Matrix adjustable flexible power supply working state intelligent switching method

Abstract

The application provides a matrix-adjustable flexible power supply working state intelligent switching method, relates to the technical field of power conversion, and comprises the following steps: collecting power grid power supply voltage information and target device operation characteristic information; voltage fluctuation analysis is conducted to obtain a fluctuation amplitude; when the fluctuation amplitude reaches a fluctuation threshold value, stable voltage supply is conducted through an energy storage unit and an inverter unit; when the fluctuation threshold value is not reached, fluctuation operation influence analysis is conducted to obtain a first stable voltage coefficient; energy storage characteristic information is collected to conduct stable voltage analysis and obtain a second stable voltage coefficient; power supply voltage information is predicted to obtain a predicted fluctuation duration, target device energy consumption analysis is conducted, and a predicted stable voltage time is obtained; a third stable voltage coefficient is obtained, a comprehensive stable voltage coefficient is calculated, and it is judged whether a switch unit is closed or not. The application solves the technical problems that a traditional power supply system lacks intelligent coping strategies when facing power grid fluctuations, resulting in low energy utilization and poor device working stability.

Description

Technical Field

[0001] The present invention relates to the technical field of power conversion, and in particular to a method for intelligently switching the working states of a matrix adjustable flexible power supply. Background Art

[0002] Matrix adjustable flexible power supplies are widely used in power systems. With the increase in the proportion of renewable energy and changes in electricity demand, power system control has become more complex. On the one hand, grid fluctuations can lead to unstable power supply voltage, which in turn affects the normal operation of target equipment and even damages the equipment. Traditional power supply systems cannot adjust in time when facing such fluctuations, resulting in unstable equipment operation; on the other hand, traditional power supply systems can only be adjusted in a fixed way when dealing with fluctuations, and cannot flexibly optimize energy utilization, resulting in energy waste. Summary of the Invention

[0003] This application provides a matrix-adjustable flexible power supply working state intelligent switching method, aiming to solve the technical problems that traditional power supply systems lack intelligent response strategies when facing unstable power supply voltage caused by grid fluctuations, and are unable to flexibly adjust the power supply mode according to power supply needs, resulting in low energy utilization and poor equipment working stability.

[0004] In view of the above problems, the present application provides a method for intelligent switching of the working state of a matrix adjustable flexible power supply.

[0005] The present application discloses a method for intelligent switching of the working state of a matrix adjustable flexible power supply, which is applied to a matrix adjustable flexible power supply, wherein the matrix adjustable flexible power supply includes a switch unit, a detection unit, an energy storage unit and an inverter unit, and the method includes: during the operation of a target device under power supply from the grid, collecting power supply voltage information of the grid and operating characteristic information of the target device through the detection unit of the matrix adjustable flexible power supply, wherein the matrix adjustable flexible power supply connects the grid and the target device, the target device is an electrical device, and the switch unit is turned on when the grid is powered; when the power supply voltage information deviates from the preset voltage, a voltage fluctuation analysis is performed based on the power supply voltage information to obtain a fluctuation amplitude, and when the fluctuation amplitude reaches a fluctuation threshold, the switch unit is turned off, and the target device is supplied with a stable voltage through the energy storage unit and the inverter unit; When the fluctuation amplitude does not reach the fluctuation threshold, a fluctuation operation impact analysis is performed based on the fluctuation amplitude and the operation characteristic information to obtain the operation impact coefficient, and the first voltage stabilization coefficient is obtained by analysis; the energy storage characteristic information of the energy storage unit is collected, and a voltage stabilization analysis is performed to obtain the second voltage stabilization coefficient; the supply voltage information is predicted to obtain a predicted fluctuation duration, and an energy consumption analysis of the target device is performed based on the operation characteristic information to obtain the device energy consumption parameters, and the predicted voltage stabilization time is obtained by analysis based on the energy storage characteristic information; a voltage stabilization analysis is performed based on the predicted fluctuation duration and the predicted voltage stabilization time to obtain a third voltage stabilization coefficient, and a comprehensive voltage stabilization coefficient is calculated based on the first voltage stabilization coefficient and the second voltage stabilization coefficient, and whether to turn off the switch unit is determined according to the comprehensive voltage stabilization coefficient, and the target device is supplied with voltage stabilization power through the energy storage unit and the inverter unit.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] By detecting grid supply voltage information and performing fluctuation analysis, the switch unit is promptly shut down when the fluctuation amplitude reaches a threshold. The target device is then stabilized and supplied with power through the energy storage unit and inverter unit, ensuring stable operation during grid fluctuations. Based on the fluctuation amplitude, operating characteristics, and energy storage characteristics, combined with the predicted fluctuation duration and predicted voltage stabilization time, the first, second, and third voltage stabilization coefficients are calculated. A comprehensive weighted voltage stabilization coefficient is then calculated to intelligently determine whether to shut down the switch unit and optimize the power supply strategy. By intelligently determining power supply demand and flexibly adjusting the power supply mode, combined with the energy storage unit to store and release electrical energy, efficient energy utilization is achieved, energy waste is reduced, and energy utilization is improved. Overall, this matrix-adjustable flexible power supply operating state intelligent switching method effectively solves the problems existing in traditional power supply systems in terms of grid fluctuations and equipment power supply management, improves power supply stability and energy utilization efficiency, and enhances the intelligence and energy efficiency of the power system.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic diagram of a process flow of a matrix adjustable flexible power supply working state intelligent switching method is provided for an embodiment of the present application;

