A distributed power supply control method for a generator vehicle based on a flexible generator set

Abstract

The present invention discloses a distributed power supply control method for a power generation vehicle based on a flexible generator set, wherein a corresponding energy storage system ESS is integrated into the synchronous generator SG of each power generation vehicle, thereby forming a flexible generator set FG; each flexible generator set FG is used to power a corresponding subsystem; an independent MPC control module is configured for each flexible generator set FG; the MPC control module collects the operating state parameters of the corresponding subsystem in real time, and performs model predictive control in combination with a reference signal, and outputs a predictive control output to the flexible generator set FG; the controller of the flexible generator set FG uses the predictive control output as a power supply control input, and outputs power according to the power supply control input. The present invention solves the technical problems of how to overcome the excessive data processing burden of centralized control and the need to configure a large-capacity ESS.

Description

Technical Field

[0001] The invention relates to the technical field of power supply control of a power generation vehicle. Background Art

[0002] The application fields of power generation vehicles are quite extensive, such as disaster relief, field construction, train power supply, etc., all of which rely on emergency power generation vehicles to provide reliable power sources. In order to ensure the reliable power supply of emergency power generation vehicles, many methods for stable control of power generation vehicles have been proposed. One of the methods is to apply the energy storage system (ESS) to the synchronous generator (SG) inside the power generation vehicle to form a flexible generator set (FG). At present, in order to synchronize the power of each synchronous generator, a centralized control mode is adopted: a lumped ESS corresponds to multiple synchronous generators SG, and information needs to be collected from different power networks and then transmitted to the central processor. The huge amount of data brings communication delays and computing bottlenecks to the processor. In addition, the lumped ESS is required to have a large capacity, and additional control is required to exit the ESS when the system reaches its nominal state. Summary of the invention

[0003] In view of the deficiencies of the above-mentioned technologies, the present invention provides a distributed power supply control method for a power generation vehicle based on a flexible generator set, which solves the technical problems of how to overcome the excessive data processing burden of centralized control and the need to configure a large-capacity ESS.

[0004] In order to solve the above technical problems, the present invention provides a distributed power supply control method for a generator vehicle based on a flexible generator set, comprising the following steps:

[0005] Integrate the corresponding energy storage system ESS into the synchronous generator SG of each power generation vehicle to form a flexible generator set FG;

[0006] Each flexible generator set FG is used to supply power to a corresponding subsystem;

[0007] Configure an independent MPC control module for each flexible generator set FG;

[0008] The MPC control module collects the operating status parameters of the corresponding subsystem in real time, and performs model predictive control in combination with the reference signal, and outputs the predictive control output to the flexible generator set FG;

[0009] The controller of the flexible generator set FG uses the predicted control output as the power supply control input and outputs power according to the power supply control input.

[0010] Furthermore, the predictive control model of model predictive control is as follows:

[0011]

[0012] In the formula, J k (x(k),u(k)) represents the objective function, k represents the time step, x(k) represents the state variable, u(k) represents the predictive control input vector, f(x(k),u(k)) represents the FG dynamic mechanical equations, and g(x(k),u(k)) represents the constraint function;

[0013] The state variable x(k+1) at time k+1 is predicted by the predictive control model and substituted into the dynamic mechanical equations of the flexible generator set FG to calculate the predictive control input vector u(k+1) at time k+1, and the predictive control output is calculated according to the predictive control input vector u(k+1) at time k+1.

[0014] Furthermore, based on the SG dynamic model and the dynamic model of the ESS power controller, the FG dynamic mechanical equations are established:

[0015]

[0016] in,

[0017] In the formula, i represents the subsystem number, δ i and ω i are the rotor angle and speed, ω s is the fundamental rotor electrical speed, ω n is the synchronous angular frequency; M is the inertia constant of FG, K Di is the damping coefficient of FG; P i is the total output power of FG; P si Represents the output power of ESS; P mi Represents the mechanical power of the synchronous generator; P ci Indicates the setting value of the turbine speed governor of the synchronous generator; P srefi represents the reference set point of the ESS transmitted active power; T si , T′ si They represent the time constant of ESS transmitting active power and the time constant transient short-circuit value respectively; T gi , R i They represent the time constant and droop coefficient of the turbine governor of the synchronous generator respectively; P ei Represents the output power of the synchronous generator; T doi , T′ doi They represent the time constant and transient short-circuit value of the synchronous generator d axis respectively; E fi Indicates the excitation voltage of the synchronous generator; u fi Represents the output voltage of the synchronous generator; x di, x′ di Represent d-axis synchronous reactance and transient reactance respectively; I di ,I qi Represent the d-axis and q-axis currents of the synchronous generator respectively;

