New energy grid-connected power quality monitoring method and device, terminal and medium

Abstract

The invention discloses a new energy grid-connected electric energy quality monitoring method and device, a terminal and a medium, and the method comprises the steps: deploying a dual-mode sensor in a grid-connected node, and collecting the electric energy quality data; adjusting the frequency of data collection according to the operation mode of the current power grid; analyzing the power quality data, and identifying power quality abnormity; adjusting a grid-connected mode according to an electric energy quality data analysis result, and managing load response; according to the invention, real-time accurate acquisition of the electric energy quality data is realized by designing the bimodal sensor, electric energy quality abnormity can be identified more accurately in combination with a deep learning algorithm, a grid-connected mode and load response are optimized according to an analysis result, and the adaptability of a power grid to new energy fluctuation is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of power quality monitoring, and in particular to a method, device, terminal and medium for monitoring power quality of a new energy grid-connected power. Background Art

[0002] With the acceleration of global energy transformation, the proportion of new energy, especially renewable energy such as wind and solar energy, in the power system has increased rapidly. However, due to the intermittent and volatile nature of new energy generation, its grid connection process poses severe challenges to the stability and power quality of the power system. Traditional power quality monitoring systems mainly rely on fixed-mode sensor configurations and cannot effectively adapt to the dynamically changing characteristics of new energy generation in the power grid.

[0003] Although some progress has been made in power quality monitoring and control, there are still some significant shortcomings. First, traditional power quality monitoring equipment usually uses single-mode sensors, which cannot flexibly adjust monitoring parameters according to the dynamic changes of the power grid and the characteristics of renewable energy generation. The limitations of this single-mode sensor result in the accuracy and timeliness of monitoring data being limited when dealing with different power generation conditions and power grid operation modes, making it difficult to meet the real-time and precision requirements of modern power grids; secondly, when faced with high-frequency power quality abnormal events, traditional monitoring systems are prone to missed reports or false reports, and cannot provide accurate grid-connected adjustment suggestions, which in turn affects the overall efficiency of renewable energy grid connection and the stability of the power grid. Summary of the invention

[0004] The purpose of the present invention is to provide a method for monitoring the quality of power connected to the grid by a new energy source, so as to solve the existing problems.

[0005] To solve the above technical problems, the present invention provides the following technical solutions, including: a method for monitoring the power quality of new energy grid-connected, characterized in that it includes: deploying dual-mode sensors in grid-connected nodes to collect power quality data; adjusting the frequency of data collection according to the current operating mode of the power grid; analyzing the power quality data to identify power quality anomalies; adjusting the grid-connected mode according to the analysis results of the power quality data, and managing load response.

[0006] As a preferred solution of the new energy grid-connected power quality monitoring method described in the present invention, power quality data is collected once per second during grid-connected operation, and the power quality data includes the voltage, current, power factor and harmonics of the power grid, and the stress, temperature and vibration data of the power grid equipment; when abnormal fluctuations are detected, the collection frequency is adjusted to 10 times per second, and the power quality data is transmitted to the central processor via an encrypted wireless network.

[0007] As a preferred solution of the new energy grid-connected power quality monitoring method described in the present invention, identifying power quality anomalies includes: extracting features from power quality data, and converting the extracted features into a state vector, the state vector includes voltage level, current intensity, power factor, harmonic components, and stress, temperature and vibration values ​​of the equipment; inputting the state vector into a DQN model to identify power quality anomalies; the DQN model includes an input layer, a hidden layer and an output layer, the hidden layer includes two fully connected layers, each layer has 64 neurons, and a ReLU activation function is used.

[0008] As a preferred solution of the new energy grid-connected power quality monitoring method described in the present invention, the dual-mode sensor includes a first sensor, a second sensor, a power supply, a bracket and a shape memory alloy shell, the first sensor includes an optical fiber sensing element, a detector and a light source, the second sensor includes a voltage sensor, a current sensor and a signal processor, and the first sensor and the second sensor are fixed by the bracket.

