A kind of spare power transfer control method and device suitable for multi-power supply system

Abstract

The application discloses a kind of spare power automatic switching control method and device suitable for multi-power supply system, comprising: using multi-power supply fusion controller, the power supply of electric power supply system is identified, registered and parameter acquisition, the information of abstracting and pooling to acquisition data, form virtual power pool;Real-time monitoring load demand, the information of each power state and preset operation strategy, the optimal power supply proportion of each power is dynamically calculated by multi-objective optimization algorithm, for multi-power normal collaborative use;If any main power supply failure is monitored, the multi-power supply fusion controller eliminates fault source in the virtual power pool and recalculates the power supply ratio of remaining power supply, in the process of eliminating fault source in the virtual power pool, through a group of power switching matrix with soft start control, load is smoothly transferred to new power combination, to avoid power quality problems in switching process.The application can realize the management between multi-power and seamless, smooth and undisturbed switching.

Description

Technical Field

[0001] This invention relates to the field of intelligent control and management technology for power supply systems, specifically to a control method, device, and equipment applicable to a multi-source hybrid power supply system including power grid, renewable energy, and energy storage. Background Technology

[0002] Automatic transfer switch (ATS), also known as automatic transfer switch, is a core device that ensures continuous power supply to critical loads. When the main power supply fails, it can automatically switch the load to the backup power supply. It is widely used in important places such as data centers, hospitals, and financial institutions.

[0003] Traditional automatic transfer switch (ATS) technology is mainly designed around a fixed and single power supply architecture such as "mains power-generator" or "dual mains power". This type of technology usually uses mechanical or static switches based on simple logic control. Its switching logic is relatively fixed, and its main function is to detect the loss of power or undervoltage of the main power supply and then trigger the switching.

[0004] However, with the rapid development of distributed energy, modern power supply systems are evolving towards multi-source and hybrid approaches, with multiple power sources such as solar photovoltaic, wind power, and energy storage batteries coexisting. At this point, traditional automatic transfer switch technology faces the following technical challenges:

[0005] (1) Switching shock problem: Traditional automatic transfer switch devices often generate large voltage dips, surge currents and frequency fluctuations at the moment of switching, which can damage sensitive loads such as servers and precision instruments.

[0006] (2) Rigid source management: Existing technologies can usually only switch between a few preset power sources in an "either / or" manner, and cannot coordinate and optimize the power supply of multiple power sources according to factors such as real-time load size, energy cost, and power status.

[0007] (3) Poor scalability: When a new power source needs to be added to the system (e.g., adding a new energy storage system), it is often necessary to make complex modifications and reprogramming to the hardware and control software of the automatic transfer switch, lacking the flexibility of plug and play.

[0008] (4) Low energy utilization: Traditional automatic transfer switch devices only monitor the main power supply during normal operation, while the backup power supply is idle or in standby mode. They cannot integrate the advantages of multiple energy sources (such as using photovoltaics to reduce electricity costs) during normal operation, resulting in energy waste.

[0009] Therefore, this application proposes a backup automatic transfer control method and device suitable for multi-power supply systems, which can intelligently manage multiple heterogeneous power sources, achieve smooth and seamless switching, and has high flexibility, so as to solve the above-mentioned technical problems. Summary of the Invention

[0010] The main objective of this invention is to provide a backup automatic transfer control method and device suitable for multi-power supply systems. By constructing a "virtual power pool" to manage all connected power sources in a unified and flexible manner, and combining adaptive load balancing and soft-start switching technologies, it achieves high-quality and uninterrupted power supply to the load, thereby solving the technical problems mentioned in the background art.

[0011] The present invention solves the above-mentioned technical problems by adopting the following technical solutions:

[0012] A backup automatic transfer control method applicable to multi-power supply systems includes:

[0013] A set of backup automatic transfer control devices are used to connect all power sources in the power supply system. Through the multi-power fusion controller built into the device, the connected power sources are identified, registered and their parameters are collected. The collected data is abstracted and pooled to form a virtual power pool for unified management of power data.

[0014] The multi-power fusion controller monitors information including load demand, power status and preset operating strategies in real time, and dynamically calculates the optimal power supply ratio of each power supply in the virtual power pool through a set of multi-objective optimization algorithms. During normal collaborative use of the multi-power supply, the multi-power supply system supplies power in coordination according to the optimal power supply ratio.

