Self-adaptive frequency voltage secondary control method and device for off-grid micro-grid

Abstract

The invention provides an off-grid micro-grid adaptive frequency voltage secondary control method and device, and belongs to the technical field of power system operation and control. The method comprises the following steps: constructing a frequency control variable and a voltage control variable for secondary control of a controlled inverter in an off-grid micro-grid; based on the frequency control variable and the voltage control variable, respectively constructing interference-related dynamic linearization models of frequency and voltage secondary control of the micro-grid; and calculating an active power control instruction and a reactive power control instruction of the inverter based on the interference-related dynamic linearization model so as to realize secondary control of the frequency and the voltage of the micro-grid. According to the method, the efficiency, safety and flexibility of micro-grid voltage and frequency control under the scene of high renewable energy source permeability and incomplete model can be greatly improved, and the running safety and stability of the micro-grid are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system operation and control, and in particular relates to an off-grid microgrid adaptive frequency and voltage secondary control method and device. Background Art

[0002] Driven by energy and environmental issues, the proportion of renewable energy in the power grid is increasing, and large-scale, high-penetration renewable energy power generation and grid connection have become the forefront and hot spot in the international energy and power fields. At the same time, the construction of microgrids has a good promoting effect on low-carbon emission reduction, development of renewable energy, improvement of energy efficiency and improvement of power supply reliability. Microgrids can operate in two modes: grid-connected and off-grid. When an accident or special scenario occurs in the large power grid, the microgrid can switch to an off-grid operation model to ensure the power supply of important loads or as a black start power supply. For off-grid microgrids, secondary control is particularly important for maintaining the voltage and frequency of the microgrid.

[0003] In traditional microgrid research, accurate model-based methods are often used to achieve voltage or frequency secondary control. However, traditional model-based optimization control methods rely on accurate system model parameters, while the ideal model of the microgrid is difficult to obtain, and this model-based optimization method is difficult to apply in practice. In order to deal with the problem of incomplete models of microgrids, data-driven control methods have been proposed in recent years, which can use the measurement data of microgrids to learn system models. However, most of the existing data-driven methods are not adaptive, that is, in the scenario where the operating conditions of the microgrid are time-varying, the latest online measurement data cannot be used to timely correct the parameter information learned from the data. In addition, the existing data-driven methods are sensitive to outliers in the measurement data. In addition, most of the existing microgrid secondary control methods only consider the scenario where the local primary control of the controllable inverter in the microgrid is based on droop control. For the scenario where the controllable inverter in the microgrid uses a new adaptive network control method as the primary control, there is a lack of relevant research on the voltage and frequency secondary control of the microgrid. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and propose an off-grid microgrid adaptive frequency and voltage secondary control method and device. The present invention takes into account the situation that the primary control layer of the inverter in the off-grid microgrid is based on the new adaptive network control technology, and can coordinate the active and reactive instructions of each inverter in the off-grid microgrid to realize the voltage and frequency secondary control of the microgrid; the present invention does not require precise system model parameters, but uses online measurement data to learn the dynamic linearization model of the microgrid; the present invention is also adaptive to changes in system operating conditions. When the system operating conditions change, the present invention can use online measurement data to update the control parameters in time, thereby maintaining good control performance. The present invention can greatly improve the voltage and frequency control quality of the microgrid and improve the safety and stability of the microgrid operation.

[0005] The first embodiment of the present invention provides an off-grid microgrid adaptive frequency and voltage secondary control method, comprising:

[0006] Construct frequency control variables and voltage control variables for secondary control of controlled inverters in off-grid microgrids;

[0007] Based on the frequency control variable and the voltage control variable, constructing interference-related dynamic linearization models of the microgrid frequency and voltage secondary control respectively;

[0008] Based on the interference-related dynamic linearization model, active power control instructions and reactive power control instructions of the inverter are calculated to achieve secondary control of the frequency and voltage of the microgrid.

[0009] In a specific embodiment of the present invention, the frequency control variable and voltage control variable of the secondary control of the controlled inverter in the off-grid microgrid are constructed, including:

[0010] 1) Establish a model of the controlled inverter in the off-grid microgrid;

[0011] There are N off-grid microgrids. i 1 controlled inverter;

[0012] Among them, the voltage and phase angle equations of the i-th inverter are expressed as:

[0013]

[0014] Where V i ,θ i are the voltage amplitude and phase angle of the node of the i-th inverter, V i r , are the voltage set point and angular frequency set point of the i-th inverter, ω i is the actual angular frequency of the i-th inverter; V i ,θ i The derivative with respect to time; V i r2 、V i 2 Respectively represent V i r 、V i The square of P i , Q i are respectively the actual output active power and reactive power of the i-th inverter, P i * , is the active power setting instruction and reactive power setting instruction of the ith inverter from the secondary control; V dc,i is the actual value of the DC voltage on the DC side of the i-th inverter, is the set value of the DC voltage on the DC side of the i-th inverter; ΔP i , ΔQ i are functions related to the setting deviation of active power and reactive power of the i-th inverter respectively; Δφ vi , Δφ ωi are the voltage deviation function and frequency deviation function of the ith inverter related to the voltage change on the DC side of the inverter; η i , α i , κ i , i is the primary control parameter of the i-th inverter;

[0015] 2) Based on the result of step 1), construct the frequency control variable and voltage control variable of the secondary control of the controlled inverter;

[0016] Among them, at the kth moment, the frequency control quantity instruction and voltage control quantity instruction of the i-th inverter are respectively expressed as:

[0017]

[0018] In the formula, is the voltage control instruction of the i-th inverter at the k-th moment, is the voltage control quantity instruction of the i-th inverter at the k-th moment; represents the square of the voltage amplitude setting value of the i-th inverter node; P i * (k) are the active power and reactive power setting instructions of the i-th inverter from the secondary control at the k-th moment respectively.

[0019] In a specific embodiment of the present invention, the interference-related dynamic linearization models for the secondary control of the frequency and voltage of the microgrid are constructed separately, including:

[0020] 1) Construct the disturbance-related dynamic linearization model of microgrid frequency secondary control, the expression is as follows:

[0021] Δy F (k+1)=S F (k) T ·Δx F (k)+ξ F (k) (7)

[0022] in,

[0023] Δy F (k+1)=y F (k+1)-y F (k), Δx F (k) = x F (k)-x F (k-1)

[0024] In the formula, y F (k+1),y F (k) represents the frequency measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n F dimensional column vector, n F is the number of measured frequencies in the microgrid; y F Each element of (k+1) is the frequency measurement value of the key frequency node in the microgrid at the k+1th moment; Δy F (k+1) represents the increment of the frequency measurement vector in the microgrid at the k+1th moment, which is n F dimensional column vector; x F (k), x F (k-1) represents the vector composed of all frequency control instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x F The i-th element of (k) is S F (k) represents the frequency control pseudo partial derivative parameter at the kth moment, which is an N i Line n F Matrix of columns; S F (k) T Represents the matrix S F The transpose of (k) is an n F Row N i Matrix of columns; ξ F (k) represents the frequency control aggregate interference parameter at the kth moment, which is an n F -dimensional column vector;

[0025] 2) Construct the disturbance-related dynamic linearization model of microgrid voltage secondary control, the expression is as follows:

[0026] Δy U (k+1)=S U (k) T ·Δx U (k)+ξ U (k) (8)

[0027] in,

[0028] Δy U (k+1)=y U (k+1)-y U (k), Δx U (k) = x U (k)-x U (k-1)

[0029] In the formula, y U (k+1),y U (k) represents the voltage square measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n U dimensional column vector, n U is the voltage quantity measured in the microgrid; U Each element of (k+1) is the square of the voltage amplitude measurement value of the key voltage node in the microgrid at the k+1th moment; Δy U (k+1) represents the increment of the voltage square measurement vector in the microgrid at the k+1th moment, which is n U dimensional column vector; x U (k), x U (k-1) represents the vector composed of all voltage control quantity instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x U The i-th element of (k) is S U (k) represents the pseudo partial derivative parameter of voltage control at the kth moment, which is an N i Line n U Matrix of columns; S U (k) T Represents the matrix S U The transpose of (k) is an n U Row N i Matrix of columns; ξ U (k) represents the voltage control lumped interference parameter at the kth moment, which is an n U -dimensional column vector.

[0030] In a specific embodiment of the present invention, the calculating the active power control instruction and the reactive power control instruction of the inverter includes:

[0031] 1) At the kth moment, collect the frequency measurement values ​​of the key frequency nodes in the microgrid and obtain the frequency measurement vector y F (k), collect the square of the voltage amplitude measurement value of the key voltage node in the microgrid and obtain the voltage square measurement vector y U (k);

[0032] 2) Update the estimated values ​​of the pseudo partial derivative parameters of voltage control and the estimated values ​​of the pseudo partial derivative parameters of frequency control;

[0033] Among them, the robust recursive linear regression method based on the maximum correlation entropy criterion calculates the estimated value of the voltage control pseudo partial derivative parameter at the kth moment according to the following expression:

[0034]

[0035] c U (k) = exp(-||e US (k)|| 2 / (2σ 2 )) (10)

[0036]

[0037] Φ U (k) = β -1 (Φ U (k-1)-g U (k)x U (k-1) T Φ U (k-1)) (12)

[0038]

[0039] In the formula, Δy U (k) = y U (k)-y U (k-1) represents the increment of the voltage square measurement vector in the microgrid at the kth moment; Δx U (k-1)=x U (k-1)-x U (k-2) represents the increment of the voltage control quantity vector in the microgrid at the k-1th moment, where, at the moment k=1, Δx U (k-1) and Δx U (k-2) is the initial control value of the device itself at the previous moment, Δy U(k-1) represents the value actually measured at the previous moment; is the estimated value of the pseudo partial derivative parameter of voltage control at the k-1th moment, which is an N i Line n U A matrix of columns; Representation Matrix The transpose of is an n U Row N i Matrix of columns; e US (k) is the output estimation error of the voltage pseudo partial derivative parameter at the kth moment; c U (k) is the correlation entropy function value of the voltage output estimation error at the kth moment; σ U is the bandwidth parameter in the maximum correlation entropy criterion in voltage control; ||e US (k)|| 2 Represents the vector e US The square of the second norm of (k); g U (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion for the voltage at the kth moment, which is an n U Column vector of columns; β U is the forgetting factor parameter in voltage control; Φ U (k-1) is the inverse information matrix in the robust recursive linear regression method of the voltage at the k-1th moment, Φ U (k) is the inverse information matrix in the robust recursive linear regression method of the voltage at the kth moment;

