Spare power automatic switching control method and device suitable for multi-power supply system

Abstract

The invention discloses a spare power automatic switching control method and device suitable for a multi-power-source power supply system, and the method comprises the steps: carrying out the recognition, registration and parameter collection of a power source of the power supply system through a multi-power-source fusion controller, carrying out the abstraction and pooling of collected data, and forming a virtual power source pool; information including a load demand, each power supply state and a preset operation strategy is monitored in real time, and the optimal power supply proportion of each power supply is dynamically calculated through a multi-target optimization algorithm for normal cooperative use of multiple power supplies; if any main power supply is monitored to have a fault, the multi-power-supply fusion controller removes a fault source in the virtual power supply pool and recalculates the power supply ratio of the remaining power supplies, and in the process of removing the fault source in the virtual power supply pool, the power supply ratio of the remaining power supplies is calculated; a load is smoothly transferred to a new power supply combination through a group of power switching matrixes with soft start control, and the problem of electric energy quality in the switching process is avoided. According to the invention, management and seamless, smooth and undisturbed switching among multiple power supplies can be realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent control and management of power supply systems, in particular to a control method and device and equipment suitable for a multi-power supply hybrid power supply system including power grids, renewable energy sources and energy storage. BACKGROUND

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

[0003] Traditional backup power supply technology mainly focuses on the design of fixed and single power supply structures such as "mains-generators" or "double mains". This type of technology usually uses mechanical or simple logic control-based static switches, and the switching logic is relatively fixed. The main function is to detect the loss of power or under-voltage of the main power supply, and then trigger the switch.

[0004] However, with the rapid development of distributed energy, modern power supply systems are evolving towards multi-source and hybridization, with multiple power supply forms such as solar photovoltaic, wind power, energy storage batteries coexisting. At this time, the traditional backup power supply technology has the following technical problems: (1) Switching impact problem: the traditional backup power supply device often produces a large voltage sag, surge current and frequency fluctuation at the moment of switching, causing damage to sensitive loads such as servers and precision instruments; (2) Source management rigidity: existing technologies can only switch between a few pre-set power sources in a "this or that" manner, and cannot perform proportional collaborative power supply and optimized scheduling of multiple power sources according to real-time load size, energy cost, power supply status and other factors; (3) Poor scalability: when a new power source needs to be added to the system (for example, a new energy storage system is added), the hardware and control software of the backup power supply often need to be complexly modified and reprogrammed, lacking the flexibility of plug-and-play; (4) Low energy utilization rate: the traditional backup power supply device only monitors the main power supply during normal operation, and the backup power supply is in idle or standby state, which cannot integrate the advantages of multiple energy sources (such as using photovoltaic to reduce electricity costs) during normal operation, resulting in waste of energy.

[0005] Therefore, the present application proposes a backup power supply control method and device suitable for a multi-power supply system, which can intelligently manage multiple heterogeneous power sources, achieve smooth and disturbance-free switching, and have high flexibility to solve the above technical problems. SUMMARY

[0006] 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.

[0007] The present invention solves the above-mentioned technical problems by adopting the following technical solutions: A backup automatic transfer control method applicable to multi-power supply systems includes: 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 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. 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.

[0008] 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:

[0009]

[0010] 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, identify the type of power source (e.g. grid, photovoltaic, energy storage); total available power of the pool is:

[0011] power source the actual available power at time , for example for energy storage, which is related to its SOC; when a new power source is hot-plugged into the system, the system performs an update operation: .

[0012] Preferably, the multi-power source fusion controller is provided with a decision algorithm for dynamically solving an optimal power distribution scheme according to the collected real-time data and in combination with the user's preset operation mode (e.g. economy priority mode, reliability priority mode, green energy priority mode), wherein the power distribution is performed in the virtual power source pool to predict the load in a short time, and the specific distribution process includes: Let be the measured load power at time t, which contains measurement noise, a set of state space models is constructed, and

[0013]

[0014] wherein, is the true load state of the system at time t, is the state transition matrix, is the observation matrix, and and are the process noise and measurement noise, respectively, which are generally Gaussian white noise; the optimal predicted value of the load power at the next time t+1 can be obtained by iterative calculation through the Kalman filter .