[0015] If any main power supply fails, the multi-power source fusion controller removes the fault source from the virtual power pool and recalculates the power supply ratio of the remaining power sources. During the process of removing the fault source from the virtual power pool, the load is smoothly transferred to the new power supply combination through a power switching matrix with soft-start control to avoid power quality problems during the switching process.

[0016] Preferably, the multi-power source fusion controller, after connecting to the power source, controls the connected... Model each power source, where each power source group is... The state is represented by a parameter vector. To describe, the virtual power pool Defined as the set of all currently available power supply parameter vectors, we have:

[0017]

[0018]

[0019] in, For power supply Rated voltage, For power supply Maximum output power For power supply At any moment The unit cost of electricity supply is time-of-use pricing for the power grid, but can be considered zero for photovoltaic power. For power supply Response rate, For power source type identification (such as grid, photovoltaic, energy storage);

[0020] Total available power of the pool for:

[0021]

[0022] For power supply At any moment The actual available power, for example for energy storage, is related to its SOC;

[0023] When a new power source When a device is hot-swapped into the system, the system performs an update operation: .

[0024] Preferably, the multi-power fusion controller is equipped with a decision algorithm to dynamically solve an optimal power allocation scheme based on the collected real-time data and the user-preset operating mode (e.g., economy priority mode, reliability priority mode, green energy priority mode). Power allocation is performed in the virtual power pool to predict the load in the short term. The specific allocation process includes:

[0025] set up for The load power measured at each time step includes measurement noise. A set of state-space models is constructed as follows:

[0026]

[0027]

[0028] in, For a moment The actual system load status, Here is the state transition matrix. For the observation matrix, and These are process noise and measurement noise, respectively, and are generally Gaussian white noise.

[0029] The optimal predicted value of the load power at the next moment can be obtained through iterative calculation using a Kalman filter. .

[0030] Preferably, the multi-objective optimization algorithm dynamically constructs a set of multi-objective optimal power allocation models based on the optimal power allocation scheme, which are used to calculate the optimal power supply ratio of each power source in the virtual power pool.

[0031] Preferably, the method for constructing the multi-objective optimal power allocation model includes:

[0032] set up For power supply At any moment The power allocation coefficient, i.e., the proportion of load it bears, is the core task of the controller. The controller's main task is to find the optimal coefficient vector and construct a set of multi-objective optimization functions. The multi-objective optimization function is:

[0033]

[0034] The power balance constraint and the power supply capacity constraint are as follows:

[0035]

[0036]

[0037] in, , and These represent the economic cost function, the stability cost function, and the environmental cost function, respectively. , and The weighting coefficients representing economic efficiency, stability, and environmental friendliness are set by the user according to the operating mode. The standard weight normalization constraint for the multi-objective optimization model is given, where k∈{1,2,3} is the dummy index of the weight coefficients, corresponding to the weights of the three sub-objectives: k=1 corresponds to... , used to represent the economic weighting coefficient, k=2 corresponds to , used to represent the stability weight coefficient, k=3 corresponds to Used to represent the environmental weighting coefficient. For power supply carbon emission factors, For power supply At any moment Actual available power Indicates in All information is known at any given time (up to) Given all the measured values ​​L(1), L(2), ..., L(t) at time t, for The optimal predicted value of the load power at any given time is the one-step prediction value of the Kalman filter;

[0038] At this point, the core task of the controller is to find the optimal coefficient vector using methods including linear programming or quadratic programming. Ultimately, the optimal power allocation coefficient can be obtained as the optimal power supply ratio.

[0039] Preferably, the main power supply uses a dynamic waveform fitting algorithm for fault monitoring, continuously comparing the real-time voltage and frequency waveforms of each main power supply with the standard normal waveform;

[0040] The dynamic waveform fitting algorithm is used to calculate the real-time voltage waveform using DTW distance. Compared with standard sine waveform The similarity between them is used to effectively handle phase drift or slight distortion in the waveform. Its mathematical expression is:

[0041]

[0042] in, Two time series and DTW distance between them This is a regular path connecting the start and end points of two sequences. For two points in the sequence and The Euclidean distance between them;

[0043] If the waveform deviation (such as voltage sag or frequency drift) exceeds a preset threshold, or if a complete power disconnection is detected, the main power supply is determined to have failed, and a high-priority switching trigger signal is generated to drive the switching of the corresponding power supply combination. During the generation of the switching trigger signal, a set of fault thresholds is set. The switch is triggered when the following conditions are met:

[0044] ;

[0045] This is a binary fault trigger flag, which is the logic level representation of a "high-priority switching trigger signal." Its value is strictly either 0 or 1, and its specific meaning is as follows:

[0046] =1 indicates that a fault has been detected in the main power supply (severe waveform deviation or complete power loss). The system immediately generates a valid (high level) switching trigger signal to drive the power switching matrix to perform automatic transfer to backup power (smoothly transferring the load to the backup power supply combination).

