CN117154788A - Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station - Google Patents

Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station Download PDF

Info

Publication number
CN117154788A
CN117154788A CN202311044589.0A CN202311044589A CN117154788A CN 117154788 A CN117154788 A CN 117154788A CN 202311044589 A CN202311044589 A CN 202311044589A CN 117154788 A CN117154788 A CN 117154788A
Authority
CN
China
Prior art keywords
power
charging station
vsg
soc
frequency modulation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202311044589.0A
Other languages
Chinese (zh)
Inventor
张帆
高宜凡
杨军
林晓明
梁柱
柯松
唐建林
吴梦维
施兴烨
钱斌
甘锴
丁乐言
魏攀
罗彬�
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China South Power Grid International Co ltd
Wuhan University WHU
Zhaoqing Power Supply Bureau of Guangdong Power Grid Co Ltd
Original Assignee
China South Power Grid International Co ltd
Wuhan University WHU
Zhaoqing Power Supply Bureau of Guangdong Power Grid Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China South Power Grid International Co ltd, Wuhan University WHU, Zhaoqing Power Supply Bureau of Guangdong Power Grid Co Ltd filed Critical China South Power Grid International Co ltd
Priority to CN202311044589.0A priority Critical patent/CN117154788A/en
Publication of CN117154788A publication Critical patent/CN117154788A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/63—Monitoring or controlling charging stations in response to network capacity
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L55/00—Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/002—Flicker reduction, e.g. compensation of flicker introduced by non-linear load
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H02J3/241—The oscillation concerning frequency
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Nonlinear Science (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention provides a virtual synchronous control method, equipment and medium for a charging station to participate in power grid frequency modulation. Providing inertial support and frequency modulated response for the microgrid. The invention can improve the frequency stability of the micro-grid operation, and the regulation potential of the excavation charging station and the electric automobile, and has wide application prospect.