[0015] Preferably, the multi-objective optimization algorithm dynamically constructs a set of multi-objective optimal power distribution models based on the optimal power distribution scheme, for calculating the optimal power supply ratio of each power source in the virtual power source pool.

[0016] Preferably, the construction method of the multi-objective optimal power distribution model includes: Let be the power at time t The core task of the controller is to solve the optimal coefficient vector, and a set of multi-objective optimization functions is constructed The multi-objective optimization functions are:

[0017] The power balance constraint condition and the power supply capacity constraint are:

[0018]

[0019] wherein, , and respectively represent the economic cost function, the stability cost function and the environmental cost function, , and respectively represent the economic, stability and environmental weight coefficients, which are set by the user according to the operation mode, and is a standard weight normalization constraint condition of the multi-objective optimization model, wherein k∈{1,2,3} is a dummy index of the weight coefficient, corresponding to the weight of the three sub-goals: k=1 corresponds to , used to represent the economic weight coefficient, k=2 corresponds to , used to represent the stability weight coefficient, and k=3 corresponds to , used to represent the environmental weight coefficient, is the carbon emission factor of the power supply , is the actual available power of the power supply at time , represents the optimal prediction value of the load power at time under the condition that all information known at time (all measurement values L(1), L(2), …, L(t) up to time ); At this time, the core task of the controller is to solve the optimal coefficient vector by linear programming or quadratic programming, and finally the optimal power distribution coefficient as the optimal power supply ratio can be obtained.

[0020] Preferably, the main power supply is monitored for failure by a dynamic waveform fitting algorithm, which continuously compares the real-time voltage and frequency waveforms of each main power supply with standard normal waveforms. The dynamic waveform fitting algorithm is used to calculate the real-time voltage waveform and the standard sine waveform by DTW distance The similarity between them is used to effectively handle phase drift or slight distortion in the waveform. Its mathematical expression is:

[0021] 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; 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: ; 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: =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). =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.

[0022] Preferably, the multi-power source fusion controller performs the following actions after receiving the switching signal: In the virtual power pool, mark the status of the fault source as unavailable; Almost simultaneously, new power allocation instructions are recalculated and issued based on the remaining available power supply; 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.

[0023] Preferably, the switching execution circuit activates a specific flow of executing the switching operation, which includes: In order to suppress the impact when performing the switching, the output voltage of the power supply is controlled by PWM The alternative is to follow a preset ramp function Smoothly rising, there are:

[0024] Among them, the ramp function can be regarded as a set of simple linear functions:

[0025] Among them, is the amplitude of the target output voltage, is the time when the switching starts, is the time elapsed from the start of the switching, is the preset voltage ramp time, for example 50ms, used to control the speed of soft start, here is only a set of auxiliary time variables, which are used to specifically represent "the time elapsed from the switching start time t_switch", and its definition is: Therefore, here and are completely the same function, and they are completely equivalent; Then by controlling the PWM duty cycle of the inverter The smooth control of the voltage can be realized: This way can limit the inrush current In a safe range, which is much smaller than the peak value in hard switching.

[0026] A backup power supply control device suitable for a multi-power supply system, which is suitable for any of the above-mentioned backup power supply control methods suitable for a multi-power supply system.

[0027] From the above technical solution, the present application provides a backup power supply control method and device suitable for a multi-power supply system. Compared with the prior art, the present application has the following advantages: 1. The present application introduces the concept of virtual power supply pool management and adaptive load balancing control strategy, which can intelligently manage multiple heterogeneous power supplies, making the system have unprecedented flexibility and scalability, realizing seamless and smooth switching between multiple power supplies, and having high flexibility, which is convenient for improving the operation economy, reliability and scalability of the entire power supply system.

[0028] 2.The application can realize the mixed and collaborative power supply of multiple power sources under normal working condition by the decision algorithm built in the controller, according to the real-time data collected and the running mode preset by the user, dynamically solving an optimal power distribution scheme, which can not only significantly reduce the comprehensive power consumption cost, but also fully utilize clean energy and improve the overall energy efficiency of the system.