[0040] Based on the maximum correlation entropy criterion, the robust recursive linear regression method calculates the estimated value of the frequency control pseudo partial derivative parameter at the kth moment according to the following expression:

[0041]

[0042] c F (k) = exp(-||e FS (k)|| 2 / (2σ 2 )) (15)

[0043]

[0044] Φ F (k) = β -1 (Φ F (k-1)-g F (k)x F (k-1) T Φ F (k-1)) (17)

[0045]

[0046] In the formula, Δy F (k) = y F (k)-y F (k-1) represents the increment of the frequency vector in the microgrid at the kth moment; Δx F (k-1)=x F (k-1)-x F (k-2) represents the increment of the frequency control quantity vector in the microgrid at the k-1th moment; is the estimated value of the frequency control pseudo partial derivative parameter at the k-1th moment, which is an N i Line n F A matrix of columns; Representation Matrix The transpose of is an n F Row N i Matrix of columns; e FS (k) is the output estimation error of the frequency pseudo partial derivative parameter at the kth moment; c F (k) is the correlation entropy function value of the frequency output estimation error at the kth moment; σ F is the bandwidth parameter in the maximum correlation entropy criterion in frequency control; ||e FS (k)|| 2 Represents the vector e FS The square of the second norm of (k); g F (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion at the kth moment frequency, which is an n F Column vector of columns; β F is the forgetting factor parameter in frequency control; Φ F (k-1) is the inverse information matrix in the robust recursive linear regression method of the k-1th moment frequency, Φ F (k) is the inverse information matrix in the robust recursive linear regression method of the frequency at the kth moment;

[0047] 3) Calculate the voltage control amount and frequency control amount;

[0048] Among them, the voltage control amount at the kth moment is calculated as follows:

[0049]

[0050] In the formula, y U ref (k+1) represents a vector composed of the squares of the voltage amplitude target reference values ​​in the microgrid at the k+1th moment; Represents y U (k) estimated value; represents the estimated value of the voltage control lumped disturbance parameter of the microgrid at the kth moment; represents the output estimation error of the voltage control lumped disturbance parameter at the kth moment; Representation Matrix The square of the norm of Ux , Ux They represent the step size parameter and inhibition term parameter of voltage control respectively; l U1 is the gain parameter of the voltage-controlled disturbance observer;

[0051] Calculate the frequency control amount at the kth moment, the expression is as follows:

[0052]

[0053] In the formula, y F ref (k+1) represents the vector composed of the frequency target reference value of the microgrid at the k+1th moment; Represents y F (k) estimated value; represents the estimated value of the frequency control lumped interference parameter of the microgrid at the kth moment; represents the output estimation error of the frequency control aggregate interference parameter at the kth moment; Representation Matrix The square of the norm of Fx , Fx They represent the step length parameter and suppression term parameter of frequency control respectively; l F1 is the gain parameter of the frequency controlled disturbance observer;

[0054] 4) Calculate the adaptive disturbance observer updates for voltage control and frequency control respectively:

[0055] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the voltage control at the kth moment is calculated in turn according to the following expression:

[0056]

[0057] In the formula, They represent the adaptive gain coefficient matrix of the voltage adaptive disturbance observer at the kth moment and the k-1th moment, respectively, and are L e n U Line n U Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n U Column vector of Uy (k) = e Uy (k)-e Uy (k-1) is the dimension nU Column vector of UO is the suppression term parameter of the adaptive disturbance observation for voltage control; for The square of the norm of ; is the estimated value of the voltage square output vector at the k+1th moment, is the estimated value of the voltage control lumped interference parameter at the k+1th moment;

[0058] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the frequency control at the kth moment is calculated in turn according to the following expression:

[0059]

[0060] In the formula, They represent the adaptive gain coefficient matrices of the frequency adaptive interference observer at the kth moment and the k-1th moment, respectively, and are L e n F Line n F Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n F Column vector of Fy (k) = e Fy (k)-e Fy (k-1) is the dimension n F Column vector of FO is the suppression term parameter of the adaptive interference observation for frequency control; for The square of the norm of ; is the estimated value of the frequency output vector at the k+1th moment, is the estimated value of the frequency control aggregate interference parameter at the k+1th moment;

[0061] 5) Calculate the active power control instructions and reactive power control instructions of each inverter respectively:

[0062] Among them, the active power control instructions and reactive power control instructions of the i-th inverter are:

[0063]

[0064] In the formula, is the voltage control vector x U The i-th element in (k), is the obtained frequency control vector x F The i-th element in (k);

[0065] 6) The active power control instructions and reactive power control instructions of each inverter obtained in step 5) are respectively issued to the local control layer of the corresponding inverter, and the local control layer of the inverter performs a control according to the issued power instructions.

[0066] The second embodiment of the present invention provides an off-grid microgrid adaptive frequency and voltage secondary control device, comprising:

[0067] A control variable construction module, used to construct frequency control variables and voltage control variables for secondary control of a controlled inverter in an off-grid microgrid;

[0068] An interference-related dynamic linearization model construction module is used to construct interference-related dynamic linearization models of the microgrid frequency and voltage secondary control respectively based on the frequency control variable and the voltage control variable;

[0069] A control module is used to calculate the active power control instruction and the reactive power control instruction of the inverter based on the interference-related dynamic linearization model to achieve secondary control of the frequency and voltage of the microgrid.

[0070] In a specific embodiment of the present invention, the frequency control variable and voltage control variable of the secondary control of the controlled inverter in the off-grid microgrid are constructed, including:

[0071] 1) Establish a model of the controlled inverter in the off-grid microgrid;

[0072] There are N off-grid microgrids. i 1 controlled inverter;

[0073] Among them, the voltage and phase angle equations of the i-th inverter are expressed as:

[0074]

[0075] Where V i ,θ i are the voltage amplitude and phase angle of the node of the i-th inverter, V i r , are the voltage set point and angular frequency set point of the i-th inverter, ω i is the actual angular frequency of the i-th inverter; V i ,θ i The derivative with respect to time; V i r2 、V i 2 Respectively represent V i r 、V i The square of Pi , Q i are respectively the actual output active power and reactive power of the i-th inverter, P i * , is the active power setting instruction and reactive power setting instruction of the ith inverter from the secondary control; V dc,i is the actual value of the DC voltage on the DC side of the i-th inverter, is the set value of the DC voltage on the DC side of the i-th inverter; ΔP i , ΔQ i are functions related to the setting deviation of active power and reactive power of the i-th inverter respectively; Δφ vi , Δφ ωi are the voltage deviation function and frequency deviation function of the ith inverter related to the voltage change on the DC side of the inverter; η i , α i , κ i , i is the primary control parameter of the i-th inverter;

[0076] 2) Based on the result of step 1), construct the frequency control variable and voltage control variable of the secondary control of the controlled inverter;

[0077] Among them, at the kth moment, the frequency control quantity instruction and voltage control quantity instruction of the i-th inverter are respectively expressed as:

[0078]

[0079] In the formula, is the voltage control instruction of the i-th inverter at the k-th moment, is the voltage control quantity instruction of the i-th inverter at the k-th moment; represents the square of the voltage amplitude setting value of the i-th inverter node; P i * (k) are the active power and reactive power setting instructions of the i-th inverter from the secondary control at the k-th moment respectively.

[0080] In a specific embodiment of the present invention, the interference-related dynamic linearization models for the secondary control of the frequency and voltage of the microgrid are constructed separately, including:

[0081] 1) Construct the disturbance-related dynamic linearization model of microgrid frequency secondary control, the expression is as follows:

[0082] Δy F (k+1)=S F (k) T ·Δx F (k)+ξF (k) (7)

[0083] in,

[0084] Δy F (k+1)=y F (k+1)-y F (k), Δx F (k) = x F (k)-x F (k-1)

[0085] In the formula, y F (k+1),y F (k) represents the frequency measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n F dimensional column vector, n F is the number of measured frequencies in the microgrid; y F Each element of (k+1) is the frequency measurement value of the key frequency node in the microgrid at the k+1th moment; Δy F (k+1) represents the increment of the frequency measurement vector in the microgrid at the k+1th moment, which is n F dimensional column vector; x F (k), x F (k-1) represents the vector composed of all frequency control instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x F The i-th element of (k) is S F (k) represents the frequency control pseudo partial derivative parameter at the kth moment, which is an N i Line n F Matrix of columns; S F (k) T Represents the matrix S F The transpose of (k) is an n F Row N i Matrix of columns; ξ F (k) represents the frequency control aggregate interference parameter at the kth moment, which is an n F -dimensional column vector;

[0086] 2) Construct the disturbance-related dynamic linearization model of microgrid voltage secondary control, the expression is as follows:

[0087] Δy U (k+1)=S U (k) T ·Δx U (k)+ξ U (k) (8)

[0088] in,

[0089] Δy U (k+1)=y U (k+1)-y U (k), Δx U (k) = x U (k)-x U (k-1)

[0090] In the formula, y U (k+1),y U (k) represents the voltage square measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n U dimensional column vector, n U is the voltage quantity measured in the microgrid; U Each element of (k+1) is the square of the voltage amplitude measurement value of the key voltage node in the microgrid at the k+1th moment; Δy U (k+1) represents the increment of the voltage square measurement vector in the microgrid at the k+1th moment, which is n U dimensional column vector; x U (k), x U (k-1) represents the vector composed of all voltage control quantity instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x U The i-th element of (k) is S U (k) represents the pseudo partial derivative parameter of voltage control at the kth moment, which is an N i Line n U Matrix of columns; S U (k) T Represents the matrix S U The transpose of (k) is an n U Row N i Matrix of columns; ξ U (k) represents the voltage control lumped interference parameter at the kth moment, which is an n U -dimensional column vector.