Description

Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station
Technical Field
The invention belongs to the field of application of electric vehicle charging stations of electric power systems, and particularly relates to a virtual synchronous control strategy for the charging stations to participate in power grid frequency modulation.
Background
How to introduce better frequency modulation resources to replace inertial support and primary frequency modulation capability brought by thermal power reduction so as to relieve the problems of stable frequency and electric energy quality of a power grid in a large-scale grid-connected background of renewable energy sources.
The micro-grid is used as a power distribution network consisting of a distributed power supply, load and energy storage, can realize autonomous operation off the grid, and is used as a controllable unit for grid-connected operation, is one of technical means for realizing plug and play of the distributed power supply, and is also an important component of a future power grid. Distributed power sources such as wind power, photovoltaic, energy storage and the like in the micro-grid and adjustable loads such as electric vehicles and the like are connected into the power grid through the power electronic conversion device, so that the inertia level of the micro-grid is obviously reduced. When the micro-grid is in grid-connected operation, the micro-grid can be regarded as a controllable unit of the power grid, and the micro-grid is subjected to scheduling control of the power grid; and when the micro-grid island runs autonomously, the stability problem is worth of intensive research. When the island micro-grid is impacted by the same power unbalance, the frequency deviation of the island micro-grid is increased, the frequency change rate is increased, and the disturbance rejection capability of the island micro-grid is reduced. The grid-built inverter control is a control mode when the micro-grid is supported to run in an island mode, and the virtual synchronous generator control is widely applied due to the fact that the virtual synchronous generator control is equivalent to a synchronous generator externally, so that the stability problem brought to the micro-grid by the weak inertia support problem is relieved.
The capacity of the micro-grid is limited, the frequency modulation resources of the micro-grid are relatively deficient, and the difficulty of maintaining the frequency stability of the micro-grid is increased by the traditional regulation means. The flexible loads such as EV accessed in the micro-grid have stronger randomness, and further threaten the running stability of the micro-grid. The electric automobile is used as a typical adjustable flexible load, and if the electric automobile and the charging station can participate in the micro-grid frequency control through corresponding control technical means, the micro-grid frequency stability level can be effectively improved. Therefore, in order to improve the inertial support and active frequency modulation capability of the island micro-grid, frequency control strategies for charging station virtual synchronization control need to be studied.
Disclosure of Invention
In order to solve the above problems, the present invention proposes a virtual synchronization control strategy for a charging station to participate in frequency modulation. Firstly, a virtual synchronous generator control framework of a charging station is designed, a real-time charging and discharging power distribution algorithm of each electric vehicle in the charging station is provided by combining an adjustable power range of the charging station and a charging and discharging power response control strategy of the electric vehicle of the charging station, and then a model predictive control algorithm is combined to solve the power instruction adjustment quantity of the virtual synchronous control algorithm when the charging station responds to frequency, so that virtual synchronous control of the charging station is realized, and inertia support and frequency modulation response are provided for a micro-grid. The invention can improve the frequency stability of the operation of the micro-grid and can mine the regulation potential of the charging station and the electric automobile.
The invention combines engineering reality, and is suitable for the design of charging station charging and discharging power control strategies for virtual synchronous control under different scale capacities.
The technical scheme of the invention is as follows:
a virtual synchronous control method for a charging station to participate in power grid frequency modulation,
collecting data of electric vehicles in a charging station, analyzing boundaries of charging and discharging power and energy of the electric vehicles in the charging station according to a charging and discharging power model constructed based on cooperation between a user charging requirement and a micro-grid frequency modulation requirement, and determining upper and lower limit constraints delta P of input control variables in an MPC optimization model ev-fmin (k),ΔP ev-fmax (k) The method comprises the steps of carrying out a first treatment on the surface of the The upper and lower limit constraints constrain the frequency modulation range of the charging station VSG. The following charging stations should meet this constraint throughout the frequency modulation process.
