Energy business internet intelligent management system based on micro-service architecture

Abstract

The invention relates to the technical field of energy management, and discloses a micro-service architecture-based energy service internet intelligent management system, which comprises an internet intelligent management system, and is characterized in that the internet intelligent management system comprises a planning module, a monitoring module, an analysis module, an optimization module, a prediction module and an interaction module; the planning module comprises a basic data acquisition module and a marking module, the basic data acquisition module is electrically connected with the photovoltaic system, and the basic data acquisition module is electrically connected with the marking module. According to the invention, the Internet intelligent management system is adopted to finely process each parameter data generated in the energy business, so as to ensure that the acquired abnormal parameter data is more reasonable and accurate and the processing time is short, multi-stage processing is adopted, and the time threshold is set, so that the energy storage of new energy is ensured, and the waste of resources is avoided.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to an energy business Internet intelligent management system based on a microservice architecture. Background Art

[0002] Microservice architecture is an architectural style that develops a single application as a group of small services. Each service runs independently in its own process and communicates and collaborates through lightweight mechanisms. In the process of energy business management, smart management systems based on microservice architecture are often used to better manage energy intelligently.

[0003] In the existing technology, with the progress of the times, new energy sources such as solar power generation and hydropower generation are increasingly being promoted. However, the existing photovoltaic new energy collection equipment is set up in a large area, which makes it difficult to manage rationally, thereby affecting the energy storage of new energy sources, which will cause waste of resources and make it difficult to timely maintain photovoltaic new energy equipment with energy collection efficiency problems.

[0004] After searching, for example, Chinese patent documents disclose a method and device for intelligent monitoring of photovoltaic energy storage systems (publication number: CN118739606B). The present invention relates to intelligent monitoring technology and discloses a method for intelligent monitoring of photovoltaic energy storage systems, including: performing extreme value highlighting processing on the state data set of the photovoltaic energy storage system obtained by collection to obtain a prominent state data set, calculating the state abnormality coefficient according to the prominent state data set, calculating the output difference between the theoretical output value and the actual output value of the photovoltaic energy storage system, calculating the current fluctuation coefficient of each energy storage battery, and calculating the comprehensive discrimination index of the photovoltaic energy storage system according to the state abnormality coefficient, the output difference and the current fluctuation coefficient of each battery. If the comprehensive discrimination index is less than the threshold, the state data of the photovoltaic energy storage system is returned to be collected again, otherwise it is determined that the photovoltaic energy storage system is abnormal and an alarm message is issued. The present invention also proposes an electronic device for intelligent monitoring of photovoltaic energy storage systems. The present invention can improve the efficiency of monitoring photovoltaic energy storage systems, but there are still the following defects: Although the above-mentioned photovoltaic energy storage system intelligent monitoring method and equipment are photovoltaic energy storage system intelligent monitoring method and equipment, they are still difficult to manage rationally, which in turn affects the energy storage of new energy, thus causing waste of resources, and it is difficult to carry out timely maintenance of photovoltaic new energy equipment with energy collection efficiency problems. Summary of the invention

[0005] The purpose of the present invention is to provide an energy business Internet intelligent management system based on a microservice architecture, which solves the problem that it is difficult to carry out rational management in the background technology, which in turn affects the energy storage of new energy, thus causing waste of resources, and it is difficult to carry out timely maintenance of photovoltaic new energy equipment with energy collection efficiency problems.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: An energy business Internet smart management system based on a microservice architecture, including an Internet smart management system, wherein the Internet smart management system includes a planning module, a monitoring module, an analysis module, an optimization module, a prediction module and an interaction module; The planning module includes a basic data acquisition module and a marking module, wherein the basic data acquisition module is electrically connected to the photovoltaic system, and the basic data acquisition module is electrically connected to the marking module; The monitoring module includes a photovoltaic component monitoring module, an energy storage device monitoring module, an inverter monitoring module, an energy management system monitoring module and a grid connection monitoring module, wherein the photovoltaic component monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module are all electrically connected to the photovoltaic system, and the photovoltaic component monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module are electrically connected to the analysis module; The analysis module includes a data processing module, an objective factor fusion module and a comparison module, wherein the data processing module is electrically connected to the objective factor fusion module, and the objective factor fusion module is electrically connected to the comparison module, and the comparison module is electrically connected to the optimization module; The optimization module is electrically connected to the interaction module; The prediction module includes a future objective factor collection module and a future prediction report generation module, wherein the future objective factor collection module is electrically connected to the future prediction report generation module, and the future prediction report generation module is electrically connected to the interaction module and the monitoring module.