[0047] =0 indicates that the current waveform of the main power supply is normal (DTW distance is within the allowable range), no switching trigger signal is generated, and the system continues to maintain the current power supply combination.

[0048] Preferably, the multi-power source fusion controller performs the following actions after receiving the switching signal:

[0049] In the virtual power pool, mark the status of the fault source as unavailable;

[0050] Almost simultaneously, new power allocation instructions are recalculated and issued based on the remaining available power supply;

[0051] Activate the switching execution circuit composed of high-speed power electronic switches (such as IGBTs). The switching execution circuit has a power switching matrix with soft-start control. By precisely controlling the conduction angle or duty cycle of the switch, the voltage and current of the alternative power supply are applied to the load in a smooth ramp function form, thereby effectively suppressing surge current and voltage surges and ensuring that the load does not feel any interruption or impact.

[0052] Preferably, the specific process for activating the switching execution circuit to perform the switching operation includes:

[0053] During switching, the power supply output voltage is controlled via PWM to suppress surges. Replacement is performed according to the preset ramp function. A smooth upward trend has the following characteristics:

[0054]

[0055] The ramp function can be viewed as a set of simple linear functions:

[0056]

[0057] in, The magnitude of the target output voltage. To switch the start time, The time elapsed since the switch began. This is a preset voltage ramp-up time, for example, 50ms, used to control the speed of soft start. This is merely a set of auxiliary time variables specifically used to represent "the time elapsed since the start of the switch t_switch", and its definition is: Therefore, here and They are exactly the same function, and are completely equivalent;

[0058] Then, by controlling the PWM duty cycle of the inverter This enables smooth voltage control:

[0059] This method can reduce surge current It is limited to a safe range and is much smaller than the peak value during hard handover.

[0060] An automatic transfer switch control device for multi-power supply systems is provided, which is applicable to any of the above-described automatic transfer switch control methods for multi-power supply systems.

[0061] As can be seen from the above technical solution, the present invention provides a backup automatic transfer control method and device suitable for multi-power supply systems. Compared with the prior art, the present invention has the following advantages:

[0062] 1. By introducing the concept of virtual power pool management and adaptive load balancing control strategy, this invention can intelligently manage multiple heterogeneous power sources, enabling the system to have unprecedented flexibility and scalability, achieving seamless and smooth switching between multiple power sources, and possessing high flexibility, which facilitates the improvement of the overall power supply system's operating economy, reliability, and scalability.

[0063] 2. This invention uses a decision algorithm built into the controller to dynamically solve an optimal power allocation scheme based on real-time data collected and user-preset operating modes. It can achieve hybrid and coordinated power supply from multiple power sources under normal operating conditions, which can not only significantly reduce the overall electricity cost, but also make full use of clean energy and improve the overall energy efficiency of the system.

[0064] It should be understood that the descriptions in this section are not intended to identify key or essential features of embodiments of the invention, nor are they intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Of course, implementing any product of the invention does not necessarily require achieving all of the advantages described above simultaneously. Attached Figure Description

[0065] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0066] Figure 1 This is a schematic diagram of the data processing flow of the present invention. Detailed Implementation

[0067] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] For details in the embodiments, please refer to Figure 1 .

[0069] like Figure 1 As shown in the embodiment of the present invention, the backup automatic transfer control method for multi-power supply systems is based on the construction of a "virtual power pool" to manage all connected power sources in a unified and flexible manner. Combined with adaptive load balancing and soft-start switching technology, it achieves high-quality, uninterrupted power supply to the load. Specifically, it includes the following steps:

[0070] S1. Construction and Management of Virtual Power Pool: A set of standby automatic transfer control devices are used to connect all power sources in the power supply system. After the device is started, it automatically scans and identifies all connected power interfaces. Each power source is regarded as an independent "source node". Its key parameters (such as voltage level, maximum power, power generation cost, response speed, energy type, etc.) are identified, registered and collected into the internal database of the controller through the multi-power fusion controller built into the device. At this time, all successfully registered source nodes are abstracted and pooled to form a unified "virtual power pool".

[0071] The "virtual power pool" here is dynamic. When a new power source is connected (such as inserting a new mobile energy storage vehicle) or an old power source goes offline, the system can automatically update the pool to achieve hot-swapping of power sources.