Obtaining a virtual SoC of the charging station VSG according to the constructed SoC and the charge-discharge power model vsg Capacity and capacity of the device; soC (System on chip) vsg Refers to the ratio of the sum of the controllable capacity of the electric automobile battery and the sum of the total battery capacity in the charging station. Is a state quantity of 0% to 100%. The capacity of the charging station VSG means that the charging station is charged within the regulation and control sectionThe sum of the battery capacities of all electric vehicles in the power station;
according to the constructed secondary frequency modulation strategy of the charging station, the VSG current input value P m And the output of MPC algorithm to calculate the input increment delta P of next moment ev-f To modify the VSG controlled input mechanical power command P m For VSG control;
according to the voltage and current signals at the grid-connected node predicted by the established power grid model, a voltage reference signal is generated to drive the inverter to work through a power outer loop and a voltage and current control inner loop which comprise a virtual rotor motion equation in a VSG control strategy, and the inverter participates in frequency modulation.
Preferably, the boundary between the charge and discharge power and the energy of the electric vehicle in the station is calculated by the following formula
Wherein E is s + ，E s - Is the boundary of charge and discharge quantity of the charging station, P s + ，P s - And N is the number of EVs in the station and is the boundary of the charging and discharging power of the charging station.
Preferably, the control ΔP of the charging station VSG is calculated from the photovoltaic, energy storage and charging pile power parameters within the charging station ev-f Value range constraint [ delta P ] of (a) ev-fmin ,ΔP ev-fmax ]Calculated according to the following formula:
preferably, the model between SoC and charge-discharge power
The SoC and capacity of the charging station are determined according to each electric vehicle in the station, and the model between the SoC and the charging/discharging power is used for determining the delta P of the charging station ev-f How to distribute power among the various EVs that are regulatable within the station.
Virtual SoC of charging station VSG vsg And the function of capacity is combined with the frequency response and regulation strategy of the power grid when the VSG of the charging station participates in the frequency modulation of the power grid.
Externally, the charging station VSG is accessed in the form of a VSG at the charging station grid-connected point, and therefore, the virtual SoC of the charging station VSG is acquired vsg And capacity, which is a state quantity determined when various frequency modulation resources are cooperated (such as an energy storage power station, a photovoltaic power station and the like) from the aspect of a power grid/micro-grid. The cooperation of the charging station with other frequency modulated resources is not referred to in this patent.
Virtual SoC of in-pair charging station VSG vsg And capacity, which is the set of SoC state and adjustable capacity of each electric car inside.
Wherein N2 is the EV number of SoC states maintained in the station at the time of frequency disturbance, and n1+n2=n; k (K) i,k cha ，K i,k dis The charge and discharge power-SoC distribution coefficients are respectively defined as follows:
when SoC i,k ≤SoC i min In the time-course of which the first and second contact surfaces,
when SoC i,k ≥SoC i max In the time-course of which the first and second contact surfaces,
when SoC i min ≤SoC i,k ≤SoC i in In the time-course of which the first and second contact surfaces,
when SoC i in ≤SoC i,k ≤SoC i max In the time-course of which the first and second contact surfaces,
when the frequency fluctuation exceeds the dead zone, the output of the EV-f controller, namely the PV-ES-CS VSG feedback compensation quantity delta P, is obtained according to the state of the EV in the station, the user demand and the micro-grid frequency modulation demand ev-f As shown below.
Input mechanical power P of VSG m The following formula is shown:
P m ＝P m_ref +ΔP ev-f
as a preferred alternative to this,
the secondary frequency modulation strategy of the charging station comprises
Primary frequency modulation: an EV-f controller feedback compensation link is added to the power-frequency controller to correct the reference value of the VSG input mechanical power as shown in the following formula.
P m ＝P ref +D p (ω N -ω)
Secondary frequency modulation: the EV frequency modulation capability is introduced into a frequency deviation feedback command, and as feedforward compensation of a VSG active-frequency controller, the secondary frequency control of the VSG is represented by the following formula:
P m ＝P ref +ΔP ev-f
wherein P is ref For the active power reference value, D p For sag factor, ΔP ev-f The power is compensated for feedback of the charging station frequency control.
Preferably, the output of the MPC algorithm includes the command adjustment value of the charging station VSG and the response power of the in-station EVs during the frequency disturbance, and the input of the model prediction algorithm is the state of charge and the charge/discharge power of each EV in the charging station and the charge/discharge power at the grid-connected point of the charging station VSG during the regulation time interval in which the frequency disturbance occurs.
The optimization target is that the minimum frequency deviation of the power grid is taken as the optimization target, and min|f (t) -f n |；
The constraint is that the response power of the charging station VSG is fed back by the compensation amount Δp ev-f ∈[ΔP ev-fmin ,ΔP ev-fmax ]。