[0091] In a specific embodiment of the present invention, the calculating the active power control instruction and the reactive power control instruction of the inverter includes:

[0092] 1) At the kth moment, collect the frequency measurement values ​​of the key frequency nodes in the microgrid and obtain the frequency measurement vector y F (k), collect the square of the voltage amplitude measurement value of the key voltage node in the microgrid and obtain the voltage square measurement vector y U (k);

[0093] 2) Update the estimated values ​​of the pseudo partial derivative parameters of voltage control and the estimated values ​​of the pseudo partial derivative parameters of frequency control;

[0094] Among them, the robust recursive linear regression method based on the maximum correlation entropy criterion calculates the estimated value of the voltage control pseudo partial derivative parameter at the kth moment according to the following expression:

[0095]

[0096] c U (k) = exp(-||e US (k)|| 2 / (2σ 2 )) (10)

[0097]

[0098] Φ U (k) = β -1 (Φ U (k-1)-g U (k)x U (k-1) T Φ U (k-1)) (12)

[0099]

[0100] In the formula, Δy U (k) = y U (k)-y U (k-1) represents the increment of the voltage square measurement vector in the microgrid at the kth moment; Δx U (k-1)=x U (k-1)-x U (k-2) represents the increment of the voltage control quantity vector in the microgrid at the k-1th moment, where, at the moment k=1, Δx U (k-1) and Δx U (k-2) is the initial control value of the device itself at the previous moment, Δy U (k-1) represents the value actually measured at the previous moment; is the estimated value of the pseudo partial derivative parameter of voltage control at the k-1th moment, which is an N i Line n U A matrix of columns; Representation Matrix The transpose of is an n U Row N i Matrix of columns; e US (k) is the output estimation error of the voltage pseudo partial derivative parameter at the kth moment; c U(k) is the correlation entropy function value of the voltage output estimation error at the kth moment; σ U is the bandwidth parameter in the maximum correlation entropy criterion in voltage control; ||e US (k)|| 2 Represents the vector e US The square of the second norm of (k); g U (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion for the voltage at the kth moment, which is an n U Column vector of columns; β U is the forgetting factor parameter in voltage control; Φ U (k-1) is the inverse information matrix in the robust recursive linear regression method of the voltage at the k-1th moment, Φ U (k) is the inverse information matrix in the robust recursive linear regression method of the voltage at the kth moment;

[0101] Based on the maximum correlation entropy criterion, the robust recursive linear regression method calculates the estimated value of the frequency control pseudo partial derivative parameter at the kth moment according to the following expression:

[0102]

[0103] c F (k) = exp(-||e FS (k)|| 2 / (2σ 2 )) (15)

[0104]

[0105] Φ F (k) = β -1 (Φ F (k-1)-g F (k)x F (k-1) T Φ F (k-1)) (17)

[0106]

[0107] In the formula, Δy F (k) = y F (k)-y F (k-1) represents the increment of the frequency vector in the microgrid at the kth moment; Δx F (k-1)=x F (k-1)-x F (k-2) represents the increment of the frequency control quantity vector in the microgrid at the k-1th moment; is the estimated value of the frequency control pseudo partial derivative parameter at the k-1th moment, which is an N i Line n F A matrix of columns; Representation Matrix The transpose of is an n F Row N i Matrix of columns; e FS (k) is the output estimation error of the frequency pseudo partial derivative parameter at the kth moment; c F (k) is the correlation entropy function value of the frequency output estimation error at the kth moment; σ F is the bandwidth parameter in the maximum correlation entropy criterion in frequency control; ||e FS (k)|| 2 Represents the vector e FS The square of the second norm of (k); g F (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion at the kth moment frequency, which is an n F Column vector of columns; β F is the forgetting factor parameter in frequency control; Φ F (k-1) is the inverse information matrix in the robust recursive linear regression method of the k-1th moment frequency, Φ F (k) is the inverse information matrix in the robust recursive linear regression method of the frequency at the kth moment;

[0108] 3) Calculate the voltage control amount and frequency control amount;

[0109] Among them, the voltage control amount at the kth moment is calculated as follows:

[0110]

[0111] In the formula, y U ref (k+1) represents a vector composed of the squares of the voltage amplitude target reference values ​​in the microgrid at the k+1th moment; Represents y U (k) estimated value; represents the estimated value of the voltage control lumped disturbance parameter of the microgrid at the kth moment; represents the output estimation error of the voltage control lumped disturbance parameter at the kth moment; Representation Matrix The square of the norm of Ux , Ux They represent the step size parameter and inhibition term parameter of voltage control respectively; l U1 is the gain parameter of the voltage-controlled disturbance observer;

[0112] Calculate the frequency control amount at the kth moment, the expression is as follows:

[0113]

[0114] In the formula, y F ref (k+1) represents the vector composed of the frequency target reference value of the microgrid at the k+1th moment; Represents y F (k) estimated value; represents the estimated value of the frequency control lumped interference parameter of the microgrid at the kth moment; represents the output estimation error of the frequency control aggregate interference parameter at the kth moment; Representation Matrix The square of the norm of Fx , Fx They represent the step length parameter and suppression term parameter of frequency control respectively; l F1 is the gain parameter of the frequency controlled disturbance observer;

[0115] 4) Calculate the adaptive disturbance observer updates for voltage control and frequency control respectively:

[0116] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the voltage control at the kth moment is calculated in turn according to the following expression:

[0117]

[0118] In the formula, They represent the adaptive gain coefficient matrix of the voltage adaptive disturbance observer at the kth moment and the k-1th moment, respectively, and are L e n U Line n U Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n U Column vector of Uy (k) = e Uy (k)-e Uy (k-1) is the dimension n U Column vector of UO is the suppression term parameter of the adaptive disturbance observation for voltage control; for The square of the norm of ; is the estimated value of the voltage square output vector at the k+1th moment, is the estimated value of the voltage control lumped interference parameter at the k+1th moment;

[0119] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the frequency control at the kth moment is calculated in turn according to the following expression:

[0120]

[0121] In the formula, They represent the adaptive gain coefficient matrices of the frequency adaptive interference observer at the kth moment and the k-1th moment, respectively, and are L e n F Line n F Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n F Column vector of Fy (k) = e Fy (k)-e Fy (k-1) is the dimension n F Column vector of FO is the suppression term parameter of the adaptive interference observation for frequency control; for The square of the norm of ; is the estimated value of the frequency output vector at the k+1th moment, is the estimated value of the frequency control aggregate interference parameter at the k+1th moment;

[0122] 5) Calculate the active power control instructions and reactive power control instructions of each inverter respectively:

[0123] Among them, the active power control instructions and reactive power control instructions of the i-th inverter are:

[0124]

[0125] In the formula, is the voltage control vector x U The i-th element in (k), is the obtained frequency control vector x F The i-th element in (k);

[0126] 6) The active power control instructions and reactive power control instructions of each inverter obtained in step 5) are respectively issued to the local control layer of the corresponding inverter, and the local control layer of the inverter performs a control according to the issued power instructions.

[0127] A third aspect of the present invention provides an electronic device, including:

[0128] at least one processor; and a memory communicatively coupled to the at least one processor;

[0129] The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the above-mentioned off-grid microgrid adaptive frequency and voltage secondary control method.

[0130] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned off-grid microgrid adaptive frequency and voltage secondary control method.

[0131] The characteristics and beneficial effects of the present invention are:

[0132] According to the characteristics of the primary control of the controllable inverter in the microgrid, the present invention constructs voltage control variables and frequency control variables for the controlled inverter respectively, so as to decouple the voltage secondary control and the frequency secondary control. Then, the interference-related dynamic linearization model of the microgrid system is constructed for the microgrid voltage secondary control and the frequency secondary control respectively. In the real-time control process, the secondary coordination controller of the microgrid continuously collects the real-time measurement data of the system, updates the pseudo partial derivative parameters in the data-driven interference-related dynamic linearization model in real time based on a robust recursive linear regression method, and estimates the lumped interference term in the data-driven interference-related dynamic linearization model based on an adaptive interference observer; based on the real-time updated data-driven interference-related dynamic linearization model, the secondary coordination controller of the microgrid iteratively updates the control instructions of the voltage control variable and the frequency control variable, and converts the voltage control variable and the frequency control variable control instructions of each inverter into the active and reactive control instructions of the inverter. Each inverter in the microgrid receives the active and reactive control instructions and executes the local primary control, and finally realizes the coordinated control of the microgrid and the voltage and frequency, so that the voltage and frequency of the microgrid can be maintained at the target reference value.

[0133] The present invention can greatly improve the efficiency, safety and flexibility of voltage and frequency control of microgrids in scenarios with high renewable energy penetration and incomplete models. It is particularly suitable for microgrids with serious model incompleteness problems and strong uncertainty. It can maintain the voltage and frequency tracking target reference values ​​of the microgrid without building a system model. It is adaptive to changes in system operating conditions and is suitable for large-scale promotion.

[0134] 1) The present invention adopts a robust recursive linear regression method based on the maximum relevant entropy criterion, uses online measurement data to learn the data-driven dynamic linearization model of the microgrid, and learns the microgrid model from historical data. It does not rely on the precise model parameters of the microgrid, and can achieve secondary control of the voltage and frequency of the microgrid in the scenario of incomplete model. When the system operating conditions change, the data-driven dynamic linearization model can be updated in real time to track system changes;

[0135] 2) The present invention estimates the lumped disturbance parameters based on an adaptive disturbance observer to improve the control performance in the presence of unmodeled system dynamics and uncertain disturbances;

[0136] 3) The present invention does not rely on the precise model parameters of the microgrid, and the control instruction update adopts a recursive calculation method, does not require complex calculations, has a simple structure that is easy to implement, has a small amount of calculation, and has strong robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0137] Figure 1 It is an overall flow chart of an off-grid microgrid adaptive frequency and voltage secondary control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0138] The present invention proposes an off-grid microgrid adaptive frequency and voltage secondary control method and device, which are further described in detail below with reference to the accompanying drawings and specific embodiments.