[0018] According to the FG dynamic mechanics equations, we can get the following in the i-th subsystem:

[0019] State variables of the predictive control model: x i =[δ i ,ω i ,P i ,P si ] T ;

[0020] Predictive control input vector of the predictive control model: u i =[P ci ,u fi ,P srefi ] T ;

[0021] The predictive control outputs of the predictive control model include: E fi , P ci , P srefi ; According to E in the FG dynamic mechanics equations fi with u fi The relationship calculation E fi .

[0022] Furthermore, the objective function J k The expression of (x(k),u(k)) is as follows:

[0023]

[0024] Where α, β, and λ are weighting factors of the normalized objective function; Δu j (k) is the change in the predicted control input: Δu j (k) = u j (k)-u j (k-1), S u Represents the set of element numbers in the predictive control input vector; ω n Indicates the synchronous angular frequency; δ ref is the reference value of the rotor angle; ω n , δ ref These are reference signals that can be set as needed.

[0025] Furthermore, the expression of the constraint function g(x(k),u(k)) is as follows:

[0026]

[0027] In the formula, They are the lower limit and upper limit of mechanical power set according to demand; They are the lower limit and upper limit of the output power of the ESS set according to demand; They are the lower limit value and upper limit value of the reference set point of the ESS transmitted active power set according to the demand; They are the lower limit and upper limit of the set value of the steam turbine governor of the synchronous generator set according to the requirements; They are respectively the lower limit and upper limit of the output voltage of the synchronous generator set according to demand.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. In the present invention, each FG has its own local controller (MPC control module). The local controller only needs the local subsystem model and local measurement to generate the optimal control behavior, which solves the risk problems of the controller in the centralized control with a single center to solve the optimal control problem: communication delay and computing bottleneck.

[0030] 2. The present invention integrates ESS and SG into one FG. Compared with the lumped ESS, each FG only needs to be equipped with a smaller ESS, and even if some of them are out of service, the remaining ESSs can still work.

[0031] 3. MPC obtains the optimal control parameters of the system at the next moment (predictive control input vector u(k+1)) by real-time collection of system information. The optimal control parameters change in real time with the operation of the system. When a disturbance occurs in the system, the value of the optimal control parameter can be adjusted in time to restore the system to a stable state as soon as possible, thereby improving the transient stability of the system.

[0032] 4. Use ω n , δ ref As a reference signal, each FG of distributed control can maintain power angle synchronization.

[0033] 5. The upper and lower limits in the constraint function are set according to requirements, making MPC control flexible and scalable. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is the system architecture diagram of the distributed power supply control of the generator vehicle;

[0035] Figure 2 It is the MPC control schematic diagram of a single flexible generator set. DETAILED DESCRIPTION

[0036] 1) Distributed control principle

[0037] A distributed power supply control method for a power generation vehicle based on a flexible generator set comprises the following steps:

[0038] refer to Figure 1 As shown, the synchronous generator SG of each power generation vehicle is integrated with a corresponding energy storage system ESS, thereby forming a flexible generator set FG;

[0039] Each flexible generator set FG is used to supply power to a corresponding subsystem;

[0040] Configure an independent MPC control module for each flexible generator set FG;

[0041] The MPC control module collects the operating status parameters of the corresponding subsystem in real time, and performs model predictive control in combination with the reference signal, and outputs the predictive control output to the flexible generator set FG;

[0042] The controller of the flexible generator set FG uses the predicted control output as the power supply control input and outputs power according to the power supply control input.

[0043] In this specific implementation, the collected operating state parameters of the corresponding subsystems include: rotor angle δ i , rotor speed ω i , ESS output power P si Indicates the mechanical power P of the synchronous generator mi , the setting value P of the turbine speed governor of the synchronous generator ci , the reference set point P of the active power transmitted by the ESS srefi The output voltage u of the synchronous generator fi The above operating state parameters are collected to construct the state variables of MPC control and the predictive control input vector of MPC control.