The specific method is as follows:
based on the collaborative charge-discharge power modeling between the user charge demand and the micro-grid frequency modulation demand, the boundary between the charge-discharge power and the energy of the electric automobile in the station is analyzed, and the upper limit constraint delta P and the lower limit constraint delta P of the input control variable in the MPC optimization model are determined ev-fmin (k),ΔP ev-fmax (k) The method comprises the steps of carrying out a first treatment on the surface of the Secondly, based on a VSG control strategy, an EV-f secondary frequency modulation controller is introduced, a secondary frequency modulation strategy of the charging station is established, and the current input value P of the VSG is combined m And the output of MPC algorithm, the input increment delta P of the next moment can be calculated ev-f To modify the VSG controlled input mechanical power command P m And finally, according to the voltage and current signals at the grid-connected node predicted by the established power grid model, generating a voltage reference signal to drive the inverter to work and participate in frequency modulation through a power outer loop and a voltage and current control inner loop which comprise a virtual rotor motion equation in a VSG control strategy.
As a preferred alternative to this,
according to the state of EV in the station, the user demand and the micro-grid frequency modulation demand, the output of the EV-f controller, namely PV-ES-CS VSG feedback compensation quantity delta P, is obtained ev-f As shown below.
Input mechanical power P of VSG m The following formula is shown:
P m ＝P m_ref +ΔP ev-f 。
an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the control method is implemented when the processor executes the program.
A non-transitory computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements the control method.
A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the control method.
Therefore, the invention has the following advantages: the invention can meet the charging requirement of the electric automobile in the charging station, and can simultaneously excavate the regulation and control potential of the charging station, so that the charging station participates in the stable control of the frequency of the power grid, and virtual inertia support and the active frequency regulation capability are provided.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a VSG active-frequency control block diagram.
Fig. 3 is a virtual synchronization control architecture of the charging station VSG.
Fig. 4 is the charge amount and the charge-discharge power of the EV in the charging station.
FIG. 5 is a flow chart of a model predictive control algorithm.
Fig. 6 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Embodiment 1 provides a virtual synchronization control method for a charging station to participate in grid frequency modulation, which specifically includes
Step 1, providing a virtual synchronous control strategy, which specifically comprises the following steps:
the definition of the virtual synchronous generator (Virtual Synchronous Generator, VSG) control strategy is to introduce the rotor equations of motion and electromagnetic transient equations of the synchronous generator into the inverter grid-tie control strategy.
In the active-frequency regulation link of the virtual synchronous generator control, a control block diagram is shown in fig. 2.
In FIG. 2, P m The input mechanical power of the prime motor is the input power of the VSG; p (P) e The grid-connected output power is electromagnetic power, namely VSG; t (T) m ,T e For corresponding torque, T D The virtual damping torque is VSG, D is virtual damping, J is virtual moment of inertia, ω is angular velocity of rotation, ω N Is the rated rotational angular velocity.
The torque equation according to the rotor motion equation is:
wherein Δω=ω - ω N 。
And then converting equation (1) into the active-frequency control equation for VSG, as follows:
wherein K is J And K D The power inertia coefficient and the power damping coefficient are respectively.
Thus, in VSG, P is received m After inputting the power command, determining the rotation angular velocity of the virtual rotor according to the torque equation of the formula (1), and comparing the rotation angular velocity with the rated rotation angular velocity omega N And taking the difference to obtain the angular acceleration of the virtual power angle delta, and integrating to obtain the virtual power angle.The inverter is connected with the grid through the filter circuit and the synchronous generator is connected with the grid through internal impedance, so that the output power P of the VSG is based on the characteristics of the angle of work e Can be calculated from the following formula:
wherein E is 0 Is the no-load electromotive force of VSG, U is the voltage of the output end of VSG, X f Is a filter reactance.
Step 2, designing a virtual synchronous control architecture of the charging station, as shown in fig. 3, specifically as follows:
in order to enable the charging station VSG to participate in frequency modulation, an EV-f controller feedback compensation link is added into the power-frequency controller to correct a reference value of the VSG input mechanical power, as shown in the following formula.
P m ＝P ref +D p (ω N -ω) (6)
Wherein P is ref For VSG active power reference value, D p Is the sag factor.
By combining the formulas (4) and (6), the transient relation between the frequency and the active power can be deduced as shown in the following formula.