[0139] The first embodiment of the present invention provides an off-grid microgrid adaptive frequency and voltage secondary control method, comprising:

[0140] Construct frequency control variables and voltage control variables for secondary control of controlled inverters in off-grid microgrids;

[0141] Based on the frequency control variable and the voltage control variable, constructing interference-related dynamic linearization models of the microgrid frequency and voltage secondary control respectively;

[0142] Based on the interference-related dynamic linearization model, active power control instructions and reactive power control instructions of the inverter are calculated to achieve secondary control of the frequency and voltage of the microgrid.

[0143] In a specific embodiment of the present invention, the off-grid microgrid adaptive frequency and voltage secondary control method has an overall process as follows: Figure 1 As shown, the following steps are included:

[0144] 1) Construct the frequency control variables and voltage control variables of the secondary control of the controlled inverter in the off-grid microgrid; the specific steps are as follows:

[0145] 1-1) Establish a model of the controlled inverter in the off-grid microgrid.

[0146] In this embodiment, it is assumed that there are N off-grid microgrids. i The primary control of the controlled inverter equipment adopts a new adaptive network control technology. For the controlled inverter, its voltage and phase angle equations are expressed as:

[0147]

[0148] Where V i ,θ i are the voltage amplitude and phase angle of the node of the i-th inverter, V i r , are the voltage set point and angular frequency set point of the i-th inverter, ω i is the actual angular frequency of the i-th inverter. V i ,θ i The derivative with respect to time. V i r2 、V i 2 Respectively represent V i r 、V i The square of P i , Q i are respectively the actual output active power and reactive power of the i-th inverter, P i * , is the active power setting command and reactive power setting command of the i-th inverter from the secondary control. dc,i is the actual value of the DC voltage on the DC side of the i-th inverter, is the set value of the DC voltage on the DC side of the i-th inverter. i , ΔQ i are functions related to the active power and reactive power setting deviations of the i-th inverter, respectively, and their definitions are shown in formula (3). vi , Δφ ωi are the voltage deviation function and frequency deviation function of the ith inverter related to the voltage change on the DC side of the inverter, respectively, and their definitions are shown in formula (4). i , α i , κ i , i is the primary control parameter of the i-th inverter, and its typical values ​​are 0.01, 0.1, 1.1, and 0.1 respectively.

[0149] 1-2) Based on the result of step 1-1), construct the frequency control variable and voltage control variable of the secondary control of the controlled inverter.

[0150] In this embodiment, at the kth moment, in order to decouple the voltage secondary control from the frequency secondary control at the secondary control layer, the frequency control value instruction and the voltage control value instruction of the controlled i-th inverter are defined as:

[0151]

[0152] In the formula, is the voltage control instruction of the i-th inverter at the k-th moment, is the voltage control instruction of the i-th inverter at the k-th moment. Represents the square of the voltage amplitude setting value of the i-th inverter node. i * (k) are the active power and reactive power setting instructions of the i-th inverter from the secondary control at the k-th moment respectively.

[0153] 2) Based on the results of step 1), the disturbance-related dynamic linearization models of microgrid frequency and voltage secondary control are constructed respectively. The specific steps are as follows:

[0154] 2-1) Construct the disturbance-related dynamic linearization model of microgrid frequency secondary control, the expression is as follows:

[0155] Δy F (k+1)=S F (k) T Δx F (k)+ξ F (k) (7)

[0156] in,

[0157] Δy F (k+1)=y F (k+1)-y F (k), Δx F (k) = x F (k)-x F (k-1)

[0158] In the formula, y F (k+1),y F (k) represents the frequency measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n F dimensional column vector, n F is the number of measured frequencies in the microgrid. F Each element of (k+1) is the frequency measurement value of the key frequency node in the microgrid at the k+1th moment. F (k+1) represents the increment of the frequency measurement vector in the microgrid at the k+1th moment, which is n Fdimensional column vector. F (k), x F (k-1) represents the vector composed of all frequency control instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector, N i is the number of controlled inverters in the off-grid microgrid. Specifically, x F The i-th element of (k) is S F (k) represents the frequency control pseudo partial derivative parameter at the kth moment, which is an N i Line n F A matrix of columns. S F (k) T Represents the matrix S F The transpose of (k) is an n F Row N i ξ is a matrix of columns. F (k) represents the frequency control aggregate interference parameter at the kth moment, which is an n F -dimensional column vector.

[0159] 2-2) Construct the disturbance-related dynamic linearization model of microgrid voltage secondary control, the expression is as follows:

[0160] Δy U (k+1)=S U (k) T Δx U (k)+ξ U (k) (8)

[0161] in,

[0162] Δy U (k+1)=y U (k+1)-y U (k), Δx U (k) = x U (k)-x U (k-1)

[0163] In the formula, y U (k+1),y U (k) represents the voltage square measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n U dimensional column vector, n U is the voltage quantity measured in the microgrid. U Each element of (k+1) is the square of the voltage amplitude measurement value of the key voltage node in the microgrid at the k+1th moment. U (k+1) represents the increment of the voltage square measurement vector in the microgrid at the k+1th moment, which is nU dimensional column vector. U (k), x U (k-1) represents the vector composed of all voltage control quantity instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector. Specifically, x U The i-th element of (k) is S U (k) represents the pseudo partial derivative parameter of voltage control at the kth moment, which is an N i Line n U A matrix of columns. S U (k) T Represents the matrix S U The transpose of (k) is an n U Row N i ξ is a matrix of columns. U (k) represents the voltage control lumped interference parameter at the kth moment, which is an n U -dimensional column vector.

[0164] 3) Starting from k=1, the kth moment is taken as the current control moment.

[0165] 4) Based on the interference-related dynamic linearization model established in step 2), the frequency and voltage secondary control instructions of the microgrid are calculated.

[0166] Among them, for k ≥ 1, the microgrid secondary coordination controller performs the following calculation steps at the kth time:

[0167] 4-1) At the kth moment, collect the real-time measurement values ​​of the microgrid.

[0168] In this embodiment, the frequency measurement values ​​of the key frequency nodes in the microgrid are collected and the frequency measurement vector y is obtained. F (k), collect the square of the voltage amplitude measurement value of the key voltage node in the microgrid and obtain the voltage square measurement vector y U (k).

[0169] 4-2) Update the estimated values ​​of the pseudo-partial derivative parameters of voltage control and the estimated values ​​of the pseudo-partial derivative parameters of frequency control.

[0170] In this embodiment, the robust recursive linear regression method based on the maximum correlation entropy criterion calculates the estimated value of the voltage control pseudo partial derivative parameter at the kth moment in sequence according to the following expression:

[0171]

[0172] c U (k) = exp(-||e US (k)||2 / (2σ 2 )) (10)

[0173]

[0174] Φ U (k) = β -1 (Φ U (k-1)-g U (k)x U (k-1) T Φ U (k-1)) (12)

[0175]

[0176] In the formula, Δy U (k) = y U (k)-y U (k-1) represents the increment of the voltage square measurement vector in the microgrid at the kth moment. Δx U (k-1)=x U (k-1)-x U (k-2) represents the increment of the voltage control quantity vector in the microgrid at the k-1th moment. At the moment k=1, Δx U (k-1) and Δx U (k-2) is the initial control value of the device itself at the previous moment, Δy U (k-1) represents the value actually measured at the previous moment. is the estimated value of the pseudo partial derivative parameter of voltage control at the k-1th moment, which is an N i Line n U Matrix of columns. Representation Matrix The transpose of is an n U Row N i A matrix of columns. US (k) is the output estimation error of the voltage pseudo partial derivative parameter at the kth moment. U (k) is the correlation entropy function value of the voltage output estimation error at the kth moment, which is a scalar. σ U is the bandwidth parameter in the maximum correlation entropy criterion in voltage control, and its typical value can be taken as 0.01. ||e US (k)|| 2 Represents the vector e US The square of the second norm of (k). g U (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion for the voltage at the kth moment, which is an n U Column vector of columns. β Uis the forgetting factor parameter in voltage control, and its typical value can be taken as 0.99. U (k-1) is the inverse information matrix in the robust recursive linear regression method of the voltage at the k-1th moment, Φ U (k) is the inverse information matrix in the robust recursive linear regression method of the voltage at the kth moment. For the preceding moment of k=1, a smaller initial value can be taken, and the typical value is to set all elements to 0.01.

[0177] Based on the maximum correlation entropy criterion, the robust recursive linear regression method calculates the estimated value of the frequency control pseudo partial derivative parameter at the kth moment according to the following expression:

[0178]

[0179] c F (k) = exp(-||e FS (k)|| 2 / (2σ 2 )) (15)

[0180]

[0181] Φ F (k) = β -1 (Φ F (k-1)-g F (k)x F (k-1) T Φ F (k-1)) (17)

[0182]

[0183] In the formula, Δy F (k) = y F (k)-y F (k-1) represents the increment of the frequency vector in the microgrid at the kth moment. Δx F (k-1)=x F (k-1)-x F (k-2) represents the increment of the frequency control quantity vector in the microgrid at the k-1th moment. is the estimated value of the frequency control pseudo partial derivative parameter at the k-1th moment, which is an N i Line n F Matrix of columns. Representation Matrix The transpose of is an n F Row N i A matrix of columns. FS (k) is the output estimation error of the frequency pseudo partial derivative parameter at the kth moment.F (k) is the value of the relevant entropy function of the frequency output estimation error at the kth moment, which is a scalar. σ F is the bandwidth parameter in the maximum correlation entropy criterion in frequency control, and its typical value can be taken as 0.01. FS (k)|| 2 Represents the vector e FS The square of the second norm of (k). g F (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion at the kth moment frequency, which is an n F Column vector of columns. β F is the forgetting factor parameter in frequency control, and its typical value can be taken as 0.99. F (k-1) is the inverse information matrix in the robust recursive linear regression method of the k-1th moment frequency, Φ F (k) is the inverse information matrix in the robust recursive linear regression method for the frequency at the kth moment.