[0072] Specifically, after the multi-power supply fusion controller is connected to the power supply, it controls the connected... Model each power source, where each power source group... The state is represented by a parameter vector. To describe, virtual power pool Defined as the set of all currently available power supply parameter vectors, we have:

[0073]

[0074]

[0075] in, For power supply Rated voltage, For power supply Maximum output power For power supply At any moment The unit cost of electricity supply (yuan / kWh) is time-of-use pricing for the grid, but can be considered zero for photovoltaic power. For power supply The response rate (kW / s). For power source type identification (such as grid, photovoltaic, energy storage);

[0076] Total available power of the pool for:

[0077]

[0078] For power supply At any moment The actual available power, for example for energy storage, is related to its SOC;

[0079] When a new power source When a device is hot-swapped into the system, the system performs an update operation: .

[0080] S2. Real-time status perception and data acquisition: The multi-power fusion controller in the system continuously collects and monitors the following data in real time at a millisecond frequency through high-precision sensors: (1) the load demand such as real-time total active power, reactive power, current, and voltage on the load side; (2) the power supply status such as the output voltage, frequency, power quality, state of charge (SOC) of the energy storage system, and instantaneous power generation of renewable energy on the power supply side; (3) external information such as the time-of-use electricity price, light intensity prediction, and wind speed prediction of the grid on the environmental and market side; (4) operation strategies (such as the lowest cost and the highest reliability).

[0081] At this point, because the multi-power fusion controller is equipped with a decision-making algorithm, it can dynamically solve for an optimal power allocation scheme based on the collected real-time data and the user-preset operating modes (e.g., economy priority mode, reliability priority mode, green energy priority mode). To achieve accurate power allocation in the virtual power pool, short-term load prediction is required. The specific allocation process includes:

[0082] set up for The load power measured at each moment includes measurement noise. A set of state-space models is constructed as follows:

[0083]

[0084]

[0085] in, For a moment The actual system load status, Here is the state transition matrix. For the observation matrix, and These are process noise and measurement noise, respectively, and are generally Gaussian white noise.

[0086] The optimal predicted value of the load power at the next moment can be obtained through iterative calculation using a Kalman filter. .

[0087] S3. Adaptive Load Balancing and Power Supply Strategy Decision: Based on the real-time data collected above, the controller uses a built-in multi-objective optimization decision algorithm and combines it with the user-preset operating modes (e.g., economy priority mode, reliability priority mode, green energy priority mode) to dynamically calculate the optimal power supply ratio of each power source in the pool. This ratio is used to coordinate power supply during normal operation.

[0088] For example, in the economy-first mode, photovoltaic power, which costs zero, will be used first during the day, with any shortfall supplemented by lower-priced grid electricity or energy storage. The algorithm outputs a precise set of power allocation coefficients, indicating the percentage of load each power source should handle.

[0089] At this point, the multi-objective optimization algorithm dynamically constructs a set of multi-objective optimal power allocation models based on the optimal power allocation scheme. These models are used to calculate the optimal power supply ratio of each power source in the virtual power pool. The methods for constructing the multi-objective optimal power allocation models include:

[0090] set up For power supply At any moment The power allocation coefficient, i.e., the proportion of load it bears, is the core task of the controller. The controller's main task is to find the optimal coefficient vector and construct a set of multi-objective optimization functions. The multi-objective optimization function is:

[0091]

[0092] The power balance constraint and the power supply capacity constraint are as follows:

[0093]

[0094]

[0095] in, , and These represent the economic cost function, the stability cost function, and the environmental cost function, respectively. , and The weighting coefficients representing economic efficiency, stability, and environmental friendliness are set by the user according to the operating mode. The standard weight normalization constraint for the multi-objective optimization model is given, where k∈{1,2,3} is the dummy index of the weight coefficients, corresponding to the weights of the three sub-objectives: k=1 corresponds to... , used to represent the economic weighting coefficient, k=2 corresponds to , used to represent the stability weight coefficient, k=3 corresponds to This is used to represent the environmental weight coefficient. Its technical purpose is to ensure that the sum of the weights of the three sub-objectives in the overall decision is 100%, avoiding non-standard situations where the sum of the weights is greater than 1 (overweighting) or less than 1 (conservative decision-making). This ensures that the comprehensive cost function after multi-objective optimization has clear physical meaning and comparability. For power supply carbon emission factors, For power supply At any moment Actual available power Indicates in All information is known at any given time (up to) Given all the measured values ​​L(1), L(2), ..., L(t) at time t, for The optimal predicted value of the load power at any given time is the one-step prediction value of the Kalman filter;

[0096] At this point, the core task of the controller is to find the optimal coefficient vector using methods including linear programming or quadratic programming. Ultimately, the optimal power allocation coefficient can be obtained as the optimal power supply ratio.