Because the conventional droop control cannot realize no-difference frequency modulation, a secondary no-difference frequency modulation controller EV-f controller needs to be designed according to the characteristics of the EV charging station, and the EV frequency modulation capability is introduced into a frequency deviation feedback command as feedforward compensation of the VSG active-frequency controller, so that the secondary frequency control of the VSG has the following formula:
P m ＝P ref +ΔP ev-f (8)
wherein DeltaP ev-f The power is compensated for feedback of the charging station frequency control.
As shown in fig. 3, the VSG control architecture can receive the instruction of the micro-grid dispatching center, actively detect the frequency of the island micro-grid, and provide the frequency modulation capability by adjusting the output power instruction of the charging station VSG when the frequency deviation occurs. But the key is how to design the EV-f controller of the charging station.
And step 3, providing a real-time charging and discharging power distribution algorithm in the charging station. VSG output P m The VSG is mainly limited by factors such as charging requirements of electric vehicles in the charging station, and the output of the VSG is provided by each controllable EV in the charging station, as shown in fig. 4.
From the perspective of frequency adjustment, an electric vehicle can take on the adjustment task as a mobile storage device. Therefore, the proper bearing of the regulation task is a control target of the V2G strategy of the electric automobile participating in the secondary frequency regulation of the micro-grid. On the other hand, soC and charging power of EVs are also somewhat limited because users use EVs for transportation.
When the EV is connected to the charging post of the charging station, the charge state and the range of the charge-discharge power thereof are shown in fig. 4. Wherein E is i ini 、E i end 、E i min 、E i max For the initial, termination, minimum and maximum charge of the ith EV, P i c 、P i d The i-th EV is the charge/discharge power.
E when an EV is parked at the charging station at a time longer than the expected time for charging and the allowable minimum charge of the EV is less than the initial charge i min ≤E i ini The battery has certain charge and discharge capability. The electric energy and power boundaries are shown in fig. 4, and satisfy the following formulas (15) - (18).
Wherein eta c ,η d For EV charge-discharge efficiency, E i + ，E i - Is the boundary of the charge and discharge quantity of the ith EV, P i + ，P i - Is the charge-discharge power boundary of the ith EV. t is t i a 、t i d The arrival and departure time of the ith EV,
when E is i min ≤E i ini EV i can be at t i a Starting to charge or discharge the power grid at any moment; when E is i min ≥E i ini EV i needs to run from t at maximum power i a From time to t i c At time of charging to E i min Then, the charge and discharge are performed. The electric energy and power boundaries are shown in fig. 5 and 6.
Therefore, by the above method, the controllable state of the EVs in the charging station can be determined, and the control margin of each EV in the station can be aggregated, as shown in the following formulas (19) and (20).
Wherein E is s + ，E s - Is the boundary of charge and discharge quantity of the charging station, P s + ，P s - And N is the number of EVs in the station and is the boundary of the charging and discharging power of the charging station.
According to the electric vehicle modeling and aggregation model, from the user requirements and the electric vehicle SoC, the charging power and the capacity of the electric vehicle at the charging station are combined with the parking time to obtain the energy and the power boundary of the electric vehicle participating in VSG frequency modulation, so that the electric vehicle can participate in VSG frequency modulationIn order to obtain the regulated power and capacity of the charging station after the EVs are polymerized in the whole charging station on the premise of meeting the charging requirements of each EV. Furthermore, delta P is provided for controlling the VSG of the charging station according to parameters such as photovoltaic, energy storage, charging pile power and the like in the charging station ev-f Value range constraint [ delta P ] of (a) ev-fmin ,ΔP ev-fmax ]。
Further, an in-station EV charge-discharge power response control strategy is proposed.
From the moment the EV accesses the charging station in a certain SoC state, the state of the EV interaction with the grid is divided into two types during the time interval until the EV leaves the charging station, one is to adjust the SoC level when the desired SoC level is not reached, and the other is to maintain the SoC level. When the frequency disturbance moment occurs and the EV participates in frequency modulation, the interactive power of the EV and the micro-grid at the current moment can be divided into two types, namely EV charging power P aiming at improving the SoC state of the battery i,k+1 cha One type is V2G discharge power P participating in grid frequency modulation i,k+1 dis . Therefore, the charging power P i,k+1 cha And V2G discharge power P i,k+1 dis The following constraints first need to be satisfied.
P i,k+1 dis +P i,k+1 cha ≤P max (15)
Further, when the desired SoC level is not reached, the SoC level needs to be adjusted,
when the charging station charges, the following relationship exists between the charging power and the electric quantity.
Wherein E is i n Is the rated capacity of EV i. When the charging power is constant, formula (16) may be rewritten as:
the EV charge power and the V2G discharge power at the time of adjusting the SoC level are respectively shown as the following formulas.
Wherein, N1 is the EV quantity for adjusting the state of the SoC in the station at the moment of frequency disturbance; p (P) ev1,k+1 cha Is to raise the actual charging power of EV SoC; p (P) ev1,k+1 dis To participate in V2G frequency modulation, the charging power is reduced.
When the SoC level is maintained, the SoC i in At a desired SoC level, when the SoC level is higher than the SoC i in When the V2G discharging power is larger than the EV charging power, the EV discharges to the power grid; when the SoC level is lower than that of SoC i in And when the V2G discharging power is smaller than the EV charging power, the EV charges the power grid. In order to build a mapping of battery V2G to V2G power, a mathematical model of the following formula is proposed.
Wherein N2 is the EV number of SoC states maintained in the station at the time of frequency disturbance, and n1+n2=n; k (K) i,k cha ，K i,k dis The charge and discharge power-SoC distribution coefficients are respectively defined as follows:
when SoC i,k ≤SoC i min In the time-course of which the first and second contact surfaces,
when SoC i,k ≥SoC i max In the time-course of which the first and second contact surfaces,
when SoC i min ≤SoC i,k ≤SoC i in In the time-course of which the first and second contact surfaces,
when SoC i in ≤SoC i,k ≤SoC i max In the time-course of which the first and second contact surfaces,
therefore, when the frequency fluctuation exceeds the dead zone, the output of the EV-f controller, namely the PV-ES-CS VSG feedback compensation quantity delta P, can be obtained according to the state of the EV in the station, the user demand and the micro-grid frequency modulation demand ev-f As shown below.
Thus, the input mechanical power P of VSG m The following formula is shown:
P m ＝P m_ref +ΔP ev-f (25)
step 4, an MPC algorithm for the charging station VSG is provided, and as shown in fig. 4, the command adjustment value of the charging station VSG and the response power of the EV in the station in the frequency disturbance process are obtained by solving, so as to realize frequency control.
During actual operation of VSG, P m P given by scheduling instruction m-ref And DeltaP ev-f And (5) jointly determining. Through the model of the step, the distribution result of the charging station regulation power in each EV in the station can be known, and specific charge and discharge power control is further realized. Based on the collaborative charge-discharge power modeling between the user charge demand and the micro-grid frequency modulation demand, the boundary between the charge-discharge power and the energy of the electric automobile in the station is analyzed, and the upper limit constraint delta P and the lower limit constraint delta P of the input control variable in the MPC optimization model are determined ev-fmin (k),ΔP ev-fmax (k) The method comprises the steps of carrying out a first treatment on the surface of the Secondly, according to modeling between SoC and charge and discharge power, obtaining virtual SoC of the charging station VSG vsg As well as capacity; further, based on the VSG control strategy, a secondary frequency modulation strategy of the charging station is established, and the current input value P of the VSG is combined m And the output of MPC algorithm, the input increment delta P of the next moment can be calculated ev-f To modify the VSG controlled input mechanical power command P m And finally, generating a voltage reference signal to drive the inverter to work so as to participate in frequency modulation.
Example 2
The embodiment provides a schematic entity structure of an electronic device, which may include: processor 810, communication interface (Communications Interface) 820, memory 830, and communication bus 840, wherein processor 810, communication interface 820, memory 830 accomplish communication with each other through communication bus 840. The processor 810 may invoke logic instructions in the memory 830 to execute the control method.
Further, the logic instructions in the memory 830 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Example 3
The present invention also provides a computer program product comprising a computer program storable on a non-transitory computer readable storage medium, the computer program being capable of performing the control method provided by the methods described above when being executed by a processor.
Example 4
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the control method provided by the above methods.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A virtual synchronous control method for a charging station to participate in power grid frequency modulation is characterized in that,
collecting data of electric vehicles in a charging station, analyzing boundaries of charging and discharging power and energy of the electric vehicles in the charging station according to a charging and discharging power model constructed based on cooperation between a user charging requirement and a micro-grid frequency modulation requirement, and determining upper and lower limit constraints delta P of input control variables in an MPC optimization model ev-fmin (k),ΔP ev-fmax (k)；
Obtaining a virtual SoC of the charging station VSG according to the constructed SoC and the charge-discharge power model vsg Capacity and capacity of the device;