[0007] Preferably, the basic data acquisition module is used to collect rated values ​​of basic parameter data in the photovoltaic system, and the basic parameter data includes photovoltaic component parameters, photovoltaic array parameters, inverter parameters and photovoltaic system electrical parameters.

[0008] The function of the marking module is to mark the output device according to the parameter data collected by the basic data collection module, and the marking method is a unique marking, and the photovoltaic panel is marked at the same time.

[0009] Preferably, the monitoring module is used to collect various parameter data generated by various devices in the photovoltaic system, so as to perform intelligent management on the acquired parameter data; The photovoltaic component monitoring module is used to monitor and obtain the output voltage parameter data, output current parameter data and output power parameter data of the photovoltaic panel in real time; The function of the energy storage device monitoring module is to monitor and obtain the voltage parameter data, current parameter data, charge and discharge state parameter data, capacity parameter data, internal resistance parameter data, and temperature parameter data of the energy storage battery in real time; The function of the inverter monitoring module is to monitor and obtain the input and output voltage parameter data, current parameter data, frequency parameter data, power factor parameter data, efficiency and other parameter data of the inverter in real time; The function of the energy management system monitoring module is to monitor and obtain the operating status, control strategy, power distribution, etc. of the energy management system in real time; The function of the grid connection monitoring module is to monitor and obtain the voltage parameter data, frequency parameter data and phase parameter data of the grid, as well as the grid-connected current and power information parameter data in real time. The voltage parameter data, frequency parameter data and phase parameter data of the grid monitored and obtained by the set grid connection monitoring module can ensure the safe and stable connection between the system and the grid and the smooth grid connection of electric energy.

[0010] Preferably, the function of the analysis module is to analyze and process the parameter data acquired by the monitoring module to obtain data with abnormalities; The function of the data processing module is to receive the parameter data acquired by the monitoring module and perform data processing. The data processing specifically includes the following methods: (1) Set a time threshold and classify and aggregate the parameter data within the time threshold; (2) Determine the data type of each parameter and complete data cleaning; (3) Visualize the data.

[0011] Preferably, the function of the future objective factor acquisition module is to collect environmental factors within the future time threshold to be predicted and fuse the impact values, the objective factors include light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data, and the impact values ​​are obtained by calculating based on the optimal light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data and the light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data within the time threshold; The function of the comparison module is to complete data comparison to obtain abnormal parameter data. The specific steps of the comparison module to complete data comparison are: Step 1: Fuse the parameter data obtained by the monitoring module with the corresponding impact thresholds; Step 2: Merge the standard values ​​of each parameter data with the corresponding impact thresholds; Step 3: Compare the same data of the same device; Step 4: Determine whether it is within the reasonable floating threshold; Step 5: Extract parameter data that are not within the floating threshold and transfer them to the optimization module.

[0012] Preferably, the function of the optimization module is to receive abnormal parameter data and analyze the abnormal parameter data to obtain a maintenance report of the equipment generating the abnormal parameter data. The specific steps of the optimization module generating the maintenance report of the equipment generating the abnormal parameter data are: Step 1: Extend the time threshold of abnormal parameter data and perform visual analysis; Step 2: Determine the time point when the abnormality occurs; Step 3: Locate the PV subsystem or component where the anomaly is located; Step 4: Generate a maintenance report for the equipment with abnormal parameter data.

