Micro-grid island division method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application disclose a micro-grid island division method and device, electronic equipment and a storage medium. The method comprises: obtaining micro-grid load parameters, and establishing a mixed integer nonlinear programming model according to each load parameter; calculating a transient frequency nonlinear model according to the mixed integer nonlinear programming model; linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model; and obtaining a micro-grid island division result according to the mixed integer linear programming model. The embodiments of the present application solve the problem of low accuracy of the existing island division method, and can quickly and accurately divide the micro-grid island.

Description

TECHNICAL FIELD

[0001] The embodiment of the application relates to the technical field of micro-grid coordinated control, and particularly relates to a micro-grid island division method and device, electronic equipment and a storage medium. BACKGROUND

[0002] Micro-grid island division is how to reasonably and effectively cut off part of the load, realize source-load power matching, so as to ensure the safe and stable operation of the micro-grid system and the continuous and continuous power supply of the key load. When the main grid encounters a fault, the frequency stability before and after the micro-grid is off-grid is an important factor to ensure the smoothness of the planned island. Improving the scientificity and accuracy of the island division strategy can improve the power quality and power experience of users.

[0003] However, at the present stage, due to the difficulty in data acquisition and the small amount of data samples, the existing island division method has low accuracy. SUMMARY

[0004] The embodiment of the application provides a micro-grid island division method, device, electronic equipment and storage medium, so as to solve the problem of low accuracy of the existing island division method, and can quickly and accurately divide the micro-grid island.

[0005] According to an aspect of the embodiment of the application, a micro-grid island division method is provided, comprising:

[0006] Obtaining micro-grid load parameters, and establishing a mixed integer nonlinear programming model according to each load parameter;

[0007] According to the mixed integer nonlinear programming model, a transient frequency nonlinear model is calculated;

[0008] The transient frequency nonlinear model is linearized to obtain a mixed integer linear programming model;

[0009] According to the mixed integer linear programming model, a micro-grid island division result is obtained.

[0010] According to another aspect of the embodiment of the application, a micro-grid island division device is provided, comprising:

[0011] The load parameter acquisition module is configured to obtain micro-grid load parameters, and establish a mixed integer nonlinear programming model according to each load parameter;

[0012] The transient frequency nonlinear model determination module is configured to calculate a transient frequency nonlinear model according to the mixed integer nonlinear programming model;

[0013] The mixed integer linear programming model determination module is configured to linearize the transient frequency nonlinear model to obtain a mixed integer linear programming model;

[0014] The island partition result determination module is configured to obtain a micro-grid island partition result according to the mixed integer linear programming model.

[0015] According to another aspect of the embodiments of the present application, an electronic device is provided, which comprises:

[0016] at least one processor; and

[0017] a memory connected to the at least one processor in communication; wherein

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the micro-grid island partition method according to any of the embodiments of the present application.

[0019] According to another aspect of the embodiments of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to perform the micro-grid island partition method according to any of the embodiments of the present application when executed.

[0020] The technical solution of the embodiments of the present application obtains the micro-grid load parameters, and establishes a mixed integer nonlinear programming model according to each load parameter; obtains a transient frequency nonlinear model according to the mixed integer nonlinear programming model; linearizes the transient frequency nonlinear model to obtain a mixed integer linear programming model; and obtains a micro-grid island partition result according to the mixed integer linear programming model, thereby solving the problem of low accuracy of the existing island partition method, and quickly and accurately partitioning the micro-grid island.

[0021] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor to limit the scope of the embodiments of the present application. Other features of the embodiments of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 is a flow chart of a micro-grid island partition method according to the first embodiment of the present application;

[0024] Figure 2is a schematic diagram of actual working mechanism of primary frequency modulation of a control system according to the embodiment one of the present application;

[0025] Figure 3 is a schematic diagram of a model according to the embodiment one of the present application;

[0026] Figure 4 is a structural schematic diagram of a micro-grid island division device according to the embodiment two of the present application;

[0027] Figure 5 is a structural schematic diagram of an electronic device for implementing the micro-grid island division method according to the embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the personnel in the technical field better understand the embodiment scheme of the present application, the technical scheme in the embodiment of the present application will be described clearly and completely in combination with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, not all. Based on the embodiment in the embodiment of the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the present application.