[0097] It's also worth noting that, unlike the simple "primary-backup" switching of traditional automatic transfer switch (ATS), this method uses a built-in decision algorithm in the controller to dynamically solve for an optimal power allocation scheme based on real-time data and user-preset operating modes. This enables hybrid and coordinated power supply from multiple power sources even under normal operating conditions. For example, with a load of 100kW, the controller can calculate the optimal allocation scheme based on real-time conditions: the grid provides 60kW (60%), the photovoltaic system provides 30kW (30%), and the energy storage battery discharges 10kW (10%). This dynamic, proportional energy mixing control not only significantly reduces overall electricity costs but also fully utilizes clean energy, improving the overall energy efficiency of the system.

[0098] S4. Fault Diagnosis and Switching Trigger: When a fault is detected in any main power supply, the system continuously compares the real-time voltage and frequency waveforms of each main power supply with the standard normal waveform using a dynamic waveform fitting algorithm. Once the waveform deviation (such as voltage sag or frequency drift) exceeds a preset threshold, or a complete power disconnection is detected, the fault diagnosis module will immediately determine that the power supply has failed and generate a high-priority switching trigger signal.

[0099] In actual use, in order to accurately detect abnormal power waveforms, the main power supply uses the DTW (Dynamic Time Warping) algorithm as a dynamic waveform fitting algorithm for fault monitoring, and continuously compares the real-time voltage and frequency waveforms of each main power supply with the standard normal waveform.

[0100] Dynamic waveform fitting algorithm is used to calculate real-time voltage waveforms using DTW distance. Compared with standard sine waveform The similarity between them is used to effectively handle phase drift or slight distortion in the waveform. Its mathematical expression is:

[0101]

[0102] in, Two time series and DTW distance between them This is a regular path connecting the start and end points of two sequences. For two points in the sequence and The Euclidean distance between them;

[0103] If the waveform deviation (such as voltage sag or frequency drift) exceeds a preset threshold, or if a complete power disconnection is detected, the main power supply is determined to have failed, and a high-priority switching trigger signal is generated to drive the switching of the corresponding power supply combination. During the generation of the switching trigger signal, a set of fault thresholds is set. The switch is triggered when the following conditions are met:

[0104]

[0105] This is a binary fault trigger flag, which is the logic level representation of a "high-priority switching trigger signal." Its value is strictly either 0 or 1, and its specific meaning is as follows:

[0106] =1 indicates that a fault has been detected in the main power supply (severe waveform deviation or complete power loss). The system immediately generates a valid (high level) switching trigger signal to drive the power switching matrix to perform automatic transfer to backup power (smoothly transferring the load to the backup power supply combination).

[0107] =0 indicates that the current waveform of the main power supply is normal (DTW distance is within the allowable range), no switching trigger signal is generated, and the system continues to maintain the current power supply combination.

[0108] S5. Seamless Switching and Soft-Start Control: Upon receiving a switching signal, the controller immediately performs the following actions: marking the status of the faulty source as "unavailable" in the virtual power pool; the multi-power fusion controller immediately removes the faulty source marked as "unavailable" from the virtual pool; then, almost simultaneously, based on the remaining available power sources, it recalculates and issues new power allocation instructions, recalculates the power supply ratio of the remaining power sources; during the process of removing faulty sources from the virtual power pool, a power switching matrix with soft-start control smoothly transfers the load to the new power supply combination to avoid power quality problems during the switching process.

[0109] The switching execution circuit is composed of high-speed power electronic switches (such as IGBTs). During the switching process, the controller activates the soft-start circuit. By precisely controlling the conduction angle or duty cycle of the switch, the voltage and current of the alternative power supply are applied to the load in a smooth ramp function form, thereby effectively suppressing surge current and voltage surges and ensuring that the load does not feel any interruption or impact.

