A method, system, device and medium for smooth switching control of on-grid and off-grid

Abstract

The present invention relates to the technical field of microgrids, and discloses a method, system, device and medium for smooth switching control between grid and off-grid, wherein the method comprises: real-time monitoring of a grid-on / off-grid switching instruction, and synchronously judging the operating state of the microgrid through a distributed power supply; the operating state is an island operating state and a grid-on operating state; when a grid-on switching to off-grid instruction is received and the operating state is an island operating state, adjusting the voltage and frequency of the microgrid according to an adaptive droop coefficient model, so that the microgrid switches from a grid-on control mode to an off-grid control mode; when an off-grid switching to grid-on instruction is received and the operating state is a grid-on operation state, adjusting the current in the microgrid according to the current in a distribution network, so that the microgrid switches from an off-grid control mode to a grid-on control mode; so as to ensure smooth switching of the microgrid operating mode and improve the stability and safety of the grid.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrids, and in particular to a method, system, device and medium for controlling smooth switching between grid and off-grid. Background Art

[0002] Micro-Grid (MG) is composed of distributed power sources (distributed photovoltaic, distributed wind power, gas turbine, electrochemical energy storage, supercapacitor, etc.), power loads (different types of loads such as important and adjustable), energy management systems (monitoring, protection and automation devices), etc. It is a power supply and consumption system that can basically achieve internal power balance. Microgrids are usually composed of distributed power generation units, energy storage units, loads and grid-connected interface converters. Microgrids can work in both grid-connected mode and island mode. During the grid-connected mode, the output power of the distributed power sources inside the microgrid is mainly used for local load consumption. When the output power of the distributed power sources is greater than the local load, the excess power is transmitted to the grid; when the output power of the distributed power sources is less than the local load, the insufficient power is provided by the grid. During grid failure or planned islanding, the energy storage unit usually switches to droop control or VF control as the main control unit to ensure the stability of the AC bus voltage and frequency, so that important loads can be supplied uninterruptedly.

[0003] During normal operation of a microgrid, the grid-connected mode and the island mode usually need to be switched smoothly. However, the traditional switching method will cause overcurrent or overvoltage, which will not only impact the grid but also damage the load. Therefore, how to achieve smooth switching of microgrid grid-connected / islanded mode is a major problem that urgently needs to be solved. Summary of the invention

[0004] The present invention provides a method, system, device and medium for controlling smooth switching between grid and off-grid, which solve the problem of how to achieve smooth switching between grid and off-grid in microgrid.

[0005] In order to solve the above technical problems, the first aspect of the present invention provides a method for controlling smooth switching between grid and off-grid, comprising:

[0006] Real-time monitoring of the microgrid's on-off switching instructions, and synchronously determining the microgrid's operating state through distributed power sources; the operating state includes an island operating state and a grid-connected operating state;

[0007] When a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, the voltage and frequency of the microgrid are adjusted according to an adaptive droop coefficient model so that the microgrid switches from a grid-connected control mode to an off-grid control mode;

[0008] When an off-grid to grid-connected switching instruction is received and the operating state is a grid-connected operating state, the current in the microgrid is adjusted according to the current in the distribution network so that the microgrid switches from an off-grid control mode to a grid-connected control mode.

[0009] Furthermore, the real-time monitoring of the microgrid's on-off switching instructions and synchronously determining the microgrid's operating state through the distributed power supply includes:

[0010] When it is detected that the grid-connected switch is disconnected, generating the grid-connected to off-grid switching instruction;

[0011] According to the island detection algorithm, whether the operating state of the microgrid is the island operating state is judged by the distributed power supply.

[0012] Further, judging whether the operating state of the microgrid is the island operating state by the distributed power source according to the island detection algorithm includes:

[0013] Integrating the frequency of the distributed power source within the island detection period to obtain a frequency integral value;

[0014] When the frequency integral value is greater than the upper limit of the frequency value, or less than the lower limit of the frequency value, the operation state of the microgrid is the island operation state.

