Energy status monitoring and feedback system for intelligent grid connection

Abstract

The present invention relates to the technical field of power grid monitoring, and discloses an energy state monitoring and feedback system for intelligent grid connection. A data acquisition module is used to monitor the energy state data of the intelligent grid connection in real time during operation, so as to ensure comprehensive monitoring of the health state of the power grid, ensure the accuracy and reliability of the data, and provide high-quality original data for subsequent processing and analysis; a data transmission module transmits the monitored energy state data to a cloud, so as to improve the efficiency of data transmission; a data processing module processes the received energy state data to obtain a comprehensive index; a state monitoring module determines whether the operation state of the intelligent grid connection is abnormal according to the processed energy state data and the comprehensive index; a feedback control module is used to feedback to the intelligent grid connection when the operation state of the intelligent grid connection is judged to be abnormal, and change the operation strategy of the intelligent grid connection, so as to optimize the operation efficiency of the intelligent grid connection, reduce energy waste, and improve the reliability and economy of power supply.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid monitoring, and in particular to an energy state monitoring and feedback system for intelligent grid connection. Background Art

[0002] With the development of smart grid and distributed energy technology, the energy interaction between microgrid and main grid has become more complex. In order to ensure the stable operation of microgrid, real-time monitoring and feedback of energy status have become crucial tasks. Existing energy monitoring systems usually rely on centralized monitoring mode, which is difficult to respond quickly to dynamically changing load demand and grid conditions. At the same time, data transmission delay and processing capacity limitations may also cause energy status feedback lag, thus affecting the efficiency and safety of the overall system. Most of them have not solved how to monitor the energy status data during the operation of smart grid connection, transmit it to the cloud for processing to obtain a comprehensive index, and judge whether the operation status of smart grid connection is abnormal based on the processed energy status data and comprehensive index, so as to feedback to the smart grid connection and change the operation strategy of smart grid connection.

[0003] For example, the Chinese patent application with publication number CN117791605A discloses an energy management and control system for a low-voltage area flexible direct current interconnection system, including a smart grid energy coordination module, which includes a coordination unit, a power distribution monitoring unit and an energy control unit; the low-voltage area includes multiple areas, and energy flows between the low-voltage areas through an interconnection device; the power distribution monitoring unit is used to monitor the load operation status of each low-voltage area and feed back the monitoring results to the coordination unit, and the coordination unit generates a control instruction based on the monitoring results and sends it to the energy control unit; the energy control unit controls the interconnection device according to the control instruction to realize the energy flow between the low-voltage areas. It can quickly monitor and locate the load energy of the area, thereby improving the positioning efficiency of energy management.

[0004] For example, the Chinese patent with the authorization announcement number CN106602607B discloses a comprehensive management system for the point where a microgrid is connected to a distribution network. The system is located at the connection point between the distribution network and the microgrid. At the physical level, it includes solid-state switches, transmission lines, transformers, and distribution network busbars. The transformer is connected to the distribution network busbar, and the transmission line is directly connected to the microgrid busbar. At the information transmission level, the PCC local state measurement information, PCC logic judgment information, and coordination control information are connected to the distribution network energy management system and the microgrid energy management system through optical cables. The system is divided into a physical system layer, a perception layer, a data-information conversion layer, a communication network layer, a policy control layer, and a scheduling application layer through a hierarchical design. It aims to solve the comprehensive problems of power quality, synchronous grid connection, island detection, and grid connection protection at the common coupling point. It can monitor power quality information in real time and adjust power quality, and combine the protection of the common coupling point to ensure that the microgrid is in a safe and stable grid-connected operation mode.