[0044] In this specific implementation mode, ω n represents the synchronous angular frequency and δ ref is the reference value of the rotor angle as the reference signal.

[0045] In this specific implementation, the predicted control output includes E fi , P ci , P srefi .

[0046] refer to Figure 2 As shown in the figure, the MPC control module outputs the predicted control output E according to the collected operating state parameters and reference signals. fi , P ci , P srefito the FG controller (including the ESS controller and the SG controller), the FG controller uses the predicted control output as the power supply control input, and outputs power according to the power supply control input, wherein the SG output power P ei , ESS output power P si , the total output power of FG is P i .

[0047] 2) Establish FG dynamic mechanics equations

[0048] Based on the SG dynamic model and the dynamic model of the ESS power controller, the FG dynamic mechanical equations are established.

[0049] The dynamic model expression of the synchronous generator SG including the turbine governor inside the power car is:

[0050]

[0051] in

[0052]

[0053] Where i represents the subsystem number (i.e. the synchronous generator number), δ and ω are the rotor angle and speed respectively, and ω n is the synchronous angular frequency; E' q is the internal voltage of the generator, E f is the magnetic field voltage; M is the rotor inertia constant, K D is the damping coefficient; Y ij ∠θ ij is the admittance between nodes i and j; P m is the mechanical power, the setting value of the turbine speed governor is P c Indicates; the speed regulator time constant is T g , the droop coefficient is R; V t is the terminal voltage amplitude, θ is the terminal voltage angle; P e , Q e are the injected active power and reactive work respectively; T do , represents the open circuit transient time constant; x d 、x' d Represent d-axis synchronous reactance and transient reactance respectively; I d ,I q Represent the d-axis and q-axis currents of the synchronous generator respectively.

[0054] After ESS joins the system, the active power injected into the grid is calculated as follows:

[0055] P i =P ei +P si

[0056] Where P i is the total output active power of FG, P si is the active power output by the ESS.

[0057] The dynamic model expression of ESS power controller is:

[0058]

[0059] in,

[0060] Where P sref and T s is the reference set point and time constant for the storage system to transfer active power, K ω and K p are the ESS controller parameters.

[0061] Combining the SG dynamic model and ESS related expressions, the dynamic model of FG is obtained as follows:

[0062]

[0063] in,

[0064] In the formula, i represents the subsystem number, δ i and ω i are the rotor angle and speed, ω s is the fundamental rotor electrical speed, ω n is the synchronous angular frequency; M is the inertia constant of FG, K Di is the damping coefficient of FG; P i is the total output power of FG; P si Represents the output power of ESS; P mi Represents the mechanical power of the synchronous generator; P ci Indicates the setting value of the turbine speed governor of the synchronous generator; P srefi represents the reference set point of the ESS transmitted active power; T si , T′ si They represent the time constant of ESS transmitting active power and the time constant transient short-circuit value respectively; T gi , R i They represent the time constant and droop coefficient of the turbine governor of the synchronous generator respectively; P ei Represents the output power of the synchronous generator; T doi , T′ doi They represent the time constant and transient short-circuit value of the synchronous generator d axis respectively; E fi Indicates the excitation voltage of the synchronous generator; u fi Represents the output voltage of the synchronous generator; xdi , x′ di Represent d-axis synchronous reactance and transient reactance respectively; I di ,I qi Represent the d-axis and q-axis currents of the synchronous generator respectively;

[0065] According to the FG dynamic mechanics equations, we can get the following in the i-th subsystem:

[0066] State variables of the predictive control model: x i =[δ i ,ω i ,P i ,P si ] T ;

[0067] Predictive control input vector of the predictive control model: u i =[P ci ,u fi ,P srefi ] T ;

[0068] The predictive control outputs of the predictive control model include: E fi , P ci , P srefi ; According to E in the FG dynamic mechanics equations fi with u fi The relationship calculation E fi .

[0069] According to the controller output u fi , derive the excitation voltage E fi The calculation formula is:

[0070]

[0071] 3) Analyze the impact of ESS on FG damping and inertia, and determine the capacity of ESS

[0072] The power capacity of ESS is determined as follows:

[0073] Step 1: Linearize the SG model and combine it with the total output active power expression of FG to obtain:

[0074]

[0075] Step 2: Assume that ΔP occurs i disturbance, and the ESS is at full capacity Introduce the scalar h so that Rewrite the expression obtained in Step 1 as follows:

[0076]

[0077] Step 3: When the ESS is not running at full load, the FG dynamic model is reformed to obtain:

[0078]

[0079] Step 4: When ESS does not reach its power capacity and reaches its power capacity, the inertia constant and damping coefficient of FG are:

[0080]

[0081] Step 5: Ignoring the angular frequency and mechanical power deviation of the SG after the load change, when the ESS just reaches its power limit, the power output of the ESS is calculated as:

[0082]

[0083] Step 6: Considering that when FG starts at full load, it can have the maximum inertia constant and damping coefficient that the corresponding ESS can provide, the power capacity of ESS is:

[0084]

[0085] Where P N is the nominal active power of SG.

[0086] Step 7: For multiple emergencies, the recovery band of the interconnected system frequency should be within 10 minutes. Considering the bidirectional power flow of ESS, ESS usually retains half of its energy capacity. Therefore, the energy capacity of ESS is: Thereby ensuring the normal operation of the system.

[0087] 4) Determine the MPC control strategy equation group using the FG model

[0088] According to the control target: restore the SG rotor speed to ω n ; Make the rotor angle follow the reference trajectory; minimize control. Objective function J k The expression of (x(k),u(k)) is as follows:

[0089]

[0090] Where α, β, and λ are weighting factors of the normalized objective function; Δu j (k) is the change in the predicted control input: Δu j (k) = u j (k)-u j (k-1), S u Represents the set of element numbers in the predictive control input vector; ω n Indicates the synchronous angular frequency; δref is the reference value of the rotor angle; ω n , δ ref These are reference signals that can be set as needed.

[0091] The expression for determining the constraint function g(x(k),u(k)) regarding the control input and the system state is as follows:

[0092]

[0093] In the formula, They are the lower limit and upper limit of mechanical power set according to demand; They are the lower limit and upper limit of the output power of the ESS set according to demand; They are the lower limit value and upper limit value of the reference set point of the ESS transmitted active power set according to the demand; They are the lower limit and upper limit of the set value of the steam turbine governor of the synchronous generator set according to the requirements; They are respectively the lower limit and upper limit of the output voltage of the synchronous generator set according to demand.

[0094] According to the objective function and constraint function, the predictive control model of model predictive control is established as follows:

[0095]

[0096] In the formula, J k (x(k),u(k)) represents the objective function, k represents the time step, x(k) represents the state variable, u(k) represents the predictive control input vector, f(x(k),u(k)) represents the FG dynamic mechanical equations, and g(x(k),u(k)) represents the constraint function;

[0097] The state variable x(k+1) at time k+1 is predicted by the predictive control model and substituted into the dynamic mechanical equations of the flexible generator set FG to calculate the predictive control input vector u(k+1) at time k+1, and the predictive control output is calculated according to the predictive control input vector u(k+1) at time k+1.

[0098] MPC (Model Predictive Control) applies the first control action in the production sequence to the system and captures updated measurements from the system output. The optimal control problem is updated using the new measurements and the above process is repeated by advancing the prediction time by one step, thereby achieving optimal control of the system and improving the transient stability of the system.