[0013] Preferably, the prediction module predicts the future output value of the managed photovoltaic system, and the specific steps of predicting the future output value by the prediction module are: Step 1: First, determine the time threshold for predicting future output values; Step 2: Build a future output value prediction model; Step 3: The future output value prediction model collects output values ​​within the past time threshold as data; Step 4: Determine the autoregressive order and the difference order of the future output value prediction model; Step 5: Fit the future output value prediction model; Step 6: Diagnose the future output value prediction model; Step 7: The future output value prediction model completes the prediction and obtains the simulated future output value; Step 8: Fusing the simulated future output value with the impact value within the future time threshold collected by the future objective factor collection module to obtain the future output value; Step 9: Transmit it to the decision terminal set through the future forecast report generation module.

[0014] Preferably, the function of the future objective factor collection module is to collect environmental factors within the future time threshold to be predicted, the objective factors include light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data, and the impact value is obtained by calculating based on the optimal light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data and the light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data within the time threshold.

[0015] The function of the future prediction report generation module is to collect simulated future output values, future output values, upper and lower limits of future output values, and interact with the decision-making terminal through the interaction module.

[0016] Preferably, the interactive module is electrically connected to the planning module, monitoring module, analysis module, optimization module, prediction module and decision terminal, and the function of the interactive module is to complete data transmission between the planning module, monitoring module, analysis module, optimization module and prediction module through the Internet, and to complete data transmission between the planning module and the monitoring module and the photovoltaic system through the Internet, and at the same time to interact the data generated by the Internet intelligent management system, the optimization plan generated by the optimization module, and the prediction report generated by the prediction module to the decision terminal through the Internet, and the interactive module is used for the objective factor fusion module and the future objective factor collection module to obtain required parameter data through the Internet.

[0017] Preferably, the specific energy storage monitoring method of the Internet smart management system is: S1: First, the basic parameters of the photovoltaic system managed by the Internet smart management system are obtained through the basic data acquisition module contained in the planning module; S2: marking the photovoltaic panels of the photovoltaic system for collecting solar energy through the marking module contained in the planning module; S3: Acquire monitoring parameter data through the monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module contained in the monitoring module; S4: The data processing module contained in the analysis module collects and processes the data of each monitored eucalyptus tree obtained by the monitoring module; S5: receiving the monitoring parameter data processed by the data processing module through the objective factor fusion module contained in the analysis module, and collecting the objective factor parameters within the past analysis time threshold; S6: The objective factor fusion module generates an impact threshold value based on the impact value of the objective factor parameter on the photovoltaic system, and fuses it with each monitoring parameter data to obtain the data index of each monitoring parameter; S7: comparing each monitoring parameter data indicator with the standard monitoring parameter data through a comparison module contained in the analysis module; S8.1.1: If the compared monitoring parameter data is within the floating threshold, the optimization module will not be executed; S8.2.1: If the compared monitoring parameter data is not within the floating threshold, the non-compliant monitoring parameter data is transmitted to the optimization module; S8.2.2: Retrieve abnormal parameter data from the monitoring parameter data through the optimization module and generate an optimization plan; S8.2.3: The optimization plan generated by the optimization module is communicated to the decision terminal through the interaction module.

[0018] Preferably, compared with the prior art, the beneficial effects achieved by the present invention are: 1. During use, the present invention adopts the Internet intelligent management system to perform fine processing on various parameter data generated in the energy business to ensure that the acquisition of abnormal parameter data is more reasonable and accurate and the processing time is short. It adopts multi-stage processing and sets time thresholds to ensure the energy storage of new energy and avoid waste of resources.

[0019] 2. During use, the present invention analyzes and processes the parameter data obtained by the monitoring module through the set analysis module, and constructs data comparison at the same time. Through rapid data collection and comparison, it can accurately analyze and obtain abnormal data. At the same time, through the set planning module and optimization module, it can quickly and accurately process the abnormal energy storage part.