[0005] The above patents have the problems raised by this background technology: the above energy management system monitors the load operation status of each low-voltage area through the distribution monitoring unit and feeds back the monitoring results to the coordination unit. The coordination unit generates control instructions according to the monitoring results and sends them to the energy control unit. The energy control unit controls the interconnection device according to the control instructions to realize the energy flow between the low-voltage areas; the above microgrid is connected to the distribution network point. The comprehensive management system solves the comprehensive problems of power quality, synchronous grid connection, island detection and grid connection protection at the common coupling point through the physical system layer, perception layer, data-information conversion layer, communication network layer, strategy control layer and scheduling application layer. The above two patents do not solve the problem of how to monitor the energy status data during the operation of the intelligent grid connection, transmit it to the cloud for processing to obtain a comprehensive index, and judge whether the operation status of the intelligent grid connection is abnormal based on the processed energy status data and the comprehensive index, so as to feed back to the intelligent grid connection and change the operation strategy of the intelligent grid connection. To solve this problem, the present invention proposes an energy status monitoring and feedback system for intelligent grid connection. Summary of the invention

[0006] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0007] In view of the above-mentioned problems existing in the existing energy status monitoring and feedback system for intelligent grid connection, the present invention is proposed.

[0008] Therefore, an object of the present invention is to provide an energy status monitoring and feedback system for intelligent grid connection.

[0009] In order to solve the above technical problems, the present invention provides an energy state monitoring and feedback system for intelligent grid connection: a data acquisition module, a data transmission module, a data processing module, a state monitoring module and a feedback control module;

[0010] The data acquisition module is used to monitor the energy status data during intelligent grid-connected operation in real time;

[0011] The data transmission module is used to transmit the monitored energy status data to the cloud;

[0012] The data processing module is used to process the received energy status data to obtain a comprehensive index;

[0013] The state monitoring module is used to determine whether the operation state of the intelligent grid connection is abnormal based on the processed energy state data and the comprehensive index;

[0014] The feedback control module is used to feed back to the smart grid when the operation state of the smart grid is judged to be abnormal, and change the operation strategy of the smart grid.

[0015] As a preferred solution of the energy state monitoring and feedback system for intelligent grid connection of the present invention, the specific steps of processing the received energy state data include:

[0016] Configure the rated frequency, rated power factor, and fundamental voltage, calculate the difference between the frequency and the rated frequency to obtain the frequency difference, calculate the difference between the power factor and the rated power factor to obtain the degree of power factor reduction, extract the characteristics of the harmonics, including the harmonic voltage, calculate the percentage of the total distortion of the harmonic voltage to the fundamental voltage to obtain the total harmonic distortion rate, and comprehensively consider the frequency difference, the degree of power factor reduction, and the total harmonic distortion rate to obtain a comprehensive index.

[0017] As a preferred solution of the energy state monitoring and feedback system for intelligent grid connection of the present invention, the function expression of the comprehensive index is as follows:

[0018] ;

[0019] In the formula, represents the comprehensive index, represents the weight coefficient of the frequency difference, represents the frequency difference, Indicates the rated frequency, The weight coefficient indicating the degree of power factor reduction, Indicates the degree of power factor reduction. Indicates the rated power factor, Represents the weight coefficient of the total harmonic distortion rate, Indicates the total harmonic distortion.

[0020] As a preferred solution of the energy state monitoring and feedback system for smart grid connection of the present invention, the method of judging whether the operation state of the smart grid connection is abnormal according to the processed energy state data and the comprehensive index includes:

[0021] An index threshold is configured, and the comprehensive index is compared with the index threshold to obtain the operation state of the smart grid connection. If the comprehensive index is greater than the index threshold, it indicates that the operation state of the smart grid connection is abnormal and the comprehensive index is abnormal.

[0022] If the comprehensive index is less than or equal to the index threshold, it means that the operation status of the smart grid connection is normal.

[0023] As a preferred solution of the energy state monitoring and feedback system for intelligent grid connection described in the present invention, wherein: a state data threshold is configured, the state data threshold includes a frequency difference threshold, a drop degree threshold and a total distortion rate threshold, the state data threshold is compared with the processed energy state data to obtain the operation state of the intelligent grid connection, if the frequency difference is greater than the frequency difference threshold, it means that the operation state of the intelligent grid connection is abnormal and the frequency difference is abnormal;

[0024] If the frequency difference is less than or equal to the frequency difference threshold, it means that the operation status of the smart grid connection is normal;

[0025] If the power factor decrease degree is greater than the decrease degree threshold, it means that the operation state of the smart grid connection is abnormal and the power factor decreases abnormally;

[0026] If the power factor decrease degree is less than or equal to the decrease degree threshold, it means that the operation status of the smart grid connection is normal;

[0027] If the total harmonic distortion rate is greater than the total distortion rate threshold, it means that the operation state of the smart grid connection is abnormal and the total harmonic distortion rate is abnormal;

[0028] If the total harmonic distortion rate is less than or equal to the total distortion rate threshold, it means that the operation status of the smart grid connection is normal.