[0029] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the application, nor to limit the scope of the application. Other features of the application will become apparent through the following description. Of course, any product implementing the application does not necessarily need to achieve all the advantages mentioned above. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings, which form a part of this specification, are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification. The drawings illustrate one illustrative embodiment of the application and, although the application will be described in connection with these specific embodiments, it will be understood that the application is not limited to any such embodiments. In the drawings: Figure 1 The data processing flow diagram of the application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. The embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work are within the protection scope of the application.

[0032] In the embodiments, refer to Figure 1 .

[0033] As Figure 1 shown, the backup power automatic switching control method suitable for the multi-power supply system proposed in the embodiments of the application is mainly to build a "virtual power source pool" to uniformly and flexibly manage all the connected power sources, and combine the adaptive load balancing and soft start switching technology to realize high-quality and uninterrupted power supply for the load, specifically including the following steps: S1. Construction and management of virtual power pool: using a set of self-throwing control devices to access all power sources of the power supply system, the device automatically scans and identifies all connected power interfaces after starting. Each power source is regarded as an independent "source node", and its key parameters (such as voltage level, maximum power, power generation cost, response speed, energy type, etc.) are identified, registered and parameter collected to the internal database of the controller through the built-in multi-power fusion controller. At this time, all registered source nodes are abstracted and pooled to form a unified management "virtual power pool".

[0034] The "virtual power pool" here is dynamically changing. When a new power source is connected (such as inserting a new mobile energy storage vehicle) or an old power source is offline, the system can automatically update the pool and realize hot plug of the power source.

[0035] Specifically, the multi-power fusion controller models the power source after accessing the power source, where the state of each group of power sources is described by a parameter vector , and the virtual power pool is defined as the set of all current available power parameter vectors, which has:

[0036]

[0037] wherein is the rated voltage of the power source , the maximum output power of the power source , the unit power supply cost (yuan / kWh) of the power source at time , the response rate (kW / s) of the power source , and the power source type identifier (such as grid, photovoltaic, and energy storage); The total available power of the pool is:

[0038] The actual available power of the power source at time , for example, for energy storage, it is related to its SOC; When a new power source is hot-plugged into the system, the system performs an update operation: .

[0039] ​​​​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).

[0040] 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: set up for The load power measured at each moment includes measurement noise. A set of state-space models is constructed as follows:

[0041]

[0042] 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. The optimal predicted value of the load power at the next moment can be obtained through iterative calculation using a Kalman filter. .

[0043] 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.

[0044] 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.

[0045] At this time, the multi-objective optimization algorithm dynamically constructs a set of multi-objective optimal power distribution models based on the optimal power distribution scheme, which is used to calculate the optimal power supply proportion of each power supply in the virtual power supply pool. The construction method of the multi-objective optimal power distribution model includes: Let be the power supply At time , the power distribution coefficient, i.e., the proportion of bearing load, the core task of the controller is to solve the optimal coefficient vector, and construct a set of multi-objective optimization functions , the multi-objective optimization function is:

[0046] The power balance constraint condition and the power supply capacity constraint are respectively:

[0047]

[0048] Among them, , and respectively represent the economic cost function, the stability cost function and the environmental cost function, , and respectively represent the weight coefficients of economy, stability and environmental protection, which are set by the user according to the operation mode, and is the standard weight normalization constraint condition of the multi-objective optimization model, wherein k∈{1,2,3} is the dummy index of the weight coefficient, corresponding to the weight of the three sub-goals respectively: k=1 corresponds to , used to represent the economy weight coefficient, k=2 corresponds to , used to represent the stability weight coefficient, k=3 corresponds to , used to represent the environmental protection weight coefficient, the technical purpose of which is to ensure that the sum of the weights of the three sub-goals in the total decision is 100%, avoiding the non-normal situation that the total weight is greater than 1 (overweight) or less than 1 (conservative decision), so as to ensure that the comprehensive cost function after multi-objective optimization has clear physical meaning and comparability, is the carbon emission factor of the power supply , is the actual available power of the power supply at time , represents the known information at time (all measurement values L(1), L(2), …, L(t) up to time ), The optimal predicted value of the momentary load power, i.e., the one-step prediction value of the Kalman filter; At this time, the core task of the controller is to solve the optimal coefficient vector by methods such as linear programming or quadratic programming , and finally obtain the optimal power distribution coefficient as the optimal power supply ratio.

[0049] At this time, it also needs to be supplemented that, unlike the traditional simple "main-backup" switching of the backup power supply, this method dynamically solves an optimal power distribution scheme according to the real-time data collected and in combination with the user's preset operation mode through the decision algorithm built in the controller, and can realize the mixed and collaborative power supply of multiple power sources in the normal working state. For example, when the load is 100kW, the controller can calculate the optimal distribution scheme as: the power grid bears 60kW (60%), the photovoltaic system bears 30kW (30%), and the energy storage battery discharges 10kW (10%). This dynamic and proportional energy mixing control not only can significantly reduce the comprehensive electricity cost, but also can fully utilize clean energy and improve the overall energy efficiency of the system.

[0050] S4. Fault diagnosis and switching triggering: when any main power supply is monitored to be faulty, the system continuously compares the real-time voltage and frequency waveforms of each main power supply with the standard normal waveform through a dynamic waveform fitting algorithm. Once the deviation (such as voltage sag, frequency drift) of the waveform exceeds the preset threshold, or the power supply is detected to be completely disconnected, the fault diagnosis module will immediately determine that the power supply is failed, and generate a high-priority switching trigger signal.

[0051] At this time, in the specific actual use process, in order to accurately detect the abnormality of the power supply waveform, the main power supply is monitored through the DTW (dynamic time warping) algorithm as the dynamic waveform fitting algorithm, and the real-time voltage and frequency waveforms of each main power supply are continuously compared with the standard normal waveform; The dynamic waveform fitting algorithm is used to calculate the similarity between the real-time voltage waveform and the standard sinusoidal waveform , so as to effectively handle the phase drift or slight distortion of the waveform, and the mathematical expression is:

[0052] wherein, is the DTW distance between two time series and , is a warping path connecting the start and end points of the two sequences, is the Euclidean distance between two points and in the sequence; ​If the waveform deviation (such as voltage sag, frequency drift) exceeds the preset threshold, or the power supply is completely disconnected, it is determined that the main power supply fails, 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 When the following conditions are met, switching is triggered:

[0053] Fault Trigger Flag is a binary fault trigger flag, which is a logical level representation of the "high-priority switching trigger signal". Its value is strictly 0 or 1, and the specific meaning is as follows: =1 indicates that a fault has been detected in the main power supply (severe waveform deviation or complete power failure), and the system immediately generates an effective (high level) switching trigger signal to drive the power switching matrix to perform the backup power transfer action (smoothly transfer the load to the backup power supply combination); =0 indicates that the main power supply is currently normal (DTW distance within the allowed range), and no switching trigger signal is generated. The system continues to maintain the current power supply combination.

[0054] S5. Seamless switching and soft start control: After receiving the switching signal, the controller immediately performs the following actions: marks the fault source as "unavailable" in the virtual power pool, and immediately excludes the marked "unavailable" fault source from the virtual pool. Then, based on the remaining available power sources, the controller recalculates and issues new power distribution instructions, recalculates the power supply ratio of the remaining power sources, and uses a power switching matrix with soft start control to smoothly transfer the load to the new power supply combination to avoid power quality problems during the switching process.

[0055] 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 to control the conduction angle or duty cycle of the switch precisely, so that the voltage and current of the replacement power source are loaded onto the load in the form of a smooth ramp function, effectively suppressing the inrush current and voltage jump, and ensuring that the load does not feel any interruption or impact.

[0056] After receiving the switching signal, the multi-power fusion controller performs the following actions: Mark the status of the fault source as "unavailable" in the virtual power pool; Recalculate and issue new power distribution instructions based on the remaining available power sources almost simultaneously; The switching execution circuit composed of high-speed power electronic switches (such as IGBT) is activated, and the switching execution circuit has a power switching matrix with soft start control. By accurately controlling the conduction angle or duty cycle of the switch, the voltage and current of the replacement power source are loaded onto the load in the form of a smooth ramp function, thereby effectively suppressing the inrush current and voltage mutation, and ensuring that the load cannot feel any interruption or impact.

