[0056] In this application, the first objective function is proposed by considering the minimization of the peak-to-valley fluctuation variance of the building system, with the minimization of the peak-to-valley fluctuation variance on the power grid side of the building system as the first goal. The energy management center of the building system ensures load stability by controlling the charging and discharging of dispatchable electric vehicles in different dispatching cycles, and the load standard deviation is used to characterize the effect of load peak shaving and valley filling. The smaller the standard deviation, the more stable the load.

[0057] Among them, the first objective function includes:

[0058] ;

[0059] in, is the basic electrical load of the building system in period t, including the basic electrical load of lighting, ventilation, equipment, electric heating and electric hot water systems. is the photovoltaic power generation output value of the building system in time period t; is the total charge and discharge power of the dispatchable electric vehicles in the building system in time period t. When the total charge and discharge power is positive, it means that all dispatchable electric vehicles are charging at this time. When the total charge and discharge power is negative, it means that all dispatchable electric vehicles are discharging. is the average electrical load of the building system, represents the number of time periods t.

[0060] The average electrical load of the building system is calculated by the following formula:

[0061] .

[0062] Among them, the photovoltaic power generation output value of the building system in time period t is calculated and determined by the following formula:

[0063] ;

[0064] ;

[0065] ;

[0066] ;

[0067] In the formula, is the photovoltaic power generation output value; To calculate the maximum solar irradiance within a time step, is the photoelectric conversion efficiency, S is the single-plate area of ​​the photovoltaic cell module, is the probability density distribution function of solar irradiance, g is the solar irradiance at the current moment, is the maximum solar irradiance during the period; p and q are the shape parameters of the Beta distribution, based on the expected value of the light intensity statistics and standard deviation calculate.

[0068] It is known that the photovoltaic output value of the building system in a day mainly depends on the irradiation intensity, and its output value presents characteristics of volatility and uncertainty with the randomness of the light irradiation intensity. Therefore, to determine its photovoltaic output value, the characteristic function of the solar amplitude illumination is first determined. The Beta distribution is usually used to simulate the random distribution of solar irradiance, and its probability density function is calculated. Therefore, in the embodiment of the present application, the above method is used to calculate the photovoltaic power generation output value of the building system in time period t.

[0069] Among them, the second objective function comprehensively considers the charging costs of the owners of electric vehicles participating in the charging and discharging scheduling and the SOC value of the battery system of the electric vehicle, with the goal of maximizing the overall charging and discharging satisfaction of all electric vehicles participating in the charging and discharging in a day, including:

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] in, The overall charging and discharging satisfaction of electric vehicle owners. is the weight coefficient, Overall satisfaction with charging costs for all electric vehicles, The overall satisfaction of all EV owners with the final SOC value; The total charging cost of all electric vehicle owners who do not participate in the charging and discharging scheduling, The total charging cost for all electric vehicle owners participating in the charging and discharging scheduling; For the The final SOC value of an electric vehicle when it leaves the building system. For the The SOC target value after the electric vehicles participate in the charging and discharging scheduling, N is all the electric vehicles participating in the charging and discharging scheduling; r is the electricity price provided by the power grid that does not participate in the charging and discharging scheduling; is the discharge compensation price for electric vehicle owners; is the charging price for electric car owners; is the discharge power of all dispatchable electric vehicles in the building system during period t; It is represented by the charging power of all dispatchable electric vehicles in the building system during period t; During peak hours, is the electricity price during peak hours, For normal period, The electricity price during normal times is The valley period, The electricity price during peak hours.

[0079] Among them, the constraints of the second objective function include:

[0080] , ;

[0081] , ;

[0082] ;

[0083] in, is the charging and discharging power of all electric vehicles in the building system, is the number of electric vehicles that can be dispatched in the building system at different time periods t, For the The charging and discharging power of electric vehicles; M is the number of electric vehicles involved in charging and discharging in a single scheduling period;

[0084] in, is the difference generally accepted by electric car owners; during the dispatch process, each electric car The value cannot exceed the upper and lower limits. is the minimum allowed SOC value of electric vehicles; is the maximum allowable SOC value of an electric vehicle;

[0085] in, For the The maximum number of charge-discharge switching times allowed for an electric vehicle during the dispatchable period.