[0110] Upon receiving the switching signal, the multi-power supply fusion controller performs the following actions:

[0111] In the virtual power pool, mark the status of the fault source as unavailable;

[0112] Almost simultaneously, new power allocation instructions are recalculated and issued based on the remaining available power supply;

[0113] The switching execution circuit, composed of high-speed power electronic switches (such as IGBTs), is activated. The switching execution circuit has a power switching matrix with soft-start control. By precisely controlling the conduction angle or duty cycle of the switch, the voltage and current of the alternative power supply are applied to the load in a smooth ramp function form, thereby effectively suppressing surge current and voltage surges and ensuring that the load does not feel any interruption or impact.

[0114] Furthermore, the specific process for activating the switching operation by switching the execution circuit at this time includes:

[0115] To suppress surges during switching, the power supply output voltage is controlled via PWM. Replacement is performed according to the preset ramp function. A smooth upward trend has the following characteristics:

[0116]

[0117] The ramp function can be viewed as a set of simple linear functions:

[0118]

[0119] in, The magnitude of the target output voltage. To switch the start time, The time elapsed since the switch began. The preset voltage ramp-up time, such as 50ms, is used to control the speed of soft start;

[0120] Here This is merely a set of auxiliary time variables specifically used to represent "the time elapsed since the start of the switch t_switch", and its definition is: Therefore, here and They are exactly the same function; they are completely equivalent.

[0121] Then, by controlling the PWM duty cycle of the inverter This enables smooth voltage control:

[0122] This method can reduce surge current. It is limited to a safe range and is much smaller than the peak value during hard handover.

[0123] It should be further explained that the virtual power pool proposed in this application can logically unify multiple physically dispersed and heterogeneous power sources into a "central energy pool" that can be flexibly scheduled and allocated on demand. This enables the system to have unprecedented flexibility and scalability. Adding or removing a power source is simply an addition or subtraction of elements in the pool for the system, without changing the core control logic. Therefore, this pooling design completely breaks away from the rigid architecture of the traditional fixed "N-choose-1" or "N-choose-2" backup power supply and can be adapted to highly uncertain energy access scenarios.

[0124] In a specific test example, the control results of the "virtual power pool" management concept and the adaptive load balancing control strategy of this application were further compared and tested, as follows:

[0125] (a) Test Scenario

[0126] To construct a power supply system for a small data center with a critical load of 200kW, the system is connected to three power sources:

[0127] (a) Mains power supply: Mains power is used;

[0128] (b) Backup power supply 1: adopts a 150kW photovoltaic + 100kWh energy storage battery system;

[0129] (c) Backup power supply 2: A 250kW diesel generator is used;

[0130] The test simulated a sudden power failure (voltage drop to 70%) at 14:00 (peak photovoltaic output) to compare the performance of the traditional backup self-discharge scheme with that of the present invention.

[0131] (II) Test Operation Procedure

[0132] (1) Testing process for traditional backup self-connection scheme

[0133] A1. Normal state: The load is entirely supplied by the mains power. The photovoltaic system is idle or only used for a small amount of its own electricity.

[0134] A2. Fault Occurrence: The automatic transfer switch detects that the mains voltage is lower than the threshold. After a 100ms delay for confirmation, it disconnects the mains side switch and closes the diesel generator side switch.

[0135] A3. Switching Process: The load experienced a complete power outage of approximately 150ms. The instant the generator started and connected to the load, a huge voltage dip (down to 85% of rated voltage) and a surge of more than 5 times the rated current were generated, which may have caused some servers to restart.

[0136] (2) Testing process of the method in this application

[0137] B1. Normal State: The controller is in "Economy Priority" mode. According to the relevant algorithm formula of the multi-objective optimal power allocation model, the system supplies power to the load in a hybrid mode of "100kW mains power + 100kW photovoltaic", and the energy storage system is in standby state;

[0138] B2. Fault Occurrence: The dynamic waveform fitting algorithm (DTW dynamic time warping algorithm) detects an abnormality in the mains waveform within 10ms and immediately triggers a switchover.

[0139] B3. Switching process:

[0140] (L1) The controller removes mains power from the virtual power pool;

[0141] (L2) Immediately recalculate the allocation scheme: the photovoltaic system maintains an output of 100kW, and the energy storage system immediately supplements an additional 100kW from 0;

[0142] (L3) Through soft-start control (using ramp function PWM control for smooth switching), the output power of the energy storage inverter smoothly increases from 0 to 100kW within 30ms;

[0143] (L4) Throughout the entire process, voltage fluctuations on the load side were suppressed to within 2%, with no perceptible power interruption. The diesel generator served as a final backup and did not need to be started at all.

[0144] (III) Comparison of Test Results

[0145] The results of the test procedures for the traditional self-connection scheme and the self-connection scheme of this application are compared in the following table:

[0146]

[0147] As can be seen from the comparison of the above test scenarios, the method proposed in this application, by introducing the concept of virtual power pool management and adaptive load balancing control strategy, can intelligently manage multiple heterogeneous power sources, enabling the system to have unprecedented flexibility and scalability, achieving seamless and smooth switching between multiple power sources, and possessing high flexibility. This facilitates the improvement of the overall power supply system's operating economy, reliability, and scalability. Compared with traditional technologies, it exhibits overwhelming advantages in power supply reliability, power quality, operating economy, and system flexibility.

[0148] On the other hand, the present invention also discloses a backup automatic transfer control device suitable for multi-power supply systems, which is applicable to any of the above-mentioned backup automatic transfer control methods suitable for multi-power supply systems.

[0149] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the backup automatic transfer control methods and apparatuses applicable to multi-power supply systems described above.

[0150] It is understood that the system provided in the embodiments of the present invention corresponds to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above methods.

[0151] This application also provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus.

[0152] Memory, used to store computer programs;

[0153] When the processor executes the program stored in the memory, it implements the above-described automatic transfer switch control method and apparatus applicable to multi-power supply systems.

[0154] The communication bus mentioned in the aforementioned electronic devices can be a peripheral component interconnection standard applicable to backup automatic transfer control methods and devices in multi-power supply systems, or an extended industrial standard structure applicable to backup automatic transfer control methods and devices in multi-power supply systems. This communication bus can be divided into address bus, data bus, control bus, etc.

[0155] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0156] The memory may include random access memory suitable for automatic switching control methods and apparatus in multi-power supply systems, or non-volatile memory suitable for automatic switching control methods and apparatus in multi-power supply systems, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0157] The aforementioned processor can be a general-purpose processor, including a central processing unit suitable for automatic transfer switching control methods and devices in multi-power supply systems, a network processor suitable for automatic transfer switching control methods and devices in multi-power supply systems, etc.; it can also be a digital signal processor suitable for automatic transfer switching control methods and devices in multi-power supply systems, an application-specific integrated circuit suitable for automatic transfer switching control methods and devices in multi-power supply systems, a field-programmable gate array suitable for automatic transfer switching control methods and devices in multi-power supply systems, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0158] It should also be noted that electronic devices also include terminal devices, which can also be referred to as backup automatic transfer control methods and devices for terminals in multi-power supply systems, backup automatic transfer control methods and devices for user equipment in multi-power supply systems, backup automatic transfer control methods and devices for mobile stations in multi-power supply systems, backup automatic transfer control methods and devices for mobile terminals in multi-power supply systems, etc. Terminal devices can be mobile phones, smart TVs, wearable devices, tablets, computers with wireless transceiver capabilities, virtual reality, augmented reality, industrial control, autonomous driving, remote surgery, smart grids, transportation safety, smart cities, smart homes, etc. The embodiments of this application do not limit the specific technology or form of the terminal devices used.

[0159] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc.

[0160] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0161] Furthermore, it should be noted that if any directional indication (such as up, down, left, right, front, back, etc.) is involved in the embodiments of the present invention, the directional indication is only used to explain the relative positional relationship and movement of each component in a specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0162] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, in the embodiments of this invention, "multiple" refers to two or more. Moreover, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

Claims

1. A backup automatic transfer control method applicable to multi-power supply systems, characterized in that, include: A set of backup automatic transfer control devices are used to connect all power sources in the power supply system. Through the multi-power fusion controller built into the device, the connected power sources are identified, registered and their parameters are collected. The collected data is abstracted and pooled to form a virtual power pool for unified management of power data. The multi-power fusion controller monitors information including load demand, power status and preset operating strategies in real time, and dynamically calculates the optimal power supply ratio of each power supply in the virtual power pool through a multi-objective optimization algorithm for normal collaborative use of the multi-power supply. If any main power supply fails, the multi-power fusion controller removes the fault source from the virtual power pool and recalculates the power supply ratio of the remaining power sources. During the process of removing the fault source from the virtual power pool, the load is smoothly transferred to the new power supply combination through a power switching matrix with soft-start control to avoid power quality problems during the switching process. The multi-power source fusion controller is equipped with a decision algorithm to dynamically solve for the optimal power allocation scheme based on the collected real-time data and the user-preset operating mode. The specific allocation process includes: set up for The load power measured at each moment includes measurement noise. A set of state-space models is constructed as follows: in, For a moment The actual system load status, Here is the state transition matrix. For the observation matrix, and These are process noise and measurement noise, respectively. The optimal predicted value of the load power at the next moment can be obtained through iterative calculation using a Kalman filter. .