[0010] Figure 2 A schematic diagram of a voltage fluctuation analysis process in a matrix adjustable flexible power supply working state intelligent switching method is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0011] The embodiment of the present application solves the technical problems that traditional power supply systems lack intelligent response strategies when facing unstable power supply voltage caused by power grid fluctuations, and are unable to flexibly adjust the power supply mode according to power supply needs, resulting in low energy utilization and poor equipment working stability, by providing a matrix-adjustable flexible power supply working state intelligent switching method.

[0012] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0013] like Figure 1 As shown, an embodiment of the present application provides a method for intelligently switching the working state of a matrix adjustable flexible power supply. The method is applied to a matrix adjustable flexible power supply, which includes a switching unit, a detection unit, an energy storage unit, and an inverter unit. The method includes:

[0014] During the operation of the target device under the power supply of the grid, the power supply voltage information of the grid and the operating characteristic information of the target device are collected through the detection unit of the matrix adjustable flexible power supply, wherein the matrix adjustable flexible power supply connects the grid and the target device, the target device is an electrical device, and the switch unit is turned on when the target device is operated under the power supply of the grid.

[0015] The matrix-adjustable flexible power supply working state intelligent switching method provided by the embodiments of the present application is applied to a matrix-adjustable flexible power supply, the matrix-adjustable flexible power supply comprises a switching unit, a detection unit, an energy storage unit and an inverter unit, wherein the switching unit is used for managing the connection and disconnection of the power supply to realize the adjustment of the output voltage; the detection unit is used for detecting the grid power supply voltage and the target device running characteristic information, so that the system can adjust according to the information; the energy storage unit is used for storing energy, which is usually a battery or a super capacitor, and is used for providing additional power support when the grid voltage fluctuates; and the inverter unit is used for converting direct current into alternating current, and in the matrix-adjustable flexible power supply, the inverter unit is used for converting the energy stored in the energy storage unit into a current or voltage form suitable for the target device.

[0016] Firstly, the matrix-adjustable flexible power supply is connected to the grid and the target device, and the target device is a power consumption device; in the case that the grid stably supplies power to the target device, the switching unit of the matrix-adjustable flexible power supply is in an open state, so that the current can flow through the circuit and supply the grid voltage to the target device; the power supply voltage information of the grid is collected by the detection unit, that is, the sensor or monitoring device is used to monitor the change of the grid voltage in real time, and the obtained grid power supply voltage information includes voltage value, voltage fluctuation frequency, voltage stability and other data. At the same time, the running characteristic information of the target device is collected, which includes the running load, running mode (such as normal running, standby, high load running, etc.), running power and the like of the target device.

[0017] When the power supply voltage information deviates from the preset voltage, voltage fluctuation analysis is performed according to the power supply voltage information to obtain the fluctuation amplitude, and when the fluctuation amplitude reaches the fluctuation threshold, the switching unit is closed, and the energy storage unit and the inverter unit are used to supply stable voltage to the target device.