[0015] Furthermore, the real-time monitoring of the microgrid's on-off switching instructions and synchronously determining the microgrid's operating state through the distributed power supply includes:

[0016] When the grid-connected switch is detected to be closed, the off-grid switching to grid-connected instruction is generated;

[0017] According to the mutual approximation entropy analysis algorithm, whether the operating state of the microgrid is the grid-connected operating state is judged by the distributed power supply.

[0018] Further, judging whether the operation state of the microgrid is the grid-connected operation state by the distributed power source according to the mutual approximate entropy analysis algorithm includes:

[0019] Acquire voltage vectors on both sides of the grid-connected switch when the embedding dimension is the first dimension, and calculate a similarity tolerance of mutual approximate entropy according to the voltage vectors;

[0020] Calculate the mutual correlation degree between the voltage vectors on both sides of the grid-connected switch in the first dimension according to the similarity tolerance to obtain a first-dimensional mutual correlation degree value;

[0021] When the embedding dimension becomes the second dimension, the cross-correlation degree between the voltage vectors on both sides of the grid-connected switch in the second dimension is calculated to obtain a cross-correlation degree value of the second dimension;

[0022] Calculate the mutual approximation entropy value according to the first-dimensional mutual correlation degree value and the second-dimensional mutual correlation degree value;

[0023] When the mutual approximate entropy value is less than a preset value, the operation state of the microgrid is the grid-connected operation state.

[0024] Further, the voltage and frequency of the microgrid are adjusted according to the adaptive droop coefficient model, including:

[0025] Acquire historical operation data of the microgrid when receiving a grid-connected switching instruction to an off-grid switching instruction and the operation state is an island operation state; the operation data at least includes an operation frequency, an operation voltage, an active power and a reactive power;

[0026] Inputting the historical operation data into the droop control equation model for calculation to obtain a frequency droop coefficient and a voltage droop coefficient;

[0027] The frequency droop coefficient and the voltage droop coefficient are optimized by using a particle swarm algorithm to obtain an adaptive frequency droop coefficient and an adaptive voltage droop coefficient;

[0028] The droop control equation is updated according to the adaptive frequency droop coefficient and the adaptive voltage droop coefficient to obtain the adaptive droop coefficient model;

[0029] The voltage and frequency of the microgrid are adjusted according to the voltage and frequency values ​​obtained by calculating the real-time operation data input into the adaptive droop coefficient model.

[0030] Further, the regulating the current in the microgrid according to the current in the distribution network includes:

[0031] The current is limited by adding a current limiting device, and / or the load connected to the power grid is reduced.

[0032] A second aspect of the present invention provides a grid-connected and off-grid smooth switching control system, comprising:

[0033] The instruction monitoring module is used to monitor the microgrid's on-off switching instructions in real time, and synchronously determine the operating state of the microgrid through the distributed power supply; the operating state is an island operating state and a grid-connected operating state;

[0034] A first regulating module is used to regulate the voltage and frequency of the microgrid according to an adaptive droop coefficient model when a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, so that the microgrid switches from a grid-connected control mode to an off-grid control mode;

[0035] The second regulating module is used to regulate the current in the microgrid according to the current in the distribution network when receiving the off-grid switching to grid-connected instruction and the operating state is the grid-connected operating state, so as to switch the microgrid from the off-grid control mode to the grid-connected control mode.

[0036] A third aspect of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the on-grid and off-grid smooth switching control method as described in any one of the first aspects above.

[0037] A fourth aspect of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the on-grid and off-grid smooth switching control method as described in any one of the above-mentioned first aspects.