[0020] 3. During use, the present invention can predict the future output value of the photovoltaic system, effectively improve the early warning of the Internet intelligent management system in the process of managing the photovoltaic system, reduce power shortages and other phenomena, further improve the management and control capabilities of energy services, and improve practicality and early warning lines. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the system structure of the present invention; Figure 2 A schematic diagram of the specific steps of completing data comparison by the comparison module of the present invention; Figure 3 A schematic diagram of the specific steps of the maintenance report of the device generating abnormal parameter data for the optimization module of the present invention; Figure 4 This is a schematic diagram of specific steps for the prediction module of the present invention to predict future output values; Figure 5 It is a schematic diagram of a specific energy storage monitoring method of the Internet intelligent management system of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Example 1: Please refer to Figure 1-5The energy business Internet intelligent management system based on microservice architecture includes an Internet intelligent management system, which includes a planning module, a monitoring module, an analysis module, an optimization module, a prediction module and an interaction module.

[0024] The planning module includes a basic data acquisition module and a marking module. The basic data acquisition module is electrically connected to the photovoltaic system, and the basic data acquisition module is electrically connected to the marking module.

[0025] The monitoring module includes a photovoltaic component monitoring module, an energy storage device monitoring module, an inverter monitoring module, an energy management system monitoring module and a grid connection monitoring module. The photovoltaic component monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module are all electrically connected to the photovoltaic system, and the photovoltaic component monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module are electrically connected to the analysis module.

[0026] The analysis module includes a data processing module, an objective factor fusion module and a comparison module. The data processing module is electrically connected to the objective factor fusion module, the objective factor fusion module is electrically connected to the comparison module, and the comparison module is electrically connected to the optimization module.

[0027] The optimization module is electrically connected to the interaction module.

[0028] The prediction module includes a future objective factor collection module and a future prediction report generation module. The future objective factor collection module is electrically connected to the future prediction report generation module, and the future prediction report generation module is electrically connected to the interaction module and the monitoring module.

[0029] The function of the basic data acquisition module is to collect the rated values ​​of the basic parameter data in the photovoltaic system. The basic parameter data includes photovoltaic module parameters, photovoltaic array parameters, inverter parameters and photovoltaic system electrical parameters.

[0030] The photovoltaic module parameters include rated power parameter data, rated open circuit voltage parameter data, rated short circuit current parameter data, rated fill factor parameter data and rated conversion efficiency parameter data; PV array parameters include array capacity, number of series modules and number of parallel branches.

[0031] The inverter parameters include the inverter rated power parameter data, the inverter maximum input voltage parameter data, the inverter maximum input current and the inverter rated conversion efficiency value.

[0032] The electrical parameters of the photovoltaic system include the rated voltage parameter data of the electrical equipment, the rated current parameter data of the electrical equipment and the rated power factor parameter data of the electrical equipment.

[0033] The function of the marking module is to mark the parameter data output devices collected by the basic data acquisition module, and the marking method is unique marking. At the same time, the photovoltaic panels are marked. The logic of marking the photovoltaic panels is that because photovoltaic panels are often distributed in arrays, the longitudinal coordinates and transverse coordinates of the photovoltaic panels are used as the unique position parameter data to complete the marking.

[0034] The function of the monitoring module is to collect the parameter data generated by each device in the photovoltaic system and to perform intelligent management on the acquired parameter data.

[0035] The function of the photovoltaic module monitoring module is to monitor and obtain the output voltage parameter data, output current parameter data and output power parameter data of the photovoltaic panel in real time. The output voltage parameter data, output current parameter data and output power parameter data monitored and obtained by the photovoltaic module monitoring module can accurately evaluate the power generation performance of the photovoltaic module and promptly discover the failure or aging problems of the module.