[0184] 4-3) Calculate the voltage control amount and frequency control amount.

[0185] In this embodiment, the voltage control amount at the kth moment is calculated, and the expression is as follows:

[0186]

[0187] In the formula, y U ref (k+1) represents a vector composed of the squares of the voltage amplitude target reference values ​​in the microgrid at the k+1th moment. Represents y U (k) is the estimated value. It represents the estimated value of the voltage control lumped disturbance parameter of the microgrid at the kth moment. Represents the output estimation error of the voltage control lumped disturbance parameter at the kth moment. Representation Matrix The square of the norm of . Ux , Ux They represent the step size parameter and suppression term parameter of voltage control, and their typical values ​​are 0.1 and 0.01 respectively. U1 is the gain parameter of the voltage-controlled disturbance observer, and its typical value can be taken as 0.9.

[0188] Calculate the frequency control amount at the kth moment, the expression is as follows:

[0189]

[0190] In the formula, y F ref(k+1) represents a vector composed of the frequency target reference values ​​of the microgrid at the k+1th moment. Represents y F (k) is the estimated value. It represents the estimated value of the frequency control lumped interference parameter of the microgrid at the kth moment. Represents the output estimation error of the frequency control aggregate interference parameter at the kth moment. Representation Matrix The square of the norm of . Fx , Fx They represent the step size parameter and suppression term parameter of frequency control, and their typical values ​​are 0.1 and 0.01 respectively. F1 is the gain parameter of the frequency-controlled disturbance observer, and its typical value can be taken as 0.9.

[0191] 4-4) Calculate the adaptive disturbance observer updates for voltage control and frequency control respectively:

[0192] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the voltage control at the kth moment is calculated in turn according to the following expression:

[0193]

[0194] In the formula, They represent the adaptive gain coefficient matrix of the voltage adaptive disturbance observer at the kth moment and the k-1th moment, respectively, and are L e n U Line n U A matrix of columns. L e ≥1 is the length of the historical time window of the adaptive disturbance observer, which is a positive integer and its typical value is 3. For a dimension L e n U Column vector of . Among them, Δe Uy (k) = e Uy (k)-e Uy (k-1) is the dimension n U λ is a column vector of UO is the suppression parameter of the adaptive disturbance observation of voltage control, and its typical value can be taken as 0.1. for The square of the norm of . is the estimated value of the voltage square output vector at the k+1th moment, is the estimated value of the voltage control lumped interference parameter at the k+1th moment.

[0195] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the frequency control at the kth moment is calculated in turn according to the following expression:

[0196]

[0197] in, They represent the adaptive gain coefficient matrices of the frequency adaptive interference observer at the kth moment and the k-1th moment, respectively, and are L e n F Line n F A matrix of columns. L e ≥1 is the length of the historical time window of the adaptive disturbance observer, which is a positive integer and its typical value is 3. For a dimension L e n F Column vector of . Among them, Δe Fy (k) = e Fy (k)-e Fy (k-1) is the dimension n F λ is a column vector of FO is the suppression parameter of the frequency-controlled adaptive interference observation, and its typical value can be taken as 0.1. for The square of the norm of . is the estimated value of the frequency output vector at the k+1th moment, is the estimated value of the frequency control aggregate interference parameter at the k+1th moment.

[0198] 4-5) Calculate the active power control command and reactive power control command of each inverter respectively:

[0199] Based on the obtained voltage and frequency control quantities, the active power control command and reactive power control command of the i-th inverter are calculated as follows:

[0200]

[0201] In the formula, is the voltage control vector x U The i-th element in (k), is the obtained frequency control vector x F The i-th element in (k).

[0202] 4-6) The secondary coordination controller sends the active power control instructions and reactive power control instructions of each inverter obtained in step 4-5) to the local control layer of the corresponding inverter respectively, and the local control layer of the inverter performs primary control according to the sent power instructions.

[0203] The method described in this embodiment issues a secondary control instruction, and the inverter itself performs local primary control adjustment according to the secondary control instruction.

[0204] 5) Let k=k+1, and then return to step 3).

[0205] To implement the above embodiment, a second aspect of the present invention provides an off-grid microgrid adaptive frequency and voltage secondary control device, comprising:

[0206] A control variable construction module, used to construct frequency control variables and voltage control variables for secondary control of a controlled inverter in an off-grid microgrid;

[0207] An interference-related dynamic linearization model construction module is used to construct interference-related dynamic linearization models of the microgrid frequency and voltage secondary control respectively based on the frequency control variable and the voltage control variable;

[0208] A control module is used to calculate the active power control instruction and the reactive power control instruction of the inverter based on the interference-related dynamic linearization model to achieve secondary control of the frequency and voltage of the microgrid.

[0209] In a specific embodiment of the present invention, the frequency control variable and voltage control variable of the secondary control of the controlled inverter in the off-grid microgrid are constructed, including:

[0210] 1) Establish a model of the controlled inverter in the off-grid microgrid;

[0211] There are N off-grid microgrids. i 1 controlled inverter;

[0212] Among them, the voltage and phase angle equations of the i-th inverter are expressed as:

[0213]

[0214]

[0215] Where V i ,θ i are the voltage amplitude and phase angle of the node of the i-th inverter, V i r , are the voltage set point and angular frequency set point of the i-th inverter, ω i is the actual angular frequency of the i-th inverter; V i ,θ i The derivative with respect to time; V i r2 、V i 2 Respectively represent V i r 、V i The square of P i , Qi are respectively the actual output active power and reactive power of the i-th inverter, P i * , is the active power setting instruction and reactive power setting instruction of the ith inverter from the secondary control; V dc,i is the actual value of the DC voltage on the DC side of the i-th inverter, is the set value of the DC voltage on the DC side of the i-th inverter; ΔP i , ΔQ i are functions related to the setting deviation of active power and reactive power of the i-th inverter respectively; Δφ vi , Δφ ωi are the voltage deviation function and frequency deviation function of the ith inverter related to the voltage change on the DC side of the inverter; η i , α i , κ i , i is the primary control parameter of the i-th inverter;

[0216] 2) Based on the result of step 1), construct the frequency control variable and voltage control variable of the secondary control of the controlled inverter;

[0217] Among them, at the kth moment, the frequency control quantity instruction and voltage control quantity instruction of the i-th inverter are respectively expressed as:

[0218]

[0219] in, is the voltage control instruction of the i-th inverter at the k-th moment, is the voltage control quantity instruction of the i-th inverter at the k-th moment; represents the square of the voltage amplitude setting value of the i-th inverter node; P i * (k) are the active power and reactive power setting instructions of the i-th inverter from the secondary control at the k-th moment respectively.

[0220] In a specific embodiment of the present invention, the interference-related dynamic linearization models for the secondary control of the frequency and voltage of the microgrid are constructed separately, including:

[0221] 1) Construct the disturbance-related dynamic linearization model of microgrid frequency secondary control, the expression is as follows:

[0222] Δy F (k+1)=S F (k) T Δx F (k)+ξ F(k) (7)

[0223] in,

[0224] Δy F (k+1)=y F (k+1)-y F (k), Δx F (k) = x F (k)-x F (k-1)

[0225] In the formula, y F (k+1),y F (k) represents the frequency measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n F dimensional column vector, n F is the number of measured frequencies in the microgrid; y F Each element of (k+1) is the frequency measurement value of the key frequency node in the microgrid at the k+1th moment; Δy F (k+1) represents the increment of the frequency measurement vector in the microgrid at the k+1th moment, which is n F dimensional column vector; x F (k), x F (k-1) represents the vector composed of all frequency control instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x F The i-th element of (k) is S F (k) represents the frequency control pseudo partial derivative parameter at the kth moment, which is an N i Line n F Matrix of columns; S F (k) T Represents the matrix S F The transpose of (k) is an n F Row N i Matrix of columns; ξ F (k) represents the frequency control aggregate interference parameter at the kth moment, which is an n F dimensional column vector;

[0226] 2) Construct the disturbance-related dynamic linearization model of microgrid voltage secondary control, the expression is as follows:

[0227] Δy U (k+1)=S U (k) T Δx U (k)+ξ U (k) (8)

[0228] in,

[0229] Δy U (k+1)=y U (k+1)-y U (k), Δx U (k) = x U (k)-x U (k-1)

[0230] In the formula, y U (k+1),y U (k) represents the voltage square measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n U dimensional column vector, n U is the voltage quantity measured in the microgrid; U Each element of (k+1) is the square of the voltage amplitude measurement value of the key voltage node in the microgrid at the k+1th moment; Δy U (k+1) represents the increment of the voltage square measurement vector in the microgrid at the k+1th moment, which is n U dimensional column vector; x U (k), x U (k-1) represents the vector composed of all voltage control quantity instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x U The i-th element of (k) is S U (k) represents the pseudo partial derivative parameter of voltage control at the kth moment, which is an N i Line n U Matrix of columns; S U (k) T Represents the matrix S U The transpose of (k) is an n U Row N i Matrix of columns; ξ U (k) represents the voltage control lumped interference parameter at the kth moment, which is an n U -dimensional column vector.