Claims

1. A distributed power supply control method for a power generation vehicle based on a flexible generator set, characterized in that: The following steps are involved: The corresponding energy storage system ESS is integrated into the synchronous generator SG of each power generation vehicle to form a flexible generator set FG; each flexible generator set FG is used to supply power to the corresponding subsystem; Configure an independent MPC control module for each flexible generator set FG; The MPC control module collects the operating status parameters of the corresponding subsystem in real time, and performs model predictive control in combination with the reference signal, and outputs the predictive control output to the flexible generator set FG; The controller of the flexible generator set FG uses the predicted control output as the power supply control input and outputs power according to the power supply control input; Among them, the predictive control model of model predictive control is as follows: In the formula, J k (x(k),u(k)) represents the objective function, k represents the time step, x(k) represents the state variable, u(k) represents the predictive control input vector, f(x(k),u(k)) represents the FG dynamic mechanical equations, and g(x(k),u(k)) represents the constraint function; The state variable x(k+1) at time k+1 is predicted by the predictive control model and substituted into the dynamic mechanical equations of the flexible generator set FG, the predictive control input vector u(k+1) at time k+1 is calculated, and the predictive control output is calculated according to the predictive control input vector u(k+1) at time k+1; Based on the SG dynamic model and the dynamic model of the ESS power controller, the FG dynamic mechanical equations are established: in, In the formula, i represents the subsystem number, δ i and ω i are the rotor angle and speed, ω s is the fundamental rotor electrical speed, ω n is the synchronous angular frequency; M is the inertia constant of FG, K Di is the damping coefficient of FG; P i is the total output power of FG; P si Represents the output power of ESS; P mi Represents the mechanical power of the synchronous generator; P ci Indicates the setting value of the turbine speed governor of the synchronous generator; P srefi represents the reference set point of the ESS transmitted active power; T si , T′ si They represent the time constant of ESS transmitting active power and the time constant transient short-circuit value respectively; T gi , R i They represent the time constant and droop coefficient of the turbine governor of the synchronous generator respectively; P ei Represents the output power of the synchronous generator; T doi 、T d ' oi They represent the time constant and transient short-circuit value of the synchronous generator d axis respectively; E fi Indicates the excitation voltage of the synchronous generator; u fi Represents the output voltage of the synchronous generator; x di , x′ di Represent d-axis synchronous reactance and transient reactance respectively; I di ,I qi Represent the d-axis and q-axis currents of the synchronous generator respectively; According to the FG dynamic mechanics equations, we can get the following in the i-th subsystem: State variables of the predictive control model: x i =[δ i ,ω i ,P i ,P si ] T ; Predictive control input vector of the predictive control model: u i =[P ci ,u fi ,P srefi ] T ; The predictive control outputs of the predictive control model include: E fi , P ci , P srefi ; According to E in the FG dynamic mechanics equations fi with u fi The relationship calculation E fi ; Objective function J k The expression of (x(k),u(k)) is as follows: Where α, β, and λ are weighting factors of the normalized objective function; Δu j (k) is the change in the predicted control input: Δu j (k) = u j (k)-u j (k-1), S u Represents the set of element numbers in the predictive control input vector; ω n Indicates the synchronous angular frequency; δ ref is the reference value of the rotor angle; ω n , δ ref All are reference signals set on demand; The expression of the constraint function g(x(k),u(k)) is as follows: In the formula, They are the lower limit and upper limit of mechanical power set according to demand; They are the lower limit and upper limit of the output power of the ESS set according to demand; They are the lower limit value and upper limit value of the reference set point of the ESS transmitted active power set according to the demand; They are the lower limit and upper limit of the set value of the steam turbine governor of the synchronous generator set according to the requirements; They are respectively the lower limit and upper limit of the output voltage of the synchronous generator set according to demand.

2. The distributed power supply control method for a power generation vehicle based on a flexible generator set according to claim 1 is characterized in that: Determine the inertia constant M of FG and the damping coefficient K of FG according to the power capacity status of ESS Di : In the formula, Indicates the power capacity of the ESS; Indicates that the output power of the ESS does not reach the power capacity of the ESS. Indicates that the output power of the ESS reaches the power capacity of the ESS; K p , K ω All represent ESS controller parameters.

3. The distributed power supply control method for a power generation vehicle based on a flexible generator set according to claim 2 is characterized in that: The power capacity of ESS is determined as follows: Step 1: Linearize the SG model and combine it with the total output active power expression of FG to obtain: Step 2: Assume that ΔP occurs i disturbance, and the ESS is at full capacity Introduce the scalar h so that Rewrite the expression obtained in Step 1 as follows: Step 3: When the ESS is not running at full load, the FG dynamic model is reformed to obtain: Step 4: Ignoring the angular frequency and mechanical power deviation of the SG after the load change, when the ESS just reaches its power limit, the power output of the ESS is calculated as: Step 5: Considering that when FG starts at full load, it has the maximum inertia constant and damping coefficient that the corresponding ESS can provide, the power capacity of ESS is: Where P N is the nominal active power of SG.

4. The distributed power supply control method for a power generation vehicle based on a flexible generator set according to claim 3 is characterized in that: The energy capacity of the ESS is set to:

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