according to the constructed secondary frequency modulation strategy of the charging station, the VSG current input value P m And the output of MPC algorithm to calculate the input increment delta P of next moment ev-f To modify the VSG controlled input mechanical power command P m For VSG control;
according to the voltage and current signals at the grid-connected node predicted by the established power grid model, a voltage reference signal is generated to drive the inverter to work through a power outer loop and a voltage and current control inner loop which comprise a virtual rotor motion equation in a VSG control strategy, and the inverter participates in frequency modulation.
2. The virtual synchronous control method for the charging station to participate in the grid frequency modulation according to claim 1, wherein the boundary of the charging and discharging power and energy of the electric vehicle in the station is calculated by the following formula
Wherein E is s + ，E s - Is the boundary of charge and discharge quantity of the charging station, P s + ，P s - And N is the number of EVs in the station and is the boundary of the charging and discharging power of the charging station.
3. The virtual synchronous control method for charging station to participate in grid frequency modulation according to claim 1, wherein control Δp of charging station VSG is calculated based on photovoltaic, energy storage and charging pile power parameters in charging station ev-f Value range constraint [ delta P ] of (a) ev-fmin ,ΔP ev-fmax ]Calculated according to the following formula:
4. the virtual synchro-control method for charging station to participate in grid frequency modulation of claim 1, wherein the SoC and charge-discharge inter-power model
Wherein N2 is the EV number of SoC states maintained in the station at the time of frequency disturbance, and n1+n2=n; k (K) i,k cha ，K i,k dis The charge and discharge power-SoC distribution coefficients are respectively defined as follows:
when SoC i,k ≤SoC i min In the time-course of which the first and second contact surfaces,
when SoC i,k ≥SoC i max In the time-course of which the first and second contact surfaces,
when SoC i min ≤SoC i,k ≤SoC i in In the time-course of which the first and second contact surfaces,
when SoC i in ≤SoC i,k ≤SoC i max In the time-course of which the first and second contact surfaces,
when the frequency fluctuation exceeds the dead zone, the output of the EV-f controller, namely the PV-ES-CS VSG feedback compensation quantity delta P, is obtained according to the state of the EV in the station, the user demand and the micro-grid frequency modulation demand ev-f As shown below;
input mechanical power P of VSG m The following formula is shown:
P m ＝P m_ref +ΔP ev-f 。
5. a virtual synchronous control method for a charging station to participate in grid frequency modulation as defined in claim 1,
the secondary frequency modulation strategy of the charging station comprises
Primary frequency modulation: an EV-f controller feedback compensation link is added in the power-frequency controller to correct a reference value of VSG input mechanical power, wherein the reference value is shown in the following formula;
P m ＝P ref +D p (ω N -ω)
secondary frequency modulation: the EV frequency modulation capability is introduced into a frequency deviation feedback command, and as feedforward compensation of a VSG active-frequency controller, the secondary frequency control of the VSG is represented by the following formula:
P m ＝P ref +ΔP ev-f
wherein P is ref For the active power reference value, D p For sag factor, ΔP ev-f The power is compensated for feedback of the charging station frequency control.
6. The virtual synchronous control method for the charging station to participate in the grid frequency modulation according to claim 1, wherein the output of the MPC algorithm comprises the command adjustment value of the charging station VSG and the response power of the in-station EV during the frequency disturbance, and the input of the model prediction algorithm is the charge state and the charge/discharge power of each EV in the charging station and the charge/discharge power at the grid connection point of the charging station VSG during the regulation time interval in which the frequency disturbance occurs;
the optimization target is that the minimum frequency deviation of the power grid is taken as the optimization target, and min|f (t) -f n |；
The constraint is that the response power of the charging station VSG is fed back by the compensation amount Δp ev-f ∈[ΔP ev-fmin ,ΔP ev-fmax ]。
7. A virtual synchronous control method for a charging station to participate in grid frequency modulation as defined in claim 1,
according to the state of EV in the station, the user demand and the micro-grid frequency modulation demand, the output of the EV-f controller, namely PV-ES-CS VSG feedback compensation quantity delta P, is obtained ev-f As shown below;
input mechanical power P of VSG m The following formula is shown:
P m ＝P m_ref +ΔP ev-f 。
8. an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the control method according to any one of claims 1 to 7 when executing the program.
9. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the control method according to any one of claims 1 to 7.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the control method according to any one of claims 1 to 7.
CN202311044589.0A 2023-08-17 2023-08-17 Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station Pending CN117154788A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311044589.0A CN117154788A (en) 2023-08-17 2023-08-17 Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311044589.0A CN117154788A (en) 2023-08-17 2023-08-17 Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station