[0029] As a preferred solution of the energy state monitoring and feedback system for smart grid connection of the present invention, the logic of feeding back to the smart grid connection and changing the operation strategy of the smart grid connection includes:

[0030] Identify the abnormal type of the operation status of the intelligent grid connection as abnormal, and if the abnormal type is the abnormal comprehensive index, adjust the generator output power and reduce the load;

[0031] If the abnormality type is frequency difference abnormality, adjust the generator frequency;

[0032] If the abnormality type is a power factor drop abnormality, then increase the power factor;

[0033] If the abnormality type is the total harmonic distortion rate abnormality, reduce the total harmonic distortion rate.

[0034] As a preferred solution of the energy state monitoring and feedback system for intelligent grid connection described in the present invention, wherein: the energy state data of the intelligent grid connection operation is monitored in real time through a sensor network, and the energy state data includes the frequency, power factor and harmonics of the power grid;

[0035] The deployment strategy of the sensor network includes:

[0036] Each sensor is used as a network node. A monitoring range threshold is configured. The distance between network nodes is determined based on the monitoring range threshold. A calibration period threshold is configured. The calibration time of the network node is determined based on the calibration period threshold. The self-diagnosis result of the network node is determined. If the self-diagnosis result of the network node is normal, it means that the sensor network deployment is normal.

[0037] If the self-diagnosis result of the network node is that the network node is abnormal, the self-calibration of the network node is started to monitor whether the network node is abnormal. If the network node is normal, it means that the self-calibration of the network node is successful and the sensor network deployment is restored to normal;

[0038] If the network node is still abnormal, it means that the network node self-calibration has failed and the network node should be replaced.

[0039] As a preferred solution of the energy state monitoring and feedback system for intelligent grid connection of the present invention, the logic of judging the self-diagnosis result of the network node includes:

[0040] Monitor the output results of the network node and compare them with the real results to obtain the error results, configure the error threshold, and if the error result is greater than or equal to the error threshold, the self-diagnosis result of the network node is that the network node is abnormal;

[0041] If the error result is less than the error threshold, the self-diagnosis result of the network node is that the network node is normal.

[0042] As a preferred solution of the energy state monitoring and feedback system for intelligent grid connection described in the present invention, wherein: the monitored energy state data is transmitted to the cloud, the transmission rate of the energy state data is determined according to the self-diagnosis result and self-calibration result of the network node, the rate base value, the rate high value and the rate extreme value are configured, and if the self-diagnosis result of the network node is that the network node is normal, the transmission rate of the energy state data is determined to be the rate base value;

[0043] If the self-diagnosis result of the network node is that the network node is abnormal and the self-calibration of the network node is successful, then the transmission rate of the energy status data is determined to be a high rate value;

[0044] If the self-diagnosis result of the network node is that the network node is abnormal and the network node self-calibration fails, it is determined that the transmission rate of the energy state data is a rate extreme value.

[0045] The beneficial effects of the present invention are as follows: the present invention monitors the energy status data of the intelligent grid-connected system in real time through the data acquisition module, ensures comprehensive monitoring of the health status of the power grid, ensures the accuracy and reliability of the data, and provides high-quality original data for subsequent processing and analysis; the data transmission module transmits the monitored energy status data to the cloud, ensures the security and integrity of the data during the transmission process, and improves the efficiency of data transmission; the data processing module processes the received energy status data to obtain a comprehensive index to reveal the potential laws of the intelligent grid-connected system and improve the accuracy and efficiency of the analysis; the status monitoring module determines whether the operating status of the intelligent grid-connected system is abnormal based on the processed energy status data and the comprehensive index, monitors the energy status of the intelligent grid-connected system in real time, and detects any abnormal situation quickly and accurately; when the operating status of the intelligent grid-connected system is judged to be abnormal, the feedback control module feeds back to the intelligent grid-connected system, changes the operating strategy of the intelligent grid-connected system, optimizes the operating efficiency of the intelligent grid-connected system, reduces energy waste, and improves the reliability and economy of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] 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:

[0047] Figure 1 A system structure diagram of the energy state monitoring and feedback system for intelligent grid connection according to the present invention;

[0048] Figure 2 A flow chart of the deployment strategy of the sensor network of the energy state monitoring and feedback system for smart grid connection of the present invention;

[0049] Figure 3 It is a data transmission flow chart of the energy status monitoring and feedback system for intelligent grid connection of the present invention;

[0050] Figure 4 The present invention is a method flow chart of the energy status monitoring and feedback method for intelligent grid connection. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned objects, 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 accompanying drawings.

[0052] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0053] 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.

[0054] Example 1

[0055] In this embodiment, a system structure diagram of an energy status monitoring and feedback system for intelligent grid connection is provided, such as Figure 1 As shown, the energy state monitoring and feedback system for intelligent grid connection includes a data acquisition module, a data transmission module, a data processing module, a state monitoring module and a feedback control module.

[0056] The data acquisition module is used to monitor the energy status data during intelligent grid-connected operation in real time.

[0057] The energy status data during intelligent grid-connected operation is monitored in real time through a sensor network. The energy status data includes the frequency, power factor and harmonics of the power grid.

[0058] The sensor network includes frequency sensors, power factor sensors and harmonic sensors. The frequency sensor is installed near the distribution cabinet to monitor the stability of the power grid frequency. The power factor sensor needs to be connected in parallel with the power load to monitor the power factor in real time to ensure the quality of power. The harmonic sensor is installed in the main distribution cabinet and key load locations to monitor harmonic pollution, ensure that the equipment operates within a safe range, and ensure that the harmonics of the power grid meet national or international standards. Environmental sensors also need to be installed, mainly deployed near the distribution cabinet to monitor the temperature, humidity and air quality near the distribution cabinet to prevent equipment in the distribution cabinet from malfunctioning due to environmental factors.

[0059] The deployment strategy of sensor networks is as follows: Figure 2 As shown, specifically including:

[0060] Each sensor is used as a network node. A monitoring range threshold is configured. The distance between network nodes is determined based on the monitoring range threshold. A calibration period threshold is configured. The calibration time of the network node is determined based on the calibration period threshold. The self-diagnosis result of the network node is determined. If the self-diagnosis result of the network node is normal, it means that the sensor network deployment is normal.

[0061] If the self-diagnosis result of the network node is that the network node is abnormal, the self-calibration of the network node is started to monitor whether the network node is abnormal. If the network node is normal, it means that the self-calibration of the network node is successful and the sensor network deployment is restored to normal;

[0062] If the network node is still abnormal, it means that the network node self-calibration has failed and the network node should be replaced.

[0063] Each sensor is identified as a network node. The monitoring range threshold configured above refers to the maximum monitoring range that each sensor can monitor. Therefore, it is necessary to ensure that the distance between each network node does not exceed the monitoring range threshold to avoid blind spots. At the same time, for key network nodes, such as the main distribution point or key load position in the distribution cabinet, at least two sensors need to be deployed to ensure the reliability and redundancy of energy status data. The calibration cycle threshold configured above refers to the self-calibration frequency set for each network node. Each sensor needs to be calibrated within the calibration cycle threshold to ensure the accuracy of energy status data. Finally, the self-diagnosis result of each network node is judged by the self-diagnosis capability of the sensor. If the network node is judged to be normal, it means that the sensor network deployment is normal. If the network node is judged to be abnormal, it is necessary to start the self-calibration function of the network node and monitor whether the network node is still abnormal. If the network node is self-calibrated and the network node is normal, it means that the network node self-calibration is successful and the sensor network deployment has returned to normal. If the network node is self-calibrated and the network node is still abnormal, it means that the network node self-calibration has failed and the network node needs to be replaced, that is, the normal sensor needs to be replaced.