[0038] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0039] The present invention provides a method, system, device and medium for smooth switching control between on-grid and off-grid, wherein the method comprises: real-time monitoring of on-grid and off-grid switching instructions of a microgrid, and synchronously judging the operating state of the microgrid through distributed power sources; the operating state is an island operating state and a grid-connected operating state; when a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, adjusting the voltage and frequency of the microgrid according to an adaptive droop coefficient model, so that the microgrid switches from a grid-connected control mode to an off-grid control mode; when an off-grid to grid-connected switching instruction is received and the operating state is a grid-connected operating state, adjusting the current in the microgrid according to the current in a distribution network, so that the microgrid switches from an off-grid control mode to a grid-connected control mode. The present invention takes advantage of the fact that a single mutual approximate entropy value can be used to compare the similarity of the voltages on both sides of the grid-connected switch, and adopts the mutual approximate entropy method to detect the synchronization problem of microgrid grid-connected, thereby overcoming the problems of the classic microgrid grid-connected synchronization detection method being cumbersome to implement and difficult to quantify; the adaptive droop coefficient model proposed in the present invention can effectively solve the large voltage fluctuation and frequency instability caused by switching from grid-connected to island mode, thereby ensuring the smooth switching of the microgrid operation mode and improving the stability and safety of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the implementation mode will be briefly introduced below. Obviously, the drawings described below are only some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a flow chart of a method for controlling smooth switching between grid and off-grid provided by a certain embodiment of the present invention;

[0042] Figure 2 is a flowchart of step S1 provided in one embodiment of the present invention;

[0043] Figure 3 is a flowchart of step S112 provided by an embodiment of the present invention;

[0044] Figure 4 is another flow chart of step S1 provided by an embodiment of the present invention;

[0045] Figure 5 is a flowchart of step S122 provided by an embodiment of the present invention;

[0046] Figure 6 is a diagram of a process of adjusting voltage and frequency in step S2 provided by an embodiment of the present invention;

[0047] Figure 7 It is a device diagram of a grid-connected and off-grid smooth switching control system provided by a certain embodiment of the present invention;

[0048] Figure 8 It is a structural diagram of an electronic device provided by a certain embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings and embodiments. 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.

[0050] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0051] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0052] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0053] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0054] In one embodiment, if Figure 1 As shown, the first aspect of the present invention provides a method for controlling smooth switching between grid and off-grid, comprising:

[0055] S1. Real-time monitoring of the microgrid's on-off switching instructions, and synchronously determining the operating state of the microgrid through distributed power sources; the operating state is an island operating state and a grid-connected operating state;

[0056] Generally, when the distribution network is normal, the grid-connected switch is in the closed state, and each distributed power source in the microgrid is connected to the grid and operated with P / Q control; when the distribution network is powered off or abnormal, the grid-connected switch is disconnected, and each distributed power source in the microgrid needs to switch from the grid-connected operation state to the island operation state (also called the off-grid operation state), and the microgrid also switches from the grid-connected control mode to the off-grid control mode; when the distribution network resumes normal power supply, the grid-connected switch is closed, and each distributed power source in the microgrid needs to switch from the island operation state to the grid-connected operation state, and the microgrid also switches from the off-grid control mode to the grid-connected control mode. During the on-grid and off-grid state switching process, the microgrid will generate an on-off switching instruction to make the switching process smooth.

[0057] In one embodiment, step S1 is as follows: Figure 2 As shown, including:

[0058] S111, when it is detected that the grid-connected switch is disconnected, generating the grid-connected to off-grid switching instruction;

[0059] S112: According to an island detection algorithm, judging by the distributed power source whether the operating state of the microgrid is the island operating state.

[0060] Specifically, when the grid-connected switch is disconnected, it means that the distribution network is out of power or abnormal. The microgrid can be switched from the grid-connected control mode to the off-grid control mode only when the island detection algorithm is used to determine that the operating state of the microgrid is an island operating state.

[0061] In one embodiment, step S112 is as follows: Figure 3 As shown, including:

[0062] S1121. Integrate the frequency of the distributed power source within the island detection period to obtain a frequency integral value. The integral formula is as follows:

[0063]

[0064] In the formula, θ Tis the frequency integral value; f(t) is the frequency of the distributed power source; t0 is the starting time of the island detection cycle; T is the island detection cycle.

[0065] S1122. When the frequency integral value is greater than the upper limit of the frequency value, or less than the lower limit of the frequency value, the operation state of the microgrid is the island operation state; assuming that the upper and lower limits of the frequency integral value within the period are θ max and θ min , if the frequency integral value θ within the period T Crossing θ max or θ min , the inverter determines that the frequency exceeds the limit and the microgrid is in an island state.