[0018] A preset voltage, that is, an ideal value of the target grid voltage, is set, and when the actual power supply voltage deviates from the preset voltage, deviation judgment is performed, for example, whether the actual voltage is greater than or less than a threshold range of the preset voltage, if the power supply voltage deviates from the preset voltage, voltage fluctuation analysis is performed to calculate the fluctuation amplitude of the voltage, and the fluctuation amplitude can represent the degree of change and stability of the voltage.

[0019] The calculated fluctuation amplitude is compared with the pre-set fluctuation threshold, and the fluctuation threshold is a standard, which represents the degree of voltage fluctuation that needs to be stabilized, if the fluctuation amplitude reaches the fluctuation threshold, the switching unit is closed, the direct power supply to the target device from the grid is stopped, at the same time, the energy storage unit and the inverter unit are enabled, the energy stored in the energy storage unit is converted into stable voltage through the inverter unit to supply the target device, the stable power supply operation is realized, and the stable power supply of the target device is ensured when the voltage fluctuation is large.

[0020] Furthermore, if Figure 2 As shown, when the supply voltage information deviates from the preset voltage, voltage fluctuation analysis is performed according to the supply voltage information to obtain the fluctuation amplitude, including:

[0021] The rated voltage of the target device during operation is obtained as the preset voltage; a sample power supply voltage information set is obtained, and a sample fluctuation amplitude set is obtained based on the deviation of different sample power supply voltage information from the rated voltage, and a voltage fluctuation analyzer is constructed; it is determined whether the power supply voltage information deviates from the preset voltage; if not, the grid power supply operation is continued; if so, the power supply voltage information is subjected to fluctuation analysis by the voltage fluctuation analyzer to obtain the fluctuation amplitude.

[0022] The rated voltage of the target device during operation is obtained from the device specifications. The rated voltage refers to the voltage value required for normal operation of the device, that is, the ideal voltage required by the device. The obtained rated voltage is used as the preset voltage.

[0023] Through the historical monitoring data records of the power supply of the power grid, a set of sample power supply voltage information over a period of time is collected. Each sample includes a corresponding power supply voltage value. For each sample, it is compared with the rated voltage of the target device, and the amplitude of the deviation of the sample power supply voltage information from the rated voltage, that is, the fluctuation amplitude, is calculated to obtain a set of sample fluctuation amplitudes.

[0024] The collected sample power supply voltage information set and the corresponding sample fluctuation amplitude set are used as the training data set, and the data set is divided into a training set and a validation set. A voltage fluctuation analyzer model is constructed based on a neural network. The training set is used to train the neural network model. The network weights and biases are updated through the back propagation algorithm to minimize the loss function. The trained model is evaluated using the validation set. The evaluation indicators can include accuracy. The model is tuned according to the evaluation results to improve the performance of the fluctuation analyzer, and finally a trained voltage fluctuation analyzer is obtained.

[0025] The current supply voltage information is compared with the rated voltage of the target device. If the difference between the current supply voltage and the preset voltage is within the allowable error range, it means there is no deviation. The grid power supply operation state is maintained and no additional voltage stabilization control is performed. Otherwise, if there is a deviation, additional voltage stabilization control is required.

[0026] In the event of a deviation, the voltage fluctuation analyzer is activated. It receives the current supply voltage information as input and analyzes the fluctuation to obtain the fluctuation amplitude. The fluctuation amplitude is used to assess the current voltage fluctuation and determine whether voltage stabilization control is needed to maintain stable operation of the equipment.

[0027] When the fluctuation amplitude does not reach the fluctuation threshold, a fluctuation operation impact analysis is performed according to the fluctuation amplitude and the operation characteristic information to obtain an operation impact coefficient, and then a first voltage stabilization coefficient is obtained through analysis.

[0028] If the fluctuation amplitude reaches the threshold, the voltage is directly stabilized and the power supply is provided. Otherwise, if the threshold is not reached, the need for voltage stabilization of the energy storage unit is analyzed from three aspects: first, based on the fluctuation amplitude and operating characteristics, the analysis shows that the greater the impact of the fluctuation amplitude on the operating characteristics, the greater the first voltage stabilization coefficient; second, the less the storage capacity, the greater the impact of discharge on the life of the energy storage unit, and the smaller the second voltage stabilization coefficient; third, the longer the predicted fluctuation duration, the shorter the predicted voltage stabilization time, and the smaller the third voltage stabilization coefficient.