[0064] The logic for determining the self-diagnosis results of the network nodes includes:

[0065] Monitor the output results of the network node and compare them with the real results to obtain the error results, configure the error threshold, and if the error result is greater than or equal to the error threshold, the self-diagnosis result of the network node is that the network node is abnormal;

[0066] If the error result is less than the error threshold, the self-diagnosis result of the network node is that the network node is normal.

[0067] Continuously monitor the accuracy of the output data of each network node, that is, the sensor, to ensure that the sensor is within the specified error range. The error result is the difference between the output result and the true result, and then divide the difference by the true result to get the value.

[0068] The data transmission module is used to transmit the monitored energy status data to the cloud.

[0069] like Figure 3As shown, the monitored energy status data is transmitted to the cloud, the transmission rate of the energy status data is determined according to the self-diagnosis result and self-calibration result of the network node, and the rate base value, rate high value and rate extreme value are configured. If the self-diagnosis result of the network node is that the network node is normal, the transmission rate of the energy status data is determined to be the rate base value;

[0070] If the self-diagnosis result of the network node is that the network node is abnormal and the self-calibration of the network node is successful, then the transmission rate of the energy status data is determined to be a high rate value;

[0071] If the self-diagnosis result of the network node is that the network node is abnormal and the network node self-calibration fails, it is determined that the transmission rate of the energy state data is a rate extreme value.

[0072] The above needs to select different transmission rates according to the status of the network node, that is, whether the sensor is normal. The above rate base value refers to the standard transmission rate of the sensor itself. When the self-diagnosis result is that the network node is abnormal and the self-calibration is successful, it is necessary to slightly increase the transmission rate to obtain more energy status data, that is, adjust the transmission rate to a high rate value. When the self-diagnosis result is that the network node is abnormal and the self-calibration fails, it is necessary to immediately increase the transmission rate to quickly obtain the energy status data for analysis, that is, adjust the transmission rate to the rate extreme value, so as to ensure the accuracy and timeliness of the energy status data.

[0073] The data processing module is used to process the received energy status data to obtain a comprehensive index.

[0074] The specific steps of processing the received energy status data include:

[0075] Configure the rated frequency, rated power factor, and fundamental voltage, calculate the difference between the frequency and the rated frequency to obtain the frequency difference, calculate the difference between the power factor and the rated power factor to obtain the degree of power factor reduction, extract the characteristics of the harmonics, including the harmonic voltage, calculate the percentage of the total distortion of the harmonic voltage to the fundamental voltage to obtain the total harmonic distortion rate, and comprehensively consider the frequency difference, the degree of power factor reduction, and the total harmonic distortion rate to obtain a comprehensive index.

[0076] The function expression of the comprehensive index is as follows:

[0077] ;

[0078] In the formula, represents the comprehensive index, represents the weight coefficient of the frequency difference, represents the frequency difference, Indicates the rated frequency, The weight coefficient indicating the degree of power factor reduction, Indicates the degree of power factor reduction. Indicates the rated power factor, Represents the weight coefficient of the total harmonic distortion rate, Indicates the total harmonic distortion.

[0079] What needs to be explained is: the weight coefficient of the frequency difference , weight coefficient of power factor drop degree Weight coefficient of total harmonic distortion rate The value range is usually between 0 and 1.

[0080] The frequency difference calculation formula is as follows:

[0081] ;

[0082] In the formula, represents the frequency difference, Indicates frequency, Indicates the rated frequency.

[0083] What needs to be explained is: frequency difference It is an important indicator used to evaluate the stability of power grid frequency. is obtained through the frequency sensor, and the rated frequency Refers to the standard frequency of the power system, usually 50Hz.

[0084] The formula for calculating the degree of power factor reduction is as follows:

[0085] ;

[0086] In the formula, Indicates the degree of power factor reduction. Indicates the power factor, Indicates the rated power factor.

[0087] What needs to be explained is: the degree of power factor reduction It is an important indicator used to evaluate the efficiency of power use. It is usually measured by a power factor sensor, with a value range between 0 and 1. It is usually set to above 0.95, which is a typical value for household or industrial loads under normal circumstances.

[0088] The function expression of total harmonic distortion is as follows:

[0089] ;

[0090] In the formula, It represents the total harmonic distortion rate. Indicates The value of subharmonic voltage, Indicates the value of the fundamental voltage.