[0066] This application synchronizes the start and end times of island state detection of each distributed power source in the microgrid through an island detection algorithm, and synchronously outputs the island detection results, thereby ensuring the consistency of control method switching between different distributed power sources in the microgrid, and laying the foundation for seamless switching from grid-connected to island state.

[0067] In one embodiment, step S1 is as follows: Figure 4 As shown, including:

[0068] S121, when monitoring that the grid-connected switch is closed, generating the off-grid switching to grid-connected instruction;

[0069] S122. According to a mutually approximate entropy analysis algorithm, judging by the distributed power source whether the operating state of the microgrid is the grid-connected operating state.

[0070] Specifically, when the grid-connected switch is closed, it means that the distribution network has returned to normal. The microgrid can be switched from the off-grid control mode to the grid-connected control mode only when the mutual approximate entropy analysis algorithm is used to determine that the operating state of the microgrid is the grid-connected operating state.

[0071] In one embodiment, step S122 is as follows: Figure 5 As shown, including:

[0072] S1221. Obtain the voltage vectors on both sides of the grid-connected switch when the embedding dimension is the first dimension, and calculate the similarity tolerance of the mutual approximation entropy according to the voltage vectors; wherein the voltage vectors on both sides of the grid-connected switch are expressed by the following formula:

[0073] U(i)=[u(i),...,u(i+m-1)],i=1,...,N-m+1

[0074] U(j)=[u(j),...,u(j+m-1)],j=1,...,N-m+1

[0075] In the formula, N is the data window of the algorithm, and the first dimension refers to the m dimension.

[0076] The similarity tolerance of mutual approximation entropy is calculated by the following formula:

[0077] r=0.2*COV(Ui,Uj)

[0078] Where r is the similarity tolerance of the mutual approximation entropy; COV is the covariance of the voltage vector array on both sides of the grid-connected switch.

[0079] S1222. Calculate the mutual correlation degree between the voltage vectors on both sides of the grid-connected switch in the first dimension according to the similarity tolerance to obtain the first-dimensional mutual correlation degree value; wherein the calculation process of the first-dimensional mutual correlation degree value is: taking the similarity tolerance as a reference, first compare and obtain the number of the difference between the arrays U(i) and U(j) that is less than the similarity tolerance; then compare the number with the total number of vectors (N-m+1) to obtain the comparison probability; finally, calculate the logarithm and average value of the comparison probability to obtain the first-dimensional mutual correlation degree value; the calculation formula of the first-dimensional mutual correlation degree value is:

[0080]

[0081] Where, T m,r (D(U(i),U(j))) is the first-dimensional mutual correlation value (also called the m-dimensional mutual correlation value); D(U(i),U(j)) is the difference between the arrays U(i) and U(j); C m,r is the comparison probability; the comparison probability represents the probability that the m-dimensional modes in the voltage arrays on both sides of the switch are close under similar tolerance r conditions.

[0082] S1223. When the embedding dimension becomes the second dimension, the mutual correlation degree between the voltage vectors on both sides of the grid-connected switch in the second dimension is calculated to obtain a second-dimensional mutual correlation degree value; specifically, when the embedding dimension becomes (m+1), the calculation process of steps S1221 and S1222 is repeated to obtain a second-dimensional mutual correlation degree value (also called an m+1-dimensional mutual correlation degree value) T m+1,r (D(U(i),U(j))).

[0083] S1224, calculating a mutual approximation entropy value according to the first-dimensional mutual correlation degree value and the second-dimensional mutual correlation degree value; subtracting the first-dimensional mutual correlation degree value from the second-dimensional mutual correlation degree value to obtain a mutual approximation entropy value, the specific expression of which is:

[0084] CApEn(m,r)=T m,r (D(U(i),U(j)))-T m+1,r (D(U(i),U(j)))

[0085] Where CApEn(m,r) is the mutual approximation entropy value.

