A microgrid distributed adaptive control method, system and device

Abstract

The present invention discloses a distributed adaptive control method, system and device for a microgrid, which belongs to the field of smart grid operation control technology, and the steps include the following: establishing a large signal control model of a distributed power source including an unknown control gain, and separating the known items and unknown items of the model parameters; establishing a distributed voltage and frequency control method based on parameter adaptive matching, realizing adaptive tracking and matching of the algorithm coefficient and the unknown control gain, and avoiding system instability caused by excessive or too small control input; establishing a precise power sharing control algorithm between distributed power sources in the microgrid, and ensuring accurate power sharing between multiple distributed power sources while solving the stable recovery control of the microgrid; establishing a parameter feasible domain calculation method based on the Lyapunov energy function, and ensuring the stable and reliable execution of the distributed control system of the microgrid. The present invention can effectively improve the robustness of the microgrid in dealing with the black box operation of the equipment through the application of the control module and the execution terminal.

Description

Technical Field

[0001] The present invention relates to the field of smart grid operation control technology, and in particular to a microgrid distributed adaptive control method, system and device. Background Art

[0002] Microgrid distributed control originates from multi-agent collaborative control. Compared with traditional microgrid centralized control, it has the advantages of high reliability, strong scalability, and plug-and-play of distributed power sources. Although existing studies have discussed various types of stability in microgrid distributed control, the problem of fuzzy or unknown model parameters of distributed power supply units has not been fully studied. On the one hand, the application of commercial and intelligent distributed power sources today makes it difficult to obtain the control parameters inside the power supply or may change adaptively; on the other hand, the high dependence and high sensitivity of conventional distributed control strategies on the accuracy of model parameters will lead to the inability to design controllers in the absence of parameters, or the occurrence of control instability caused by the mismatch between the controller and the control unit parameters, affecting the safe and stable operation of the microgrid. Therefore, it is urgent to propose a distributed adaptive control method, system and device for microgrids that considers the unknown parameters of distributed power sources. Summary of the invention

[0003] In view of the fact that the existing microgrid distributed control is difficult to solve the problem of power supply parameter uncertainty, the present invention proposes a microgrid distributed adaptive control method, system and device, which solve the problems raised in the background technology.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] The first aspect of the present application discloses a microgrid distributed adaptive control method, comprising:

[0006] Based on the unknown and time-varying problems of some control gains on the equipment side, a full-order and full-dynamic large-signal dynamic control model of distributed power supply for droop control is constructed;

[0007] Design a control parameter adaptive matching mechanism to match the unknown control gains related to voltage and frequency in the full-order and full-dynamic large-signal dynamic control model of distributed power sources, and simultaneously consider the tracking execution errors between adjacent interconnected distributed power sources to determine the microgrid adaptive distributed voltage and frequency control algorithm;

[0008] Based on the unbalanced active power output between adjacent interconnected distributed power sources and the active power output and operating power coefficient of the interconnected distributed power sources in the microgrid, the precise power sharing control algorithm between the distributed power sources in the microgrid is determined;

[0009] In order to avoid the accurate execution of the above-mentioned adaptive matching mechanism and the overall control system, a multidimensional planning problem of control parameters and stable execution of the system is established based on the Lyapunov energy function, and the feasible domain of each coefficient of the microgrid adaptive distributed voltage and frequency control algorithm and the microgrid distributed power generation precise power sharing control algorithm is calculated;

[0010] Distributed adaptive control of the microgrid is performed through the microgrid adaptive distributed voltage and frequency control algorithm and the precise power sharing control algorithm between distributed power sources in the microgrid.

[0011] In some embodiments, the distributed power supply large signal dynamic control model includes a distributed power supply large signal dynamic voltage control model and a distributed power supply large signal dynamic frequency control model, and the construction of the model includes the following steps:

[0012] Assume that there is a N A distributed power source based on droop control, then i The full-order and full-dynamic control model of distributed power source based on droop control is expressed as:

[0013] (1)

[0014] in, is the control state of the distributed power source, Status The derivative of and is the active power and reactive power output of the distributed power source, is the frequency angle variable of the distributed generation, and is the dq axis component of the internal current of the distributed generation, and The dq-axis components of the distributed power supply output current, and is the dq axis component of the distributed power output voltage, , , as well as All of them are the intermediate states of the dual-loop control inside the distributed power supply. is the input state, is the voltage output reference, is the frequency output reference, is the disturbance state, is the grid side frequency, and is the grid side voltage, and as well as express Related to the uncertain nonlinear gains in the model;

[0015] When the gain term in the above distributed power model When the known terms are unknown and time-varying, the simplified microgrid can be obtained by linearizing the known terms through the state expansion observer. i The large signal dynamic voltage control model of a distributed power supply is:

[0016] (2)

[0017] in, represents the unknown and time-varying control gain term in voltage control; and is the voltage control state, and To correspond to and The derivative of is the estimator obtained by state expansion observation, expressed as , is the voltage control input, which is given by the subsequent distributed voltage control algorithm;

[0018] Microgrid i The large signal dynamic frequency control model of a distributed power supply is expressed as:

[0019] (3)

[0020] in, represents the unknown and time-varying control gain term in frequency control, is the frequency control state, Yes Status The derivative of is the frequency control input, is the active power droop coefficient.

[0021] In some embodiments, the microgrid adaptive distributed voltage and frequency control algorithm includes a microgrid adaptive distributed voltage consistency control algorithm and a microgrid adaptive distributed frequency consistency control algorithm, and its construction includes the following steps:

[0022] Based on graph theory and distributed communication topology between distributed power sources, the voltage control tracking error between distributed power sources in the microgrid is established as:

[0023] (4)

[0024] in, and is the interconnection characterization parameter in the Laplacian matrix in graph theory, and is the tracking error of the voltage control state, and represents the voltage control state of the adjacent j-th distributed generation, It is the reference for global voltage consistency control;

[0025] Based on i The distributed generation large signal dynamic voltage control model (2) and the microgrid adaptive distributed voltage consistency control algorithm with parameter adaptive matching mechanism can be expressed as:

[0026] (5)

[0027] in, , , and is a positive real number, is the unknown and time-varying control gain term in the adaptive voltage control introduced by the present invention Adaptive matching coefficient.

[0028] In some embodiments, a frequency control tracking error between distributed power sources in a microgrid is established based on graph theory and a distributed communication topology between distributed power sources:

[0029] (6)

[0030] in, is the tracking error of the distributed frequency state, It is the global frequency consistent control reference;

[0031] Based on i The distributed generation large signal dynamic frequency control model (3) and the microgrid adaptive distributed frequency consistency control algorithm with parameter adaptive matching mechanism can be expressed as:

[0032] (7)

[0033] in, is a positive real number, is to adapt to the unknown input gain Adaptive matching coefficient.

[0034] In some embodiments, the construction of the precise power sharing control algorithm between distributed power sources in the microgrid includes the following steps:

[0035] To achieve accurate power sharing control among distributed power sources in a microgrid, it is necessary to realize:

[0036] (8)

[0037] in, and They are respectively the active droop coefficient and output power status of the adjacent distributed generation;

[0038] Control input status by defining , then the precise power sharing control algorithm between distributed power sources in the microgrid can be expressed as:

[0039] (9)

[0040] in, is a positive real number;

[0041] Finally, based on formulas (3) and (7), the distributed frequency control input of the microgrid can be expressed as:

[0042] (10).

[0043] In some embodiments, the calculation of the feasible domain of each coefficient of the microgrid adaptive distributed voltage and frequency control algorithm and the microgrid distributed power generation precise power sharing control algorithm specifically includes the following steps:

[0044] Establish the following equivalent intermediate state:

[0045] (11)

[0046] Then the equivalent intermediate state in global vector form is expressed as:

[0047] (12)

[0048] in, To correspond to The global vector of is the Laplace operator of the interconnected distributed power sources in the microgrid, and Control status and The global vector form of ; for dimensional identity matrix;

[0049] Based on the intermediate state, the following Lyapunov equation is designed:

[0050] (13)

[0051] in, is a positive real number, for The matrix transpose of for The matrix transpose of ;

[0052] The derivative form of the above Lyapunov equation is expressed as:

[0053] (14)

[0054] Among them, the definition matrix , for The derivative form of the uncertain gain coefficient should be a bounded function satisfying , and is a bounded positive real number, and , is a bounded positive real number, is the defined state vector; is the adaptive parameter matrix defined, is a positive definite matrix defined as, Z is the intermediate coefficient matrix defined, where each matrix coefficient is expressed as:

[0055]

[0056] The stability condition of the distributed adaptive control method of the microgrid of the present invention is satisfied ; This condition can be equivalent to the coefficient matrix is a positive definite matrix. By establishing this problem as a linear programming problem, it can be calculated that the feasible domain of the algorithm parameters must meet the following conditions:

[0057] (15)

[0058] in, is the initial running value of the coefficient matrix M.

[0059] The second aspect of the present application discloses a microgrid distributed adaptive control system, including various types of computing and execution module systems constructed corresponding to the algorithm of the first aspect:

[0060] Distributed power supply dynamic model calculation module: Based on the unknown and time-varying problems of some control gains on the equipment side, a full-order and full-dynamic large-signal dynamic control model of distributed power supply for droop control is constructed;

[0061] Microgrid distributed control execution module: Based on the control parameter adaptive matching mechanism and taking into account the tracking execution error between adjacent interconnected distributed power sources, the microgrid adaptive distributed voltage and frequency control algorithm is determined;

[0062] Microgrid power sharing control execution module: Based on the unbalanced active power output between adjacent interconnected distributed power sources and the active output and operating power coefficient of the interconnected distributed power sources in the microgrid, the precise power sharing control algorithm between the distributed power sources in the microgrid is determined;

[0063] Control parameter feasible domain calculation module: establishes the multi-dimensional planning problem of control parameters and system stable execution based on Lyapunov energy function, and calculates the feasible domain of each coefficient of the algorithm;

[0064] Microgrid joint control execution module: Distributed adaptive control of the microgrid is performed through the microgrid adaptive distributed voltage and frequency control algorithm and the precise power sharing control algorithm between the distributed power sources of the microgrid.

[0065] The third aspect of the present application discloses a terminal device, including a memory, a processor, and an algorithm program or algorithm module system stored in the memory and capable of running on the processor, characterized in that the memory stores an algorithm program or algorithm module system capable of running on the processor, and when the processor loads and executes the algorithm program, it adopts the microgrid distributed adaptive control algorithm or control system described in the first aspect or the second aspect.

[0066] The fourth aspect of the present application discloses a readable storage medium of a distributed control algorithm, wherein the algorithm readable storage medium stores an algorithm or system module program. When the algorithm or system module program is loaded and executed by a processor, the microgrid distributed adaptive control algorithm or control system as described in the first aspect or the second aspect is adopted.

[0067] Beneficial effects of the present invention:

[0068] The distributed adaptive control method proposed in the present invention can be designed and executed when the control coefficient of the distributed power unit is unknown. This feature enables the method to solve the problem of high sensitivity and high dependence of conventional distributed control on the control parameters, and is more suitable for the actual engineering practice of microgrids, especially those microgrids that integrate various types of commercial distributed power sources or introduce different types of distributed power sources in stages.

[0069] The distributed adaptive control method provided by the present invention introduces an adaptive control rate based on the real-time operating error state and operating state change of the distributed power source to achieve real-time matching of the control input and the unit control coefficient. Therefore, the provided method can not only achieve the matching of unknown control parameters, but also achieve dynamic real-time tracking of parameter changes caused by actual demand changes of the control unit. Therefore, the strategy provided by the present invention can better avoid the occurrence of oscillation and instability problems caused by parameter mismatch, and improve the operating stability and reliability of the overall collaborative control system of the microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The present invention will be further described below in conjunction with the accompanying drawings.