[0091] What needs to be explained is: Total harmonic distortion It is an important parameter for evaluating power quality. Subharmonic voltage values It is obtained through the harmonic sensor, reflecting the strength of specific harmonic components and the value of the fundamental voltage. Represents the main sinusoidal component, usually the lowest frequency component.

[0092] The received frequency, power factor and harmonics are processed, and the energy status data is comprehensively considered through the above formula to obtain a comprehensive index to evaluate the operating status of the intelligent grid-connected system. At the same time, specific values, such as frequency difference, power factor reduction degree and total harmonic distortion rate, are included. The comprehensive index and specific values ​​are displayed in the form of charts and dashboards, so that grid managers can intuitively understand the operating status of the grid.

[0093] The status monitoring module is used to determine whether the operating status of the intelligent grid-connected system is abnormal based on the processed energy status data and comprehensive index.

[0094] Configure the index threshold, compare the comprehensive index with the index threshold to obtain the operation status of the smart grid connection. If the comprehensive index is greater than the index threshold, it means that the operation status of the smart grid connection is abnormal and the comprehensive index is abnormal.

[0095] If the comprehensive index is less than or equal to the index threshold, it means that the operation status of the smart grid connection is normal.

[0096] Configure the status data threshold, which includes the frequency difference threshold, the drop degree threshold and the total distortion rate threshold. Compare the status data threshold with the processed energy status data to obtain the operation status of the smart grid. If the frequency difference is greater than the frequency difference threshold, it means that the operation status of the smart grid is abnormal and the frequency difference is abnormal.

[0097] If the frequency difference is less than or equal to the frequency difference threshold, it means that the operation status of the smart grid connection is normal;

[0098] If the power factor decrease degree is greater than the decrease degree threshold, it means that the operation state of the smart grid connection is abnormal and the power factor decreases abnormally;

[0099] If the power factor decrease degree is less than or equal to the decrease degree threshold, it means that the operation status of the smart grid connection is normal;

[0100] If the total harmonic distortion rate is greater than the total distortion rate threshold, it means that the operation state of the smart grid connection is abnormal and the total harmonic distortion rate is abnormal;

[0101] If the total harmonic distortion rate is less than or equal to the total distortion rate threshold, it means that the operation status of the smart grid connection is normal.

[0102] At the same time, it provides functions such as historical data comparison and trend analysis to help power grid managers better understand the operating rules of the power grid. When the operating status of the smart grid is abnormal, the warning mechanism is directly triggered and fed back to the smart grid, sending warning information to the power grid managers, and recording the abnormal information in the database for subsequent analysis and processing, and giving targeted optimization suggestions, such as changing the operating strategy of the smart grid, strengthening daily maintenance and inspection work, timely discovering and eliminating potential safety hazards, improving the technical level and safety awareness of operators, and ensuring smart grid connection.

[0103] The feedback control module is used to feedback to the smart grid when the operation status of the smart grid is judged to be abnormal, and change the operation strategy of the smart grid.

[0104] The logic of feeding back to the smart grid and changing the operation strategy of the smart grid includes:

[0105] Identify the abnormal type of the operation status of the intelligent grid connection as abnormal, and if the abnormal type is the abnormal comprehensive index, adjust the generator output power and reduce the load;

[0106] If the abnormality type is frequency difference abnormality, adjust the generator frequency;

[0107] If the abnormality type is a power factor drop abnormality, then increase the power factor;

[0108] If the abnormal type is abnormal total harmonic distortion rate, reduce the total harmonic distortion rate;

[0109] The status monitoring module determines whether the operating status of the intelligent grid-connected system is abnormal, and the abnormal types are obtained as abnormal comprehensive index, abnormal frequency difference, abnormal power factor decrease and abnormal total harmonic distortion rate. According to the corresponding abnormal type, the corresponding intelligent grid-connected operation strategy is changed. If the comprehensive index is abnormal, it is necessary to adjust the generator output power and reduce the load to reduce the comprehensive index. If the frequency difference is abnormal, it is necessary to adjust the generator frequency. If the power factor decrease is abnormal, it is necessary to add a reactive compensation device to improve the power factor. If the total harmonic distortion rate is abnormal, it is necessary to start the harmonic filter to reduce the total harmonic distortion rate. In this way, the operation strategy of the intelligent grid-connected system is changed to achieve the normal operation status of the intelligent grid-connected system.