[0036] The function of the energy storage device monitoring module is to monitor and obtain the voltage parameter data, current parameter data, charge and discharge state parameter data, capacity parameter data, internal resistance parameter data, and temperature parameter data of the energy storage battery in real time. The voltage parameter data, current parameter data, charge and discharge state parameter data, capacity parameter data, internal resistance parameter data, and temperature parameter data monitored and obtained by the set energy storage device monitoring module can timely discover the degree of battery aging so that maintenance or replacement measures can be taken in advance. At the same time, the performance and life of the battery can be accurately protected, and heat dissipation measures can be taken.

[0037] The function of the inverter monitoring module is to monitor and obtain the input and output voltage parameter data, current parameter data, frequency parameter data, power factor parameter data, efficiency and other parameter data of the inverter in real time. The voltage parameter data, current parameter data, frequency parameter data, power factor parameter data, efficiency and other parameter data monitored and obtained by the set inverter monitoring module can timely detect the abnormality of the inverter. When the output voltage or frequency of the inverter is abnormal, it may affect the normal operation of the electrical equipment and even cause damage to the equipment. In this way, the abnormality discovered in time can be dealt with in time.

[0038] The function of the energy management system monitoring module is to monitor and obtain the operating status, control strategy, power distribution and other conditions of the energy management system in real time. By setting up the energy management system monitoring module, the coordinated operation of photovoltaic power generation, energy storage and electricity consumption can be ensured, avoiding the lag of control strategy or power distribution strategy, which leads to energy storage.

[0039] The function of the grid connection monitoring module is to monitor and obtain the voltage parameter data, frequency parameter data and phase parameter data of the grid, as well as the grid-connected current and power information parameter data in real time. The voltage parameter data, frequency parameter data and phase parameter data of the grid monitored and obtained by the set grid connection monitoring module can ensure the safe and stable connection between the system and the grid and the smooth grid connection of electricity.

[0040] The function of the analysis module is to analyze and process the parameter data obtained by the monitoring module to obtain data with abnormalities.

[0041] The function of the data processing module is to receive the parameter data obtained by the monitoring module for data processing. Through the set data processing module, data visualization can be completed, and the processed data can be displayed in the form of intuitive graphics, charts, etc., so that decision makers can quickly understand the information contained in the data, while ensuring the integrity and accuracy of the data. Data processing specifically includes the following methods: (1) Set a time threshold and classify and aggregate the parameter data within the time threshold; (2) Determine the data type of each parameter and complete data cleaning; (3) Visualize the data.

[0042] The function of the future objective factor collection module is to collect the environmental factors within the future time threshold to be predicted and integrate the impact values. The objective factors include light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data. The impact values ​​are obtained by calculating the optimal light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data with the light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data within the time threshold.

[0043] The function of the optimization module is to receive abnormal parameter data and analyze the abnormal parameter data to obtain a maintenance report of the equipment that generates the abnormal parameter data.

[0044] The function of the future objective factor collection module is to collect the environmental factors within the future time threshold to be predicted. The objective factors include light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data. The impact value is obtained by calculating the optimal light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data with the light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data within the time threshold.

[0045] The function of the future forecast report generation module is to collect simulated future output values, future output values, upper and lower limits of future output values, and interact with the decision-making terminal through the interactive module.

[0046] The future objective factor collection module also adopts an interactive module connected with electricity to collect future objective factors through the Internet.

[0047] The interactive module is electrically connected to the planning module, monitoring module, analysis module, optimization module, prediction module and decision-making terminal, and the function of the interactive module is to complete data transmission between the planning module, monitoring module, analysis module, optimization module and prediction module through the Internet, and to complete data transmission between the planning module and the monitoring module and the photovoltaic system through the Internet. At the same time, it is used to interact the data generated by the Internet intelligent management system, the optimization plan generated by the optimization module, and the prediction report generated by the prediction module to the decision-making terminal through the Internet, and the interactive module is used for the objective factor fusion module and the future objective factor collection module to obtain the required parameter data through the Internet.

[0048] The interactive module includes a cloud database, and the function of the cloud database is to store the data parameters collected by the planning module and the monitoring module through the interactive module. At the same time, the cloud database can also be used by the decision-making terminal through the interactive module.

[0049] Example 2: Please refer to Figure 1-5 , the energy business Internet intelligent management system based on microservice architecture includes a comparison module. The function of the comparison module is to complete data comparison to obtain abnormal parameter data. The specific steps of the comparison module to complete data comparison are: Step 1: Fuse the parameter data obtained by the monitoring module with the corresponding impact thresholds; Step 2: Merge the standard values ​​of each parameter data with the corresponding impact thresholds; Step 3: Compare the same data of the same device; Step 4: Determine whether it is within the reasonable floating threshold; Step 5: Extract parameter data that are not within the floating threshold and transfer them to the optimization module.

[0050] Example 3: Please refer to Figure 1-5 , the energy business Internet smart management system based on microservice architecture includes an optimization module. The specific steps of the maintenance report of the equipment with abnormal parameter data generated by the optimization module are: Step 1: Extend the time threshold of abnormal parameter data and perform visual analysis; Step 2: Determine the time point when the abnormality occurs; Step 3: Locate the PV subsystem or component where the anomaly is located; Step 4: Generate a maintenance report for the equipment with abnormal parameter data.

[0051] Example 4: Please refer to Figure 1-5The energy business Internet intelligent management system based on microservice architecture includes a prediction module. The prediction module predicts the future output value of the managed photovoltaic system. The specific steps of the prediction module for predicting the future output value are as follows: Step 1: First, determine the time threshold for predicting future output values; Step 2: Build a future output value prediction model; Step 3: The future output value prediction model collects output values ​​within the past time threshold as data; Step 4: Determine the autoregressive order and the difference order of the future output value prediction model; Step 5: Fit the future output value prediction model; Step 6: Diagnose the future output value prediction model; Step 7: The future output value prediction model completes the prediction and obtains the simulated future output value; Step 8: Fusing the simulated future output value with the impact value within the future time threshold collected by the future objective factor collection module to obtain the future output value; Step 9: Transmit it to the decision terminal set through the future forecast report generation module.

[0052] In step 2, the future output value prediction module adopts a time series prediction model and adapts the prediction of future output values ​​through the characteristics of the time series prediction model.

[0053] In step 4, the autoregressive order is the number of days of the future time threshold, and the difference order is the difference value of the output value within the past time threshold.

[0054] Example 5: Please refer to Figure 1-5 , the energy business Internet smart management system based on microservice architecture includes the Internet smart management system. The specific energy storage monitoring method of the Internet smart management system is: S1: First, the basic parameters of the photovoltaic system managed by the Internet smart management system are obtained through the basic data acquisition module contained in the planning module; S2: marking the photovoltaic panels of the photovoltaic system for collecting solar energy through the marking module contained in the planning module; S3: Acquire monitoring parameter data through the monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module contained in the monitoring module; S4: The data processing module contained in the analysis module collects and processes the data of each monitored eucalyptus tree obtained by the monitoring module; S5: receiving the monitoring parameter data processed by the data processing module through the objective factor fusion module contained in the analysis module, and collecting the objective factor parameters within the past analysis time threshold; S6: The objective factor fusion module generates an impact threshold value based on the impact value of the objective factor parameter on the photovoltaic system, and fuses it with each monitoring parameter data to obtain the data index of each monitoring parameter; S7: comparing each monitoring parameter data indicator with the standard monitoring parameter data through a comparison module contained in the analysis module; S8.1.1: If the compared monitoring parameter data is within the floating threshold, the optimization module will not be executed; S8.2.1: If the compared monitoring parameter data is not within the floating threshold, the non-compliant monitoring parameter data is transmitted to the optimization module; S8.2.2: Retrieve abnormal parameter data from the monitoring parameter data through the optimization module and generate an optimization plan; S8.2.3: The optimization plan generated by the optimization module is communicated to the decision terminal through the interaction module.