[0086] Through the above constraints, the integer number of electric vehicles to be charged and discharged, the number of electric vehicles that can be dispatched at different time periods t, and the SOC value travel demand of all charged electric vehicles when leaving the building are constrained, ensuring that each electric vehicle itself The changing value cannot exceed the upper and lower limits, as well as the impact of the number of charge and discharge switching times of all electric vehicles on battery life.

[0087] In some embodiments, the building system in the present application includes: ground floors, which are constructed based on photovoltaic building integrated BIPV technology, and use the facade resources of the building to arrange photovoltaic cell components to form a distributed photovoltaic power generation system; underground parking lots, such as the first floor of an underground parking lot, which is connected to the transportation network, equipped with an intelligent traffic monitoring system, and deployed with electric vehicle smart charging piles, and is also equipped with an energy management center to schedule the charging and discharging of battery vehicles in smart charging spaces during different periods of the day.

[0088] In some embodiments, the underground parking lot in the present application is provided with a vehicle identification device for identifying parked vehicles in the underground parking lot when they enter or exit the underground parking lot, so as to facilitate guidance after identification and guide the vehicle to a smart charging parking space or a non-smart charging ordinary parking space according to the situation.

[0089] Furthermore, in some embodiments, the underground parking lot in the present application is provided with a navigation device for providing parking navigation guidance for identified vehicles based on networking technology, for guiding electric vehicles with no charging and discharging needs to non-intelligent charging parking spaces, and guiding electric vehicles with charging and discharging needs to smart charging parking spaces for charging and discharging, wherein electric vehicles with no charging needs and willing to participate in V2G (a technology for electric vehicles to supply electricity to the power grid) are guided to smart charging parking spaces, and the batteries are discharged through smart charging columns; at the same time, the intelligent traffic detection system records the time when vehicles with charging needs enter and leave the building system in the data storage server.

[0090] In some embodiments, considering the requirements of vibration and noise reduction of the building energy management center, the building energy management center is set up in the corresponding area on the underground floor to dispatch electric vehicles in smart charging parking spaces at different times of the day and monitor the energy output of various parts of the integrated energy system building.

[0091] In this application, in view of the diversity of travel patterns of different electric vehicle owners in the building system, the analysis of electric vehicle travel characteristics is refined to the owner's behavior pattern. Using the intelligent traffic monitoring system, the electric vehicle owners participating in charging and discharging in the building system are divided into two categories. The first category is electric vehicles with charging needs, and the second category is electric vehicles with discharging needs. The time of entering and leaving the building system of the first category of electric vehicles with charging needs is collected separately, and the number of the second category of electric vehicles participating in V2G and staying in the building system all day is collected.

[0092] Existing studies have shown that the travel patterns of electric vehicle owners in building systems follow a normal distribution. The travel data of household electric vehicles in various types of building systems on weekdays are more regular than the travel of electric vehicles on non-working days (such as weekends). Therefore, in this application, the travel data on weekdays collected by the intelligent traffic monitoring system is used, and then the travel data is sampled and features are extracted to obtain the parking time of electric vehicles on weekdays and the number of vehicles participating in V2G that stay in the building all day.

[0093] In some embodiments, the time of entering and leaving the building of the first type of electric vehicles with charging needs is collected by adopting an importance random sampling method to sample the time data of N electric vehicles entering / exiting the building system, and the time distribution of the electric vehicles entering / exiting is quantified, and the number of times the electric vehicles enter / exit the building system in each time period is converted into a probability value of the electric vehicle arriving at the building system in the time period, and finally a standard normal distribution curve is fitted, and then the time for each electric vehicle to enter / exit the building on a working day is determined by sampling.

[0094] In some embodiments, the number of electric vehicles of the second category participating in V2G and staying in the building system all day is collected by calculating the collected data of electric vehicles participating in V2G and staying all day using an arithmetic mean method to determine the number of electric vehicles staying in V2G all day.