[0110] At the same time, the operation strategy of smart grid connection is changed by adjusting the charging and discharging strategy. First of all, for charging, the energy storage equipment of the distribution cabinet needs to reduce the charging power or temporarily stop charging to reduce the burden of smart grid connection. At the same time, for discharging, the energy storage equipment of the distribution cabinet needs to increase the discharge power to meet the needs of smart grid connection and maintain the stability of smart grid connection. The charging and discharging cycle of the energy storage equipment is dynamically adjusted according to the capacity of the energy storage equipment in the distribution cabinet to ensure the efficient utilization of the energy storage equipment and the stable operation of the smart grid connection.

[0111] Example 2

[0112] In this embodiment, a method flow chart of an energy state monitoring and feedback method for smart grid connection is provided, such as Figure 4 As shown, the energy status monitoring and feedback method for smart grid connection includes:

[0113] S1. Real-time monitoring of energy status data during intelligent grid-connected operation;

[0114] S2, transmitting the monitored energy status data to the cloud;

[0115] S3, processing the received energy status data to obtain a comprehensive index;

[0116] S4. Judging whether the operation status of the intelligent grid connection is abnormal according to the processed energy status data and the comprehensive index;

[0117] S5. When the operation status of the smart grid is judged to be abnormal, feedback is given to the smart grid and the operation strategy of the smart grid is changed;

[0118] For the specific contents of the energy state monitoring and feedback method for intelligent grid connection, please refer to the energy state monitoring and feedback system for intelligent grid connection, which will not be described in detail here.

[0119] Example 3

[0120] In this embodiment, a computer device is provided, including a memory and a processor, the memory is used to store instructions, and the processor is used to execute the instructions, so that the computer device executes the steps of implementing the above-mentioned energy status monitoring and feedback method for intelligent grid connection.

[0121] Example 4

[0122] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed, the steps of the above-mentioned energy status monitoring and feedback method for intelligent grid connection are implemented.

[0123] The computer-readable storage medium includes: a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk, and other media for storing program codes.

[0124] 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 can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. Energy status monitoring and feedback system for intelligent grid connection, characterized by: include: Data acquisition module, data transmission module, data processing module, status monitoring module and feedback control module; The data acquisition module is used to monitor the energy status data during intelligent grid-connected operation in real time; The data transmission module is used to transmit the monitored energy status data to the cloud; The data processing module is used to process the received energy status data to obtain a comprehensive index, which is obtained by comprehensively considering the frequency difference, the degree of power factor reduction and the total harmonic distortion rate; The specific steps of processing the received energy status data include: Configure the rated frequency, rated power factor, and fundamental voltage, calculate the difference between the frequency and the rated frequency to obtain the frequency difference, calculate the difference between the power factor and the rated power factor to obtain the degree of power factor reduction, extract the characteristics of harmonics, including harmonic voltage, calculate the percentage of total distortion of harmonic voltage to fundamental voltage to obtain the total harmonic distortion rate, and comprehensively consider the frequency difference, power factor reduction degree, and total harmonic distortion rate to obtain a comprehensive index; The function expression of the comprehensive index is as follows: ； In the formula, represents the comprehensive index, represents the weight coefficient of the frequency difference, represents the frequency difference, Indicates the rated frequency, The weight coefficient indicating the degree of power factor reduction, Indicates the degree of power factor reduction. Indicates the rated power factor, Represents the weight coefficient of the total harmonic distortion rate, Indicates the total harmonic distortion rate; The state monitoring module is used to determine whether the operation state of the intelligent grid connection is abnormal based on the processed energy state data and the comprehensive index; According to the processed energy status data and comprehensive index, it is judged whether the operation status of the smart grid connection is abnormal, including: An index threshold is configured, and the comprehensive index is compared with the index threshold to obtain the operation state of the smart grid connection. If the comprehensive index is greater than the index threshold, it indicates that the operation state of the smart grid connection is abnormal and the comprehensive index is abnormal. If the comprehensive index is less than or equal to the index threshold, it means that the operation status of the smart grid connection is normal; Judging whether the operation state of the intelligent grid connection is abnormal according to the processed energy state data and the comprehensive index, further comprising: configuring a state data threshold, wherein the state data threshold comprises a frequency difference threshold, a drop degree threshold and a total distortion rate threshold, comparing the state data threshold with the processed energy state data to obtain the operation state of the intelligent grid connection, and if the frequency difference is greater than the frequency difference threshold, it indicates that the operation state of the intelligent grid connection is abnormal and the frequency difference is abnormal; If the frequency difference is less than or equal to the frequency difference threshold, it means that the operation status of the smart grid connection is normal; If the power factor decrease degree is greater than the decrease degree threshold, it means that the operation state of the smart grid connection is abnormal and the power factor decreases abnormally; If the power factor decrease degree is less than or equal to the decrease degree threshold, it means that the operation status of the smart grid connection is normal; If the total harmonic distortion rate is greater than the total distortion rate threshold, it means that the operation state of the smart grid connection is abnormal and the total harmonic distortion rate is abnormal; If the total harmonic distortion rate is less than or equal to the total distortion rate threshold, it means that the operation status of the smart grid connection is normal; The feedback control module is used to feed back to the smart grid when the operation state of the smart grid is judged to be abnormal, and change the operation strategy of the smart grid.

2. The energy status monitoring and feedback system for intelligent grid connection according to claim 1, characterized in that: The logic of feeding back to the smart grid and changing the operation strategy of the smart grid includes: Identify the abnormal type of the operation status of the intelligent grid connection as abnormal, and if the abnormal type is the abnormal comprehensive index, adjust the generator output power and reduce the load; If the abnormality type is frequency difference abnormality, adjust the generator frequency; If the abnormality type is a power factor drop abnormality, then increase the power factor; If the abnormality type is the total harmonic distortion rate abnormality, reduce the total harmonic distortion rate.

3. The energy status monitoring and feedback system for intelligent grid connection according to claim 2, characterized in that: Real-time monitoring of energy status data during intelligent grid-connected operation through a sensor network, wherein the energy status data includes the frequency, power factor and harmonics of the grid; The deployment strategy of the sensor network includes: Each sensor is used as a network node. A monitoring range threshold is configured. The distance between network nodes is determined based on the monitoring range threshold. A calibration period threshold is configured. The calibration time of the network node is determined based on the calibration period threshold. The self-diagnosis result of the network node is determined. If the self-diagnosis result of the network node is normal, it means that the sensor network deployment is normal. If the self-diagnosis result of the network node is that the network node is abnormal, the self-calibration of the network node is started to monitor whether the network node is abnormal. If the network node is normal, it means that the self-calibration of the network node is successful and the sensor network deployment is restored to normal; If the network node is still abnormal, it means that the network node self-calibration has failed and the network node should be replaced.

4. The energy status monitoring and feedback system for intelligent grid connection according to claim 3, characterized in that: The logic of determining the self-diagnosis result of the network node includes: Monitor the output results of the network node and compare them with the real results to obtain the error results, configure the error threshold, and if the error result is greater than or equal to the error threshold, the self-diagnosis result of the network node is that the network node is abnormal; If the error result is less than the error threshold, the self-diagnosis result of the network node is that the network node is normal.

5. The energy status monitoring and feedback system for intelligent grid connection according to claim 4, characterized in that: The monitored energy status data is transmitted to the cloud, the transmission rate of the energy status data is determined according to the self-diagnosis result and self-calibration result of the network node, and the rate base value, rate high value and rate extreme value are configured. If the self-diagnosis result of the network node is that the network node is normal, the transmission rate of the energy status data is determined to be the rate base value; If the self-diagnosis result of the network node is that the network node is abnormal and the self-calibration of the network node is successful, then the transmission rate of the energy status data is determined to be a high rate value; If the self-diagnosis result of the network node is that the network node is abnormal and the network node self-calibration fails, it is determined that the transmission rate of the energy state data is a rate extreme value.

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