[0057] Further, the specific process of the switching execution circuit activating the switching operation at this time includes: In order to suppress the impact during the switching, the output voltage of the power supply is controlled by PWM The replacement is performed according to the preset ramp function Smoothly rising, there are:

[0058] Among them, the ramp function can be regarded as a group of simple linear functions:

[0059] Among them, is the amplitude of the target output voltage, is the time when the switching starts, is the time elapsed from the start of the switching, is the preset voltage ramp time, for example, 50ms, used to control the speed of soft start; Here is only a group of auxiliary time variables, which are used to specifically represent "the time elapsed from the switching start time t_switch", and its definition is: Therefore, here is the same function as is completely equivalent Then, by controlling the PWM duty cycle of the inverter The smooth control of the voltage can be realized: This way can limit the inrush current to a safe range, which is much smaller than the peak value in hard switching.

[0060] At this time, it needs to be supplemented that the virtual power pool proposed in this application can logically unify the physically dispersed and heterogeneous multiple power sources into a "central energy library" that can be flexibly scheduled and allocated on demand, so that the system can have unprecedented flexibility and scalability. At this time, adding or removing a power source is only an increase or decrease of elements in the pool, without the need to change the core control logic. Therefore, this pooling design completely gets rid of the rigid architecture of traditional backup power supply fixed "N selects 1" or "N selects 2", and can be applied to highly uncertain energy access scenarios.

[0061] In a specific test example, the "virtual power cell" management concept and adaptive load balancing control strategy control results of the present application are further compared and tested as follows: (I) Test scenario A small data center power supply system is constructed, with a key load of 200kW. The system is connected to three power sources: (a) Main power supply: using commercial power; (b) Backup power supply 1: using a 150kW photovoltaic + 100kWh energy storage battery system; (c) Backup power supply 2: using a 250kW diesel generator; The test content is to simulate a sudden failure of commercial power at 14:00 (peak period of photovoltaic output) (voltage drop to 70%), in order to compare the performance of the traditional backup automatic switching scheme and the scheme of the present application.

[0062] (II) Test operation process (1) Test process of traditional backup automatic switching scheme A1. Normal state: the load is completely supplied by commercial power. The photovoltaic system is idle or only used in small amounts; A2. Fault occurs: the backup automatic switching detects that the commercial power voltage is lower than the threshold value, and after a 100ms delay confirmation, the commercial power side switch is opened and the diesel generator side switch is closed; A3. Switching process: the load experiences a complete power failure time of about 150ms. At the moment when the generator starts and brings up the load, a huge voltage sag (dropping to 85% of rated voltage) and a surge of more than 5 times the rated current are generated, which may cause some servers to restart.

[0063] (2) Test process of the method of the present application B1. Normal state: the controller is in "economic priority" mode. According to the relevant algorithm formula of the multi-objective optimal power distribution model, the system supplies power to the load in a mixed mode of "commercial power 100kW + photovoltaic 100kW", and the energy storage system is in standby state; B2. Fault occurs: the dynamic waveform fitting algorithm (DTW dynamic time warping algorithm) detects abnormal commercial power waveform within 10ms, and immediately triggers switching.

[0064] B3. Switching process: (L1) The controller removes commercial power from the virtual power cell; (L2) Immediately recalculate the distribution scheme: photovoltaic remains 100kW output, and the energy storage system immediately supplements an additional 100kW from 0; (L3) Through the soft start control (smooth switching by using the PWM control of the ramp function), the output power of the energy storage inverter is smoothly climbed from 0 to 100kW within 30ms; (L4) During the whole process, the voltage fluctuation of the load side is suppressed within 2%, without any perceptible power interruption. The diesel generator as the last backup does not need to be started throughout the journey.

[0065] (Three) Test effect comparison The results of the comparison between the test process based on the traditional backup automatic switching scheme and the test process based on the backup automatic switching scheme of the present application are shown in the following table:

[0066] Through the comparison of the above test scenarios, it can be seen that the method proposed in the present application can intelligently manage multiple heterogeneous power sources by introducing the concept of virtual power pool management and adaptive load balancing control strategy, so that the system has unprecedented flexibility and scalability, realizes seamless and smooth and undisturbed switching between multiple power sources, and has high flexibility, which is convenient for improving the operation economy, reliability and scalability of the entire power supply system. Compared with the traditional technology, it has overwhelming advantages in power supply reliability, power quality, operation economy and system flexibility.

