A distribution network voltage regulation system and method based on electric driverless vehicles and V2G technology

Abstract

The present invention proposes a distribution network voltage regulation system and method based on electric driverless vehicles and V2G technology, which can alleviate overvoltage and undervoltage problems by allocating EAVs at appropriate charging facilities and adjusting the power exchange between charging facilities and the power grid. Simulation results show that the method of the present invention can effectively suppress voltage overlimit problems in distribution network systems with high renewable energy penetration.

Description

Technical Field

[0001] The present invention belongs to the field of power grid technology, and specifically relates to the field of vehicle-to-grid (V2G) technology, as well as a system and method for regulating the voltage of a distribution network by coordinating the charging, discharging and parking plans of electric driverless vehicles. Background Art

[0002] At present, the proportion of renewable energy sources (RESs) in the power system is increasing. Due to the large variation of its power generation over time, it causes voltage fluctuations and low power quality in the distribution network, affecting the safe and stable operation of the power grid. Traditional countermeasures include upgrading distribution lines, adding protection equipment, and using on-load tap changers and distributed generator inverters in substations for voltage regulation. However, these measures are not economical and their operational flexibility is also greatly limited.

[0003] Nowadays, electric vehicles are used as a means of controlling voltage. The onboard battery of an electric vehicle can be used as a distributed energy storage unit. When the onboard battery needs to be charged, the electricity flows from the power grid to the vehicle; when the electric vehicle is parked and not in use, the electricity of the onboard battery can be sold to the power grid, and the electricity flows from the vehicle to the power grid, that is, V2G. By adjusting the charging strategy and connection time of electric vehicles, the impact of renewable energy on the power grid can be mitigated, and voltage fluctuations can be reduced, thereby obtaining higher power quality at a lower cost. However, the parking plan of electric vehicles is currently determined by the driver and is not subject to unified scheduling.

[0004] Compared with ordinary electric vehicles, electric autonomous vehicles (EAVs) have the advantage of good controllability. The control center can remotely dispatch EAVs to park at appropriate parking facilities to support V2G services. In previous studies, EAVs can only park at pre-set parking facilities and cannot change parking locations, which affects the flexibility of V2G services. In addition, existing technologies only consider the number of vehicles as an indicator of V2G services, without considering V2G power exchange and its impact on voltage. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a distribution network voltage regulation system based on electric driverless vehicles and V2G technology, including: a distribution network system, multiple EAVs, a control center and multiple electric vehicle charging stations, wherein:

[0006] The power distribution network system includes a plurality of nodes connected to the plurality of electric vehicle charging stations;

[0007] The multiple electric vehicle charging stations are connected via a road network to provide V2G services and charge or discharge the multiple EAVs;

[0008] The control center receives the travel plan of the EAV and controls the charging, discharging and parking plans of the plurality of EAVs according to the operating parameters of the distribution network system, the battery status and travel plan of the EAV and the information of the electric vehicle charging station;

[0009] The EAV receives control from the control center and executes the charging, discharging and parking plan.

[0010] Preferably, the distribution network system is connected to a renewable energy power station.

[0011] Preferably, the control center controls the charging, discharging and parking plans of the multiple EAVs according to the number of EAVs, the battery capacity and charging and discharging power of each EAV, the parameters of the renewable energy power station, the location information of multiple electric vehicle charging stations, and the connection status between the nodes and the electric vehicle charging stations.

[0012] Preferably, the control center controls the charging, discharging and parking plan of the EAV in different time periods.

[0013] Preferably, the control center also controls the EAV to charge at a designated electric vehicle charging station within a designated time period.

[0014] Preferably, the control center also controls the EAV to discharge at a designated electric vehicle charging station within a designated time period.

[0015] Preferably, the control center also controls the EAV to leave the current electric vehicle charging station and go to the next electric vehicle charging station within a specified time period, so that it obtains active power at different nodes.

[0016] According to another aspect of the present invention, there is provided a method for the above system, comprising:

[0017] Step 1, the control center receives the driving plan of the EAV;

[0018] Step 2, the control center optimizes the EAV charging, discharging and parking plan according to the power supply information of the node, the battery status and driving plan of the EAV and the information of the electric vehicle charging station according to the optimization method;

[0019] Step 3, the control center sends the parking and charging and discharging plan to the EAV;

[0020] Step 4: The EAV receives and executes the charging, discharging and parking plan.

[0021] Preferably, the charging, discharging and parking plan includes moving the EAV from one electric vehicle charging station to another electric vehicle charging station so that it obtains active power from different nodes to perform voltage regulation.

[0022] Preferably, the optimization method includes controlling the voltage of the node within a specified range, with a lower voltage limit of 0.95pu and an upper voltage limit of 1.05pu.

[0023] Preferably, the charging, discharging and parking plan includes optimization according to the following formula:

[0024]

[0025] in,

[0026] k represents each EAV, Represents a collection of EAVs that can be used for parking coordination;

[0027] t represents the tth period, It is a collection of multiple time periods divided into horizontal time periods;

[0028] i represents the i-th node, Represents a collection of nodes;

[0029] f represents an electric vehicle charging station, represents a collection of electric vehicle charging stations;

[0030] V i,t represents the voltage of node i at time t;

[0031] T represents the transposed matrix.

[0032] Preferably, the charging, discharging and parking plan includes optimization according to the following power flow constraints:

[0033]

[0034]

[0035]

[0036]

[0037]

[0038] in,

[0039] i represents a node;

[0040] t represents time;

[0041] P i+1,t and Q i+1,tRespectively represent the active power and reactive power of node i+1 at time t;

[0042] P i,t and Q i,t Respectively represent the active power and reactive power between node i and node i+1 at time t;

[0043] and represents the active load and RES injection of node i+1 at time t;

[0044] represents the total charging or discharging power of the EAV of node i;

[0045] Represents a collection of nodes;

[0046] Represents a set of time periods;

[0047] represents the load of node i+1 at time t;

[0048] represents the reactive power of the RES inverter of node i at time t;

[0049] and represents the active load and RES injection of node i at time t;

[0050] V i+1,t represents the voltage of node i+1 at time t;

[0051] V i,t represents the voltage of node i at time t;

[0052] r i Indicates line resistance;

[0053] x i Indicates line reactance;

[0054] V S Indicates the substation voltage;

[0055] S i represents the apparent power capacity allowed by the RES inverter at node i;

[0056] Indicates the power passing through the substation;

[0057] Indicates the lower limit of the power flowing through the substation;

[0058] Indicates the upper limit of the power flowing through the substation.

[0059] Preferably, the charging, discharging and parking plan includes optimizing such that the total charging or discharging power of the EAVs of the nodes is equal to the sum of the power injections of the EAVs at the corresponding parking facilities.

[0060] Preferably, the charging, discharging and parking plan includes optimization according to which the total charging and discharging power of the parking facility should not exceed the charging facility power limit.

[0061] Preferably, the charging, discharging and parking plan includes optimization in the following manner: when the EAV is parked, the change in SOC during the corresponding time period should be equal to the charging or discharging energy in the parking facility; when not parked, the change in SOC should be equal to the driving energy consumption.

[0062] Preferably, the charging, discharging and parking plan includes optimization according to the charging power, discharging power and driving power consumption rate of the EAV. For a parked EAV, the change of SOC is limited by the charging or discharging power limit. In other cases, the change of SOC is limited by the driving power consumption rate.

[0063] Preferably, the charging, discharging and parking plan includes optimizing each EAV so that it leaves a parking facility with sufficient SOC to ensure that it can reach the next parking facility.

[0064] Preferably, the optimization method adopts a standard MIQP solver for calculation, and the solver is a Gurobi optimizer.

[0065] According to yet another aspect of the present invention, there is further provided a computer-readable storage medium having a computer program stored thereon, wherein the program implements the steps according to the above method when executed by a processor.

[0066] According to another aspect of the present invention, there is provided a computer device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and wherein the processor implements the steps of the above method when executing the program.

[0067] By coordinating the charging, discharging and parking plan of EAVs, the overvoltage and undervoltage problems can be alleviated. At the same time, the present invention simulates the modified 15-node distribution network system, and the results show that the method of the present invention can effectively suppress the voltage over-limit problem in the distribution network system with high renewable energy penetration. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is an example of an operating method in one embodiment of the present invention.

[0069] Figure 2It is a schematic diagram of a modified 15-node power distribution network system used in the simulation of the present invention.

[0070] Figure 3 The simulation verification node voltage curve of the present invention when the EAV quantity is 0 is shown.

[0071] Figure 4 The simulation verification node voltage curve of the present invention when the EAV number is 20 is shown.

[0072] Figure 5 The simulation verification node voltage curve of the present invention when the EAV number is 50 is shown. DETAILED DESCRIPTION

[0073] The specific implementation of the present invention is described below in conjunction with the accompanying drawings and specific embodiments.

[0074] In order to clearly describe the implementation steps of the method, the structure of the system according to the present invention is first introduced.

[0075] According to one embodiment of the present invention, the system is composed of a power distribution network system, a road network, a plurality of EAVs, a control center and a plurality of electric vehicle charging stations. Each component is introduced below.

[0076] 1) Distribution network system

[0077] According to one embodiment of the present invention, the power distribution network system includes a node set and line collection For each node V i ,θ i Represent the voltage amplitude and phase angle respectively. (i,j) represents the line between node i and node j, And use r i and x iRepresents the resistance and reactance of line (i, j). Assume that node 1 is a substation with a voltage value of 1.0pu (pu represents the voltage per unit value). The node of the present invention is a concept in the circuit. The node is the intersection of the branch and obeys Kirchhoff's current law in the circuit calculation. Power system flow calculation belongs to circuit calculation. Power system flow calculation is to determine the calculation of steady-state operating state parameters of each part of the power system based on the given grid structure, parameters and operating conditions of components such as generators and loads. Usually the given operating conditions include the power of each power source and load point in the system, the hub voltage, the voltage and phase angle of the balance point. The operating state parameters to be calculated include the voltage amplitude and phase angle of each bus node of the power grid, the power distribution of each branch, the power loss of the network, etc. The nodes in the power system flow calculation are divided into three categories: PQ nodes, PV nodes, and balance nodes. In the present invention, the substation bus, the connection point of the charging station to the distribution network, and the connection point of the RESs to the distribution network are all nodes in the flow calculation.

[0078] 2) Road Network

[0079] The road network between EAV and parking facilities is represented by a directed graph Indicates that represents the designated location of parking facilities and EAVs. ε is the set of road segments connecting the designated locations. The road segment between locations m and n is represented by (m, n), (m, n)∈ε, d mn and μ mn denote the distance and travel time of the shortest path between locations m and n, respectively.

[0080] 3) Electric self-driving cars

[0081] A collection of EAVs that can be used for parking coordination k represents each EAV, By 8-tuple Specify, where

[0082] Each EAV k at time t k Request at location v k parking,

[0083] e k Indicates the battery energy storage state (State of charge, referred to as SOC), and specifies the time return And ensure that SOC is greater than or equal to SOC is used to reflect the remaining capacity of the battery. Its value is defined as the ratio of the remaining capacity to the battery capacity. Its value range is 0 to 1. When SOC = 0, it means that the battery is fully discharged, and when SOC = 1, it means that the battery is fully charged.

[0084] is the SOC set of EAV k, where e k，t is the SOC of EAV k at time t;

[0085] The control center or EAV can calculate EAV k from v k The time required to reach parking facility f and the time from v f arrive Average time, where v f is the position of f, Function α k According to the corresponding vehicle k parameter is defined as:

[0086]

[0087] in,

[0088] w k is k from v k Arrival f time;

[0089] is k from v f Back to time;

[0090] represents the set of times when EAV k moves from f to f′, where f′ represents other positions except f, i.e.

[0091] Indicates that from v f return When , SOC decreases by this value.

[0092] 4) Control Center

[0093] The control center is responsible for coordinating The charging, discharging and parking plan of the EAV in the control center. Parking requests and parking instructions can be transmitted between the control center and the EAV through advanced vehicle communication technologies such as IEEE 802.11p. Using the data collected from the EAV, calculations are performed in the control center, and instructions are issued from the control center to the EAV, instructing the EAV to charge, discharge and park.

[0094] 5) Parking facilities

[0095] The parking facility is an electric vehicle charging station, which is responsible for charging the battery of the electric vehicle or electric driverless car and controlling the discharge of the electric vehicle or electric driverless car to the power grid. Represents a group of parking facilities, each of which can support V2G services. By 5-tuple It indicates that,

[0096] v f represents the position of f, v f ∈v;

[0097] i represents the node where the electric vehicle charging station is connected to the power grid, where

[0098] ρ f represents the demand curve for f, in represents the power output of EAV at time t, which should meet the needs of V2G service at f;

[0099] and They respectively represent the maximum charge and discharge power allowed by f during EAV charge and discharge operations.

[0100] 6) Renewable energy and load model:

[0101] Preferably, a constant PQ model is used, and the renewable energy generator operates in maximum power point tracking (MPPT) and unity power factor mode. For simplicity, it is assumed that the forecast error of renewable energy output and load in the optimization period is negligible.

[0102] In the present invention, it is assumed that the EAV is entrusted to the control center to coordinate the parking scheduling of its idle time. The system works on a time-sharing basis, dividing time into multiple time periods {t=1,…,T} in the horizontal direction. In each time period, if the EAV is ready to park, it sends a request containing its attributes through the vehicle communication device. At time t = 0, the control center calculates The optimal charging, discharging and parking schedule for each period is calculated, where the optimization problem is introduced below. Then, the optimal schedule is assigned to the EAV. In addition, the system allows the EAV to be scheduled between parking facilities. In other words, the EAV can move from one parking facility to another and obtain active power from different nodes to achieve voltage regulation. Figure 1 The system and operation method of the present invention are described with reference to the examples.

[0103] exist Figure 1In the figure, at time t, an EAV prepares to park and arrives at f1 at t+1. It is available for V2G service and charging and discharging at time t+2. Different parking facilities require different numbers of vehicles to support V2G services, depending on the specific conditions of the parking facilities. The EAV is instructed to leave f1 at time t+3 and stop at f2 at time t+4 to meet the requirement at f2 at time t+5. Finally, the EAV leaves the parking facility at time t+6 and arrives at the designated location at t+7.

[0104] The inventors have found that in order to obtain the best voltage regulation effect, that is, to adjust the voltage to, for example, 1.0 pu as much as possible, the following objective function should be used to optimize the charging, discharging and parking of the EAV, taking into account the changes in renewable energy and load:

[0105]

[0106] The constraints are formulas (3)-(19)

[0107] Among them, V i,t represents the voltage of node i at time t.

[0108] This problem is a mixed integer quadratic programming (MIQP) problem, which can be solved by a standard MIQP solver, preferably by a Gurobi optimizer.

[0109] The constraints represented by equations (3)-(19) are described in detail below.

[0110] In the following constraints, two binary variables are used and

[0111] in,

[0112]

[0113]

[0114] In the prior art, the power flow in radial distribution networks is described by the linearized DistFlow formula, which is given in formulas (3)-(5). Other studies have pointed out that the power loss can be ignored compared with the line power flow.

[0115]

[0116]

[0117]

[0118]

[0119]

[0120] in,

[0121] i represents a node;

[0122] t represents time;

[0123] P i+1，t and Q i+1，t Respectively represent the active power and reactive power of node i+1 at time t;

[0124] P i，t and Q i，t Respectively represent the active power and reactive power between node i and node i+1 at time t;

[0125] and represents the active load and RES injection of node i+1 at time t;

[0126] represents the total charging or discharging power of the EAV of node i;

[0127] Represents a collection of nodes;

[0128] Represents a set of time periods;

[0129] represents the load of node i+1 at time t;

[0130] represents the reactive power of the RES inverter of node i at time t;

[0131] and represents the active load and RES injection of node i at time t;

[0132] V i+1，t represents the voltage of node i+1 at time t;

[0133] V i，t represents the voltage of node i at time t;

[0134] r i Indicates line resistance;

[0135] x i Indicates line reactance;

[0136] V S Indicates the substation voltage;

[0137] S i represents the apparent power capacity allowed by the RES inverter at node i;

[0138] Indicates the power passing through the substation;

[0139] Indicates the lower limit of the power flowing through the substation;

[0140] Indicates the upper limit of the power flowing through the substation;

[0141] Constraint (6) indicates that the reactive power output of the RES inverter is limited by its apparent power capacity and active power.

[0142] Constraint (7) represents the limits on the dispatch power flow and reverse power flow through the substation.

[0143] According to one embodiment of the present invention, all EAVs can be reallocated to support V2G services during the parking period specified by the user. The total charging / discharging power of the EAVs of node i is equal to the sum of the power injections of the EAVs at the corresponding parking facility f:

[0144]

[0145] in,

[0146] is the charging / discharging power of EAV k to the parking facility at time t.

[0147] The total charging and discharging power of the parking facility should not exceed the charging and discharging power limit, expressed as:

[0148]

[0149] If EAV k is not parked at time t, then is equal to zero. Therefore, if it is not parked at parking facility f, we can To limit its output power, expressed as:

[0150]

[0151] When the EAV is parked, the change in SOC during the corresponding time period should be equal to the charge / discharge energy in the parking facility. When not parked, the change in SOC should be equal to the driving energy consumption. This is equivalent to:

[0152]

[0153] Among them, W k is the driving power consumption rate of EAV k.

[0154] For a parked EAV, the change in SOC is limited by the charging or discharging power limit. In other cases, the change in SOC is limited by the driving power consumption rate, expressed as:

[0155]

[0156] Among them, R c and R d Represent the charging and discharging power limits of EAV respectively.

[0157] To meet user-specified requirements and from v f arrive The energy consumed, which must be ensured that each EAV has sufficient SOC when leaving the parking facility, is expressed as:

[0158]

[0159] For EAV k, it needs w k time period from the original location to the parking facility f, as described in formula (1). k arrives at f at time t, and before that, it should reserve w k The EAV k parking mode is determined by its user in t k Therefore, t k It should not be assigned or parked in any parking space before. The limit is zero to ensure that:

[0160]

[0161] Similarly, for the return trip, we can get the following formula: after k leaves f at time t, it should retain time period, and should be Return the vehicle to the specified location at all times:

[0162]

[0163] If necessary, the EAV k can be assigned to another parking facility f′, so that during the parking period of the EAV, it either stays at the parking facility or travels on the road from f to f′. This can be ensured by the following formula:

[0164]

[0165] Before going from f to f′, EAV k should stop at f continuously, expressed as:

[0166]

[0167] Similarly, unless k is assigned to another parking facility, it should always park at f′, expressed as:

[0168]

[0169] As described in formula (1), k needs to go from f to f′ time period, which means that during the k driving period, it should be maintained at least Within a period of time This can be specified in the following ways:

[0170]

[0171] According to one embodiment of the present invention, there is provided a method for regulating the voltage of a power distribution network, comprising:

[0172] Step 1: The control center receives the driving plan of the EAV; the parking request of the EAV is transmitted to the control center through advanced vehicle communication technology (such as IEEE 802.11p).

[0173] In the present invention, the method works on a time-division basis, dividing time horizontally into multiple time periods {t=1,…,T}. In a certain time period, if an EAV is ready to park, it sends a request containing its attributes through the vehicle communication device. in,

[0174] v k represents the location where EAV k requests to park;

[0175] Indicates the position to which EAV k is to return;

[0176] t k represents the time when EAV k requests to stop;

[0177] Indicates the time when EAV k returns to the specified position;

[0178] e k represents the SOC when EAV k requests to stop;

[0179] It indicates the minimum SOC that EAV k should have when returning to the specified position;

[0180] α k is a function defined according to the parameters of vehicle k:

[0181]

[0182] in,

[0183] w k is k from v k Arrival f time;

[0184] is k from v f Back to time;

[0185] represents the set of times when EAV k moves from f to f′, where f′ represents other positions except f, i.e.

[0186] Indicates that from v f return When , SOC decreases by this value.

[0187] Step 2, the control center optimizes the EAV charging, discharging and parking plan according to the optimization target based on the power supply information of the node, the battery status and driving plan of the EAV and the information of the electric vehicle charging station;

[0188] In order to obtain the best voltage regulation effect, the voltage is adjusted to, for example, 1.0 pu as much as possible;

[0189] According to one embodiment of the present invention, the following objective function should be used to optimize the charging, discharging and parking of the EAV, taking into account the changes in renewable energy and load:

[0190]

[0191] in,

[0192] min means taking the minimum value;

[0193] k represents each EAV, Represents a collection of EAVs that can be used for parking coordination;

[0194] t represents the tth period, It is a collection of multiple time periods divided into horizontal time periods;

[0195] i represents the i-th node, Represents a collection of nodes;

[0196] f represents an electric vehicle charging station, represents a collection of electric vehicle charging stations;

[0197] V i,t represents the voltage of node i at time t;

[0198] T represents the transposed matrix.

[0199] According to one embodiment of the present invention, the charging, discharging and parking plan includes moving the EAV from one electric vehicle charging station to another electric vehicle charging station so that it obtains active power from different nodes to perform voltage regulation.

[0200] According to one embodiment of the present invention, the charging, discharging and parking plan includes optimizing such that the total charging or discharging power of the EAVs of the nodes is equal to the sum of the power injections of the EAVs at the corresponding parking facilities.

[0201] According to one embodiment of the present invention, the charging, discharging and parking plan includes optimizing according to which the total charging and discharging power of the parking facility should not exceed the charging facility power limit.

[0202] According to one embodiment of the present invention, the charging, discharging and parking plan includes optimization in the following manner: when the EAV is parked, the change in SOC within the corresponding time period should be equal to the charging or discharging energy in the parking facility; when not parked, the change in SOC should be equal to the driving energy consumption.

[0203] According to one embodiment of the present invention, the charging, discharging and parking plan includes optimization according to the charging power, discharging power and driving power consumption rate of the EAV. For a parked EAV, the change of its SOC is limited by the charging or discharging power limit. In other cases, the change of SOC is limited by the driving power consumption rate.

[0204] According to one embodiment of the present invention, the charging, discharging and parking plan includes optimizing each EAV so that it has enough SOC when leaving the parking facility to ensure that it can reach the next parking facility.

[0205] According to one embodiment of the present invention, the optimization method adopts a standard MIQP solver for calculation, and the solver is a Gurobi optimizer.

[0206] Step 3: The control center may send the parking and charging plan to EAV via advanced vehicle communication technology (such as IEEE802.11p).

[0207] Step 4: The EAV receives and executes the charging and parking plan.

[0208] The method proposed in the present invention is simulated on a modified radial distribution network system with 15 nodes. Figure 2As shown. Four electric vehicle charging stations are connected to nodes {3, 8, 9, 12}, and a solar photovoltaic power generation system (PV) is connected to nodes {6, 9, 11} as a renewable energy source. According to the existing general specifications for electric vehicles, it is assumed that the charging and discharging power of the EAV is 16.5kW and the battery capacity is 100kWh. This example simulates a typical 6-hour working period during which the EAV user goes to work in the morning. The departure time is uniformly randomly selected between 9 and 10 a.m. The required SOC (i.e. ) are uniformly randomly selected between 60% and 80% of the battery capacity. The following introduces the simulation results according to the different numbers of EAVs in the system.

[0209] Example A. No EAV in the system

[0210] When there is no EAV in the system, the voltage curve is as follows Figure 3 As shown, each curve represents the voltage fluctuation of a node over time. It can be seen that during the optimization period, the voltage of all nodes except the substation exceeded the upper limit of 1.05pu. If there is no appropriate parking plan, the voltage at the key node will increase seriously when the PV is controlled in MPPT mode. In this case, the 20 electric vehicles in the charging state act as controllable loads, but their parking plan cannot be controlled, so only the optimal charging plan is applied. Obviously, without the participation of control devices such as capacitor banks, the system voltage cannot be adjusted within the predetermined range.

[0211] Example B. The system contains 20 EAVs

[0212] In order to avoid voltage over-limit in the above case, 20 EAVs are first added to the network in this example. As mentioned above, EAVs are activated by randomly setting their arrival and departure times. Based on the proposed optimization framework, Figure 4 The voltage curves under the same solar power generation and load conditions as in Example A are given in FIG. It can be seen that most node voltages are within the predetermined range, while voltage over-limit conditions still exist during the peak period of solar power generation. According to the method of the present invention, the charging, discharging and parking plan of the EAV will follow the fluctuation of solar energy, and obviously, the charging power will be reduced to cope with the high solar irradiance at noon. The above results show that the calculated optimal charging, discharging and parking plan of the EAV is very effective, but in order to avoid voltage over-limit during the day, more EAVs are needed to provide V2G services.

[0213] Example C. The system contains 50 EAVs

[0214] In order to further suppress voltage over-limit, 50 EAVs are used in the system in this example to reduce the impact of solar energy access and peak power load. Figure 5As shown, it can be seen that without reducing photovoltaic power generation or installing other equipment, the node voltage is controlled between 0.95pu and 1.05pu. From the above results, it can be seen that the voltage is controlled within a range much smaller than the predetermined value, and 50 EAVs are sufficient to meet the needs of V2G services.

[0215] In summary, the distribution network voltage regulation system and method based on electric driverless vehicles and V2G technology proposed in the present invention can alleviate overvoltage and undervoltage problems by allocating EAV at appropriate charging facilities and adjusting the power exchange between charging facilities and the power grid. Simulation results show that the method of the present invention can effectively suppress the voltage over-limit problem in the distribution network system with high renewable energy penetration.

[0216] It should be noted that not all steps described in the above embodiments are necessary, and those skilled in the art may make appropriate choices, replacements, modifications, etc. according to actual needs.

[0217] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention is described in detail with reference to the embodiments above, it should be understood by those skilled in the art that any modification or equivalent replacement of the technical solutions of the present invention does not depart from the spirit and scope of the technical solutions of the present invention and should be included in the scope of the claims of the present invention.

Claims

1. A distribution network voltage regulation system based on electric driverless vehicles and V2G technology, include: The distribution network system, multiple electric driverless vehicles (EAVs), a control center and multiple electric vehicle charging stations, among which, The power distribution network system includes a plurality of nodes connected to the plurality of electric vehicle charging stations; The multiple electric vehicle charging stations are connected via a road network to provide V2G services and charge or discharge the multiple EAVs; The control center receives the travel plan of the EAV and controls the charging, discharging and parking plans of the plurality of EAVs according to the operating parameters of the distribution network system, the battery status and travel plan of the EAV and the information of the electric vehicle charging station; The EAV receives control from the control center and executes the charging, discharging and parking plan; Receiving the travel plan of the EAV includes receiving a request including its attributes sent by the EAV when the EAV is ready to park, wherein the request sent by the kth EAV among the plurality of EAVs, namely, EAV k, is denoted as in, v k Indicates the location where EAVk requests parking; Indicates the location where EAVk is to return; t k Indicates the time when EAVk requests to stop; Indicates the time when EAVk returns to the specified position; e k Indicates the battery energy storage status when EAVk requests parking; Indicates the minimum battery energy storage state that the EAVk should have when returning to the specified position; α k is a function defined according to the parameters of vehicle k: in, w k is EAV k from v k Arrival f time, v f is the location of parking facility f; is EAV k from v f Back to time; Indicates that EAVk is from f to f ′ The set of times where f ′ represents other positions except f, that is, Indicates that from v f return When , the battery energy storage state decreases by a certain value; d mn and μ mn Respectively represent the distance and travel time of the shortest path between locations m and n; And wherein the charging, discharging and parking plan is obtained by optimizing using the following objective function; Among them, min means taking the minimum value; k means each EAV, represents the set of EAVs that can be used for parking coordination; t represents the tth time period, is a set of multiple time periods divided horizontally; i represents the i-th node, represents a collection of nodes; f represents an electric vehicle charging station, represents the set of electric vehicle charging stations; V i,t represents the voltage of node i at time t; T represents the transposed matrix.

2. The system according to claim 1, wherein the power distribution network system is connected to a renewable energy power station.

3. The system according to claim 2, in, The control center controls the charging, discharging and parking plans of the multiple EAVs according to the number of EAVs, the battery capacity and charging and discharging power of each EAV, the parameters of the renewable energy power station, the location information of multiple electric vehicle charging stations, and the connection status between the nodes and the electric vehicle charging stations.

4. The system according to any one of claims 1-3, wherein the control center controls the charging, discharging and parking plan of the EAV in different time periods.

5. The system according to any one of claims 1-3, wherein the control center further controls the EAV to charge at a designated electric vehicle charging station within a designated time period.

6. The system according to any one of claims 1-3, wherein the control center further controls the EAV to discharge at a designated electric vehicle charging station within a designated time period.

7. According to the system of any one of claims 1-3, the control center further controls the EAV to leave the current electric vehicle charging station and go to the next electric vehicle charging station within a specified time period, so that it obtains active power at different nodes.

8. A method for use in the system of any one of claims 1 to 7, include: Step 1, the control center receives the driving plan of the EAV; Step 2, the control center optimizes the EAV charging, discharging and parking plan according to the power supply information of the node, the battery status and driving plan of the EAV and the information of the electric vehicle charging station according to the optimization method; Step 3, the control center sends the parking and charging and discharging plan to the EAV; Step 4: The EAV receives and executes the charging, discharging and parking plan.

9. The method of claim 8, wherein the charging, discharging and parking plan includes moving the EAV from one electric vehicle charging station to another electric vehicle charging station so that it obtains active power from different nodes to perform voltage regulation.

10. The method according to claim 8, wherein the optimization method comprises controlling the voltage of the node to be within a specified range, with a lower voltage limit of 0.95 pu and an upper voltage limit of 1.05 pu.

11. The method according to claim 10, wherein the charging, discharging and parking plan comprises optimizing according to the following power flow constraints: in, i represents a node; t represents time; P i+1,t and Q i+1,t Respectively represent the active power and reactive power of node i+1 at time t; P i,t and Q i,t Respectively represent the active power and reactive power between node i and node i+1 at time t; and represents the active load and RES injection of node i+1 at time t; represents the total charging or discharging power of the EAV of node i; Represents a collection of nodes; Represents a set of time periods; represents the load of node i+1 at time t; represents the reactive power of the RES inverter of node i at time t; and represents the active load and RES injection of node i at time t; V i+1,t represents the voltage of node i+1 at time t; V i,t represents the voltage of node i at time t; r i Indicates line resistance; x i Indicates line reactance; V S Indicates the substation voltage; S i represents the apparent power capacity allowed by the RES inverter at node i; Indicates the power passing through the substation; Indicates the lower limit of the power flowing through the substation; Indicates the upper limit of the power flowing through the substation.

12. The method of claim 10, wherein the charging, discharging and parking plan comprises optimizing such that a total charging or discharging power of the EAVs of a node is equal to a sum of power injections of the EAVs at corresponding parking facilities.

13. The method of claim 10, wherein the charging, discharging and parking plan comprises optimizing according to which the total charging and discharging power of the parking facility should not exceed the charging facility power limit.

14. The method of claim 10, wherein the charging, discharging and parking plan includes optimizing in the following manner: when the EAV is parked, the change in SOC during the corresponding time period should be equal to the charging or discharging energy in the parking facility; when not parked, the change in SOC should be equal to the driving energy consumption.

15. The method of claim 10, wherein the charging, discharging and parking plan includes optimizing the EAV according to its charging power, discharging power and driving power consumption rate. For a parked EAV, the change of its SOC is limited by the charging or discharging power limit. In other cases, the change of SOC is limited by the driving power consumption rate.

16. The method of claim 10, wherein the charging, discharging and parking planning includes optimizing each EAV to have sufficient SOC when leaving a parking facility to ensure that it can reach the next parking facility.

17. The method according to any one of claims 10-16, wherein the optimization method is calculated using a standard MIQP solver, and the solver is a Guro i optimizer.

18. A computer-readable storage medium having a computer program stored thereon, in, When the program is executed by a processor, the steps of the method according to any one of claims 8 to 17 are implemented.

19. A computer device comprising a memory and a processor, wherein a computer program capable of being executed on the processor is stored in the memory, It is characterized in that When the processor executes the program, the steps of the method according to any one of claims 8 to 17 are implemented.

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