[0086] S1225. When the mutual approximation entropy value is less than a preset value, the operation state of the microgrid is the grid-connected operation state. The present application adopts the mutual approximation entropy method for the voltage waveforms on both sides of the microgrid switch, which is equivalent to the mean of the logarithmic conditional probability of the similarity of the two waveforms, that is, the mutual similarity of the time series of the voltages on both sides of the switch in the pattern. The smaller the similarity, the greater the value of the mutual approximation entropy. In the process of microgrid grid connection, the above method is used to continuously calculate the mutual approximation entropy value of the voltages at both ends of the grid-connected switch, and then by adjusting the voltage on the microgrid side, the mutual approximation entropy value is gradually made as small as possible, so that the voltages at both ends are closest, synchronous grid connection is achieved, and the impact of microgrid grid connection due to voltage inconsistency is reduced.

[0087] This application uses a mutual entropy analysis algorithm to determine whether a microgrid is in a grid-connected state. It takes advantage of a single mutual entropy value to compare the similarity of the voltages on both sides of the grid-connected switch. The mutual entropy method is used to detect the synchronization problem of the microgrid grid-connected, overcoming the problems of the classic microgrid grid-connected synchronization detection method, which is cumbersome to implement and difficult to quantify.

[0088] S2. When a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, the voltage and frequency of the microgrid are adjusted according to an adaptive droop coefficient model to switch the microgrid from a grid-connected control mode to an off-grid control mode; specifically, only when a grid-connected to off-grid switching instruction is received and it is determined that the operating state of the microgrid is an island operating state, the voltage and frequency of the microgrid can be adjusted to switch the microgrid from a grid-connected control mode to an off-grid control mode.

[0089] In one embodiment, the voltage and frequency are adjusted in step S2 as follows: Figure 5 As shown, including:

[0090] S21, obtaining historical operation data of the microgrid when receiving a grid-connected switching instruction to an off-grid operation instruction and the operation state is an island operation state; the operation data at least includes an operation frequency, an operation voltage, an active power and a reactive power;

[0091] S22, inputting the historical operation data into the droop control equation model for calculation to obtain the frequency droop coefficient and the voltage droop coefficient; wherein the droop control equation model is expressed as follows:

[0092] f=f0-K p (P0-P)

[0093] U=U0-K q (Q0-Q)

[0094] In the formula, K p , K qare the frequency and voltage droop coefficients respectively; f0 and U0 are the rated frequency and voltage respectively; P and Q are the active power and reactive power respectively; P0 and Q0 are the rated operating points of active power and reactive power respectively; m p 、m q are the rated frequency and voltage droop coefficient respectively; f and U are the actual frequency and voltage respectively.

[0095] S23. Optimize the frequency droop coefficient and the voltage droop coefficient by using a particle swarm algorithm to obtain an adaptive frequency droop coefficient and an adaptive voltage droop coefficient. The particle swarm algorithm here is only one of many optimization algorithms and is a public algorithm. Other optimization algorithms can also be used here, and no further details will be given here.

[0096] S24, updating the droop control equation according to the adaptive frequency droop coefficient and the adaptive voltage droop coefficient to obtain the adaptive droop coefficient model;

[0097] S25. According to the voltage value and frequency value calculated by inputting the real-time operation data into the adaptive droop coefficient model, the voltage and frequency of the microgrid are adjusted.

[0098] This application identifies the droop control equation model through historical operation data in the same state - when the microgrid receives the grid-connected switching to off-grid instruction and the operation state is an island operation state, and adjusts the microgrid through the frequency droop coefficient and voltage droop coefficient in the model; and uses the obtained coefficients to update the model so that it can learn the voltage and frequency fluctuation law, and use the model after learning the law to adjust the voltage and frequency of the microgrid. The present invention can train the model through historical operation data, and use the trained model to adjust the microgrid to achieve the switching of the grid-connected and off-grid control modes, with low cost, high accuracy and wide application range.

[0099] The present application changes the droop coefficient by updating historical operation data and then dynamically changes the working curve, so that when the microgrid switches from the grid-connected mode to the island mode, it operates according to the voltage and frequency values ​​calculated by the adaptive droop coefficient model, so that the voltage and frequency drop of the microgrid is reduced. To a certain extent, it can effectively solve the large voltage fluctuations and unstable frequency caused by switching from the grid-connected mode to the island mode, ensure the smooth switching of the microgrid operation mode, and improve the stability and safety of the power grid.

[0100] S3. When an off-grid to grid-connected switching instruction is received and the operating state is a grid-connected operating state, the current in the microgrid is adjusted according to the current in the distribution network to switch the microgrid from an off-grid control mode to a grid-connected control mode; wherein the adjusting the current in the microgrid according to the current in the distribution network includes: limiting the current by adding a current limiting device, and / or reducing the load connected to the grid.

[0101] The current limiting device is preferably a resistor, and the current limiting device and the load reduction treatment of the load connected to the power grid can prevent convection from occurring during off-grid switching, which causes excessive current. Connecting a current limiting resistor during off-grid switching can prevent excessive current, and disconnecting the current limiting resistor after the switching is completed to reduce losses, thereby achieving the goal of avoiding excessive startup current of the energy storage converter and affecting the safety of electrical appliances through hardware design.

[0102] In the embodiment of the present application, based on the problem of how to achieve smooth grid-connected / islanded switching of a microgrid, a grid-connected and off-grid smooth switching control method is designed, which realizes real-time monitoring of the grid-connected and off-grid switching instructions of the microgrid, and synchronously determines the operating state of the microgrid through distributed power sources; the operating state is an island operating state and a grid-connected operating state; when a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, the voltage and frequency of the microgrid are adjusted according to an adaptive droop coefficient model to switch the microgrid from a grid-connected control mode to an off-grid control mode; when an off-grid to grid-connected switching instruction is received and the operating state is a grid-connected operating state, the current in the microgrid is adjusted according to the current in the distribution network to switch the microgrid from an off-grid control mode to a grid-connected control mode. The technical solution ensures smooth switching of the microgrid operating mode, improves the stability and safety of the power grid, and greatly improves the safety of electrical appliances.

[0103] It should be noted that although the steps in the above flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders.

[0104] In another embodiment, if Figure 7 As shown, the second aspect of the present invention provides a grid-connected and off-grid smooth switching control system, comprising:

[0105] The instruction monitoring module 10 is used to monitor the microgrid's on-off switching instructions in real time, and to determine the operation state of the microgrid through the distributed power supply synchronization; the operation state is an island operation state and a grid-connected operation state;

[0106] A first regulating module 20 is used to regulate the voltage and frequency of the microgrid according to an adaptive droop coefficient model when a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, so that the microgrid switches from a grid-connected control mode to an off-grid control mode;

[0107] The second regulating module 30 is used to regulate the current in the microgrid according to the current in the distribution network when receiving the off-grid switching to grid-connected instruction and the operating state is the grid-connected operating state, so as to switch the microgrid from the off-grid control mode to the grid-connected control mode.

[0108] It should be noted that each module in the above-mentioned control system based on smooth switching between grid and off-grid can be fully or partially implemented by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules. For the specific definition of a smooth switching control system for grid and off-grid, please refer to the definition of a smooth switching control method for grid and off-grid above. The two have the same functions and effects, which will not be repeated here.

[0109] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0110] processor, memory, and bus;

[0111] The bus is used to connect the processor and the memory;

[0112] The memory is used to store operation instructions;

[0113] The processor is used to call the operation instruction, and the executable instruction enables the processor to perform operations corresponding to a method for smooth switching control of on-grid and off-grid as shown in the first aspect of the present application.

[0114] In an alternative embodiment, an electronic device is provided, such as Figure 8 As shown, Figure 8 The electronic device 5000 shown includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are connected, such as through a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that in actual applications, the transceiver 5004 is not limited to one, and the structure of the electronic device 5000 does not constitute a limitation on the embodiments of the present application.

[0115] Processor 5001 may be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 5001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0116] The bus 5002 may include a path to transmit information between the above components. The bus 5002 may be a PCI bus or an EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0117] The memory 5003 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an EEPROM, a CD-ROM or other optical disk storage, an optical disk storage (including a compressed optical disk, a laser disk, an optical disk, a digital versatile disk, a Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0118] The memory 5003 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 5001. The processor 5001 is used to execute the application code stored in the memory 5003 to implement the content shown in any of the above method embodiments.

[0119] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.

[0120] The fourth aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, a method for controlling smooth switching between on-grid and off-grid networks as shown in the first aspect of the present application is implemented.

[0121] Another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0122] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

[0123] In summary, the present invention relates to the field of microgrid technology, and discloses a method, system, device and medium for smooth switching control between grid and off-grid, wherein the method includes: real-time monitoring of the grid-on and off-grid switching instructions of the microgrid, and synchronously judging the operating state of the microgrid through distributed power sources; the operating state is an island operating state and a grid-connected operating state; when receiving a grid-connected to off-grid switching instruction and the operating state is an island operating state, adjusting the voltage and frequency of the microgrid according to an adaptive droop coefficient model, so that the microgrid switches from a grid-connected control mode to an off-grid control mode; when receiving an off-grid to grid-connected switching instruction and the operating state is a grid-connected operating state, adjusting the current in the microgrid according to the current in the distribution network, so that the microgrid switches from an off-grid control mode to a grid-connected control mode. The present invention ensures the smooth switching of the microgrid operating mode, improves the stability and safety of the power grid, and the safety of electrical appliances.

[0124] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A method for controlling smooth switching between grid and off-grid, characterized in that: include: Monitor the switching instructions of the microgrid in real time, and determine the operating status of the microgrid synchronously through the distributed power supply; The operating states are an island operating state and a grid-connected operating state; When a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, the voltage and frequency of the microgrid are adjusted according to an adaptive droop coefficient model so that the microgrid switches from a grid-connected control mode to an off-grid control mode; When an off-grid switching to grid-connected instruction is received and the operating state is a grid-connected operating state, the current in the microgrid is adjusted according to the current in the distribution network, so that the microgrid is switched from an off-grid control mode to a grid-connected control mode; The real-time monitoring of the microgrid's on-off switching instructions and synchronously determining the microgrid's operating state through distributed power sources include: When the grid-connected switch is detected to be closed, the off-grid switching to grid-connected instruction is generated; According to the mutual approximate entropy analysis algorithm, judging whether the operating state of the microgrid is the grid-connected operating state through the distributed power supply; The step of judging whether the operating state of the microgrid is the grid-connected operating state by the distributed power source according to the mutual approximate entropy analysis algorithm includes: Acquire voltage vectors on both sides of the grid-connected switch when the embedding dimension is the first dimension, and calculate a similarity tolerance of mutual approximate entropy according to the voltage vectors; Calculate the mutual correlation degree between the voltage vectors on both sides of the grid-connected switch in the first dimension according to the similarity tolerance to obtain a first-dimensional mutual correlation degree value; When the embedding dimension becomes the second dimension, the cross-correlation degree between the voltage vectors on both sides of the grid-connected switch in the second dimension is calculated to obtain a cross-correlation degree value of the second dimension; Calculate the mutual approximation entropy value according to the first-dimensional mutual correlation degree value and the second-dimensional mutual correlation degree value; When the mutual approximation entropy value is less than a preset value, the operation state of the microgrid is the grid-connected operation state; The step of adjusting the voltage and frequency of the microgrid according to the adaptive droop coefficient model includes: Acquire historical operation data of the microgrid when receiving a grid-connected switching instruction to an off-grid switching instruction and the operation state is an island operation state; the operation data at least includes an operation frequency, an operation voltage, an active power and a reactive power; Inputting the historical operation data into the droop control equation model for calculation to obtain a frequency droop coefficient and a voltage droop coefficient; The frequency droop coefficient and the voltage droop coefficient are optimized by using a particle swarm algorithm to obtain an adaptive frequency droop coefficient and an adaptive voltage droop coefficient; The droop control equation is updated according to the adaptive frequency droop coefficient and the adaptive voltage droop coefficient to obtain the adaptive droop coefficient model; The voltage and frequency of the microgrid are adjusted according to the voltage and frequency values ​​obtained by calculating the real-time operation data input into the adaptive droop coefficient model.