[0071] Figure 1 It is a microgrid operation scenario and distributed operation control system architecture diagram provided by the present invention;

[0072] Figure 2 is a flowchart of the steps of the method provided by the present invention;

[0073] Figure 3 It is a schematic diagram of the distributed power supply structure and unknown control coefficients of the droop control in the present invention;

[0074] Figure 4 It is a test simulation system architecture diagram based on IEEE-34 bus node of the present invention;

[0075] Figure 5 It is the simulation test result of the present invention. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", 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 invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0078] Figure 1 The microgrid application scenario of the present invention and the system control structure of the distributed control method provided by the present invention are given. Figure 1 As shown in (a), the microgrid system operates in an island model. In order to realize the consumption of renewable energy, controllable distributed power supply devices including photovoltaic, wind power, energy storage, etc. adopting droop control strategy are decentralized and connected in this microgrid, and data exchange is carried out between devices in a hand-in-hand communication mode. However, due to the different suppliers in the construction of microgrids, photovoltaic, wind power, energy storage and other equipment need to face the problem of heterogeneous, unknown or time-varying parameters. This practical problem will be solved by the strategy of the present invention.

[0079] The distributed control architecture of the method provided by the present invention is Figure 1 The method proposed in the present invention belongs to the secondary control method of distributed power source, which obtains the reference signal of the local power source by receiving the operation information of the adjacent distributed power source equipment, and then sends the calculated signal to the local controller of the distributed power source to realize the tracking of the control signal.

[0080] like Figure 2 As shown, the specific implementation of the microgrid distributed adaptive control method considering the unknown control gain of distributed power sources provided by the present invention includes the following steps:

[0081] Step (1): Establish a large signal dynamic control model of distributed power supply with unknown and time-varying control gains:

[0082] like Figure 3 As shown in the figure, in order to support the stable frequency and voltage operation of the isolated microgrid, the distributed power source adopts a droop control algorithm. Therefore, considering the power calculation, droop and internal double-loop control process in the distributed power source control structure, the full-order and full-dynamic control model of the distributed power source based on droop control can be expressed as:

[0083] (1)

[0084] in, is the control state of the distributed power source, Status The derivative of and is the active power and reactive power output of the distributed power source, is the frequency angle variable of the distributed power source, and is the dq axis component of the internal current of the distributed generation, and The dq-axis components of the distributed power supply output current, and is the dq axis component of the distributed power output voltage, and and as well as All of them are the intermediate states of the dual-loop control inside the distributed power supply. is the input state, is the voltage output reference, is the frequency output reference, is the disturbance state, is the grid side frequency, and is the grid side voltage, and as well as express Related to the uncertain nonlinear gains in the model.

[0085] Then, the simplified microgrid can be obtained by linearizing the known items through the state expansion observer. i The large signal dynamic voltage control model of a distributed power supply is:

[0086] (2)

[0087] in, represents the unknown and time-varying control gain term in voltage control. and is the voltage control state, and To correspond to and The derivative of is the estimator obtained by state expansion observation, expressed as , is the voltage control input, which is given by the subsequent distributed voltage control algorithm;

[0088] Microgrid i The large signal dynamic frequency control model of a distributed power supply is expressed as:

[0089] (3)

[0090] in, represents the unknown and time-varying control gain term in frequency control, is the frequency control state, Yes Status The derivative of is the frequency control input, is the active power droop coefficient.

[0091] Step (2): Establish a distributed voltage and frequency control method based on parameter adaptive matching:

[0092] Based on graph theory and distributed communication topology between distributed power sources, the voltage control tracking error between distributed power sources in the microgrid is established as:

[0093] (4)

[0094] in, and is the interconnection characterization parameter in the Laplacian matrix in graph theory, and is the tracking error of the voltage control state, and represents the voltage control state of the adjacent j-th distributed generation, It is the global voltage consistency control reference.

[0095] Based on i The distributed generation large signal dynamic voltage control model (2) and the microgrid adaptive distributed voltage consistency control algorithm with parameter adaptive matching mechanism can be expressed as:

[0096] (5)

[0097] in, , , and is a positive real number, is the unknown and time-varying control gain term in the adaptive voltage control introduced by the present invention Adaptive matching coefficient.

[0098] Furthermore, based on graph theory and distributed communication topology between distributed power sources, the frequency control tracking error between distributed power sources in the microgrid is established:

[0099] (6)

[0100] in, is the tracking error of the distributed frequency state, Reference for global frequency consistency control.

[0101] Based on i The distributed generation large signal dynamic frequency control model (3) and the microgrid adaptive distributed frequency consistency control algorithm with parameter adaptive matching mechanism can be expressed as:

[0102] (7)

[0103] in, is a positive real number, is to adapt to the unknown input gain Adaptive matching coefficient.

[0104] Step (3): Establish an accurate power sharing control algorithm between distributed power sources in the microgrid:

[0105] To achieve accurate power sharing control among distributed power sources in a microgrid, it is necessary to realize:

[0106] (8)

[0107] in, and They are respectively the active droop coefficient and output power status of the adjacent distributed generation;

[0108] Control input status by defining , then the precise power sharing control algorithm between distributed power sources in the microgrid can be expressed as:

[0109] (9)

[0110] in, is a positive real number.

[0111] Finally, based on formulas (3) and (7), the distributed frequency control input of the microgrid can be expressed as:

[0112] (10)

[0113] Step (4): Establish a parameter feasible domain calculation method based on Lyapunov energy function:

[0114] Establish the following equivalent intermediate state:

[0115] (11)

[0116] Then the equivalent intermediate state in global vector form is expressed as:

[0117] (12)

[0118] in, To correspond to The global vector of is the Laplace operator of the interconnected distributed power sources in the microgrid, and Control status and The global vector form of ; for dimensional identity matrix.

[0119] Based on the intermediate state, the following Lyapunov equation is designed:

[0120] (13)

[0121] in, is a positive real number, for The matrix transpose of for The matrix transpose of ;

[0122] The derivative form of the above Lyapunov equation is expressed as:

[0123] (14)

[0124] Among them, the definition matrix , for The derivative form of the uncertain gain coefficient should be a bounded function satisfying , and is a bounded positive real number, and , is a bounded positive real number, is the defined state vector. is the adaptive parameter matrix defined, is a positive definite matrix defined as, Z is the intermediate coefficient matrix defined, where each matrix coefficient is expressed as:

[0125]

[0126] The stability condition of the distributed adaptive control method of the microgrid of the present invention is satisfied . This condition can be equivalent to the coefficient matrix is a positive definite matrix. By establishing this problem as a linear programming problem, it can be calculated that the feasible domain of the algorithm parameters must meet the following conditions:

[0127] (15)

[0128] in, is the initial running value of the coefficient matrix M.

[0129] like Figure 4 As shown, the test scenario of the method provided by the present invention is an improved island microgrid system based on IEEE-34 nodes. In this system, four distributed power sources and some uncontrollable operating loads are decentralized. The controllable distributed power sources adopt a droop control model and are interconnected through a hand-in-hand distributed communication method. In addition, in order to test the tracking ability of the method provided by the present invention for unknown and time-varying parameters, the active droop systems of the distributed power sources are designed as follows:

[0130] , ,

[0131] In the test scenario setting, the control method provided by the present invention is connected at t=4s; at t=6s and t=8s, load #7 is connected and disconnected respectively; at t=10s and t=12s, distributed power source #1 is disconnected from the microgrid and reconnected to the microgrid system respectively.

[0132] Figure 5The control performance in (a) and (b) proves that the distributed adaptive control method for microgrids considering unknown control gains of distributed power sources provided by the present invention has stable frequency and voltage consistency recovery capabilities. In the initial stage of the disturbance event, due to the different control coefficients of the distributed power sources and the different distances from the disturbance, the response dynamics of the four distributed power sources are quite different. In this case, the method adaptively adjusts the algorithm gain to adapt to the operating dynamics of different power sources and avoids oscillations caused by heterogeneous dynamics. Adaptive adjustment of algorithm coefficients such as Figure 5 (d) In addition, the solution provided by the present invention can still solve the required frequency / voltage recovery under the significant interference conditions of the distributed power supply disconnection and reconnection. The power ratio result is shown in Figure 5 (c) Even if the distributed power sources are configured with different control gain systems, the method provided by the present invention can also solve the power sharing problem well.

[0133] In addition, the present application embodiment discloses a microgrid distributed adaptive control system, including:

[0134] Distributed power supply dynamic model calculation module: Based on the unknown and time-varying problems of some control gains on the equipment side, a full-order and full-dynamic large-signal dynamic control model of distributed power supply for droop control is constructed;

[0135] Microgrid distributed control execution module: Based on the control parameter adaptive matching mechanism and taking into account the tracking execution error between adjacent interconnected distributed power sources, the microgrid adaptive distributed voltage and frequency control algorithm is determined;

[0136] Microgrid power sharing control execution module: Based on the unbalanced active power output between adjacent interconnected distributed power sources and the active output and operating power coefficient of the interconnected distributed power sources in the microgrid, the precise power sharing control algorithm between the distributed power sources in the microgrid is determined;

[0137] Control parameter feasible domain calculation module: Based on the Lyapunov energy function, a multidimensional planning problem of control parameters and system stable execution is established, and the feasible domain of each coefficient of the algorithm is calculated.

[0138] Microgrid joint control execution module: Distributed adaptive control of the microgrid is performed through the microgrid adaptive distributed voltage and frequency control algorithm and the precise power sharing control algorithm between the distributed power sources of the microgrid.

[0139] An embodiment of the present application also discloses a terminal device, including a memory, a processor, and an algorithm program or algorithm module system stored in the memory and capable of running on the processor, characterized in that the memory stores an algorithm program or algorithm module system capable of running on the processor, and when the processor loads and executes the algorithm program, it adopts the microgrid distributed adaptive control algorithm or control system described in any one of the above embodiments.

[0140] Among them, the terminal device can be a desktop computer, workstation, device-side integrated controller or cloud server and other devices that can realize real-time computing, and the terminal device includes but is not limited to a processor and a memory. For example, the terminal device can also include input and output devices, network access devices and buses, etc.

[0141] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0142] Among them, the memory can be an internal storage unit of the terminal device, such as a hard disk or memory of the terminal device, or it can be an external storage device of the terminal device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD) or flash memory card (FC) equipped on the terminal device, and the memory can also be a combination of an internal storage unit and an external storage device of the terminal device. The memory is used to store algorithm programs and other programs and data required by the terminal device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0143] Among them, through this terminal device, any one of the microgrid distributed adaptive control algorithms or system modules in the above embodiments is stored in the memory of the terminal device, and is loaded and executed on the processor of the terminal device for easy use.

[0144] An embodiment of the present application also discloses a distributed control algorithm readable storage medium, and the algorithm readable storage medium stores an algorithm or system module program, wherein when the computer program is executed by a processor, any one of the microgrid distributed adaptive control methods in the above embodiments is adopted.

[0145] Among them, the algorithm program can be stored in various types of algorithm-readable storage media, the algorithm program includes algorithm program code, the algorithm program code can be in source code form, object code form, executable file or certain middleware form, etc. Various types of algorithm-readable storage media include any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that various types of algorithm-readable storage media include but are not limited to the above-mentioned components.

[0146] Among them, through the algorithm-readable storage medium, any one of the microgrid distributed adaptive control methods in the above embodiments is stored in the algorithm-readable storage medium, and is loaded and executed on the processor to facilitate the storage and application of the above method.

[0147] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A distributed adaptive control method for a microgrid, characterized in that: include: Based on the unknown and time-varying problems of some control gains on the equipment side, a full-order and full-dynamic large-signal dynamic control model of distributed power supply for droop control is constructed; Design a control parameter adaptive matching mechanism to match the unknown control gains related to voltage and frequency in the full-order and full-dynamic large-signal dynamic control model of distributed power sources, and simultaneously consider the tracking execution errors between adjacent interconnected distributed power sources to determine the microgrid adaptive distributed voltage and frequency control algorithm; Based on the unbalanced active power output between adjacent interconnected distributed power sources and the active power output and operating power coefficient of the interconnected distributed power sources in the microgrid, the precise power sharing control algorithm between the distributed power sources in the microgrid is determined; Based on the Lyapunov energy function, a multidimensional planning problem of control parameters and system stable execution is established, and the feasible domain of each coefficient of the microgrid adaptive distributed voltage and frequency control algorithm and the microgrid distributed power generation precise power sharing control algorithm is calculated; Distributed adaptive control of the microgrid is carried out through the microgrid adaptive distributed voltage and frequency control algorithm and the precise power sharing control algorithm between the distributed power sources of the microgrid; The construction of the precise power sharing control algorithm between distributed power sources in the microgrid includes the following steps: To achieve accurate power sharing control among distributed power sources in a microgrid, it is necessary to realize: (8) in, and are the active droop coefficient and output power state of the i-th distributed generation in the microgrid, and are the active droop coefficient and output power state of the jth distributed generation in the microgrid, respectively, and N represents the number of distributed generation based on droop control in the microgrid; Control input status by defining , then the precise power sharing control algorithm between distributed power sources in the microgrid is expressed as: (9) in, is a positive real number, Characterize parameters for interconnections in the Laplacian matrix in graph theory; The distributed frequency control input of the microgrid is expressed as: (10) in, is the frequency control input, is to adapt to the unknown input gain The adaptive matching coefficient, represents the unknown and time-varying control gain term in frequency control, is a positive real number, is the tracking error of the distributed frequency state, It is the frequency control state.

2. The microgrid distributed adaptive control method according to claim 1, characterized in that: The distributed power supply full-order full-dynamic large signal dynamic control model includes a distributed power supply large signal dynamic voltage control model and a distributed power supply large signal dynamic frequency control model, and its construction includes the following steps: Assume that there is a N A distributed power source based on droop control, then i The full-order and full-dynamic control model of distributed power source based on droop control is expressed as: (1) in, is the control state of the distributed power source, Status The derivative of and is the active power and reactive power output of the distributed power source, is the frequency angle variable of the distributed generation, and is the dq axis component of the internal current of the distributed generation, and The dq-axis components of the distributed power supply output current, and is the dq axis component of the distributed power output voltage, , and as well as All of them are the intermediate states of the dual-loop control inside the distributed power supply. is the input state, is the voltage output reference, is the frequency output reference, is the disturbance state, is the grid side frequency, and is the grid side voltage, and as well as express Related to the uncertain nonlinear gains in the model; When the gain term in the above distributed power model When the known terms are unknown and time-varying, the simplified microgrid is obtained by linearizing the known terms through the state expansion observer. i The large signal dynamic voltage control model of a distributed power supply is: (2) in, represents the unknown and time-varying control gain term in voltage control; and is the voltage control state, and To correspond to and The derivative of is the estimator obtained by state expansion observation, expressed as , is the voltage control input, which is given by the subsequent distributed voltage control algorithm; Microgrid i The large signal dynamic frequency control model of a distributed power supply is expressed as: (3) in, Yes Status The derivative of .

3. The microgrid distributed adaptive control method according to claim 2, characterized in that: The microgrid adaptive distributed voltage and frequency control algorithm includes a microgrid adaptive distributed voltage consistency control algorithm and a microgrid adaptive distributed frequency consistency control algorithm, and its construction includes the following steps: Based on graph theory and distributed communication topology between distributed power sources, the voltage control tracking error between distributed power sources in the microgrid is established as: (4) in, and is the interconnection characterization parameter in the Laplacian matrix in graph theory, and is the tracking error of the voltage control state, and represents the voltage control state of the adjacent j-th distributed generation, It is the reference for global voltage consistency control; Based on i A distributed power source large signal dynamic voltage control model (2) is proposed. The microgrid adaptive distributed voltage consistency control algorithm with parameter adaptive matching mechanism is expressed as: (5) in, , , and is a positive real number, is the unknown and time-varying control gain term introduced in the adaptive voltage control Adaptive matching coefficient of Furthermore, based on graph theory and distributed communication topology between distributed power sources, the frequency control tracking error between distributed power sources in the microgrid is established: (6) in, It is the global frequency consistent control reference; Based on i A distributed generation large signal dynamic frequency control model (3) is proposed. The microgrid adaptive distributed frequency consistency control algorithm with parameter adaptive matching mechanism is expressed as: (7)。 4. The microgrid distributed adaptive control method according to claim 3, characterized in that: The calculation of the feasible domain of each coefficient of the microgrid adaptive distributed voltage and frequency control algorithm and the microgrid distributed power generation precise power sharing control algorithm specifically includes the following steps: The following equivalent intermediate states are established: (11) Then the equivalent intermediate state in global vector form is expressed as: (12) in, To correspond to The global vector of is the Laplace operator of the interconnected distributed power sources in the microgrid, and Control status and The global vector form of ; for dimensional identity matrix; Based on the intermediate state, the following Lyapunov equation is designed: (13) in, is a positive real number, for The matrix transpose of for The matrix transpose of ; The derivative form of the above Lyapunov equation is expressed as: (14) Among them, the definition matrix , for The derivative form of the uncertain gain coefficient should be a bounded function satisfying , and is a bounded positive real number, and , is a bounded positive real number, is the defined state vector; is the adaptive parameter matrix defined, is a positive definite matrix defined as, Z is the intermediate coefficient matrix defined, where each matrix coefficient is expressed as: The stability condition of the microgrid distributed adaptive control method is satisfied ; This condition is equivalent to the coefficient matrix is a positive definite matrix. By establishing this problem as a linear programming problem, the feasible domain of the algorithm parameters must satisfy the following conditions: (15) in, is the initial running value of the coefficient matrix M.

5. A microgrid distributed adaptive control system, characterized in that: It includes various types of computing and execution module systems constructed based on the distributed adaptive control method for a microgrid as claimed in any one of claims 1 to 4: Distributed power supply dynamic model calculation module: Based on the unknown and time-varying problems of some control gains on the equipment side, a full-order and full-dynamic large-signal dynamic control model of distributed power supply for droop control is constructed; Microgrid distributed control execution module: Based on the control parameter adaptive matching mechanism and taking into account the tracking execution error between adjacent interconnected distributed power sources, the microgrid adaptive distributed voltage and frequency control algorithm is determined; Microgrid power sharing control execution module: Based on the unbalanced active power output between adjacent interconnected distributed power sources and the active output and operating power coefficient of the interconnected distributed power sources in the microgrid, the precise power sharing control algorithm between the distributed power sources in the microgrid is determined; Control parameter feasible domain calculation module: establishes the multi-dimensional planning problem of control parameters and system stable execution based on Lyapunov energy function, and calculates the feasible domain of each coefficient of the algorithm; Microgrid joint control execution module: Distributed adaptive control of the microgrid is performed through the microgrid adaptive distributed voltage and frequency control algorithm and the precise power sharing control algorithm between the distributed power sources of the microgrid.

6. A terminal device, comprising a memory, a processor, and an algorithm program or an algorithm module system stored in the memory and capable of running on the processor, characterized in that: The memory stores an algorithm program or an algorithm module system that can be run on a processor. When the processor loads and executes the algorithm program, the microgrid distributed adaptive control method described in any one of claims 1 to 4 is adopted.

7. A readable storage medium of a distributed control algorithm, wherein the algorithm or system module program is stored in the readable storage medium of the algorithm, characterized in that: When the algorithm or system module program is loaded and executed by the processor, the microgrid distributed adaptive control method according to any one of claims 1 to 4 is adopted.

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