[0055] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit thereof, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An energy business Internet smart management system based on a microservice architecture, including an Internet smart management system, characterized by: The Internet intelligent management system includes a planning module, a monitoring module, an analysis module, an optimization module, a prediction module and an interaction module; The planning module includes a basic data acquisition module and a marking module, wherein the basic data acquisition module is electrically connected to the photovoltaic system, and the basic data acquisition module is electrically connected to the marking module; The monitoring module includes a photovoltaic component monitoring module, an energy storage device monitoring module, an inverter monitoring module, an energy management system monitoring module and a grid connection monitoring module, wherein the photovoltaic component monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module are all electrically connected to the photovoltaic system, and the photovoltaic component monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module are electrically connected to the analysis module; The analysis module includes a data processing module, an objective factor fusion module and a comparison module, wherein the data processing module is electrically connected to the objective factor fusion module, and the objective factor fusion module is electrically connected to the comparison module, and the comparison module is electrically connected to the optimization module; The optimization module is electrically connected to the interaction module; The prediction module includes a future objective factor collection module and a future prediction report generation module, wherein the future objective factor collection module is electrically connected to the future prediction report generation module, and the future prediction report generation module is electrically connected to the interaction module and the monitoring module.

2. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The function of the basic data acquisition module is to collect the rated values ​​of the basic parameter data in the photovoltaic system, and the basic parameter data includes photovoltaic module parameters, photovoltaic array parameters, inverter parameters and photovoltaic system electrical parameters; The function of the marking module is to mark the output device according to the parameter data collected by the basic data collection module, and the marking method is a unique marking, and the photovoltaic panel is marked at the same time.

3. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The monitoring module is used to collect various parameter data generated by various devices in the photovoltaic system, so as to intelligently manage the acquired parameter data; The photovoltaic component monitoring module is used to monitor and obtain the output voltage parameter data, output current parameter data and output power parameter data of the photovoltaic panel in real time; The function of the energy storage device monitoring module is to monitor and obtain the voltage parameter data, current parameter data, charge and discharge state parameter data, capacity parameter data, internal resistance parameter data, and temperature parameter data of the energy storage battery in real time; The function of the inverter monitoring module is to monitor and obtain the input and output voltage parameter data, current parameter data, frequency parameter data, power factor parameter data, efficiency and other parameter data of the inverter in real time; The function of the energy management system monitoring module is to monitor and obtain the operating status, control strategy, power distribution, etc. of the energy management system in real time; The function of the grid connection monitoring module is to monitor and obtain the voltage parameter data, frequency parameter data and phase parameter data of the grid, as well as the grid-connected current and power information parameter data in real time. The voltage parameter data, frequency parameter data and phase parameter data of the grid monitored and obtained by the set grid connection monitoring module can ensure the safe and stable connection between the system and the grid and the smooth grid connection of electric energy.

4. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The function of the analysis module is to analyze and process the parameter data acquired by the monitoring module to obtain data with abnormalities; The function of the data processing module is to receive the parameter data acquired by the monitoring module and perform data processing. The data processing specifically includes the following methods: (1) Set a time threshold and classify and aggregate the parameter data within the time threshold; (2) Determine the data type of each parameter and complete data cleaning; (3) Visualize the data.

5. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The objective factor fusion module is used to collect the objective factors within the time threshold collected by the data processing module, and obtain the impact threshold according to the status of the objective factors, wherein the objective factors include light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data, and the impact threshold is obtained by calculating the optimal light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data and the light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data within the time threshold; The function of the comparison module is to complete data comparison to obtain abnormal parameter data. The specific steps of the comparison module to complete data comparison are: Step 1: Fuse the parameter data obtained by the monitoring module with the corresponding impact thresholds; Step 2: Merge the standard values ​​of each parameter data with the corresponding impact thresholds; Step 3: Compare the same data of the same device; Step 4: Determine whether it is within the reasonable floating threshold; Step 5: Extract parameter data that are not within the floating threshold and transfer them to the optimization module.

6. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The function of the optimization module is to receive abnormal parameter data and analyze the abnormal parameter data to obtain a maintenance report of the equipment generating the abnormal parameter data. The specific steps of the optimization module generating the maintenance report of the equipment generating the abnormal parameter data are as follows: Step 1: Extend the time threshold of abnormal parameter data and perform visual analysis; Step 2: Determine the time point when the abnormality occurs; Step 3: Locate the PV subsystem or component where the anomaly is located; Step 4: Generate a maintenance report for the equipment with abnormal parameter data.

7. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The prediction module is used to predict the future output value of the managed photovoltaic system. The specific steps of predicting the future output value by the prediction module are as follows: Step 1: First, determine the time threshold for predicting future output values; Step 2: Build a future output value prediction model; Step 3: The future output value prediction model collects output values ​​within the past time threshold as data; Step 4: Determine the autoregressive order and the difference order of the future output value prediction model; Step 5: Fit the future output value prediction model; Step 6: Diagnose the future output value prediction model; Step 7: The future output value prediction model completes the prediction and obtains the simulated future output value; Step 8: Fusing the simulated future output value with the impact value within the future time threshold collected by the future objective factor collection module to obtain the future output value; Step 9: Transmit it to the decision terminal set through the future forecast report generation module.

8. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The function of the future objective factor acquisition module is to collect environmental factors within the future time threshold to be predicted and fuse the impact values, wherein the objective factors include light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data, and the impact values ​​are obtained by calculating the optimal light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data with the light intensity, light direction, ambient temperature parameter data and ambient humidity parameter data within the time threshold; The function of the future prediction report generation module is to collect simulated future output values, future output values, upper and lower limits of future output values, and interact with the decision-making terminal through the interaction module.

9. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The interactive module is electrically connected to the planning module, monitoring module, analysis module, optimization module, prediction module and decision terminal, and the function of the interactive module is to complete data transmission between the planning module, monitoring module, analysis module, optimization module and prediction module through the Internet, and to complete data transmission between the planning module and the monitoring module and the photovoltaic system through the Internet, and at the same time to interact the data generated by the Internet intelligent management system, the optimization plan generated by the optimization module and the prediction report generated by the prediction module to the decision terminal through the Internet, and the interactive module is used for the objective factor fusion module and the future objective factor collection module to obtain required parameter data through the Internet.

10. The energy business Internet intelligent management system based on microservice architecture according to claim 1 is characterized by: The specific energy storage monitoring method of the Internet smart management system is: S1: First, the basic parameters of the photovoltaic system managed by the Internet smart management system are obtained through the basic data acquisition module contained in the planning module; S2: marking the photovoltaic panels of the photovoltaic system for collecting solar energy through the marking module contained in the planning module; S3: Acquire monitoring parameter data through the monitoring module, the energy storage device monitoring module, the inverter monitoring module, the energy management system monitoring module and the grid connection monitoring module contained in the monitoring module; S4: The data processing module contained in the analysis module collects and processes the data of each monitored eucalyptus tree obtained by the monitoring module; S5: receiving the monitoring parameter data processed by the data processing module through the objective factor fusion module contained in the analysis module, and collecting the objective factor parameters within the past analysis time threshold; S6: The objective factor fusion module generates an impact threshold value based on the impact value of the objective factor parameter on the photovoltaic system, and fuses it with each monitoring parameter data to obtain the data index of each monitoring parameter; S7: comparing each monitoring parameter data indicator with the standard monitoring parameter data through a comparison module contained in the analysis module; S8.1.1: If the compared monitoring parameter data is within the floating threshold, the optimization module will not be executed; S8.2.1: If the compared monitoring parameter data is not within the floating threshold, the non-compliant monitoring parameter data is transmitted to the optimization module; S8.2.2: Retrieve abnormal parameter data from the monitoring parameter data through the optimization module and generate an optimization plan; S8.2.3: The optimization plan generated by the optimization module is communicated to the decision terminal through the interaction module.

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