[0067] On the other hand, the present application also discloses a backup automatic switching control device suitable for a multi-power supply system, which is suitable for any of the backup automatic switching control methods suitable for a multi-power supply system.

[0068] In another embodiment provided by the present application, a computer program product containing instructions is also provided, which, when running on a computer, causes the computer to execute any of the backup automatic switching control methods and devices suitable for a multi-power supply system in the above embodiments.

[0069] It can be understood that the system provided by the embodiments of the present application corresponds to the method provided by the embodiments of the present application, and the explanation, examples and beneficial effects of the related content can refer to the corresponding parts in the above method.

[0070] The present application also provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus, The memory is used to store computer programs; The processor is used to execute the programs stored on the memory, so as to realize the backup automatic switching control method and device suitable for a multi-power supply system.

[0071] The communication bus mentioned in the above electronic device can be a peripheral component interconnect bus or an extended industry standard architecture bus.

[0072] The communication interface is used for communication between the above electronic device and other devices.

[0073] The memory can include a random access memory, and can also include a non-volatile memory, for example, at least one disk memory. Optionally, the memory can also be at least one storage device located away from the processor.

[0074] The processor mentioned above can be a general-purpose processor, including a central processing unit, a network processor, etc. It can also be a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0075] It should be further explained that the electronic device also includes a terminal device, which can also be referred to as a terminal. The terminal device can be a mobile phone, a smart television, a wearable device, a tablet computer, a computer with wireless transceiver function, a virtual reality terminal device, an augmented reality terminal device, a wireless terminal in an industrial control terminal device, a wireless terminal in an unmanned driving terminal device, a wireless terminal in a remote surgery terminal device, a wireless terminal in a smart grid terminal device, a wireless terminal in a transportation safety terminal device, a wireless terminal in a smart city terminal device, a wireless terminal in a smart home terminal device, and the like. Embodiments of the present application do not limit the specific technology and specific device form of the terminal device.

[0076] In the above embodiments, the implementation can be achieved by software, hardware, firmware or any combination thereof, entirely or partially. When implemented by software, the implementation can be achieved in the form of a computer program product, entirely or partially. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the flow or function described in the embodiments of the present application is entirely or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired or wireless means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media sets. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc.

[0077] The above merely describes preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0078] In addition, it should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement condition, etc. between components in a certain posture, and if the certain posture changes, the directional indications also change accordingly.

[0079] In addition, if the embodiments of the present application involve descriptions of "first", "second", etc., the descriptions of "first", "second", etc. are only for description purposes and cannot be understood as indicating or implying the relative importance of the technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing throughout the text includes three parallel solutions. Taking "A and / or B" as an example, it includes A solution, or B solution, or A and B solutions. In addition, in the embodiments of the present application, "a plurality of" means two or more. In addition, the technical solutions of each embodiment can be combined with each other, but it must be based on the realization of ordinary skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, nor is it within the protection scope required by the present application.

Claims

1. A kind of spare power supply control method suitable for multi-power supply system, it is characterized in that, The application relates to a backup automatic switching control method for a multi-power supply system. The multi-power supply fusion controller monitors the load demand, the state of each power supply and the preset operation strategy in real time, dynamically calculates the optimal power supply proportion of each power supply in the virtual power supply pool through a multi-objective optimization algorithm, and the multi-power supply is normally used in cooperation. If any main power supply fails, the multi-power supply fusion controller excludes the fault source in the virtual power supply pool and recalculates the power supply proportion of the remaining power supplies. The multi-power supply fusion controller is provided with a decision algorithm for dynamically solving an optimal power distribution scheme according to the collected real-time data and the preset operation mode of a user.

2. The backup power transfer control method for a multi-power supply power supply system according to claim 1, characterized in that, The multi-source fusion controller models the accessed power sources, where the state of each group of power sources is described by a parameter vector The virtual power pool is defined as the set of all currently available power parameter vectors, and there is: 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 The system performs an update operation when a hot plug-in access system: .