[0029] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment one

[0031] Figure 1 A flowchart of a micro-grid island division method according to the embodiment one of the present application is provided, which can be applicable to the case of dividing the micro-grid into islands. The method can be executed by a micro-grid island division device, which can be realized in the form of hardware and / or software, and can be configured in an electronic device, which can be a computer, a server or a tablet computer, etc. in the embodiment. Specifically, referring to Figure 1 , the method specifically includes the following steps:

[0032] In step 110, the micro-grid load parameters are acquired, and a mixed integer nonlinear programming model is established according to the load parameters.

[0033] The micro-grid load parameters can include at least one of the following: load amount, power, transient frequency, steady-state frequency and power supply, and are not limited in the embodiment.

[0034] In an optional implementation of the embodiment, a plurality of load parameters of the micro-grid can be acquired, and a mixed integer nonlinear programming model is established according to the acquired load parameters; in the embodiment, the mixed integer nonlinear programming model can include a target function, a constraint condition or the target function and the constraint condition; the target function mainly aims to minimize the cut load amount; the constraint condition can include at least one of the following: load constraint, power supply constraint, power constraint, transient frequency constraint and steady-state frequency constraint.

[0035] In the embodiment, the target function can have the following form:

[0036]

[0037] wherein x i =1 represents that the i th load is cut off, x i =0 represents that the i th load is not cut off; P Loadi represents the active power of the i th load; λ i =1 represents a first-level load, λ i =0.1 represents a second-level load, and λ i =0.01 represents a third-level load.

[0038] In the embodiment, the load constraint can be x i =0 when λ i =1; the power supply constraint can be P DGi_min,k ≤P DGi,k ≤P DGi_max,k , Q DGi_min,k ≤Q DGi,k ≤Q DGi_max,k ; the power constraint can be ΔP=∑P Load -∑P DG =0; the transient frequency constraint can be Δf t_min，k ≤Δf t，k ≤Δf t_max，k , Δf t_min , k=-0.01, f t_max , k=0.01; and the steady-state frequency constraint can be Δf s_min,k ≤Δf s,k ≤Δf s_max,k , Δf s_min,k =-0.004, Δf s_max,k= 0.004.

[0039] wherein, P DGi_max,k , P DGi_min,k represents the upper and lower limits of the active power output of the small hydropower, Q DGi_max,k , Q DGi_min,k represents the upper and lower limits of the reactive power output of the small hydropower; ∑P Load represents the total active power of the load, ∑P DG represents the total active power output of the small hydropower; Δf t_max,k , Δf t_min,k represents the upper and lower limits of the transient frequency, Δf s_max,k , Δf s_min,k represents the upper and lower limits of the steady-state frequency.

[0040] Step 120, calculating the transient frequency nonlinear model according to the mixed integer nonlinear programming model.

[0041] In an optional implementation of the embodiment, after the mixed integer nonlinear programming model is established according to the obtained load parameters, the transient frequency nonlinear model can be further calculated according to the established mixed integer nonlinear programming model.

[0042] In the embodiment, calculating the transient frequency nonlinear model according to the mixed integer nonlinear programming model can include: calculating the transient frequency nonlinear model according to the actual working mechanism of the primary frequency modulation of the control system.

[0043] In order to better understand the embodiments of the present application, Figure 2 is a schematic diagram of the actual working mechanism of the primary frequency modulation of a control system according to an embodiment of the present application, according to Figure 2 Modeling the frequency response process of the control system can obtain a model as shown in Figure 3 ; Figure 3 In the model, ΔP0 is the initial power shortage of the system; ΔP L is the load variation (cut load amount in the design); ΔP2 is the difference between the given power shortage and the output power of the water turbine and the load variation; Δμ is the variation of the guide vane opening; ΔP ref is the increased power of the water turbine; and ΔP1 represents the increased power of the water turbine after the limiting link.