[0009] As a preferred solution of the new energy grid-connected power quality monitoring method described in the present invention, wherein: adjusting the grid-connected mode includes: evaluating the availability of the generator set based on the power quality data analysis results; setting decision thresholds and adjustment modes respectively, the decision thresholds include the basic generator set full load threshold T1, the standby generator set activation threshold T2 and the extreme load threshold T3, and the adjustment modes include the basic mode M1, the enhanced mode M2, the standby mode M3 and the emergency mode M4; selecting the adjustment mode based on the decision threshold, the real-time load of the power grid and the total power generation capacity, and reconfiguring the power grid topology and transferring the overload load to the standby line.

[0010] As a preferred solution of the method for monitoring the power quality of new energy grid-connected power described in the present invention, managing load response includes: charging the battery during low-load periods and releasing the stored power during high-load periods.

[0011] As a preferred solution of the new energy grid-connected power quality monitoring method described in the present invention, it includes: the user interface displays power quality data in real time through a holographic display screen. When the power quality is abnormal, the user interface issues visual and auditory alarms, and pops up an analysis report. The analysis report contains the cause of the abnormality, historical trends, and provides operational suggestions.

[0012] The present invention also provides a new energy grid-connected power quality monitoring device, including: a method for implementing the new energy grid-connected power quality monitoring method as described in any of the above items, the new energy grid-connected power quality monitoring device including: an acquisition module, used to deploy dual-modal sensors in grid-connected nodes to collect power quality data; a data acquisition optimization module, used to adjust the frequency of data collection according to the current operation mode of the power grid; an analysis module, used to analyze the power quality data and identify power quality anomalies; a decision module, used to adjust the grid connection mode according to the analysis results of the power quality data, and manage the load response; a monitoring module, used to display the power quality data in real time through a holographic display screen. When the power quality is abnormal, the user interface sends out visual and auditory alarms, and pops up an analysis report, the analysis report contains the cause of the abnormality, historical trends, and provides operation suggestions.

[0013] The present invention also provides a terminal device, comprising: one or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the new energy grid-connected power quality monitoring method as described in any of the above items.

[0014] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the method for monitoring the power quality of new energy grid-connected power as described in any one of the above items.

[0015] Beneficial effects of the present invention: The present invention realizes real-time and accurate collection of power quality data by designing a dual-modal sensor. At the same time, combined with a deep learning algorithm, it can more accurately identify power quality anomalies, and optimize the grid connection mode and load response according to the analysis results, thereby enhancing the adaptability of the power grid to fluctuations in renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them: Figure 1 A schematic flow chart of a method for monitoring power quality of new energy grid-connected power according to a first embodiment of the present invention; Figure 2 A schematic diagram of the process of power quality data analysis according to the first embodiment of the present invention; Figure 3It is a schematic diagram of the process of adjusting the grid connection mode according to the first embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0020] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0021] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0022] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0023] Example 1 Reference Figure 1 to Figure 3 , which is the first embodiment of the present invention, and provides a method for monitoring the quality of power connected to a new energy grid, comprising: S1: Deploy dual-modal sensors in grid-connected nodes to collect power quality data.

[0024] The grid-connected node may be a photovoltaic inverter, a wind turbine, an energy storage system, a large-scale grid access point, etc., which is not limited in this embodiment.

[0025] The dual-mode sensor includes a first sensor, a second sensor, a power supply, a bracket and a shape memory alloy shell. The first sensor includes an optical fiber sensing element, a detector and a light source. The second sensor includes a voltage sensor, a current sensor and a signal processor. The first sensor and the second sensor are fixed by the bracket.

[0026] Specifically, the optical fiber sensing element utilizes the characteristics of light waves transmitted in the optical fiber to continuously sense and measure along the length of the optical fiber, wherein the cladding portion of the optical fiber is etched by a hydrofluoric acid solution, and the optical fiber sensing element is embedded with a microfluidic channel, which introduces a colloidal solution containing magnetic nanoparticles. When an external magnetic field is applied, the distribution pattern of the magnetic nanoparticles will change with the strength and direction of the external magnetic field, and the magnetic particles tend to aggregate into chains along the direction of the magnetic field, and the refractive index of the colloid will change accordingly.