2. The automatic transfer switch control method for multi-power supply systems as described in claim 1, characterized in that, The multi-power fusion controller, after connecting to the power supply, [processes / controls] the connected power supply. Model each power source, where each power source group is... The state is represented by a parameter vector. To describe, the virtual power pool Defined as the set of all currently available power supply parameter vectors, we have: in, For power supply Rated voltage, For power supply Maximum output power For power supply At any moment The unit cost of electricity supply is time-of-use pricing for the power grid, but can be considered zero for photovoltaic power. For power supply Response rate, For power source type identification (such as grid, photovoltaic, energy storage); When a new power source When a device is hot-swapped into the system, the system performs an update operation: .

3. The automatic transfer switch control method for multi-power supply systems as described in claim 2, characterized in that, The multi-objective optimization algorithm dynamically constructs a set of multi-objective optimal power allocation models based on the optimal power allocation scheme, which are used to calculate the optimal power supply ratio of each power source in the virtual power pool.

4. The automatic transfer switch control method for multi-power supply systems as described in claim 3, characterized in that, The method for constructing the multi-objective optimal power allocation model includes: set up For power supply At any moment The power allocation coefficients are used to construct a set of multi-objective optimization functions. The multi-objective optimization function is: The power balance constraint and the power supply capacity constraint are as follows: in, , and These represent the economic cost function, the stability cost function, and the environmental cost function, respectively. , and These represent the weighting coefficients for economic efficiency, stability, and environmental friendliness, respectively. The standard weight normalization constraint for the multi-objective optimization model is given, where k∈{1,2,3} are the subscript indices of the weight coefficients, corresponding to the weights of the three sub-objectives: k=1 corresponds to... , used to represent the economic weighting coefficient, k=2 corresponds to , used to represent the stability weight coefficient, k=3 corresponds to Used to represent the environmental weighting coefficient. For power supply carbon emission factors, For power supply At any moment Actual available power Indicates in Given that all information is known at all times, for The optimal predicted value of the load power at any given time is the one-step prediction value of the Kalman filter; The optimal coefficient vector can be found using methods including linear programming or quadratic programming. The optimal power allocation coefficient is obtained as the optimal power supply ratio.

5. The automatic transfer switch control method for multi-power supply systems as described in claim 4, characterized in that, The main power supply uses a dynamic waveform fitting algorithm for fault monitoring, continuously comparing the real-time voltage and frequency waveforms of each main power supply with the standard normal waveform. If the waveform deviation exceeds the preset threshold, or if the power supply is completely disconnected, the main power supply is determined to be faulty, and a high-priority switching trigger signal is generated to drive the switching of the corresponding power supply combination.

6. The automatic transfer switch control method for multi-power supply systems as described in claim 5, characterized in that, The dynamic waveform fitting algorithm is used to calculate the real-time voltage waveform using DTW distance. Compared with standard sine waveform The similarity between them can be expressed mathematically as follows: in, Two time series and DTW distance between them This is a regular path connecting the start and end points of two sequences. For two points in the sequence and The Euclidean distance between them.

7. The automatic transfer switch control method for multi-power supply systems as described in claim 6, characterized in that, Upon receiving the switching signal, the multi-power supply fusion controller performs the following actions: In the virtual power pool, mark the status of the fault source as unavailable; Recalculate and issue new power allocation instructions based on the remaining available power; The switching execution circuit is activated. The switching execution circuit has a power switching matrix with soft-start control. By precisely controlling the conduction angle or duty cycle of the switch, the voltage and current of the alternative power supply are applied to the load in a smooth ramp function form.

8. The automatic transfer switch control method for multi-power supply systems as described in claim 7, characterized in that, The specific process for activating and executing the switching operation by the switching execution circuit includes: The output voltage of the power supply is controlled by PWM. Replacement is performed according to the preset ramp function. A smooth upward trend has the following characteristics: The ramp function can be considered as a linear function: ; in, The magnitude of the target output voltage. To switch the start time, The time elapsed since the switch began. This is the preset voltage ramp-up time; Then, by controlling the PWM duty cycle of the inverter This allows for smooth voltage control.

9. A backup automatic transfer control device suitable for multi-power supply systems, characterized in that, The automatic transfer switch control method applicable to multi-power supply systems as described in any one of claims 1-8 above.

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