3. The backup power transfer control method for a multi-power supply power supply system according to claim 2, characterized in that, The multi-objective optimization algorithm dynamically constructs a multi-objective optimal power distribution model based on the optimal power distribution scheme, and the model is used for calculating the optimal power supply proportion of each power supply in the virtual power supply pool. Let To The measured load power at the moment, which contains measurement noise, constructs a set of state space models, which are: wherein, is the system true load state at time is the state transition matrix, is the observation matrix, and are the process noise and measurement noise, respectively;​ The optimal predicted value of the load power at the next time can be obtained by iterative calculation through the Kalman filter .

4. The backup power transfer control method for a multi-power supply power supply system according to claim 3, characterized in that, The multi-objective optimal power distribution model is constructed by the following method:

5. The backup power transfer control method for a multi-power supply power supply system according to claim 4, characterized in that, The power balance constraint condition and the power supply capacity constraint condition are respectively as follows: Set Power supply At time The power distribution coefficient, a set of multi-objective optimization functions , the multi-objective optimization function is: The main power supply is monitored for failure through a dynamic waveform fitting algorithm, and the real-time voltage and frequency waveforms of each main power supply are continuously compared with standard normal waveforms. wherein, , and represent economic cost function, stability cost function and environmental cost function, respectively, , and represent the weight coefficients of economy, stability and environmental protection, respectively, and is the standard weight normalization constraint condition of the multi-objective optimization model, wherein k ∈ {1, 2, 3} is the index of the weight coefficient, corresponding to the weight of the three sub-goals respectively: k = 1 corresponds to , used to represent the economy weight coefficient, k = 2 corresponds to , used to represent the stability weight coefficient, and k = 3 corresponds to , used to represent the environmental protection weight coefficient, is the carbon emission factor of the power supply , is the actual available power of the power supply at time , represents the optimal prediction value of the load power at time under the condition of knowing all information at time , that is, the one-step prediction value of the Kalman filter. Solving the optimal coefficient vector by methods including linear programming or quadratic programming Obtaining the optimal power distribution coefficient as the optimal power supply ratio.

6. The backup power transfer control method for a multi-power supply power supply system according to claim 5, wherein, If the waveform deviation exceeds the preset threshold value or the power supply is completely disconnected, the main power supply is determined to be invalid, and a high-priority switching trigger signal is generated to drive the switching of the corresponding power supply combination. After the multi-power supply fusion controller receives the switching signal, the following actions are performed:

7. The method for the backup power transfer control suitable for the multi-power supply system according to claim 6, characterized in that, The dynamic waveform fitting algorithm is used to calculate the similarity between real-time voltage waveforms by DTW distance and a standard sinusoidal waveform The mathematical expression is as follows: wherein, is the DTW distance between two time series and , is a warping path connecting the start and end points of the two sequences, is the Euclidean distance between two points and in the sequences.

8. The backup power transfer control method for a multi-power supply power supply system according to claim 5, wherein, The state of the fault source is marked as unavailable in the virtual power supply pool; The new power distribution instruction is recalculated and issued based on the remaining available power supplies; The switching execution circuit is activated, the switching execution circuit is provided with a soft-start-controlled power switching matrix, the on-angle or duty cycle of the switch is accurately controlled, and the voltage and current of the replacement power supply are loaded onto the load in the form of a smooth ramp function. The specific process of the switching execution circuit for executing the switching operation includes:

9. The backup power transfer control method for a multi-power supply power supply system according to claim 8, wherein, The application is suitable for the backup automatic switching control method for the multi-power supply system. Controlling the output voltage of a power supply by PWM Substitution, with a predetermined ramp function Smooth ramp up, with: Wherein, the ramp function can be regarded as a linear function: ; wherein, is the amplitude of the target output voltage, is the time of the start of the switching, is the time elapsed from the start of the switching, is the preset voltage ramp-up time; Afterwards the PWM duty cycle of the inverter is controlled This allows a smooth control of the voltage.

10. A kind to be used for the spare power supply system of multi-power supply, it is characterized in that, ​

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