Publications (1)

Publication Number Publication Date
CN117154788A true CN117154788A (en) 2023-12-01

Family

ID=88899834

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311044589.0A Pending CN117154788A (en) 2023-08-17 2023-08-17 Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station

Country Status (1)

Country Link
CN (1) CN117154788A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117748567A (en) * 2024-02-08 2024-03-22 天津大学 Charging station control method and system for power grid frequency control

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117748567A (en) * 2024-02-08 2024-03-22 天津大学 Charging station control method and system for power grid frequency control
CN117748567B (en) * 2024-02-08 2024-04-23 天津大学 Charging station control method and system for power grid frequency control

Similar Documents

Publication Publication Date Title
CN110571871B (en) Energy storage power station participating power grid primary frequency modulation depth control and contribution analysis method
CN104659804B (en) Micro-capacitance sensor containing hybrid energy-storing and its control method
CN110299717B (en) Distributed hybrid energy storage system energy balance control strategy based on model predictive control
Khokhar et al. A novel adaptive intelligent MPC scheme for frequency stabilization of a microgrid considering SoC control of EVs
CN109687490B (en) Variable adjustment factor SOC droop control method of distributed energy storage system
CN109659960B (en) Combined frequency modulation control strategy for improving frequency of wind power plant alternating current-direct current grid-connected system
CN112769149B (en) Hybrid wind-solar micro-grid rapid frequency response distributed coordination control method and system
CN117154788A (en) Virtual synchronous control method, equipment and medium for participating in power grid frequency modulation of charging station
CN112803505A (en) Distributed voltage source converter cooperative control method and alternating current-direct current parallel-serial micro-grid
CN112039092B (en) Island direct-current output AGC model prediction control method considering energy storage SOC recovery
CN115102239A (en) Energy storage power station primary frequency modulation control method and system considering SOC balance
CN112952862A (en) Hybrid energy storage frequency division coordination controller for stabilizing wind power fluctuation and implementation method
CN110611332B (en) Energy storage device of offshore wind power system and control method thereof
CN116470528A (en) Multi-time scale auxiliary frequency modulation method for regional power grid optical storage station
CN115579910A (en) Micro-grid frequency and voltage control method and terminal
CN111525597B (en) Method for optimizing double-battery imbalance state in wind storage combined system
CN115102228A (en) Multi-target coordination frequency optimization method and device for wind power plant containing flywheel energy storage
CN111404177B (en) Self-adaptive secondary frequency modulation method for micro-grid of multiple virtual synchronous machines
CN115021336A (en) Optimization method for high-proportion new energy power system inertia deficiency scene
CN109038564B (en) Subsynchronous oscillation suppression system and method based on improved particle swarm optimization
CN117175654A (en) Charging station cluster weak-centering frequency modulation control method and medium based on virtual leader
CN117913875A (en) Electric power system energy storage unit state of charge control method and system based on consistency algorithm
CN116826809A (en) Virtual inertial power compensator control method, system and medium applied to electric vehicle charging station
Zhao et al. Analysis on the Contribution of Virtual Synchronous Generator Controlled Energy Storage System to Primary Frequency Modulation
Elalfy et al. Frequency Regulation Based on Antlion Optimization Technique for Microgrids with Electric Vehicles

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination