Charging station voltage control method and system based on vehicle-network cooperation

Abstract

The invention discloses a charging station voltage control method and system based on vehicle-network cooperation. The method comprises the steps that the charging demand and charging parameter information of a to-be-dispatched electric vehicle are acquired; obtaining operation data of the power distribution network and load information of a charging station which is accessed to the power distribution network and is closest to the to-be-dispatched electric vehicle; calculating the charging waiting time of the to-be-dispatched electric vehicle and the voltage change condition of each charging station, and selecting the charging station according to the charging waiting time of the to-be-dispatched electric vehicle and the voltage change condition of the charging station; an electric vehicle to be dispatched enters the selected charging station to be charged, and an optimization control model with the comprehensive minimum power distribution network node voltage deviation and reactive compensation as the target is constructed; and in the charging process, according to the voltage deviation of the charging station, the voltage of the charging station is adjusted in a reactive compensation adjustment or active compensation and reactive compensation combined adjustment mode in combination with the optimal control model. The charging requirement of the electric vehicle can be met, and meanwhile the requirement for safe and stable operation of a power grid is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-grid collaborative dispatching control, and more specifically, to a charging station voltage control method and system based on vehicle-grid collaboration. Background Art

[0002] Against the backdrop of the current global energy transition, electric vehicles (EVs), as a crucial component of green mobility, are rapidly gaining popularity. This trend not only promotes energy conservation and emission reduction in the transportation sector, but also presents new challenges and opportunities for the power system.

[0003] The disorderly connection of large numbers of electric vehicles to the grid for charging, especially during peak hours, can lead to surges in local grid loads, causing voltage fluctuations and even voltage overshoots. The randomness and uncertainty of electric vehicle charging behavior further complicates distribution network operation and management. When a large number of electric vehicles are connected to the grid for charging simultaneously, localized line overloads and transformer overheating can occur, leading to voltage drops and impacting the electricity consumption of other users. Furthermore, predicting electric vehicle charging loads is further complicated by differences in driving habits, charging preferences, and battery capacity among different vehicle owners. This uncertainty not only complicates grid scheduling but, in extreme cases, can also increase the risk of voltage collapse.

[0004] In the existing technology, the charging planning method for charging vehicles usually solves the electric vehicle charging planning problem from the perspective of optimizing objective functions such as electric vehicle charging costs. There is a lack of consideration for distribution network voltage control and scheduling electric vehicles to participate in solving the distribution network voltage control problem. Summary of the Invention

[0005] To address the deficiencies in the prior art, the present invention provides a charging station voltage control method based on vehicle-grid collaboration, which is used to coordinate the relationship between electric vehicles and the power grid, avoid voltage fluctuations or over-limit problems caused by electric vehicle charging, ensure that the grid voltage is within a safe and reliable range, and at the same time improve the efficiency and convenience of electric vehicle charging.

[0006] The present invention adopts the following technical solutions.

[0007] Obtain the charging requirements and charging parameter information of the electric vehicles to be dispatched;

[0008] Obtain distribution network operation data and load information of the charging station connected to the distribution network and closest to the electric vehicle to be dispatched;

[0009] Based on the charging demand, charging parameter information, distribution network operation data and charging station load information of the electric vehicles to be dispatched, the charging waiting time of the electric vehicles to be dispatched and the voltage changes of each charging station are calculated, and the charging station is selected according to the charging waiting time of the electric vehicles to be dispatched and the voltage changes of the charging stations;

[0010] The electric vehicles to be dispatched enter the selected charging station for charging, and an optimization control model is constructed with the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes;

[0011] During the charging process, the voltage of the charging station is adjusted according to the voltage deviation of the charging station in combination with the optimization control model, using reactive compensation adjustment or a combination of active compensation and reactive compensation.

[0012] Preferably, obtaining the charging demand of the vehicle to be dispatched includes: after the electric vehicle to be dispatched sends a charging request to the vehicle network coordination center through the vehicle network, the vehicle network coordination center obtains the power demand of the electric vehicle to be dispatched;

[0013] The charging parameter information of the vehicle to be dispatched includes the charging rated power and geographic coordinates.

[0014] Preferably, the distribution network operation data includes the rated voltage, rated current, actual voltage, actual current, active power, and reactive power of the regional distribution network;

[0015] The load information of the charging station includes the working status of each charging pile and the queuing status of electric vehicles.

[0016] Preferably, the charging station is selected according to the charging waiting time of the electric vehicle to be scheduled and the voltage change of the charging station, specifically including:

[0017] Calculate the charging waiting time of the scheduled vehicles at different charging stations, sort them from smallest to largest, and select the charging stations in the top N positions;

[0018] According to the rated charging power of the vehicle to be dispatched, the output power of N charging stations, the active power and reactive power of the distribution network are used in turn, and simulation calculations are performed based on the power balance equation to obtain the voltage change of each charging station. The charging station with the smallest voltage change is selected as the charging station for the electric vehicle to be dispatched.

[0019] Preferably, the charging waiting time of the scheduled vehicle at different charging stations is calculated as follows:

[0020] The charging waiting time of the electric vehicle to be dispatched includes the time it takes for the electric vehicle to be dispatched to travel to the charging station and the waiting time after arriving at the station; the time it takes for the electric vehicle to be dispatched to travel to the charging station is calculated based on the distance and average speed.

[0021] The calculation of waiting time after arrival includes:

[0022] If there is an idle charging pile in the charging station, the waiting time after arriving at the station is 0;

[0023] If there is no idle charging pile in the charging station, the time it takes for the electric vehicle currently charging in the charging station to complete charging is calculated, and the shortest time is selected as the waiting time after arriving at the station. The time it takes for the electric vehicle currently charging to complete charging, T c The calculation formula is as follows:

[0024]

[0025] Among them, B total is the battery capacity, B soc is the percentage of remaining battery power, P c is the actual charging power, and θ is the charging efficiency.

[0026] Preferably, the optimized control model is as follows:

[0027]

[0028] in, is the voltage deviation of the i-th charging station, n is the total number of charging stations in the distribution network, is the reactive output of the i-th charging station, α and β are the first and second weight coefficients respectively.

[0029] Preferably, based on the voltage deviation of the charging station and in combination with the optimization control model, a reactive compensation adjustment method or an adjustment method combining active compensation and reactive compensation is adopted to control the voltage of the charging station, specifically including:

[0030] When the voltage deviation of the i-th charging station in the distribution network is ΔV i Satisfy |ΔV i When |≤5%, the voltage of the charging station is controlled by the reactive compensation adjustment method;

[0031] When the voltage deviation of the i-th charging station in the distribution network is ΔV i Satisfy |ΔV i When |>5%, the voltage of the charging station is controlled by combining reactive compensation and active compensation.

[0032] Preferably, the reactive power compensation adjustment method specifically includes:

[0033] Reactive power distribution is performed based on the sensitivity coefficient. The reactive power output Q of the mth electric vehicle in the charging station is ev,m for:

[0034]

[0035] Among them, Q z Indicates the maximum reactive compensation amount, K v,z,m K represents the sensitivity coefficient of the mth electric vehicle in charging station Z to charging station Z; v,z It represents the sensitivity coefficient of charging station Z to the distribution network. The calculation formula of the sensitivity coefficient is as follows:

[0036]

[0037] Among them, V z Represents the voltage of charging station Z, V z,m represents the charging voltage of the mth electric vehicle in the charging station Z.

[0038] Preferably, the active power compensation includes dynamically adjusting the active power of the charging pile according to the operating load information of the distribution network and the status information of the charging electric vehicle, including:

[0039] When the voltage is lower than the lower limit of the voltage fluctuation range, the charging power adjustment formula of the charging pile is as follows:

[0040] P c‘ =P c (1-ΔV)

[0041] When the voltage is higher than the upper limit of the voltage fluctuation range, the charging power adjustment formula of the charging pile is as follows:

[0042] P c‘ =P c (1+ΔV)

[0043] Among them, P c‘ is the adjusted charging power, P c is the actual charging power, Δu is the voltage deviation scale, and satisfies V e is the rated voltage of the charging pile, V fa is the actual voltage value of the charging pile.

[0044] The present invention also proposes a charging station voltage control system based on vehicle-grid collaboration, which is used to implement the charging station voltage control method based on vehicle-grid collaboration, including: a data acquisition module, a charging pile selection module, a model construction module and an adjustment module;

[0045] The data acquisition module is used to obtain the charging requirements of the vehicles to be dispatched and their charging-related parameter information, as well as the distribution network operation data and the load information of the charging stations connected to the distribution network;

[0046] The charging pile selection module is used to calculate the charging waiting time of the electric vehicles to be dispatched and the voltage changes of each charging station based on the charging demand, charging parameter information, operation data of the distribution network and load information of the charging station, and select the charging station according to the charging waiting time of the electric vehicles to be dispatched and the voltage changes of the charging stations;

[0047] The model building module is used to build an optimization control model based on the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes;

[0048] The regulation module is used to regulate the voltage of the charging station during the charging process according to the voltage deviation of the charging station in combination with the optimization control model, using reactive compensation regulation or a combination of active compensation and reactive compensation.

[0049] The present invention also provides a terminal, comprising a processor and a storage medium;

[0050] The storage medium is used to store instructions;

[0051] The processor is used to operate according to the instructions to execute the steps of the charging station voltage control method based on vehicle-grid collaboration.

[0052] The present invention also proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the charging station voltage control method based on vehicle-grid collaboration are implemented.

[0053] The beneficial effects of the present invention are that, compared with existing technologies, the present invention studies the impact of large-scale electric vehicle access on grid voltage and its effective management strategy. By comprehensively considering factors such as the characteristics of electric vehicle charging behavior, the operating status of the grid, and user needs, it provides a vehicle-grid coordinated charging scheduling method based on voltage stability to meet the charging needs of electric vehicles while ensuring the safe and stable operation of the grid. The present invention has at least the following technical effects:

[0054] 1. The present invention avoids local overloads through intelligent scheduling of the electric vehicle charging process, utilizes vehicle-grid collaborative technology to reduce damage to grid equipment, and improves the overall efficiency of the charging process and the utilization rate of power resources.

[0055] 2. The present invention adjusts the charging power of electric vehicles based on the dynamic relative proportion adjustment method according to the actual load level and voltage level of the power grid, thereby improving voltage stability. At the same time, the present invention dispatches electric vehicles to participate in the reactive power supplement of the power grid to stabilize the voltage, thereby controlling the voltage fluctuation or over-limit problem caused by the charging of electric vehicles, and ensuring that the power grid voltage is within a safe and reliable range. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1This is a flow chart of the vehicle-grid collaborative charging scheduling method based on voltage stability in the present invention;

[0057] Figure 2 This is a calculation flow chart for selecting a charging pile in the present invention;

[0058] Figure 3 It is the overall block diagram of system data integration in the present invention;

[0059] Figure 4 It is a structural diagram of the vehicle-grid collaborative charging scheduling system based on voltage stability in the present invention. DETAILED DESCRIPTION

[0060] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without making creative efforts are all within the scope of protection of the present invention.

[0061] As attached Figure 1 As shown, the present invention proposes a charging station voltage control method based on vehicle-grid collaboration, which includes the following steps:

[0062] Step 1: Obtain the charging demand information and charging-related parameter information of the vehicle to be dispatched;

[0063] Among them, the information on electric vehicle charging demand and charging-related parameters obtained based on the Internet of Vehicles system mainly includes:

[0064] The electric vehicle sends a charging request to the vehicle network coordination center through the vehicle network system. At this time, the electric vehicle is used as a dispatched vehicle and uploads the charging parameter information of the dispatched vehicle. The charging parameter information includes the charging rated power, geographical coordinates, and vehicle license plate of the dispatched vehicle. Figure 3 shown.

[0065] Step 2: Obtain the voltage, current, active power, and reactive power operation data of the regional distribution network and the load information of the charging stations connected to the distribution network;

[0066] Furthermore, the voltage, current, active power and reactive power operation data of the regional distribution network and the current, voltage and power (including active power and reactive power) of each charging pile in the charging station connected to the distribution network are obtained, mainly including:

[0067] 1) Obtain equipment records and electrical topology information of each distribution network in the region through the power grid resource center system to monitor the operating data of distribution network equipment (current, voltage, power information) and assist in calculating the distribution network flow;

[0068] 2) Obtain the voltage, current, active power, reactive power grid operation data of each node of each distribution network in the region through the distribution automation system;

[0069] 3) Obtain information about charging stations and power current, voltage, and power (including active power and reactive power) through the electricity consumption information collection system and customer service center;

[0070] 4) Obtain the working status, charging power, and queue status of electric vehicles at each charging station through the customer's self-built system.

[0071] Step 3: Based on the charging demand, charging parameter information, distribution network operation data, and charging station load information of the electric vehicles to be dispatched, the charging waiting time of the electric vehicles to be dispatched and the voltage change of each charging station are calculated, and the charging station is selected according to the charging waiting time of the electric vehicles to be dispatched and the voltage change of the charging station;

[0072] like Figure 2 As shown in the figure, based on the charging demand of electric vehicles and the operation data of the distribution network, the voltage stability constraint of the charging station is considered to generate a charging plan for electric vehicles and guide the charging of electric vehicles;

[0073] Based on the charging needs and geographical location of the electric vehicle, the travel time to the nearest charging station can be calculated, with the goal of taking into account the travel time and queue situation of each charging station and simulating the minimum voltage fluctuation during charging.

[0074] The present invention proposes a fast decision-making algorithm to solve the electric vehicle charging plan. The fast decision-making algorithm is a two-stage optimal solution matching algorithm, including two stages: the electric vehicle charging waiting time and the minimum average change of the grid voltage.

[0075] Specifically, the charging stations selected based on the charging waiting time of the electric vehicles to be dispatched and the voltage change of the charging stations include:

[0076] Calculate the charging waiting time of the electric vehicles to be dispatched, obtain the charging waiting time of the vehicles to be dispatched at different charging stations, sort them from small to large, and select the set of N charging stations with the shortest charging waiting time;

[0077] According to the rated charging power of the vehicle to be dispatched, the output power of N charging stations, the active power and reactive power of the distribution network are used in turn, and simulation calculations are performed based on the power balance equation to obtain the voltage change of each charging station. The charging station with the smallest voltage change is selected as the charging station for the electric vehicle to be dispatched.

[0078] The charging waiting time is calculated as follows:

[0079] The charging waiting time of the electric vehicle to be dispatched includes the time it takes for the electric vehicle to travel to the charging station and the waiting time after arriving at the station. It is calculated based on the geographical location parameters uploaded by the electric vehicle to be dispatched, the location of the nearby charging stations, and the charging status of the charging piles in the charging station. The charging waiting time T total The calculation formula is as follows:

[0080] T total =T drive +T wait

[0081] Among them, T drive The time it takes for a car to travel to a charging station is usually calculated based on the distance and average speed. wait Waiting time after arrival at the station;

[0082] The calculation of waiting time after arrival includes:

[0083] If there is an idle charging pile in the charging station, the waiting time after arriving at the station is T wait is 0;

[0084] If there is no idle charging pile in the charging station, the time it takes for the electric vehicle currently charging in the charging station to complete charging is calculated, and the shortest time is selected as the waiting time after arriving at the station. The time it takes for the electric vehicle currently charging to complete charging, T c The calculation formula is as follows:

[0085]

[0086] Among them, T c The time (hours) to complete charging of the electric vehicle being charged, B total is the battery capacity (kWh), B soc is the percentage of remaining battery power, P c is the charging power (kW), θ is the charging efficiency, usually 0.85-0.95. Select the smallest T in the charging station c As the waiting time after arrival T wait .

[0087] The result set of charging waiting time of electric vehicles at all charging stations in the area is calculated and sorted from small to large according to waiting time. Usually, the result set retains the 5 candidate results with the shortest waiting time.

[0088] Furthermore, the voltage variation of each charging station is simulated and calculated based on the balance equation of the output power of the charging station group, the active power and reactive power of the distribution network, including:

[0089] According to the charging power of the electric vehicle to be dispatched, the output power of each charging station in the set is calculated, and the active power P is calculated.i and reactive power Q i The balance equation is simulated to calculate the voltage change of each node, and the charging station with the smallest average voltage change is selected.

[0090] Furthermore, the active power P i and reactive power Q i The equilibrium equation is calculated as follows:

[0091] The distribution network power flow is calculated based on the equipment inventory and electrical topology information of the distribution network. Each charging station in the distribution network is regarded as a node of the distribution network. Based on the electrical topology information of the distribution network and the operating data of each distribution network equipment, each node i in the distribution network is analyzed to construct the balance equation of the active power Pi and reactive power Qi of each node in the distribution network as follows:

[0092]

[0093] Among them, V i and V j is the voltage amplitude at nodes i and j, θ ij is the voltage phase angle difference between nodes i and j, G ij and B ij are the real and imaginary parts of the elements in the node admittance matrix.

[0094] In the calculation, the voltage is usually obtained by iteratively solving the power balance equation and the given initial voltage value. The voltage equation can be expressed as:

[0095]

[0096] Among them, V i is the voltage at node i, i ij is the complex current flowing in branch ij, Z ij is the complex impedance of branch ij. The number and amplitude of voltage fluctuations are constrained for different distribution networks, typically between -7% and +7% of the rated voltage. This means that their lower and upper limits are typically 0.93 and 1.07 times the grid reference voltage, respectively.

[0097] Finally, the reasonable charging waiting time and the selected charging station for electric vehicles are obtained. When there are multiple electric vehicles for dispatch, they are calculated in sequence according to the access order, and the dispatched electric vehicles are used as known conditions to participate in the simulation calculation.

[0098] Step 4: The electric vehicles to be dispatched enter the selected charging station for charging, and an optimization control model is constructed with the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes;

[0099] Among them, the optimization control model with the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes is constructed as follows:

[0100]

[0101] in, is the voltage deviation of the ith node, n is the total number of nodes, is the reactive output of node i, α and β are the first weight coefficient and the second weight coefficient respectively. The values of the weight coefficients are different in different situations.

[0102] The smaller the voltage deviation, the more stable the system voltage is and the closer it is to the rated value.

[0103] Among them, the voltage deviation constraint is: |ΔV i |<7%. In power systems, voltage must be maintained within a certain range to ensure the normal operation of electrical equipment. The absolute value of voltage deviation at each node is required to not exceed 7% to ensure system voltage quality. Excessive voltage deviation can cause equipment damage, reduced efficiency, and other problems.

[0104] During the charging process, the reactive capacity constraint of the electric vehicle satisfies: Q ev,min ≤Q ev,m ≤Q ev,max The reactive power output capacity of each electric vehicle is limited, Q ev,min and Q ev,max are the lower limit and upper limit of the reactive power output of the mth electric vehicle respectively.

[0105] The SOC constraints of electric vehicles are as follows:

[0106] SOC m ≥SOC min

[0107] SOC m is the battery state of charge (SOC) of the mth electric vehicle min The minimum state of charge allowed for the battery. This constraint takes into account that the electric vehicle cannot consume excessive battery power when performing reactive power support.

[0108] Among them, the balance constraints of active power Pi and reactive power Qi of each charging station node in the distribution network are as follows:

[0109]

[0110] Among them, V i and V j is the voltage amplitude at nodes i and j, θ ij is the voltage phase angle difference between nodes i and j, Gij and B ij are the real and imaginary parts of the elements in the node admittance matrix.

[0111] Step 5: During the charging process, the voltage of the charging station is adjusted according to the voltage deviation of the charging station in combination with the optimization control model, using reactive compensation adjustment or a combination of active compensation and reactive compensation.

[0112] When the voltage deviation of the i-th charging station in the distribution network is ΔV i Satisfy |ΔV i When |≤5%, reactive power compensation is used to regulate the voltage, as follows:

[0113] Set α and β to 0.4 and 0.6 respectively, the voltage stability weight coefficient is relatively small, and the optimized control model is:

[0114]

[0115] The optimal values of charging voltage and reactive compensation are obtained by calculating through multi-objective optimization algorithms, preferably particle swarm optimization, genetic optimization and other methods.

[0116] Furthermore, the sensitivity coefficient of each electric vehicle is calculated and normalized, and then multiplied by the maximum reactive compensation allowed by the charging station Q z , the reactive power output of each electric vehicle in the charging station can be obtained after adjustment, and the reactive power task can be reasonably distributed according to the voltage regulation ability of each electric vehicle, thereby achieving the economy of reactive power regulation under the premise of ensuring voltage stability.

[0117] Specifically, the reactive output Q of the mth electric vehicle being charged in the charging station is ev,m for:

[0118]

[0119] Among them, K v,z,m K represents the sensitivity coefficient of the mth electric vehicle in charging station Z to charging station Z; v,z represents the sensitivity coefficient of charging station Z to the distribution network, Q z Indicates the maximum reactive compensation amount.

[0120] The sensitivity coefficient indicates the influence of reactive output on voltage. The sensitivity coefficient K of charging station Z to distribution network is v,z The calculation formula is as follows:

[0121]

[0122] Among them, V z Represents the voltage of node Z in the charging station, V z,mDenote the charging voltage of the mth electric vehicle in the charging station Z, and obtain the optimal values of the charging voltage and reactive power compensation.

[0123] When the voltage deviation of the i-th charging station node in the distribution network is ΔV i Satisfy |ΔV i When |>5%, the voltage is adjusted by combining reactive power compensation and active power compensation, as follows:

[0124] Set α and β to 0.6 and 0.4 respectively. The optimal control model is:

[0125]

[0126] Furthermore, calculation is performed through a multi-objective optimization algorithm, preferably a particle swarm optimization, a genetic algorithm optimization, or the like.

[0127] Reactive power compensation is calculated according to the above method.

[0128] The calculation of active power compensation is as follows:

[0129] Dynamically adjust the active power of the charging pile based on the distribution network operating load information and the status information of the charging electric vehicle, specifically including:

[0130] Based on the real-time operating status data of the distribution network and the voltage conditions of the charging station, the charging power of each charging pile is dynamically adjusted based on the grid load and voltage fluctuations.

[0131] Furthermore, a voltage fluctuation range is set. When the voltage is lower than the lower limit of the voltage fluctuation range, the charging power of the charging pile is reduced to prevent the voltage from continuing to drop; when the voltage is higher than the upper limit of the voltage fluctuation range, the charging power of the charging pile is increased to absorb excess reactive power, thereby reducing the voltage.

[0132] Furthermore, when the voltage is lower than the lower limit of the voltage fluctuation range, the charging power adjustment formula of the charging pile is as follows:

[0133] P c‘ =P c (1-ΔV)

[0134] When the voltage is higher than the upper limit of the voltage fluctuation range, the charging power adjustment formula of the charging pile is as follows:

[0135] P c‘ =P c (1+ΔV)

[0136] Among them, P c‘ is the adjusted charging power, P c is the actual charging power, ΔV is the voltage deviation from the scale, and satisfies Ve Indicates rated voltage, V fa is the actual voltage value collected.