[0029] Furthermore, when the fluctuation amplitude does not reach the fluctuation threshold, a fluctuation operation impact analysis is performed based on the fluctuation amplitude and the operation characteristic information to obtain an operation impact coefficient, including:

[0030] Based on the operation records of the target device, a sample fluctuation amplitude set and a sample operation feature information set are obtained; according to the operation quality impact amplitude of the target device under different sample fluctuation amplitudes and sample operation feature information, a sample operation impact coefficient set is obtained; using the sample fluctuation amplitude set and the sample operation feature information set as input, and using the sample operation impact coefficient set as output, an operation impact analyzer is constructed, and an operation impact analysis is performed on the fluctuation amplitude and operation feature information to obtain the operation impact coefficient.

[0031] Through historical data records, the target device's operating records over the past period are obtained, including information such as power supply voltage, operating load, operating mode, and operating power. For each operating record, the fluctuation amplitude is calculated based on the difference between its power supply voltage and the preset voltage, forming a sample fluctuation amplitude set. Based on the target device's operating records, operating characteristic information is extracted. Operating characteristic information includes multiple attributes, each corresponding to the device's operating status under different circumstances, such as operating load, operating mode, and operating power. All operating characteristic information is integrated into a sample operating characteristic information set. The sample fluctuation amplitude set is paired with the sample operating characteristic information set, and each sample fluctuation amplitude has a one-to-one correspondence with the corresponding operating characteristic information.

[0032] The influence coefficient reflects the degree of influence of voltage fluctuations and operating characteristics on the operating quality of the target equipment. It can be determined through expert evaluation, data analysis, etc. For the obtained sample fluctuation amplitude set and sample operation characteristic information set, for each sample, the influence coefficient is calculated based on the sample fluctuation amplitude and sample operation characteristic information, and the influence coefficients corresponding to each sample are integrated to form a sample operation influence coefficient set.

[0033] The obtained sample fluctuation amplitude set and sample operation feature information set are used as input data, and the corresponding sample operation impact coefficient set is used as output data. An operation impact analyzer is constructed based on a neural network, and the data set is divided into a training set and a validation set. For example, 80% of the data is used as a training set and 20% of the data is used as a validation set. The neural network model is trained using the training set, and the network weights and biases are updated through the back-propagation algorithm to minimize the loss function. The trained model is evaluated using the validation set. The evaluation indicators may include loss values, etc. The model is optimized according to the evaluation results to improve the performance of the operation impact analyzer and obtain a trained operation impact analyzer.

[0034] Furthermore, the first voltage regulation coefficient is obtained by analysis, including:

[0035] Based on the operation data records of the target device, a set of sample operation influence coefficients is obtained; according to the improvement degree of the operation quality of the voltage-regulated power supply to the target device under different sample operation influence coefficients, a set of sample first voltage stabilization coefficients is obtained; using the sample operation influence coefficient set and the sample first voltage stabilization coefficient set, a first voltage stabilization analyzer is constructed, and a voltage stabilization analysis is performed on the operation influence coefficient to obtain the first voltage stabilization coefficient.

[0036] The operation data records of the target device within a certain time range are obtained, and the sample operation impact coefficients are extracted from them to form a sample operation impact coefficient set.

[0037] Determine the degree of impact of different sample operation impact coefficients on the target device's regulated power supply and obtain a first voltage stabilization coefficient, which is used to measure the degree to which the regulated power supply improves the device's operational quality. This coefficient can be expressed as a percentage, for example. Calculate the first voltage stabilization coefficient based on the improvement in operational quality after regulated power supply to the target device under different sets of sample operation impact coefficients. Collect the first voltage stabilization coefficients corresponding to each sample operation impact coefficient to form a sample first voltage stabilization coefficient set.