[0095] In the embodiment of the present application, the overall charge and discharge power of electric vehicles at different times in the integrated energy building and the specific charge and discharge strategy of each electric vehicle are obtained by optimizing and solving the electric vehicle charge and discharge scheduling model in the integrated energy building system. In the embodiment of the present application, the electric load of the building system is optimized by optimizing and controlling the charge and discharge of each electric vehicle in the building system during the scheduling period; the scheduling problem of the upper and lower layer optimization scheduling model established belongs to a high-dimensional multi-objective multi-constrained nonlinear integer optimization problem. By solving the multi-objective optimization problem, the optimal solution of the optimization problem is obtained. Based on the optimal solution, the overall charge and discharge power of the dispatchable electric vehicles at different times and the optimal scheduling strategy for each electric vehicle in the output building are obtained.

[0096] For example, the representative NSGA-II algorithm can be used for solution. This algorithm is not the innovation of this application and will not be described in detail. Only the solution process of the NSGA-II algorithm is given. The solution process is as follows:

[0097] Step 1: Before a scheduling cycle begins, access the data in the data storage server of the energy management center to obtain the basic power load of the building system and the local solar irradiance curve throughout the year. Obtain the travel data of electric vehicles through the intelligent traffic monitoring system to determine the scheduling period of each electric vehicle and its charging requirements.

[0098] Step 2: Initialize the charging and discharging power of electric vehicles in the building system And the goals of each electric vehicle involved in charging and discharging scheduling value.

[0099] Step 3: Based on the multi-objective optimization problem composed of the first objective function and the second objective function, the NSGA-II algorithm is used to solve the Pareto solution set of the optimization problem.

[0100] Step 4: Calculate the evaluation factor of each Pareto solution in the Pareto solution set, select the solution with the largest evaluation factor as the overall charging and discharging power of the dispatchable electric vehicles in different time periods, and output the optimal dispatching strategy for each electric vehicle in the building system.

[0101] The technology implemented in the present invention adds an intelligent traffic monitoring system to the integrated energy building system to guide vehicles entering the building under different conditions, increases the total charging and discharging power of electric vehicles at different time periods, further expands the overall dispatchability of electric vehicles, and ensures the building's demand for the stability of the power grid.

[0102] The technology of the embodiment of the present invention comprehensively considers the charging costs of the owners of electric vehicles after participating in the charging and discharging scheduling and the SOC value of the battery system of the electric vehicle, and proposes a second objective function that maximizes the satisfaction of the owners of the electric vehicle, so as to take into account the satisfaction of the owners of the electric vehicle during the scheduling process.

[0103] In summary, the technology of the embodiments of the present invention takes into account the dispatchable capacity of electric vehicle owners in different travel modes in the building and comprehensively determines the charging and discharging satisfaction of electric vehicle users based on multiple factors, further expanding the overall dispatchable capacity of electric vehicles. At the same time, this technology comprehensively considers the satisfaction of electric vehicle owners in participating in charging and discharging based on multiple factors, ensures the building's demand for the stability of the power grid, and takes into account the satisfaction of electric vehicle owners in the scheduling process.

[0104] Take a residential building in a certain place as an example. The building is 62m high, with a construction area of ​​22,000m², two underground floors, 19 above-ground floors, and a roof area of ​​1,200m². Building Integrated Photovoltaic (BIPV) technology is used to maximize the use of the building's facade resources to form a distributed photovoltaic power generation system. At the same time, lighting, ventilation, equipment, electric heating and electric hot water systems are considered as basic electrical loads; considering summer working conditions, historical load data of the building system is collected at an interval of 15 minutes.

[0105] The traffic network is connected to the parking lot on the first underground floor of the residential building, an intelligent traffic detection system is installed, and intelligent charging piles for electric vehicles are deployed to form an energy zone on the first underground floor of the residential building. In the energy zone, the parking vehicles are identified and the parking space navigation technology is provided to the car owners using networking technology, so that electric vehicles and non-electric vehicles are guided to ordinary parking spaces and parking spaces equipped with intelligent charging piles respectively. Electric vehicles without charging needs will be guided to ordinary parking spaces. When the owners with charging needs enter the building, they declare the charging needs and report them to the energy management system through the system to arrange their charging and discharging. The intelligent traffic detection system also records the time when vehicles with charging needs enter and leave the building in the data storage server. Among them, considering that some electric vehicles without charging needs have no travel plans for the whole day the next day, the electric vehicles willing to participate in V2G (vehicle-to-grid) are guided to the intelligent charging piles, and the vehicles that do not participate are guided to ordinary parking spaces; considering the requirements of the energy management center for anti-vibration and noise reduction, the building energy management system is set in other areas on the first underground floor of the residential building to dispatch electric vehicles on the intelligent charging piles at different times of the day and monitor the energy output of each part of the building system. The specific optimization process is as follows:

[0106] First, the importance method is used to randomly sample the time data of 1,000 electric vehicles arriving at the building system, and then the time distribution of electric vehicle arrival behavior is quantified, and the number of electric vehicles arriving at the building system in each time period is converted into the probability value of electric vehicles arriving at the building system in that time period. Finally, the standard normal distribution curve is used for fitting. According to the sampling fitting results, on weekdays, the time probability of electric vehicles arriving at the building in the building system follows a general normal distribution with a mean of 18.26 and a standard deviation of 1.40. The probability density function after fitting is shown in the following formula;

[0107] ;

[0108] in , .

[0109] The time when electric vehicles leave the building system is also obtained using the above method; according to the sampling fitting results, on weekdays, the probability of the time when electric vehicles leave the building system in the building system follows a general normal distribution with a mean of 7.16 and a standard deviation of 1.30. The probability density function after fitting is as follows:

[0110] ;

[0111] in, , , then 50 electric vehicles are sampled according to the above probability density function to obtain the time when electric vehicles enter and leave the building system. To obtain the number of electric vehicles participating in V2G staying in the building system all day, the collected data is calculated using the arithmetic mean method;

[0112] ;

[0113] in, The number of electric vehicles that stay in the building all day to participate in V2G; is the number of electric vehicles participating in V2G staying in the building all day collected by the intelligent traffic detection system on day d; y is the number of days in a year, and finally The value is 5. The specific values ​​involved in solving the above objective function are as follows:

[0114]

[0115] Assume that the charging and discharging power of all electric vehicles in the building system is The value is 4kW, which is generally accepted by electric car owners. The value is 0.1; the minimum allowable The value is 0.1; the maximum allowable The value is taken as 0.95, and the maximum number of charge and discharge switching allowed for the i-th electric vehicle during the dispatchable period is 3 times; based on the first objective function and the second objective function, the electric vehicle charging and discharging scheduling model in the integrated energy building system is optimized and solved, and the overall charging and discharging power of the dispatchable electric vehicles in the integrated energy building at different time periods and the specific charging and discharging strategy of each electric vehicle are obtained, and finally the charging and discharging of each electric vehicle in the energy building system during the dispatching period is optimized and controlled.

[0116] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention; therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is limited by the attached claims rather than the above description, and it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the present invention.

[0117] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. An optimization scheduling method for integrating electric vehicle charging and discharging into a building system, characterized in that: include: Extract features from the electric vehicle travel data participating in charging and discharging scheduling in the building system on weekdays during the statistical period collected by the intelligent traffic monitoring system in the building system, determine the parking time of electric vehicles on weekdays and the number of electric vehicles participating in V2G that stay all day, and obtain the electric vehicles that can be dispatched in each time period and their charging and discharging needs; Based on the dispatchable electric vehicles and their charging and discharging requirements in each time period, the constructed in-building electric vehicle charging and discharging dispatching model is used to determine the overall charging and discharging power of the dispatchable electric vehicles in different time periods in the building system and the charging and discharging strategy of each electric vehicle: The in-building electric vehicle charging and discharging scheduling model includes an in-building electric vehicle charging and discharging scheduling upper model and an in-building electric vehicle charging and discharging scheduling lower model; The upper-level model of charging and discharging scheduling of electric vehicles in buildings includes the first objective function established with the goal of minimizing the peak-to-valley fluctuation variance of the building system grid side during a working day; The lower-level model of charging and discharging scheduling of electric vehicles in buildings includes a second objective function established with the goal of maximizing the overall charging and discharging satisfaction of owners of electric vehicles participating in charging and discharging in the building system on a weekday; the overall charging and discharging satisfaction of owners includes the overall satisfaction with the charging costs of electric vehicles and the overall satisfaction with the final SOC value of the vehicle battery.

2. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 1 is characterized in that: The first objective function includes: ； in, is the basic electrical load of the building system in time period t, is the photovoltaic power generation output value of the building system in time period t; is the total charge and discharge power of the dispatchable electric vehicles in the building system in time period t. When the total charge and discharge power is positive, it means that all dispatchable electric vehicles are charging at this time. When the total charge and discharge power is negative, it means that all dispatchable electric vehicles are discharging. is the average electrical load of the building system, represents the number of time periods t.

3. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 2 is characterized in that: The average electrical load of the building system is calculated by the following formula: 。 4. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 3 is characterized in that: The photovoltaic power generation output value of the building system in time period t is calculated and determined by the following formula: ； ； ； ； In the formula, is the photovoltaic power generation output value; To calculate the maximum solar irradiance within a time step, is the photoelectric conversion efficiency, S is the single-plate area of ​​the photovoltaic cell module, is the probability density distribution function of solar irradiance, g is the solar irradiance at the current moment, is the maximum solar irradiance in time period t; p and q are the shape parameters of Beta distribution, and the expected value of the statistical data of light intensity is and standard deviation calculate.

5. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 4 is characterized in that: The second objective function includes: ； ； ； ； ； ； ； ； in, The overall charging and discharging satisfaction of electric vehicle owners. are the weight coefficients, Overall satisfaction with charging costs for all electric vehicles, The overall satisfaction of all EV owners with the final SOC value; The total charging cost of all electric vehicle owners who do not participate in the charging and discharging scheduling, The total charging cost for all electric vehicle owners participating in the charging and discharging scheduling; For the The final SOC value of an electric vehicle when it leaves the building system. For the The SOC target value after the electric vehicles participate in the charging and discharging scheduling, N is all the electric vehicles participating in the charging and discharging scheduling; r is the electricity price provided by the power grid that does not participate in the charging and discharging scheduling; is the discharge compensation price for electric vehicle owners; is the charging price for electric car owners; is the discharge power of all dispatchable electric vehicles in the building system during period t; It is represented by the charging power of all dispatchable electric vehicles in the building system during period t; During peak hours, is the electricity price during peak hours, For normal period, The electricity price during normal times is The valley period, The electricity price during peak hours.

6. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 5 is characterized in that: The constraints of the second objective function include: ， ； ， ； ； in, is the charging and discharging power of electric vehicles in the building system, is the number of electric vehicles that can be dispatched in the building system at different time periods t, For the The charging and discharging power of electric vehicles; M is the number of electric vehicles involved in charging and discharging in a single scheduling period; in, is the difference generally accepted by electric car owners; during the dispatch process, each electric car The value cannot exceed the upper and lower limits. is the minimum allowed SOC value of electric vehicles; is the maximum allowable SOC value of an electric vehicle; in, For the The maximum number of charge-discharge switching times allowed for an electric vehicle during the dispatchable period.

7. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to any one of claims 1 to 6, characterized in that: Building systems include: The above-ground floors are constructed based on the photovoltaic building integrated BIPV technology, using the building's facade resources to arrange photovoltaic cell components to form a distributed photovoltaic power generation system; The underground parking lot is connected to the transportation network, equipped with an intelligent traffic monitoring system, and deployed with smart charging piles for electric vehicles. It is also equipped with an energy management center to schedule the charging and discharging of battery vehicles on the smart charging piles at different times of the day.

8. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 7 is characterized in that: The underground parking lot is equipped with: The vehicle identification device is used to identify the parked vehicles in the underground parking lot when the parked vehicles enter or exit the underground parking lot.

9. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 8 is characterized in that: The underground parking lot is equipped with: The navigation device is used to provide parking navigation guidance for the identified vehicles based on networking technology, and is used to guide electric vehicles without charging and discharging requirements to non-intelligent charging parking spaces, and guide electric vehicles with charging and discharging requirements to intelligent charging parking spaces for charging and discharging.

10. The optimization scheduling method for integrating electric vehicle charging and discharging into a building system according to claim 1, characterized in that: The importance random sampling method is used to sample the time data of N electric vehicles entering / driving out of the building system, and the time distribution of electric vehicles entering / driving out is quantified. The number of electric vehicles entering / driving out of the building system in each time period is converted into the probability value of the electric vehicle arriving at the building system in the time period. Finally, the standard normal distribution curve is used for fitting, and then the time of each electric vehicle entering / driving out of the building system on weekdays is determined by sampling. The collected data of electric vehicles participating in V2G staying all day are calculated using the arithmetic mean method to determine the number of electric vehicles staying in V2G all day.

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