[0231] In a specific embodiment of the present invention, the calculating the active power control instruction and the reactive power control instruction of the inverter includes:

[0232] 1) At the kth moment, collect the frequency measurement values ​​of the key frequency nodes in the microgrid and obtain the frequency measurement vector y F (k), collect the square of the voltage amplitude measurement value of the key voltage node in the microgrid and obtain the voltage square measurement vector y U (k);

[0233] 2) Update the estimated values ​​of the pseudo partial derivative parameters of voltage control and the estimated values ​​of the pseudo partial derivative parameters of frequency control;

[0234] Among them, the robust recursive linear regression method based on the maximum correlation entropy criterion calculates the estimated value of the voltage control pseudo partial derivative parameter at the kth moment according to the following expression:

[0235]

[0236] c U (k) = exp(-||e US (k)|| 2 / (2σ 2 )) (10)

[0237]

[0238] Φ U (k) = β -1 (Φ U (k-1)-g U (k)x U (k-1) T Φ U (k-1)) (12)

[0239]

[0240] In the formula, Δy U (k) = y U (k)-y U (k-1) represents the increment of the voltage square measurement vector in the microgrid at the kth moment; Δx U (k-1)=x U (k-1)-x U (k-2) represents the increment of the voltage control quantity vector in the microgrid at the k-1th moment, where, at the moment k=1, Δx U (k-1) and Δx U (k-2) is the initial control value of the device itself at the previous moment, Δy U (k-1) represents the value actually measured at the previous moment; is the estimated value of the pseudo partial derivative parameter of voltage control at the k-1th moment, which is an N i Line n U A matrix of columns; Representation Matrix The transpose of is an n U Row N i Matrix of columns; e US (k) is the output estimation error of the voltage pseudo partial derivative parameter at the kth moment; c U(k) is the correlation entropy function value of the voltage output estimation error at the kth moment; σ U is the bandwidth parameter in the maximum correlation entropy criterion in voltage control; ||e US (k)|| 2 Represents the vector e US The square of the second norm of (k); g U (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion for the voltage at the kth moment, which is an n U Column vector of columns; β U is the forgetting factor parameter in voltage control; Φ U (k-1) is the inverse information matrix in the robust recursive linear regression method of the voltage at the k-1th moment, Φ U (k) is the inverse information matrix in the robust recursive linear regression method of the voltage at the kth moment;

[0241] Based on the maximum correlation entropy criterion, the robust recursive linear regression method calculates the estimated value of the frequency control pseudo partial derivative parameter at the kth moment according to the following expression:

[0242]

[0243] c F (k) = exp(-||e FS (k)|| 2 / (2σ 2 )) (15)

[0244]

[0245] Φ F (k) = β -1 (Φ F (k-1)-g F (k)x F (k-1) T Φ F (k-1)) (17)

[0246]

[0247] In the formula, Δy F (k) = y F (k)-y F (k-1) represents the increment of the frequency vector in the microgrid at the kth moment; Δx F (k-1)=x F (k-1)-x F (k-2) represents the increment of the frequency control quantity vector in the microgrid at the k-1th moment; is the estimated value of the frequency control pseudo partial derivative parameter at the k-1th moment, which is an N i Line n F A matrix of columns; Representation Matrix The transpose of is an n F Row N i Matrix of columns; e FS (k) is the output estimation error of the frequency pseudo partial derivative parameter at the kth moment; c F (k) is the correlation entropy function value of the frequency output estimation error at the kth moment; σ F is the bandwidth parameter in the maximum correlation entropy criterion in frequency control; ||e FS (k)|| 2 Represents the vector e FS The square of the second norm of (k); g F (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion at the kth moment frequency, which is an n F Column vector of columns; β F is the forgetting factor parameter in frequency control; Φ F (k-1) is the inverse information matrix in the robust recursive linear regression method of the k-1th moment frequency, Φ F (k) is the inverse information matrix in the robust recursive linear regression method of the frequency at the kth moment;

[0248] 3) Calculate the voltage control amount and frequency control amount;

[0249] Among them, the voltage control amount at the kth moment is calculated as follows:

[0250]

[0251] In the formula, y U ref (k+1) represents a vector composed of the squares of the voltage amplitude target reference values ​​in the microgrid at the k+1th moment; Represents y U (k) estimated value; represents the estimated value of the voltage control lumped disturbance parameter of the microgrid at the kth moment; represents the output estimation error of the voltage control lumped disturbance parameter at the kth moment; Representation Matrix The square of the norm of Ux , Ux They represent the step size parameter and inhibition term parameter of voltage control respectively; l U1 is the gain parameter of the voltage-controlled disturbance observer;

[0252] Calculate the frequency control amount at the kth moment, the expression is as follows:

[0253]

[0254] Among them, y F ref (k+1) represents the vector composed of the frequency target reference value of the microgrid at the k+1th moment; Represents y F (k) estimated value; represents the estimated value of the frequency control lumped interference parameter of the microgrid at the kth moment; represents the output estimation error of the frequency control aggregate interference parameter at the kth moment; Representation Matrix The square of the norm of Fx , Fx They represent the step length parameter and suppression term parameter of frequency control respectively; l F1 is the gain parameter of the frequency controlled disturbance observer;

[0255] 4) Calculate the adaptive disturbance observer updates for voltage control and frequency control respectively:

[0256] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the voltage control at the kth moment is calculated in turn according to the following expression:

[0257]

[0258] in, They represent the adaptive gain coefficient matrix of the voltage adaptive disturbance observer at the kth moment and the k-1th moment, respectively, and are L e n U Line n U Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n U , where Δe Uy (k) = e Uy (k)-e Uy (k-1) is the dimension n U Column vector of UO is the suppression term parameter of the adaptive disturbance observation for voltage control; for The square of the norm of ; is the estimated value of the voltage square output vector at the k+1th moment, is the estimated value of the voltage control lumped interference parameter at the k+1th moment;

[0259] Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the frequency control at the kth moment is calculated in turn according to the following expression:

[0260]

[0261] in, They represent the adaptive gain coefficient matrices of the frequency adaptive interference observer at the kth moment and the k-1th moment, respectively, and are L e n F Line n F Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n F , where Δe Fy (k) = e Fy (k)-e Fy (k-1) is the dimension n F Column vector of FO is the suppression term parameter of the adaptive interference observation for frequency control; for The square of the norm of ; is the estimated value of the frequency output vector at the k+1th moment, is the estimated value of the frequency control aggregate interference parameter at the k+1th moment;

[0262] 5) Calculate the active power control instructions and reactive power control instructions of each inverter respectively:

[0263] Among them, the active power control instructions and reactive power control instructions of the i-th inverter are:

[0264]

[0265] In the formula, is the voltage control vector x U The i-th element in (k), is the obtained frequency control vector x F The i-th element in (k);

[0266] 6) The active power control instructions and reactive power control instructions of each inverter obtained in step 5) are respectively issued to the local control layer of the corresponding inverter, and the local control layer of the inverter performs a control according to the issued power instructions.

[0267] To implement the above embodiment, a third aspect of the present invention provides an electronic device, including:

[0268] at least one processor; and a memory communicatively coupled to the at least one processor;

[0269] The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the above-mentioned off-grid microgrid adaptive frequency and voltage secondary control method.

[0270] To implement the above-mentioned embodiment, the fourth aspect of the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned off-grid microgrid adaptive frequency and voltage secondary control method.

[0271] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0272] The computer readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the off-grid microgrid adaptive frequency and voltage secondary control method of the above embodiment.

[0273] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0274] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0275] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0276] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0277] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0278] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0279] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0280] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0281] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. An off-grid microgrid adaptive frequency and voltage secondary control method, characterized in that: include: Construct frequency control variables and voltage control variables for secondary control of controlled inverters in off-grid microgrids; Based on the frequency control variable and the voltage control variable, constructing interference-related dynamic linearization models of the microgrid frequency and voltage secondary control respectively; Based on the interference-related dynamic linearization model, active power control instructions and reactive power control instructions of the inverter are calculated to achieve secondary control of the frequency and voltage of the microgrid.

2. The method according to claim 1, characterized in that The frequency control variable and voltage control variable of the secondary control of the controlled inverter in the off-grid microgrid are constructed, including: 1) Establish a model of the controlled inverter in the off-grid microgrid; There are N off-grid microgrids. i 1 controlled inverter; Among them, the voltage and phase angle equations of the i-th inverter are expressed as: Where V i ,θ i are the voltage amplitude and phase angle of the node of the i-th inverter, V i r , are the voltage set point and angular frequency set point of the i-th inverter, ω i is the actual angular frequency of the i-th inverter; V i ,θ i The derivative with respect to time; V i r2 、V i 2 Respectively represent V i r 、V i The square of P i , Q i are respectively the actual output active power and reactive power of the i-th inverter, P i * , is the active power setting instruction and reactive power setting instruction of the ith inverter from the secondary control; V dc,i is the actual value of the DC voltage on the DC side of the i-th inverter, is the set value of the DC voltage on the DC side of the i-th inverter; ΔP i , ΔQ i are functions related to the setting deviation of active power and reactive power of the i-th inverter respectively; Δφ vi , Δφ ωi are the voltage deviation function and frequency deviation function of the ith inverter related to the voltage change on the DC side of the inverter; η i , α i , κ i , i is the primary control parameter of the i-th inverter; 2) Based on the result of step 1), construct the frequency control variable and voltage control variable of the secondary control of the controlled inverter; Among them, at the kth moment, the frequency control quantity instruction and voltage control quantity instruction of the i-th inverter are respectively expressed as: In the formula, is the voltage control instruction of the i-th inverter at the k-th moment, is the voltage control quantity instruction of the i-th inverter at the k-th moment; represents the square of the voltage amplitude setting value of the i-th inverter node; are the active power and reactive power setting instructions of the i-th inverter from the secondary control at the k-th moment respectively.

3. The method according to claim 2, characterized in that The interference-related dynamic linearization models for the secondary control of the frequency and voltage of the microgrid are constructed respectively, including: 1) Construct the disturbance-related dynamic linearization model of microgrid frequency secondary control, the expression is as follows: Δy F (k+1)=S F (k) T ·Δx F (k)+ξ F (k) (7) in, Δy F (k+1)=y F (k+1)-y F (k),Δx F (k)=x F (k)-x F (k-1) In the formula, y F (k+1),y F (k) represents the frequency measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n F dimensional column vector, n F is the number of measured frequencies in the microgrid; F Each element of (k+1) is the frequency measurement value of the key frequency node in the microgrid at the k+1th moment; Δy F (k+1) represents the increment of the frequency measurement vector in the microgrid at the k+1th moment, which is n F dimensional column vector; x F (k), x F (k-1) represents the vector composed of all frequency control instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x F The i-th element of (k) is S F (k) represents the frequency control pseudo partial derivative parameter at the kth moment, which is an N i Line n F Matrix of columns; S F (k) T Represents the matrix S F The transpose of (k) is an n F Row N i Matrix of columns; ξ F (k) represents the frequency control aggregate interference parameter at the kth moment, which is an n F -dimensional column vector; 2) Construct the disturbance-related dynamic linearization model of microgrid voltage secondary control, the expression is as follows: Δy U (k+1)=S U (k) T ·Δx U (k)+ξ U (k) (8) in, Δy U (k+1)=y U (k+1)-y U (k),Δx U (k)=x U (k)-x U (k-1) In the formula, y U (k+1),y U (k) represents the voltage square measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n U dimensional column vector, n U is the voltage quantity measured in the microgrid; U Each element of (k+1) is the square of the voltage amplitude measurement value of the key voltage node in the microgrid at the k+1th moment; Δy U (k+1) represents the increment of the voltage square measurement vector in the microgrid at the k+1th moment, which is n U dimensional column vector; x U (k), x U (k-1) represents the vector composed of all voltage control quantity instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x U The i-th element of (k) is S U (k) represents the pseudo partial derivative parameter of voltage control at the kth moment, which is an N i Line n U Matrix of columns; S U (k) T Represents the matrix S U The transpose of (k) is an n U Row N i Matrix of columns; ξ U (k) represents the voltage control lumped interference parameter at the kth moment, which is an n U -dimensional column vector.

4. The method according to claim 3, characterized in that The calculating the active power control instruction and the reactive power control instruction of the inverter comprises: 1) At the kth moment, collect the frequency measurement values ​​of the key frequency nodes in the microgrid and obtain the frequency measurement vector y F (k), collect the square of the voltage amplitude measurement value of the key voltage node in the microgrid and obtain the voltage square measurement vector y U (k); 2) Update the estimated values ​​of the pseudo partial derivative parameters of voltage control and the estimated values ​​of the pseudo partial derivative parameters of frequency control; Among them, the robust recursive linear regression method based on the maximum correlation entropy criterion calculates the estimated value of the voltage control pseudo partial derivative parameter at the kth moment according to the following expression: c U (k)=exp(-||e US (k)|| 2 / (2σ 2 )) (10) F U (k)=β -1 (F U (k-1)-g U (k)x U (k-1) T F U (k-1)) (12) In the formula, Δy U (k) = y U (k)-y U (k-1) represents the increment of the voltage square measurement vector in the microgrid at the kth moment; Δx U (k-1)=x U (k-1)-x U (k-2) represents the increment of the voltage control quantity vector in the microgrid at the k-1th moment, where, at the moment k=1, Δx U (k-1) and Δx U (k-2) is the initial control value of the device itself at the previous moment, Δy U (k-1) represents the value actually measured at the previous moment; is the estimated value of the pseudo partial derivative parameter of voltage control at the k-1th moment, which is an N i Line n U A matrix of columns; Representation Matrix The transpose of is an n U Row N i Matrix of columns; e US (k) is the output estimation error of the voltage pseudo partial derivative parameter at the kth moment; c U (k) is the correlation entropy function value of the voltage output estimation error at the kth moment; σ U is the bandwidth parameter in the maximum correlation entropy criterion in voltage control; ||e US (k)|| 2 Represents the vector e US The square of the second norm of (k); g U (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion for the voltage at the kth moment, which is an n U Column vector of columns; β U is the forgetting factor parameter in voltage control; Φ U (k-1) is the inverse information matrix in the robust recursive linear regression method of the voltage at the k-1th moment, Φ U (k) is the inverse information matrix in the robust recursive linear regression method of the voltage at the kth moment; Based on the maximum correlation entropy criterion, the robust recursive linear regression method calculates the estimated value of the frequency control pseudo partial derivative parameter at the kth moment according to the following expression: c F (k)=exp(-||e FS (k)|| 2 / (2σ 2 )) (15) F F (k)=β -1 (F F (k-1)-g F (k)x F (k-1) T F F (k-1)) (17) In the formula, Δy F (k) = y F (k)-y F (k-1) represents the increment of the frequency vector in the microgrid at the kth moment; Δx F (k-1)=x F (k-1)-x F (k-2) represents the increment of the frequency control quantity vector in the microgrid at the k-1th moment; is the estimated value of the frequency control pseudo partial derivative parameter at the k-1th moment, which is an N i Line n F A matrix of columns; Representation Matrix The transpose of is an n F Row N i Matrix of columns; e FS (k) is the output estimation error of the frequency pseudo partial derivative parameter at the kth moment; c F (k) is the correlation entropy function value of the frequency output estimation error at the kth moment; σ F is the bandwidth parameter in the maximum correlation entropy criterion in frequency control; ||e FS (k)|| 2 Represents the vector e FS The square of the second norm of (k); g F (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion at the kth moment frequency, which is an n F Column vector of columns; β F is the forgetting factor parameter in frequency control; Φ F (k-1) is the inverse information matrix in the robust recursive linear regression method of the k-1th moment frequency, Φ F (k) is the inverse information matrix in the robust recursive linear regression method of the frequency at the kth moment; 3) Calculate the voltage control amount and frequency control amount; Among them, the voltage control amount at the kth moment is calculated as follows: In the formula, y U ref (k+1) represents a vector composed of the squares of the voltage amplitude target reference values ​​in the microgrid at the k+1th moment; Represents y U (k) estimated value; represents the estimated value of the voltage control lumped disturbance parameter of the microgrid at the kth moment; represents the output estimation error of the voltage control lumped disturbance parameter at the kth moment; Representation Matrix The square of the norm of Ux , Ux They represent the step size parameter and inhibition term parameter of voltage control respectively; l U1 is the gain parameter of the voltage-controlled disturbance observer; Calculate the frequency control amount at the kth moment, the expression is as follows: In the formula, y F ref (k+1) represents the vector composed of the frequency target reference value of the microgrid at the k+1th moment; Represents y F (k) estimated value; represents the estimated value of the frequency control lumped interference parameter of the microgrid at the kth moment; represents the output estimation error of the frequency control aggregate interference parameter at the kth moment; Representation Matrix The square of the norm of Fx , Fx They represent the step length parameter and suppression term parameter of frequency control respectively; l F1 is the gain parameter of the frequency controlled disturbance observer; 4) Calculate the adaptive disturbance observer updates for voltage control and frequency control respectively: Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the voltage control at the kth moment is calculated in turn according to the following expression: In the formula, They represent the adaptive gain coefficient matrix of the voltage adaptive disturbance observer at the kth moment and the k-1th moment, respectively, and are L e n U Line n U Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n U , where Δe Uy (k) = e Uy (k)-e Uy (k-1) is the dimension n U Column vector of UO is the suppression term parameter of the adaptive disturbance observation for voltage control; for The square of the norm of ; is the estimated value of the voltage square output vector at the k+1th moment, is the estimated value of the voltage control lumped interference parameter at the k+1th moment; Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the frequency control at the kth moment is calculated in turn according to the following expression: In the formula, They represent the adaptive gain coefficient matrices of the frequency adaptive interference observer at the kth moment and the k-1th moment, respectively, and are L e n F Line n F Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n F , where Δe Fy (k) = e Fy (k)-e Fy (k-1) is the dimension n F Column vector of FO is the suppression term parameter of the adaptive interference observation for frequency control; for The square of the norm of ; is the estimated value of the frequency output vector at the k+1th moment, is the estimated value of the frequency control aggregate interference parameter at the k+1th moment; 5) Calculate the active power control instructions and reactive power control instructions of each inverter respectively: Among them, the active power control instructions and reactive power control instructions of the i-th inverter are: In the formula, is the voltage control vector x U The i-th element in (k), is the obtained frequency control vector x F The i-th element in (k); 6) The active power control instructions and reactive power control instructions of each inverter obtained in step 5) are respectively issued to the local control layer of the corresponding inverter, and the local control layer of the inverter performs a control according to the issued power instructions.

5. An off-grid microgrid adaptive frequency and voltage secondary control device, characterized in that: include: A control variable construction module, used to construct frequency control variables and voltage control variables for secondary control of a controlled inverter in an off-grid microgrid; An interference-related dynamic linearization model construction module is used to construct interference-related dynamic linearization models of the microgrid frequency and voltage secondary control respectively based on the frequency control variable and the voltage control variable; A control module is used to calculate the active power control instruction and the reactive power control instruction of the inverter based on the interference-related dynamic linearization model to achieve secondary control of the frequency and voltage of the microgrid.

6. The device according to claim 5, characterized in that The frequency control variable and voltage control variable of the secondary control of the controlled inverter in the off-grid microgrid are constructed, including: 1) Establish a model of the controlled inverter in the off-grid microgrid; There are N off-grid microgrids. i 1 controlled inverter; Among them, the voltage and phase angle equations of the i-th inverter are expressed as: Where V i ,θ i are the voltage amplitude and phase angle of the node of the i-th inverter, V i r , are the voltage set point and angular frequency set point of the i-th inverter, ω i is the actual angular frequency of the i-th inverter; V i ,θ i The derivative with respect to time; V i r2 、V i 2 Respectively represent V i r 、V i The square of P i , Q i are respectively the actual output active power and reactive power of the i-th inverter, P i * , is the active power setting instruction and reactive power setting instruction of the ith inverter from the secondary control; V dc,i is the actual value of the DC voltage on the DC side of the i-th inverter, is the set value of the DC voltage on the DC side of the i-th inverter; ΔP i , ΔQ i are functions related to the setting deviation of active power and reactive power of the i-th inverter respectively; Δφ vi , Δφ ωi are the voltage deviation function and frequency deviation function of the ith inverter related to the voltage change on the DC side of the inverter; η i , α i , κ i , i is the primary control parameter of the i-th inverter; 2) Based on the result of step 1), construct the frequency control variable and voltage control variable of the secondary control of the controlled inverter; Among them, at the kth moment, the frequency control quantity instruction and voltage control quantity instruction of the i-th inverter are respectively expressed as: In the formula, is the voltage control instruction of the i-th inverter at the k-th moment, is the voltage control quantity instruction of the i-th inverter at the k-th moment; represents the square of the voltage amplitude setting value of the i-th inverter node; P i * (k) are the active power and reactive power setting instructions of the i-th inverter from the secondary control at the k-th moment respectively.

7. The device according to claim 6, characterized in that The interference-related dynamic linearization models for the secondary control of the frequency and voltage of the microgrid are constructed respectively, including: 1) Construct the disturbance-related dynamic linearization model of microgrid frequency secondary control, the expression is as follows: Δy F (k+1)=S F (k) T ·Δx F (k)+ξ F (k) (7) in, Δy F (k+1)=y F (k+1)-y F (k),Δx F (k)=x F (k)-x F (k-1) In the formula, y F (k+1),y F (k) represents the frequency measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n F dimensional column vector, n F is the number of measured frequencies in the microgrid; F Each element of (k+1) is the frequency measurement value of the key frequency node in the microgrid at the k+1th moment; Δy F (k+1) represents the increment of the frequency measurement vector in the microgrid at the k+1th moment, which is n F dimensional column vector; x F (k), x F (k-1) represents the vector composed of all frequency control instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x F The i-th element of (k) is S F (k) represents the frequency control pseudo partial derivative parameter at the kth moment, which is an N i Line n F Matrix of columns; S F (k) T Represents the matrix S F The transpose of (k) is an n F Row N i Matrix of columns; ξ F (k) represents the frequency control aggregate interference parameter at the kth moment, which is an n F -dimensional column vector; 2) Construct the disturbance-related dynamic linearization model of microgrid voltage secondary control, the expression is as follows: Δy U (k+1)=S U (k) T ·Δx U (k)+ξ U (k) (8) in, Δy U (k+1)=y U (k+1)-y U (k),Δx U (k)=x U (k)-x U (k-1) In the formula, y U (k+1),y U (k) represents the voltage square measurement vector in the microgrid at the k+1th moment and the kth moment, respectively, and is n U dimensional column vector, n U is the voltage quantity measured in the microgrid; U Each element of (k+1) is the square of the voltage amplitude measurement value of the key voltage node in the microgrid at the k+1th moment; Δy U (k+1) represents the increment of the voltage square measurement vector in the microgrid at the k+1th moment, which is n U dimensional column vector; x U (k), x U (k-1) represents the vector composed of all voltage control quantity instructions of the microgrid at the kth moment and the k-1th moment, which is an N i dimensional column vector; x U The i-th element of (k) is S U (k) represents the pseudo partial derivative parameter of voltage control at the kth moment, which is an N i Line n U Matrix of columns; S U (k) T Represents the matrix S U The transpose of (k) is an n U Row N i Matrix of columns; ξ U (k) represents the voltage control lumped interference parameter at the kth moment, which is an n U -dimensional column vector.

8. The device according to claim 7, characterized in that The calculating the active power control instruction and the reactive power control instruction of the inverter comprises: 1) At the kth moment, collect the frequency measurement values ​​of the key frequency nodes in the microgrid and obtain the frequency measurement vector y F (k), collect the square of the voltage amplitude measurement value of the key voltage node in the microgrid and obtain the voltage square measurement vector y U (k); 2) Update the estimated values ​​of the pseudo partial derivative parameters of voltage control and the estimated values ​​of the pseudo partial derivative parameters of frequency control; Among them, the robust recursive linear regression method based on the maximum correlation entropy criterion calculates the estimated value of the voltage control pseudo partial derivative parameter at the kth moment according to the following expression: c U (k)=exp(-||e US (k)|| 2 / (2σ 2 )) (10) F U (k)=β -1 (F U (k-1)-g U (k)x U (k-1) T F U (k-1)) (12) In the formula, Δy U (k) = y U (k)-y U (k-1) represents the increment of the voltage square measurement vector in the microgrid at the kth moment; Δx U (k-1)=x U (k-1)-x U (k-2) represents the increment of the voltage control quantity vector in the microgrid at the k-1th moment, where, at the moment k=1, Δx U (k-1) and Δx U (k-2) is the initial control value of the device itself at the previous moment, Δy U (k-1) represents the value actually measured at the previous moment; is the estimated value of the pseudo partial derivative parameter of voltage control at the k-1th moment, which is an N i Line n U A matrix of columns; Representation Matrix The transpose of is an n U Row N i Matrix of columns; e US (k) is the output estimation error of the voltage pseudo partial derivative parameter at the kth moment; c U (k) is the correlation entropy function value of the voltage output estimation error at the kth moment; σ U is the bandwidth parameter in the maximum correlation entropy criterion in voltage control; ||e US (k)|| 2 Represents the vector e US The square of the second norm of (k); g U (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion for the voltage at the kth moment, which is an n U Column vector of columns; β U is the forgetting factor parameter in voltage control; Φ U (k-1) is the inverse information matrix in the robust recursive linear regression method of the voltage at the k-1th moment, Φ U (k) is the inverse information matrix in the robust recursive linear regression method of the voltage at the kth moment; Based on the maximum correlation entropy criterion, the robust recursive linear regression method calculates the estimated value of the frequency control pseudo partial derivative parameter at the kth moment according to the following expression: c F (k)=exp(-||e FS (k)|| 2 / (2σ 2 )) (15) F F (k)=β -1 (F F (k-1)-g F (k)x F (k-1) T F F (k-1)) (17) In the formula, Δy F (k) = y F (k)-y F (k-1) represents the increment of the frequency vector in the microgrid at the kth moment; Δx F (k-1)=x F (k-1)-x F (k-2) represents the increment of the frequency control quantity vector in the microgrid at the k-1th moment; is the estimated value of the frequency control pseudo partial derivative parameter at the k-1th moment, which is an N i Line n F A matrix of columns; Representation Matrix The transpose of is an n F Row N i Matrix of columns; e FS (k) is the output estimation error of the frequency pseudo partial derivative parameter at the kth moment; c F (k) is the correlation entropy function value of the frequency output estimation error at the kth moment; σ F is the bandwidth parameter in the maximum correlation entropy criterion in frequency control; ||e FS (k)|| 2 Represents the vector e FS The square of the second norm of (k); g F (k) is the iterative gain vector in the robust recursive linear regression method based on the maximum correlation entropy criterion at the kth moment frequency, which is an n F Column vector of columns; β F is the forgetting factor parameter in frequency control; Φ F (k-1) is the inverse information matrix in the robust recursive linear regression method of the k-1th moment frequency, Φ F (k) is the inverse information matrix in the robust recursive linear regression method of the frequency at the kth moment; 3) Calculate the voltage control amount and frequency control amount; Among them, the voltage control amount at the kth moment is calculated as follows: In the formula, y U ref (k+1) represents a vector composed of the squares of the voltage amplitude target reference values ​​in the microgrid at the k+1th moment; Represents y U (k) estimated value; represents the estimated value of the voltage control lumped disturbance parameter of the microgrid at the kth moment; represents the output estimation error of the voltage control lumped disturbance parameter at the kth moment; Representation Matrix The square of the norm of Ux , Ux They represent the step size parameter and inhibition term parameter of voltage control respectively; l U1 is the gain parameter of the voltage-controlled disturbance observer; Calculate the frequency control amount at the kth moment, the expression is as follows: In the formula, y F ref (k+1) represents the vector composed of the frequency target reference value of the microgrid at the k+1th moment; Represents y F (k) estimated value; represents the estimated value of the frequency control lumped interference parameter of the microgrid at the kth moment; represents the output estimation error of the frequency control aggregate interference parameter at the kth moment; Representation Matrix The square of the norm of Fx , Fx They represent the step length parameter and suppression term parameter of frequency control respectively; l F1 is the gain parameter of the frequency controlled disturbance observer; 4) Calculate the adaptive disturbance observer updates for voltage control and frequency control respectively: Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the voltage control at the kth moment is calculated in turn according to the following expression: In the formula, They represent the adaptive gain coefficient matrix of the voltage adaptive disturbance observer at the kth moment and the k-1th moment, respectively, and are L e n U Line n U Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n U , where Δe Uy (k) = e Uy (k)-e Uy (k-1) is the dimension n U Column vector of UO is the suppression term parameter of the adaptive disturbance observation for voltage control; for The square of the norm of ; is the estimated value of the voltage square output vector at the k+1th moment, is the estimated value of the voltage control lumped interference parameter at the k+1th moment; Based on the adaptive disturbance observer method, the adaptive disturbance observation update of the frequency control at the kth moment is calculated in turn according to the following expression: In the formula, They represent the adaptive gain coefficient matrices of the frequency adaptive interference observer at the kth moment and the k-1th moment, respectively, and are L e n F Line n F Matrix of columns; L e is the length of the historical time window of the adaptive disturbance observer, which is a positive integer; For a dimension L e n F , where Δe Fy (k) = e Fy (k)-e Fy (k-1) is the dimension n F Column vector of FO is the suppression term parameter of the adaptive interference observation for frequency control; for The square of the norm of ; is the estimated value of the frequency output vector at the k+1th moment, is the estimated value of the frequency control aggregate interference parameter at the k+1th moment; 5) Calculate the active power control instructions and reactive power control instructions of each inverter respectively: Among them, the active power control instructions and reactive power control instructions of the i-th inverter are: In the formula, is the voltage control vector x U The i-th element in (k), is the obtained frequency control vector x F The i-th element in (k); 6) The active power control instructions and reactive power control instructions of each inverter obtained in step 5) are respectively issued to the local control layer of the corresponding inverter, and the local control layer of the inverter performs a control according to the issued power instructions.

9. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 4.

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