[0044] In the embodiment, according to Figure 3 the following transfer function expression can be obtained:

[0045]

[0046] In the above formula, H represents the inertia time constant of the hydroelectric generating set, T w represents the flow inertia time constant of the hydroelectric generating set, T yrepresents the response time constant of the servomotor, K p ,K I represents the proportional gain and integral gain of the governor of the hydraulic turbine, b p represents the steady-state difference coefficient of the governor of the hydraulic turbine.

[0047] In step 130, the transient frequency nonlinear model is linearized to obtain a mixed integer linear programming model.

[0048] In an optional implementation of the embodiment, after the transient frequency nonlinear model is calculated, the calculated transient frequency nonlinear model can be further linearized to obtain a mixed integer linear programming model.

[0049] In an optional implementation of the embodiment, linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model can include: using a bilinear transformation to convert the transfer function of the transient frequency nonlinear model from a frequency domain equation to a discrete domain equation; and converting the discrete domain equation to a time domain equation to linearize the transfer function.

[0050] In a specific example of the embodiment, the transfer function G1(s) in the frequency domain can be converted to a transfer function G1(z) in the discrete domain using a bilinear transformation, and then the transfer function G1(z) in the discrete domain is converted to a time domain equation; for example, for the transfer function G1(s) in the frequency domain can be converted to and then converted to y(t) = f{y(t-1),...,y(t-k),x(t),...x(t-k)}, that is, the linearization of the transfer function expression is achieved.

[0051] In another optional implementation of the embodiment, linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model can include: linearizing the nonlinear factors caused by the limiting amplitude link by using a big M method to obtain a mixed integer linear programming model.

[0052] In a specific example of the embodiment, the nonlinear factors caused by the limiting amplitude link are linearized by using a big M method, and the piecewise function of the output adjustment range of the generator governor is represented as:

[0053]

[0054] where P DGj is the actual output of the hydraulic turbine; P DGj_ref is the output power of the hydraulic turbine after primary frequency modulation.

[0055] Linearization by using a big M method obtains:

[0056]

[0057]

[0058]

[0059] Finally, a mixed integer linear programming model is obtained.

[0060] In step 140, a micro-grid island partition result is obtained according to the mixed integer linear programming model.

[0061] In an optional implementation of the embodiment, after linearization of the transient frequency nonlinear model to obtain the mixed integer linear programming model, the micro-grid island partition result can be further obtained according to the obtained mixed integer linear programming model.

[0062] In an optional implementation of the embodiment, obtaining the micro-grid island partition result according to the mixed integer linear programming model can include processing the mixed integer linear programming model by a solver to obtain the micro-grid island partition result.

[0063] In the embodiment, the island partition result considering the transient frequency constraint can be obtained based on a commercial solver, and then the micro-grid can successfully implement the planned island operation according to the partition result.

[0064] The embodiment of the application ensures that the micro-grid frequency does not exceed the limit by considering the transient frequency constraint, reduces the difficulty of transient frequency calculation by linearization processing method, ensures the smooth implementation of the planned island operation of the micro-grid, and improves the power supply reliability. Compared with the existing island partition method, the embodiment of the application has the advantages of high calculation accuracy and reliable calculation result, effectively achieves the planned island operation of the micro-grid on the basis of ensuring the power supply quality of the user.

[0065] The technical scheme of the embodiment includes obtaining micro-grid load parameters, establishing a mixed integer nonlinear programming model according to each load parameter, calculating a transient frequency nonlinear model according to the mixed integer nonlinear programming model, linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model, and obtaining a micro-grid island partition result according to the mixed integer linear programming model. The embodiment solves the problem of low accuracy of the existing island partition method, and can quickly and accurately partition the micro-grid island.

[0066] Embodiment two

[0067] Figure 4 A structural schematic diagram of a micro-grid island partition device provided by the embodiment two of the application is shown in FIG. 2. Figure 4As shown, the device comprises: a load parameter acquisition module 410, a transient frequency nonlinear model determination module 420, a mixed integer linear programming model determination module 430, and an island division result determination module 440.

[0068] The load parameter acquisition module 410 is configured to acquire micro-grid load parameters, and establish a mixed integer nonlinear programming model according to each of the load parameters.

[0069] The transient frequency nonlinear model determination module 420 is configured to calculate a transient frequency nonlinear model according to the mixed integer nonlinear programming model.

[0070] The mixed integer linear programming model determination module 430 is configured to linearize the transient frequency nonlinear model to obtain a mixed integer linear programming model.

[0071] The island division result determination module 440 is configured to obtain a micro-grid island division result according to the mixed integer linear programming model.

[0072] The scheme of the embodiment acquires micro-grid load parameters through the load parameter acquisition module, and establishes a mixed integer nonlinear programming model according to each of the load parameters; calculates a transient frequency nonlinear model according to the mixed integer nonlinear programming model through the transient frequency nonlinear model determination module; linearizes the transient frequency nonlinear model to obtain a mixed integer linear programming model through the mixed integer linear programming model determination module; and obtains a micro-grid island division result according to the mixed integer linear programming model through the island division result determination module, thereby solving the problem of low precision of existing island division methods, and quickly and accurately dividing the micro-grid island.

[0073] In an optional implementation of the embodiment, the micro-grid load data comprises at least one of the following: load amount, power, transient frequency, steady-state frequency, and power supply.

[0074] In an optional implementation of the embodiment, the mixed integer nonlinear programming model comprises an objective function and / or a constraint condition; the objective function aims to minimize the amount of cut load; and the constraint condition comprises at least one of the following: load constraint, power supply constraint, power constraint, transient frequency constraint, and steady-state frequency constraint.

[0075] In an optional implementation of the embodiment, the transient frequency nonlinear model determination module 420 is specifically configured to calculate the transient frequency nonlinear model according to the actual working mechanism of the primary frequency control system.

[0076] In an optional implementation of the embodiment, the mixed integer linear programming model determination module 430 is specifically configured to transform a transfer function of the transient frequency nonlinear model from a frequency domain equation to a discrete domain equation by using a bilinear transformation; and transform the discrete domain equation into a time domain equation to linearize the transfer function.

[0077] In an optional implementation of the embodiment, the mixed integer linear programming model determination module 430 is specifically configured to linearize a nonlinear factor caused by a limiting amplitude link by using a big M method to obtain the mixed integer linear programming model.

[0078] In an optional implementation of the embodiment, the island partition result determination module 440 is specifically configured to process the mixed integer linear programming model by using a solver to obtain the micro-grid island partition result.

[0079] The micro-grid island partition device provided in the embodiment can execute the micro-grid island partition method provided in any of the embodiments, and has the corresponding function modules and beneficial effects of the execution method.

[0080] Embodiment three

[0081] Figure 5 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0082] As Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer programs stored in the read-only memory (ROM) 12 or loaded into the random access memory (RAM) 13 from the storage unit 18. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0083] Various components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, a speaker, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0084] The processor 11 can be various general and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the microgrid island partitioning method.

[0085] In some embodiments, the microgrid island partitioning method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the microgrid island partitioning method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the microgrid island partitioning method by any other appropriate means, such as by means of firmware.

[0086] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a load programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0087] Computer programs used to implement embodiments of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented on the computer or other programmable apparatus. The computer programs can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0088] In the context of embodiments of the present application, a computer- readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0089] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0090] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), blockchain network, and the Internet.

[0091] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0092] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present application. For example, the steps recited in the embodiments of the present application can be executed in parallel, in series, or in a different order, and the present application is not limited herein as to the order in which the steps are executed, as long as the desired results of the technical solutions of the embodiments of the present application are achieved.

[0093] The above detailed description does not limit the scope of the embodiments of the application. It is to be understood that any modifications, combinations, sub-combinations and alternatives are possible based on design requirements and other factors in the engineering field. Any modifications, equivalent replacements, improvements, and the like made within the spirit and principle of the embodiments of the application shall fall in the scope of the embodiments of the application.

Claims

1. A microgrid island partitioning method, characterized in that, The method comprises the following steps: obtaining micro-grid load parameters, and establishing a mixed integer nonlinear programming model according to each of the load parameters; calculating a transient frequency nonlinear model according to the mixed integer nonlinear programming model; linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model; obtaining a micro-grid island partition result according to the mixed integer linear programming model; wherein the step of calculating a transient frequency nonlinear model according to the mixed integer nonlinear programming model comprises: calculating the transient frequency nonlinear model according to the actual working mechanism of the primary frequency modulation of the control system; wherein the transient frequency nonlinear model is: wherein ΔP0 is the initial power shortage of the system; ΔP L is the load variation; ΔP2 is the difference between the given power shortage and the output power of the water turbine and the load variation; Δμ is the variation of the guide vane opening; ΔP ref is the additional power of the water turbine; ΔP1 represents the additional power of the water turbine after the limiting link; H is the inertia time constant of the hydroelectric generator set, T w is the flow inertia time constant of the hydroelectric generator set, T y is the response time constant of the servomotor, K p ,K I is the proportional gain and integral gain of the water turbine governor, b p is the steady-state difference coefficient of the water turbine governor; wherein the step of linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model comprises: using a bilinear transformation to convert the transfer function of the transient frequency nonlinear model from a frequency domain equation to a discrete domain equation; converting the discrete domain equation into a time domain equation to linearize the transfer function; or linearizing the nonlinear factors caused by the limiting amplitude link through a large M method to obtain a mixed integer linear programming model; the step of obtaining a micro-grid island partition result according to the mixed integer linear programming model comprises: processing the mixed integer linear programming model through a solver to obtain a micro-grid island partition result.

2. The method of claim 1, wherein, The micro-grid load data comprises at least one of the following: load amount, power, transient frequency, steady-state frequency, and power supply.

3. The method of claim 2, wherein, The mixed integer nonlinear programming model comprises an objective function and / or a constraint condition; the objective function aims to minimize the amount of load shedding; the constraint condition comprises at least one of the following: load constraint, power supply constraint, power constraint, transient frequency constraint, and steady-state frequency constraint.

4. A microgrid island partitioning device, comprising: The method comprises the following steps: a load parameter acquisition module is configured to obtain micro-grid load parameters, and establish a mixed integer nonlinear programming model according to each of the load parameters; a transient frequency nonlinear model determination module is configured to calculate a transient frequency nonlinear model according to the mixed integer nonlinear programming model; wherein the step of calculating a transient frequency nonlinear model according to the mixed integer nonlinear programming model comprises: calculating the transient frequency nonlinear model according to the actual working mechanism of the primary frequency modulation of the control system; wherein the transient frequency nonlinear model is: Wherein, ΔP0 is the initial power shortage of the system; ΔP L is the load variation; ΔP2 is the difference between the given power shortage and the output power of the hydraulic turbine and the load variation; Δμ is the variation of the guide vane opening; ΔP ref is the output power of the hydraulic turbine; ΔP1 represents the output power of the hydraulic turbine after the limiting link; H is the inertia time constant of the hydroelectric generator set, T w is the flow inertia time constant of the hydroelectric generator set, T y is the response time constant of the servomotor, K p ,K I is the proportional gain and integral gain of the hydraulic turbine governor, b p is the steady-state difference coefficient of the hydraulic turbine governor; the mixed integer linear programming model determination module is used for linearization of the transient frequency nonlinear model to obtain a mixed integer linear programming model; wherein the step of linearizing the transient frequency nonlinear model to obtain a mixed integer linear programming model comprises: using a bilinear transformation to convert the transfer function of the transient frequency nonlinear model from a frequency domain equation to a discrete domain equation; converting the discrete domain equation into a time domain equation to linearize the transfer function; or linearizing the nonlinear factors caused by the limiting amplitude link through a large M method to obtain a mixed integer linear programming model an island partition result determination module is configured to obtain a micro-grid island partition result according to the mixed integer linear programming model; specifically, the island partition result determination module is configured to process the mixed integer linear programming model through a solver to obtain a micro-grid island partition result.

5. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the micro-grid island division method in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to implement the micro-grid island division method in any one of claims 1-3 when executed.

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