[0137] like Figure 4 As shown, the present invention also proposes a charging station voltage control system based on vehicle-grid collaboration, which is used to implement the above-mentioned charging station voltage control method based on vehicle-grid collaboration. The system specifically includes: a data acquisition module, a charging pile selection module, a model construction module and an adjustment module;

[0138] The data acquisition module is used to obtain the charging requirements of the vehicles to be dispatched and their charging-related parameter information, as well as the distribution network operation data and the load information of the charging stations connected to the distribution network;

[0139] The charging pile selection module is used to calculate the charging waiting time of the electric vehicles to be dispatched and the voltage changes of each charging station based on the charging demand, charging parameter information, operation data of the distribution network and load information of the charging station, and select the charging station according to the charging waiting time of the electric vehicles to be dispatched and the voltage changes of the charging stations;

[0140] The model building module is used to build an optimization control model based on the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes;

[0141] The regulation module is used to regulate the voltage of the charging station during the charging process according to the voltage deviation of the charging station in combination with the optimization control model, using reactive compensation regulation or a combination of active compensation and reactive compensation.

[0142] The beneficial effect of the present invention is that, compared with the existing technology, the present invention provides a vehicle-grid collaborative charging scheduling method based on voltage stability by comprehensively considering factors such as the characteristics of electric vehicle charging behavior, the operating status of the power grid and user needs, so as to meet the charging needs of electric vehicles and ensure the safe and stable operation of the power grid.

[0143] The present disclosure may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0144] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0145] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0146] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, and conventional procedural programming languages such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., utilizing an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions. The electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A charging station voltage control method based on vehicle-grid collaboration, characterized in that: The steps include: Obtain the charging requirements and charging parameter information of the electric vehicles to be dispatched; Obtain distribution network operation data and load information of the charging station connected to the distribution network and closest to the electric vehicle to be dispatched; Based on the charging demand, charging parameter information, distribution network operation data and charging station load information of the electric vehicles to be dispatched, the charging waiting time of the electric vehicles to be dispatched and the voltage changes of each charging station are calculated, and the charging station is selected according to the charging waiting time of the electric vehicles to be dispatched and the voltage changes of the charging stations; The electric vehicles to be dispatched enter the selected charging station for charging, and an optimization control model is constructed with the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes; During the charging process, the voltage of the charging station is adjusted according to the voltage deviation of the charging station in combination with the optimization control model, using reactive compensation adjustment or a combination of active compensation and reactive compensation.

2. The charging station voltage control method based on vehicle-grid collaboration according to claim 1 is characterized in that: Obtaining the charging demand of the vehicle to be dispatched includes: after the electric vehicle to be dispatched sends a charging request to the vehicle network collaboration center through the vehicle network, the vehicle network collaboration center obtains the power demand of the electric vehicle to be dispatched; The charging parameter information of the vehicle to be dispatched includes the charging rated power and geographic coordinates.

3. The charging station voltage control method based on vehicle-grid collaboration according to claim 1 is characterized in that: Distribution network operation data includes the rated voltage, rated current, actual voltage, actual current, active power, and reactive power of the regional distribution network; The load information of the charging station includes the working status of each charging pile and the queuing status of electric vehicles.

4. The charging station voltage control method based on vehicle-grid collaboration according to claim 3 is characterized in that: The charging stations to be selected based on the charging waiting time of the electric vehicles to be dispatched and the voltage changes of the charging stations include: Calculate the charging waiting time of the scheduled vehicles at different charging stations, sort them from smallest to largest, and select the charging stations in the top N positions; According to the rated charging power of the vehicle to be dispatched, the output power of N charging stations, the active power and reactive power of the distribution network are used in turn, and simulation calculations are performed based on the power balance equation to obtain the voltage change of each charging station. The charging station with the smallest voltage change is selected as the charging station for the electric vehicle to be dispatched.

5. The charging station voltage control method based on vehicle-grid collaboration according to claim 4 is characterized in that: Calculate the charging waiting time of the dispatched vehicle at different charging stations as follows: The charging waiting time of the electric vehicle to be dispatched includes the time it takes for the electric vehicle to be dispatched to travel to the charging station and the waiting time after arriving at the station; the time it takes for the electric vehicle to be dispatched to travel to the charging station is calculated based on the distance and average speed. The calculation of waiting time after arrival includes: If there is an idle charging pile in the charging station, the waiting time after arriving at the station is 0; If there is no idle charging pile in the charging station, the time it takes for the electric vehicle currently charging in the charging station to complete charging is calculated, and the shortest time is selected as the waiting time after arriving at the station. The time it takes for the electric vehicle currently charging to complete charging, T c The calculation formula is as follows: Among them, B total is the battery capacity, B soc is the percentage of remaining battery power, P c is the actual charging power, and θ is the charging efficiency.

6. The charging station voltage control method based on vehicle-grid collaboration according to claim 1, characterized in that: The optimized control model is as follows: in, is the voltage deviation of the i-th charging station, n is the total number of charging stations in the distribution network, is the reactive output of the i-th charging station, α and β are the first and second weight coefficients respectively.

7. The charging station voltage control method based on vehicle-grid collaboration according to claim 1, characterized in that: Based on the voltage deviation of the charging station and combined with the optimization control model, the voltage of the charging station is controlled by adopting a reactive compensation adjustment method or a combination of active and reactive compensation. Specifically, the following methods are included: When the voltage deviation of the i-th charging station in the distribution network is ΔV i Satisfy |ΔV i When |≤5%, the voltage of the charging station is controlled by the reactive compensation adjustment method; When the voltage deviation of the i-th charging station in the distribution network is ΔV i Satisfy |ΔV i When |>5%, the voltage of the charging station is controlled by combining reactive compensation and active compensation.

8. The charging station voltage control method based on vehicle-grid collaboration according to claim 7 is characterized in that: The specific adjustment methods of reactive power compensation include: Reactive power distribution is performed based on the sensitivity coefficient. The reactive power output Q of the mth electric vehicle in the charging station is ev,m for: Among them, Q z Indicates the maximum reactive compensation amount, K v,z,m K represents the sensitivity coefficient of the mth electric vehicle in charging station Z to charging station Z; v,z It represents the sensitivity coefficient of charging station Z to the distribution network. The calculation formula of the sensitivity coefficient is as follows: Among them, V z Represents the voltage of charging station Z, V z,m represents the charging voltage of the mth electric vehicle in the charging station Z.

9. The charging station voltage control method based on vehicle-grid collaboration according to claim 8, characterized in that: Active power compensation involves dynamically adjusting the active power of the charging pile based on the distribution network's operating load information and the status information of the charging electric vehicle, including: When the voltage is lower than the lower limit of the voltage fluctuation range, the charging power adjustment formula of the charging pile is as follows: P c‘ =P c (1-ΔV) When the voltage is higher than the upper limit of the voltage fluctuation range, the charging power adjustment formula of the charging pile is as follows: P c‘ =P c (1+ΔV) Among them, P c‘ is the adjusted charging power, P c is the actual charging power, ΔV is the voltage deviation from the scale, and satisfies V e is the rated voltage of the charging pile, V fa is the actual voltage value of the charging pile.

10. A charging station voltage control system based on vehicle-grid collaboration, used to implement the charging station voltage control method based on vehicle-grid collaboration according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, charging pile selection module, model building module and adjustment module; The data acquisition module is used to obtain the charging requirements of the vehicles to be dispatched and their charging-related parameter information, as well as the distribution network operation data and the load information of the charging stations connected to the distribution network; The charging pile selection module is used to calculate the charging waiting time of the electric vehicles to be dispatched and the voltage changes of each charging station based on the charging demand, charging parameter information, operation data of the distribution network and load information of the charging station, and select the charging station according to the charging waiting time of the electric vehicles to be dispatched and the voltage changes of the charging stations; The model building module is used to build an optimization control model based on the goal of minimizing the voltage deviation and reactive power compensation of the distribution network nodes; The regulation module is used to regulate the voltage of the charging station during the charging process according to the voltage deviation of the charging station in combination with the optimization control model, using reactive compensation regulation or a combination of active compensation and reactive compensation.

11. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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