2. A method for controlling smooth switching between grid and off-grid according to claim 1, characterized in that: The real-time monitoring of the microgrid's on-off switching instructions and synchronously determining the microgrid's operating state through distributed power sources include: When it is detected that the grid-connected switch is disconnected, generating the grid-connected to off-grid switching instruction; According to the island detection algorithm, whether the operating state of the microgrid is the island operating state is judged by the distributed power supply.

3. A method for controlling smooth switching between grid and off-grid according to claim 2, characterized in that: The step of judging whether the operating state of the microgrid is the island operating state by the distributed power source according to the island detection algorithm includes: Integrating the frequency of the distributed power source within the island detection period to obtain a frequency integral value; When the frequency integral value is greater than the upper limit of the frequency value, or less than the lower limit of the frequency value, the operation state of the microgrid is the island operation state.

4. The method for controlling smooth switching between grid and off-grid according to claim 1, characterized in that: The step of regulating the current in the microgrid according to the current in the distribution network comprises: The current is limited by adding a current limiting device, and / or the load connected to the power grid is reduced.

5. A grid-connected and off-grid smooth switching control system, characterized in that: include: An instruction monitoring module is used to monitor the switching instructions of the microgrid in real time and synchronously determine the operating status of the microgrid through the distributed power supply; The operating states are an island operating state and a grid-connected operating state; A first regulating module is used to regulate the voltage and frequency of the microgrid according to an adaptive droop coefficient model when a grid-connected to off-grid switching instruction is received and the operating state is an island operating state, so that the microgrid switches from a grid-connected control mode to an off-grid control mode; A second regulating module is used to regulate the current in the microgrid according to the current in the distribution network when receiving an off-grid switching to grid-connected instruction and the operating state is a grid-connected operating state, so that the microgrid switches from an off-grid control mode to a grid-connected control mode; The real-time monitoring of the microgrid's on-off switching instructions and synchronously determining the microgrid's operating state through distributed power sources include: When the grid-connected switch is detected to be closed, the off-grid switching to grid-connected instruction is generated; According to the mutual approximate entropy analysis algorithm, judging whether the operating state of the microgrid is the grid-connected operating state through the distributed power supply; The step of judging whether the operating state of the microgrid is the grid-connected operating state by the distributed power source according to the mutual approximate entropy analysis algorithm includes: Acquire voltage vectors on both sides of the grid-connected switch when the embedding dimension is the first dimension, and calculate a similarity tolerance of mutual approximate entropy according to the voltage vectors; Calculate the mutual correlation degree between the voltage vectors on both sides of the grid-connected switch in the first dimension according to the similarity tolerance to obtain a first-dimensional mutual correlation degree value; When the embedding dimension becomes the second dimension, the cross-correlation degree between the voltage vectors on both sides of the grid-connected switch in the second dimension is calculated to obtain a cross-correlation degree value of the second dimension; Calculate the mutual approximation entropy value according to the first-dimensional mutual correlation degree value and the second-dimensional mutual correlation degree value; When the mutual approximation entropy value is less than a preset value, the operation state of the microgrid is the grid-connected operation state; The step of adjusting the voltage and frequency of the microgrid according to the adaptive droop coefficient model includes: Acquire historical operation data of the microgrid when receiving a grid-connected switching instruction to an off-grid switching instruction and the operation state is an island operation state; the operation data at least includes an operation frequency, an operation voltage, an active power and a reactive power; Inputting the historical operation data into the droop control equation model for calculation to obtain a frequency droop coefficient and a voltage droop coefficient; The frequency droop coefficient and the voltage droop coefficient are optimized by using a particle swarm algorithm to obtain an adaptive frequency droop coefficient and an adaptive voltage droop coefficient; The droop control equation is updated according to the adaptive frequency droop coefficient and the adaptive voltage droop coefficient to obtain the adaptive droop coefficient model; The voltage and frequency of the microgrid are adjusted according to the voltage and frequency values ​​obtained by calculating the real-time operation data input into the adaptive droop coefficient model.

6. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for controlling smooth switching between grid and off-grid is implemented as claimed in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for controlling smooth switching between grid and off-grid as claimed in any one of claims 1 to 4.

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