[0038] The set of sample operating influence coefficients is used as input data, and the corresponding set of sample first voltage stabilization coefficients is used as output data. A first voltage stabilization analyzer is constructed based on a neural network. The dataset is divided into a training set and a validation set. The training set is used to train the neural network model, and the trained model is evaluated using the validation set. Based on the evaluation results, the model is adjusted and optimized to obtain a trained first voltage stabilization analyzer. The first voltage stabilization analyzer is used to perform voltage stabilization analysis on the current operating influence coefficients. The model predicts the first voltage stabilization coefficient based on the learned features and patterns.

[0039] Collect energy storage characteristic information of the energy storage unit, perform voltage stabilization analysis, and obtain a second voltage stabilization coefficient.

[0040] Furthermore, collecting energy storage characteristic information of the energy storage unit, performing voltage stabilization analysis, and obtaining a second voltage stabilization coefficient include:

[0041] The present storage energy information of the energy storage unit is collected as the energy storage characteristic information; a set of sample energy storage characteristic information is obtained, and a set of sample second voltage stabilization coefficients is obtained based on the magnitude of the impact of power supply of the energy storage unit on the life of the energy storage unit under different sample energy storage characteristic information, wherein the magnitude of the impact is negatively correlated with the sample second voltage stabilization coefficient; a second voltage stabilization analyzer is constructed using the sample energy storage characteristic information set and the sample second voltage stabilization coefficient set, and a voltage stabilization analysis is performed on the energy storage characteristic information to obtain the second voltage stabilization coefficient.

[0042] Sensors or monitoring devices collect real-time information about the energy storage unit's current energy storage capacity, such as the battery charge level and the amount of energy stored in the unit. This collected energy storage capacity information is used as part of the energy storage characteristic information and combined with other characteristics of the energy storage unit, such as its type, rated capacity, and charge and discharge characteristics, to construct a complete energy storage characteristic information.

[0043] Energy storage characteristic information of different samples is collected. The sample data covers various situations that may occur in the energy storage unit. Based on the set of energy storage characteristic information, the degree of influence of the power supply of the energy storage unit on the life of the energy storage unit under different samples is analyzed. Based on the analysis results, a set of sample second voltage regulation coefficients is obtained, where the influence amplitude and the second voltage regulation coefficient are negatively correlated, which means that the greater the influence amplitude, the smaller the second voltage regulation coefficient, and vice versa.

[0044] The sample energy storage characteristic information set is used as input data, and the corresponding sample second voltage stabilization coefficient set is used as output data. A second voltage stabilization analyzer is constructed based on a neural network. The data set is divided into a training set and a validation set. The training set is used to train the neural network model, and the validation set is used to evaluate the trained model. The model is optimized based on the evaluation results to obtain a trained second voltage stabilization analyzer. The second voltage stabilization analyzer is used to perform voltage stabilization analysis on the current energy storage characteristic information and predict the second voltage stabilization coefficient.

[0045] The power supply voltage information is predicted to obtain a predicted fluctuation duration, energy consumption analysis of the target device is performed based on the operation characteristic information to obtain device energy consumption parameters, and the predicted voltage stabilization time is analyzed and obtained in combination with the energy storage characteristic information.

[0046] Furthermore, predicting the supply voltage information to obtain a predicted fluctuation duration, performing energy consumption analysis on the target device based on the operation characteristic information to obtain device energy consumption parameters, and analyzing and obtaining a predicted voltage stabilization time in combination with the energy storage characteristic information, includes:

[0047] Based on the power supply voltage recording data of the power grid, a sample power supply voltage information set and a sample fluctuation duration set are obtained to construct a voltage fluctuation predictor; based on the voltage fluctuation predictor, the power supply voltage information is predicted to obtain the predicted fluctuation time; based on the operating characteristic information, the energy consumption of the target equipment is analyzed to obtain the equipment energy consumption parameters; combined with the equipment energy consumption parameters and energy storage characteristic information, the predicted voltage stabilization time is analyzed and obtained.

[0048] Collect historical data of the power grid supply voltage, extract a sample power supply voltage information set, including the power supply voltage values ​​at different time points, and calculate the duration of each voltage fluctuation to form a sample fluctuation duration set.

[0049] A voltage fluctuation predictor is constructed based on a neural network. The sample supply voltage information set is used as input data, and the sample fluctuation duration set is used as output data. The data set is divided into a training set and a validation set. The training set is used to train the fluctuation predictor model, and the validation set is used to evaluate the trained fluctuation predictor model. The model is optimized according to the evaluation results to improve the performance and accuracy of the fluctuation predictor.

[0050] The power supply voltage information is used as input data and input into the trained voltage fluctuation predictor model. The model predicts the fluctuation of the power supply voltage in the future based on the characteristic information of the input data and the pattern learned from historical data, and obtains the prediction result, that is, the predicted fluctuation time.

[0051] Based on the operational characteristics, data analysis is performed to fit an energy consumption model. This energy consumption model can be based on physical principles, such as equipment operating efficiency and energy consumption curves, or it can be based on statistical analysis, such as regression analysis. Based on the energy consumption model, the energy consumption parameters of the target equipment under different operating conditions, such as average energy consumption, peak energy consumption, and energy consumption curves, are calculated to obtain the equipment energy consumption parameters.

[0052] Analyze the relationship between the equipment's energy consumption parameters and energy storage characteristics, such as the relationship between stored energy and power supply time, and the impact of discharge on the life of the energy storage unit. Calculate the predicted voltage stabilization time. That is, based on factors such as the capacity, charge and discharge efficiency, and current stored energy of the energy storage unit, predict the voltage stabilization time that the energy storage unit can provide under given energy consumption conditions. This is the predicted voltage stabilization time.

[0053] A voltage stabilization analysis is performed based on the predicted fluctuation duration and the predicted voltage stabilization time to obtain a third voltage stabilization coefficient. The first voltage stabilization coefficient and the second voltage stabilization coefficient are combined to calculate a comprehensive voltage stabilization coefficient. According to the comprehensive voltage stabilization coefficient, it is determined whether to turn off the switch unit, and the target device is supplied with voltage stabilization through the energy storage unit and the inverter unit.

[0054] Furthermore, a voltage stabilization analysis is performed based on the predicted fluctuation duration and the predicted voltage stabilization time to obtain a third voltage stabilization coefficient, including:

[0055] According to the predicted fluctuation duration and the predicted voltage stabilization time, a third voltage stabilization coefficient is calculated as follows:

[0056]

[0057] Among them, K3 is the third voltage regulation coefficient, T w To predict the stabilization time, T b To predict the duration of fluctuations.

[0058] Specifically, according to the predicted fluctuation duration and the predicted voltage stabilization time, a third voltage stabilization coefficient is calculated as follows:

[0059]

[0060] In this formula, the third voltage stabilization coefficient K3 is calculated based on the predicted fluctuation duration T b And the predicted stabilization time T w If the predicted voltage stabilization time T w Greater than or equal to the predicted fluctuation duration T b , then the third voltage stabilization coefficient K3 is 1, which means that in this case, the estimated time for the device to require voltage stabilization power supply exceeds the duration of the grid fluctuation, so the voltage stabilization power supply is directly performed; if the predicted voltage stabilization time T w Less than the predicted fluctuation duration T b , then the third voltage stabilization coefficient K3 is This means that the time the device is expected to need a regulated power supply is shorter than the duration of the grid fluctuation. Therefore, the third voltage regulation coefficient will be adjusted according to this ratio to more accurately determine whether a regulated power supply from the energy storage unit is required.

[0061] Furthermore, combining the first voltage stabilization coefficient and the second voltage stabilization coefficient to calculate a comprehensive voltage stabilization coefficient, determining whether to turn off the switch unit according to the comprehensive voltage stabilization coefficient, and providing a stable voltage supply to the target device through the energy storage unit and the inverter unit, including:

[0062] Perform weighted calculation on the first voltage stabilization coefficient, the second voltage stabilization coefficient and the third voltage stabilization coefficient to obtain the comprehensive voltage stabilization coefficient; determine whether the comprehensive voltage stabilization coefficient is greater than the voltage stabilization coefficient threshold, and if so, turn off the switch unit and provide stable voltage supply to the target device through the energy storage unit and the inverter unit.

[0063] The first voltage stabilization coefficient, the second voltage stabilization coefficient, and the third voltage stabilization coefficient are weighted and calculated according to preset weights to obtain a comprehensive voltage stabilization coefficient, wherein the preset weights are determined according to actual needs and system characteristics.

[0064] The calculated comprehensive voltage regulation coefficient is compared with the pre-set voltage regulation coefficient threshold. If the comprehensive voltage regulation coefficient is greater than the voltage regulation coefficient threshold, it means that the target device can be supplied with voltage regulation power by the energy storage unit and the inverter unit, and the switch unit is turned off at this time; if the comprehensive voltage regulation coefficient is less than or equal to the voltage regulation coefficient threshold, the energy storage unit does not need to be supplied with voltage regulation power at the current situation, and the switch unit can continue to supply power directly.

[0065] In summary, the method for intelligently switching the working state of a matrix-adjustable flexible power supply provided in the embodiments of the present application has the following technical effects:

[0066] 1. By detecting grid power supply voltage information and performing fluctuation analysis, the system promptly shuts down the switch unit when the fluctuation amplitude reaches the threshold, and provides stable power supply to the target device through the energy storage unit and inverter unit, ensuring that the device can maintain stable operation during grid fluctuations.

[0067] 2. Based on the fluctuation amplitude, operating characteristics, and energy storage characteristics, combined with the predicted fluctuation duration and predicted voltage stabilization time, the first, second, and third voltage stabilization coefficients are calculated. A comprehensive weighted calculation of the overall voltage stabilization coefficient is then performed to intelligently determine whether to shut down the switch unit and optimize the power supply strategy.

[0068] 3. Through intelligent judgment of power supply demand and flexible adjustment of power supply mode, combined with energy storage units to store and release electrical energy, efficient energy utilization can be achieved, energy waste can be reduced, and energy utilization rate can be improved.

[0069] Overall, this matrix-adjustable flexible power supply working state intelligent switching method effectively solves the problems of traditional power supply systems in grid fluctuations and equipment power supply management, improves power supply stability and energy utilization efficiency, and enhances the intelligence and energy efficiency of the power system.

[0070] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A matrix adjustable flexible power supply working state intelligent switching method, characterized in that: The method is applied to a matrix adjustable flexible power supply, which includes a switch unit, a detection unit, an energy storage unit, and an inverter unit. The method includes: During the operation of the target device under the power supply of the grid, the power supply voltage information of the grid and the operating characteristic information of the target device are collected by the detection unit of the matrix adjustable flexible power supply, wherein the matrix adjustable flexible power supply is connected to the grid and the target device, the target device is an electrical device, and the switch unit is turned on when the target device is under the power supply of the grid; When the supply voltage information deviates from the preset voltage, a voltage fluctuation analysis is performed based on the supply voltage information to obtain a fluctuation amplitude. When the fluctuation amplitude reaches a fluctuation threshold, the switch unit is turned off, and a stable voltage supply is provided to the target device through the energy storage unit and the inverter unit. When the fluctuation amplitude does not reach the fluctuation threshold, performing a fluctuation operation impact analysis based on the fluctuation amplitude and the operation characteristic information to obtain an operation impact coefficient, and analyzing and obtaining a first voltage stabilization coefficient; Collecting energy storage characteristic information of the energy storage unit, performing voltage stabilization analysis, and obtaining a second voltage stabilization coefficient; Predicting the supply voltage information to obtain a predicted fluctuation duration, performing energy consumption analysis on the target device based on the operation characteristic information to obtain device energy consumption parameters, and analyzing and obtaining a predicted voltage stabilization time in combination with the energy storage characteristic information; Performing a voltage stabilization analysis based on the predicted fluctuation duration and the predicted voltage stabilization time to obtain a third voltage stabilization coefficient, calculating a comprehensive voltage stabilization coefficient by combining the first voltage stabilization coefficient, the second voltage stabilization coefficient, and the third voltage stabilization coefficient, and determining whether to turn off the switch unit according to the comprehensive voltage stabilization coefficient, and providing a stable voltage supply to the target device through the energy storage unit and the inverter unit; The first voltage stabilization coefficient is obtained by analysis, including: Based on the operation data records of the target equipment, a set of sample operation influence coefficients is obtained; Obtain a first voltage stabilization coefficient set of the samples according to the improvement of the operation quality of the voltage stabilization power supply to the target device under different sample operation impact coefficients; Using the sample operation influence coefficient set and the sample first voltage stabilization coefficient set, constructing a first voltage stabilization analyzer, performing voltage stabilization analysis on the operation influence coefficient, and obtaining the first voltage stabilization coefficient; The process of collecting energy storage characteristic information of the energy storage unit, performing voltage stabilization analysis, and obtaining a second voltage stabilization coefficient includes: Collecting the current storage energy information of the energy storage unit as energy storage characteristic information; Obtaining a set of sample energy storage characteristic information, and processing to obtain a set of sample second voltage stabilization coefficients based on the magnitude of the impact of power supply by the energy storage unit on the life of the energy storage unit under different sample energy storage characteristic information, wherein the magnitude of the impact is negatively correlated with the sample second voltage stabilization coefficient; Using the sample energy storage characteristic information set and the sample second voltage stabilization coefficient set, constructing a second voltage stabilization analyzer, performing voltage stabilization analysis on the energy storage characteristic information, and obtaining a second voltage stabilization coefficient; The voltage stabilization analysis is performed according to the predicted fluctuation duration and the predicted voltage stabilization time to obtain a third voltage stabilization coefficient, including: According to the predicted fluctuation duration and the predicted voltage stabilization time, a third voltage stabilization coefficient is calculated as follows: ； in, is the third voltage regulation coefficient, To predict the stabilization time, To predict the duration of fluctuation.

2. The method according to claim 1, characterized in that When the supply voltage information deviates from a preset voltage, performing voltage fluctuation analysis based on the supply voltage information to obtain a fluctuation amplitude includes: Obtain the rated voltage of the target device during operation as the preset voltage; Obtain a set of sample power supply voltage information, and according to the magnitude of deviation of different sample power supply voltage information from the rated voltage, obtain a set of sample fluctuation amplitudes to construct a voltage fluctuation analyzer; Determine whether the power supply voltage information deviates from the preset voltage. If not, continue the grid power supply operation. If so, perform fluctuation analysis on the power supply voltage information through the voltage fluctuation analyzer to obtain the fluctuation amplitude.

3. The method according to claim 1, characterized in that When the fluctuation amplitude does not reach the fluctuation threshold, a fluctuation operation impact analysis is performed based on the fluctuation amplitude and the operation characteristic information to obtain an operation impact coefficient, including: Based on the operation records of the target device, a sample fluctuation amplitude set and a sample operation feature information set are obtained; Obtain a set of sample operation influence coefficients according to the operation quality influence amplitude of the target device under different sample fluctuation amplitudes and sample operation characteristic information; The sample fluctuation amplitude set and the sample operation characteristic information set are used as input, and the sample operation impact coefficient set is used as output to construct an operation impact analyzer, perform operation impact analysis on the fluctuation amplitude and operation characteristic information, and obtain the operation impact coefficient.

4. The method according to claim 1, wherein Predicting the supply voltage information to obtain a predicted fluctuation duration, performing energy consumption analysis on the target device based on the operation characteristic information to obtain device energy consumption parameters, and analyzing and obtaining a predicted voltage stabilization time in combination with the energy storage characteristic information, including: According to the power supply voltage record data of the power grid, a sample power supply voltage information set and a sample fluctuation duration set are obtained to build a voltage fluctuation predictor; Based on the voltage fluctuation predictor, predict the supply voltage information to obtain the predicted fluctuation duration; Performing energy consumption analysis on the target device based on the operation characteristic information to obtain device energy consumption parameters; The predicted voltage stabilization time is obtained by analyzing the energy consumption parameters and energy storage characteristic information of the equipment.

5. The method according to claim 1, wherein The method comprises: calculating a comprehensive voltage stabilization coefficient by combining the first voltage stabilization coefficient, the second voltage stabilization coefficient, and the third voltage stabilization coefficient; determining whether to turn off the switch unit according to the comprehensive voltage stabilization coefficient; and providing a stable voltage supply to the target device through the energy storage unit and the inverter unit, including: performing weighted calculation on the first voltage stabilization coefficient, the second voltage stabilization coefficient, and the third voltage stabilization coefficient to obtain the comprehensive voltage stabilization coefficient; It is determined whether the comprehensive voltage regulation coefficient is greater than a voltage regulation coefficient threshold. If so, the switch unit is turned off, and the target device is supplied with voltage regulation power through the energy storage unit and the inverter unit.

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