[0027] The light source emits light of a specific wavelength, which is transmitted through the optical fiber, and the reflected spectrum is received by the detector, and the changes in the spectrum are analyzed to measure the physical quantity. Preferably, the first sensor designed in the present application can perform highly sensitive detection of stress, temperature and vibration in the power quality, thereby improving the overall measurement accuracy and response speed.

[0028] The second sensor uses a signal processor to analyze and calculate the voltage and current data collected by the voltage sensor and the current sensor, thereby obtaining harmonics and power factor.

[0029] Furthermore, the first sensor and the second sensor are fixed by a bracket, which includes a base, a column and an adjustable fixing plate. The base is used to provide stability, and the adjustable fixing plate is installed on the column to ensure that it can fix different types of sensors.

[0030] Preferably, the sensor housing is made of shape memory alloy, so that the sensor can automatically adjust its sensitivity when it senses abnormal vibration or temperature, which can effectively reduce false alarms and optimize measurement accuracy when the sensor environment changes. The power supply uses electromagnetic interference or tiny vibrations in the power grid environment to obtain electrical energy to power the first sensor and the second sensor, reducing dependence on external power supplies, making the sensor more stable and reliable in long-term operation.

[0031] S2: Adjust the frequency of data collection according to the current operation mode of the power grid.

[0032] During the grid-connected operation, power quality data is collected once a second. The power quality data includes the voltage, current, power factor and harmonics of the grid, and the stress, temperature and vibration data of the grid equipment; When abnormal fluctuations are detected, the acquisition frequency is adjusted to 10 times per second, and the power quality data is transmitted to the central processor via an encrypted wireless network to ensure a rapid response to power quality issues.

[0033] The data transmission process uses high-speed optical fiber or wireless network to ensure that the collected power quality data can be quickly transmitted to the central processor for analysis.

[0034] S3: Analyze the power quality data and identify power quality anomalies.

[0035] Reference Figure 1 ,After receiving the power quality data, the central processor extracts the features of the power quality data and converts the extracted features into a state vector, which includes voltage level, current intensity, power factor, harmonic components, and stress, temperature and vibration values ​​of the equipment; The state vector is input into the DQN (Deep Q-Network) model to identify power quality anomalies; the DQN model includes an input layer, a hidden layer, and an output layer; the hidden layer includes two fully connected layers for extracting and transforming state vector features. Each layer has 64 neurons, and the ReLU activation function is used to increase the nonlinear expression ability of the network; the output layer is used to output the Q value of each action, that is, the expected reward of each action under a given state.

[0036] Furthermore, the DQN model is trained. The specific steps are as follows: (1) Randomly initialize the weights of the DQN model and the target DQN model; (2) During training, a random action is selected with a certain probability ε (exploration), otherwise the action with the highest Q value is selected (exploitation); (3) Use the Bellman equation to update the Q value and calculate the target Q value as: In the formula, r is the reward, γ is the discount factor, It represents the maximum expected reward that can be obtained by selecting the best action a′ in the new state s′.

[0037] (4) Through the loss function And back-propagation updates the weights of the DQN model: In the formula, It represents the Q value of taking action a in the current state s.

[0038] S4: Adjust the grid connection mode and manage load response based on the power quality data analysis results.

[0039] Reference Figure 3 , dynamically select the grid connection mode according to load demand and power generation capacity, specifically: (1) Evaluate the availability of generator sets based on the power quality data analysis results, that is, give priority to dispatching equipment with normal power quality data analysis results; (2) setting decision thresholds and adjustment modes respectively. The decision thresholds include the full load threshold T1 of the basic generator set (set as the maximum load capacity of the basic generator set), the activation threshold T2 of the standby generator set (set as 110% of the full load of the basic generator set) and the extreme load threshold T3 (absolute load capacity boundary). The adjustment modes include the basic mode M1, enhanced mode M2, standby mode M3 and emergency mode M4; (3) Select the adjustment mode according to the decision threshold, real-time grid load and total power generation capacity, and reconfigure the grid topology and transfer the overload load to the backup line.

[0040] Basic Mode M1: Condition: Real-time load ≤ T1.

[0041] Action: The basic generator set operates normally and there is no need to enable the standby generator set.

[0042] Monitoring: Monitor load changes to ensure that the load is within the carrying capacity of the basic generator set.

[0043] Enhanced Mode M2: Condition: T1<real-time load≤T2.

[0044] Action: Start one or more of the standby generator sets to meet the increased load demand.

[0045] Action details: The priority of starting the standby generator sets should be based on their starting time and power generation efficiency.

[0046] Alternate Mode M3: Condition: T2<real-time load≤total power generation capacity.

[0047] Action: Enable all available standby generator sets.

[0048] Action details: While ensuring load demand, optimize the activation sequence of generator sets to reduce fuel consumption and operating costs.

[0049] Emergency Mode M4: Condition: real-time load > total power generation capacity.

[0050] Action: Start emergency standby generators and consider external measures (load demand response, load shedding, etc.).

[0051] Action details: Communicate with dispatchers to implement load scheduling and demand response strategies to ensure the stability of power supply.

[0052] Further, the grid topology is reconfigured and the overload load is transferred to the backup lines.

[0053] In this embodiment, a certain power grid system is used as an example to configure the power grid topology. The power grid system includes multiple power stations, substations and distribution lines. The topology of the power grid is determined by multiple switch devices (such as circuit breakers and transfer switches).

[0054] Specifically, the configuration of the power grid system is: Distribution lines: Line A: main power supply line, connecting power station 1 to substation 1; Line B: backup line, connecting power station 2 to substation 2; Line C: connecting substation 1 and substation 2. When the load on line A is reduced, the backup lines B and C will take over part of the load to maintain the normal operation of the power grid.

[0055] Power stations: Power station 1, Power station 2.

[0056] Substation: Substation 1, Substation 2.

[0057] It was detected that the power supply line (line A) was overloaded under high load conditions, while the load conditions of lines B and C were still within a safe range.

[0058] Treatment measures: disconnect substation 1 from line A, connect substation 1 to standby line B, adjust the load distribution of line C, and reduce the load of line A. That is, the power grid system sends the following execution instructions, and the control switch equipment executes according to the instructions: Close switch command: disconnect substation 1 from line A; Open switch command: transfer the load to substation 1 through line B; Adjust the switch command: adjust the load distribution of line C and reduce the load of line A.

[0059] The reconfigured grid topology becomes: Power station 1 is connected to substation 1 via line C; substation 1 is connected to power station 2 via line B; substation 2 is connected to substation 1 via line C. The load on line A is reduced, and the backup lines B and C take over part of the load to maintain the normal operation of the grid.

[0060] Furthermore, load response management is performed, including charging the battery during low load periods and releasing the stored power during high load periods.

[0061] S5: The user interface displays power quality data in real time through a holographic display. When the power quality is abnormal, the user interface issues visual and auditory alarms, and an analysis report pops up, including the cause of the abnormality, historical trends, and operational suggestions.

[0062] Based on the problem type and analysis results, the user interface provides a variety of operational suggestions, such as adjusting the grid connection mode, managing load response, and performing equipment maintenance, etc., and each recommended operation is accompanied by a concise step-by-step guide.

[0063] Example 2 This embodiment takes a certain power grid as an example, analyzes the power quality data, inputs the power quality data into the central processing unit of Embodiment 1, and identifies power quality anomalies through the DQN model: Multiple dual-mode sensors are installed in a grid-connected node, and the historical power quality data collected is as follows: Voltage (V): 230V, 232V, 228V, 234V, 220V Current (A): 10.1A, 10.2A, 9.9A, 10.3A, 10.5A Power factor: 0.98, 0.97, 0.96, 0.95, 0.94 Harmonic content (%): 2.8%, 3.0%, 3.2%, 3.1%, 3.3% Equipment stress: 80, 85, 90, 88, 92 Temperature (°C): 65, 66, 67, 68, 70 Vibration (mm / s): 0.1, 0.12, 0.13, 0.11, 0.14 Furthermore, the power quality data is preprocessed to remove outliers and noise; the power quality data is standardized so as to be input into the DQN model.

[0064] Further, define the state space and action space; (1) Define the state space; one of the state vectors is as follows: states = [0.95, 0.98, 0.96, 3.1, 0.90, 0.65, 0.12] Each value represents the normalized voltage, current, power factor, harmonic content, equipment stress, temperature, and vibration.

[0065] (2) Define the action space: Action 1: Issue a warning and perform equipment inspection; Action 2: Adjust the grid load to stabilize the voltage; Action 3: Enable the backup device; Action 4: Perform a system check. Furthermore, real-time data is collected: Voltage: 220V Current: 10.5A Power factor: 0.94 Harmonic content: 3.3% Equipment stress: 92 Temperature: 72°C Vibration: 0.15 mm / s Convert real-time grid data into a state vector: state = [0.90, 1.02, 0.94, 3.3, 0.92, 0.72, 0.15] The state vector is input into the DQN model. The DQN model identifies abnormal features such as voltage drop, current increase, power factor reduction, harmonic content increase, equipment stress and temperature increase by comparing the current state with the normal mode in the historical data. The Q value of each action output by the DQN model is [3.2, 2.5, 1.8, 2.0]. The action with the highest Q value, i.e. action 1, is selected, indicating that the power quality of the power grid is abnormal, and a warning is issued to notify the staff to conduct an inspection.

[0066] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention but are not intended to limit the present invention.

[0067] Example 3 The present invention provides a new energy grid-connected power quality monitoring device, which is used to implement the steps of the new energy grid-connected power quality monitoring method as described in any of the above embodiments. The new energy grid-connected power quality monitoring device includes: The acquisition module is used to deploy dual-mode sensors in grid-connected nodes to collect power quality data; Data collection optimization module, used to adjust the frequency of data collection according to the current operation mode of the power grid; An analysis module is used to analyze power quality data and identify power quality anomalies; The decision-making module is used to adjust the grid connection mode according to the power quality data analysis results and manage the load response.

[0068] The monitoring module is used to display power quality data in real time through a holographic display screen. When the power quality is abnormal, the user interface will issue visual and auditory alarms, and an analysis report will pop up. The analysis report contains the cause of the abnormality, historical trends, and provides operational suggestions.

[0069] Example 4 This embodiment provides a terminal device, including: one or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for monitoring power quality of new energy grid-connected power.

[0070] The processor is used to control the overall operation of the terminal device to complete all or part of the steps of the above-mentioned new energy grid-connected power quality monitoring method. The memory is used to store various types of data to support the operation of the terminal device, and these data may include, for example, instructions for any application or method used to operate on the terminal device, as well as application-related data. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk.

[0071] The terminal device can be implemented by one or more application-specific integrated circuits (Application Specific1n Integrated Circuit, ASC), digital signal processors (Digital Signal Processor, DSP), digital signal processing devices (Digital Signal Processing Device, DSPD), programmable logic devices (Programmable Logic Device, PLD), field programmable gate arrays (Field Programmable Gate Array, FPGA), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the new energy grid-connected power quality monitoring method as described in any of the above embodiments, and achieve the same technical effect as the above method.

[0072] Example 5 This embodiment provides a computer-readable storage medium, and when the program instructions are executed by a processor, the steps of the method for monitoring the power quality of the new energy grid-connected power grid as described in any of the above embodiments are implemented. For example, the computer-readable storage medium can be the above-mentioned memory including the program instructions, and the above-mentioned program instructions can be executed by the processor of the terminal device to complete the method for monitoring the power quality of the new energy grid-connected power grid as described in any of the above embodiments, and achieve the same technical effect as the above method.

[0073] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in an assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed ASIC for this purpose.

[0074] Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. The computer program includes a plurality of instructions that may be executed by one or more processors.

[0075] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor, the invention described herein includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques described in the present invention, the present invention also includes the computer itself. The computer program can be applied to input data to perform the functions described herein, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on a display.

[0076] As used in this application, the terms "component", "module", "system", etc. are intended to refer to a computer-related entity, which can be hardware, firmware, a combination of hardware and software, software, or software in operation. For example, a component can be, but is not limited to: a process running on a processor, a processor, an object, an executable file, a thread in execution, a program, and / or a computer. As an example, an application running on a computing device and the computing device can both be components. One or more components can exist in a process and / or thread in execution, and a component can be located in a computer and / or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures thereon. These components can communicate in a local and / or remote process manner, such as according to a signal having one or more data packets (e.g., data from a component that interacts with another component in a local system, a distributed system, and / or interacts with other systems in a signal manner through a network such as the Internet).

[0077] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the quality of power connected to the grid of renewable energy, characterized in that: include: Deploy dual-modal sensors in grid-connected nodes to collect power quality data; Adjust the frequency of data collection according to the current operation mode of the power grid; Analyze power quality data and identify power quality anomalies; Adjust the grid connection mode and manage load response based on the power quality data analysis results.

2. The method for monitoring the quality of power connected to the grid of new energy as claimed in claim 1, characterized in that: include: During the grid-connected operation, power quality data is collected once a second. The power quality data includes the voltage, current, power factor and harmonics of the grid, and the stress, temperature and vibration data of the grid equipment; When abnormal fluctuations are detected, the acquisition frequency is adjusted to 10 times per second, and the power quality data is transmitted to the central processor via an encrypted wireless network.

3. The method for monitoring the quality of power connected to the grid of new energy as claimed in claim 2, characterized in that: Identifying power quality anomalies includes: Extract features from power quality data and convert the extracted features into a state vector, which includes voltage level, current intensity, power factor, harmonic components, and stress, temperature, and vibration values ​​of equipment; The state vector is input into the DQN model to identify abnormal power quality; the DQN model includes an input layer, a hidden layer and an output layer, the hidden layer includes two fully connected layers, each layer has 64 neurons, and uses a ReLU activation function.

4. The method for monitoring the quality of power connected to the grid of new energy as claimed in claim 3, characterized in that: The dual-modal sensor includes a first sensor, a second sensor, a power supply, a bracket and a shape memory alloy shell. The first sensor includes an optical fiber sensing element, a detector and a light source. The second sensor includes a voltage sensor, a current sensor and a signal processor. The first sensor and the second sensor are fixed by the bracket.

5. The method for monitoring the quality of power connected to the grid of new energy as claimed in claim 4, characterized in that: Adjusting the grid connection mode includes: Evaluate the availability of generator sets based on power quality data analysis results; The decision thresholds and adjustment modes are set respectively, wherein the decision thresholds include a full load threshold T1 of a basic generator set, an enabling threshold T2 of a standby generator set, and an extreme load threshold T3, and the adjustment modes include a basic mode M1, an enhanced mode M2, a standby mode M3, and an emergency mode M4; The adjustment mode is selected according to the decision threshold, the real-time load of the power grid and the total power generation capacity, and the power grid topology is reconfigured and the overload load is transferred to the backup line.

6. The method for monitoring the quality of power connected to the grid of new energy as claimed in claim 5, characterized in that: Managing load response includes: The battery is charged during low-load periods and the stored energy is released during high-load periods.

7. The method for monitoring the quality of power connected to the grid of new energy as claimed in claim 6, characterized in that: include: The user interface displays power quality data in real time through a holographic display screen. When the power quality is abnormal, the user interface issues visual and auditory alarms, and an analysis report pops up, which contains the cause of the abnormality, historical trends, and provides operational suggestions.

8. A new energy grid-connected power quality monitoring device, used to implement the new energy grid-connected power quality monitoring method as claimed in any one of claims 1 to 7, characterized in that: The new energy grid-connected power quality monitoring device comprises: The acquisition module is used to deploy dual-mode sensors in grid-connected nodes to collect power quality data; Data collection optimization module, used to adjust the frequency of data collection according to the current operation mode of the power grid; An analysis module is used to analyze power quality data and identify power quality anomalies; A decision-making module, which is used to adjust the grid connection mode and manage load response according to the power quality data analysis results; The monitoring module is used to display the power quality data in real time through the holographic display screen. When the power quality is abnormal, the user interface will issue visual and auditory alarms, and an analysis report will pop up. The analysis report contains the cause of the abnormality, historical trends, and provides operational suggestions.

9. A terminal device, characterized in that: include: one or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the new energy grid-connected power quality monitoring method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the method for monitoring the quality of power connected to the grid of new energy as described in any one of claims 1 to 7.

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