A microgrid power supply system based on distributed energy storage of wind, light, diesel and battery at the team level

Abstract

The present invention discloses a microgrid power supply system based on wind-solar-diesel-storage unit-level energy storage, belonging to the technical field of intelligent microgrids. The system analyzes power generation data and meteorological data, establishes an LSTM model to predict wind power generation and photovoltaic power generation, calculates the wear degree of power generation equipment according to the prediction results, and establishes an equipment efficiency analysis model to fit the relationship curve among the wear degree of power generation equipment, the number of maintenance times and the power generation efficiency loss value, calculates the power generation efficiency loss value of the current power generation equipment, formulates an effective power generation equipment maintenance evaluation system, enabling users to intuitively evaluate the wear degree of the current power generation equipment; judges the power generation equipment maintenance according to future meteorological data and the power generation efficiency loss value of the current power generation equipment, avoiding unnecessary resource waste. At the same time, it reduces the operation and maintenance management cost of power generation equipment and improves the power generation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent microgrids, and specifically to a microgrid power supply system based on wind-solar-diesel-battery energy storage at the detachment level. Background Technique

[0002] A microgrid power supply system based on wind-solar-diesel-battery energy storage at the detachment level is a distributed energy system integrating wind power generation, solar photovoltaic power generation, diesel generators, and energy storage devices; it can operate in parallel with the external power grid or independently, greatly improving the flexibility and reliability of energy supply; in such a system, wind power generation and solar photovoltaic power generation are two main renewable energy power generation methods. Wind power generation uses wind turbines to convert wind energy into electrical energy, while solar photovoltaic power generation converts solar energy into electrical energy through solar photovoltaic panels. However, these two power generation methods are greatly affected by weather conditions; additional power is provided by diesel generators when wind energy and solar energy are insufficient to meet the demand, ensuring the continuous operation of the system.

[0003] When power generation equipment such as wind turbines, solar photovoltaic panels, and diesel generators are in operation, an increase in the service life will cause wear and tear on the equipment itself, resulting in a decrease in power generation efficiency; adopting a regular maintenance method can effectively extend the stability of the equipment, but frequent maintenance will lead to waste of resources, and an overly long maintenance cycle may cause equipment failures; in the prior art, it is difficult to formulate an effective maintenance evaluation system for power generation equipment based on existing data, resulting in an increase in the operation and maintenance costs and wear degree of the equipment, causing unnecessary waste of resources. Summary of the Invention

[0004] The purpose of the present invention is to provide a microgrid power supply system based on wind-solar-diesel-battery energy storage at the detachment level to solve the problems raised in the above background technique.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A microgrid power supply system based on wind-solar-diesel-battery energy storage at the detachment level, the system includes a power generation equipment management module, a database, a model analysis and prediction module, a detachment-level energy storage management module, an intelligent monitoring module, an energy-saving analysis and evaluation module, and a visualization display module;

[0006] The power generation equipment management module is used to control the power generation of power generation equipment, collect power generation data and meteorological data during the operation of the power generation equipment; send the power generation data and meteorological data to the database; send the meteorological data to the model analysis and prediction module; send the power generation data to the intelligent monitoring module and the detachment-level energy storage management module; the power generation equipment includes wind turbines, solar photovoltaic panels, and diesel generators; the power generation data includes wind power generation, photovoltaic power generation, and diesel power generation;

[0007] The database is used to store the power generation data and meteorological data sent by the power generation equipment management module as historical data;

[0008] The model analysis and prediction module is used to analyze the historical data in the database, establish an LSTM model, predict the wind power generation and photovoltaic power generation, and predict the diesel power generation according to the rated power of the diesel generator; send the predicted power generation data to the intelligent monitoring module;

[0009] The sub-unit level energy storage management module is used to control the charging and discharging process of the energy storage device according to the power generation data sent by the power generation equipment management module, balance the power supply and demand of electricity, and control the power generation of the power generation equipment in the power generation equipment management module;

[0010] The intelligent monitoring module is used to calculate the wear degree of the power generation equipment according to the historical power generation data in the database and the predicted power generation data in the model analysis and prediction module; establish an equipment efficiency analysis model, fit the relationship curve between the wear degree of the power generation equipment, the number of maintenance times and the power generation efficiency loss value, and determine the current wear degree of the power generation equipment according to the power generation data sent by the power generation equipment management module, and predict the power generation efficiency loss value of the current power generation equipment; send the power generation efficiency loss values of the current wind turbine generator and solar photovoltaic panel to the energy conservation analysis and evaluation module, and send the power generation efficiency loss value of the current power generation equipment to the visualization display module;

[0011] The energy conservation analysis and evaluation module is used to predict the future loss of power generation according to the power generation loss alarm threshold, future meteorological data and the power generation efficiency loss values of the current wind turbine generator and solar photovoltaic panel sent by the energy conservation analysis and evaluation module, and judge whether power generation equipment maintenance is required; if so, send a maintenance signal to the visualization display module; if not, continue to judge;

[0012] The visualization display module is used to digitally display the predicted power generation efficiency loss value of the current power generation equipment in the intelligent monitoring module; among them, when receiving the maintenance signal sent by the energy conservation analysis and evaluation module, send the power generation equipment maintenance information to the user.

[0013] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: By analyzing power generation data and meteorological data, an LSTM model is established to predict wind power generation and photovoltaic power generation. According to the prediction results, the wear degree of power generation equipment is calculated, and an equipment efficiency analysis model is established to calculate the power generation efficiency loss value of the current power generation equipment. An effective power generation equipment maintenance evaluation system is formulated, enabling users to intuitively evaluate the wear degree of the current power generation equipment; According to future meteorological data and the power generation efficiency loss value of the current power generation equipment, the maintenance of power generation equipment is judged, avoiding unnecessary resource waste. At the same time, the operation and maintenance management cost of power generation equipment is reduced, and the power generation efficiency is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a schematic structural diagram of a microgrid power supply system based on a wind-solar-diesel storage unit-level energy storage of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0016] Please refer to Figure 1 , the present invention provides a technical solution:

[0017] Please refer to Figure 1 , in this embodiment: A microgrid power supply system based on a wind-solar-diesel storage unit-level energy storage is provided. The system includes a power generation equipment management module, a database, a model analysis and prediction module, a unit-level energy storage management module, an intelligent monitoring module, an energy-saving analysis and evaluation module, and a visualization display module;

[0018] The power generation equipment management module is used to control the power generation of power generation equipment and collect power generation data and meteorological data during the operation of the power generation equipment; send the power generation data and meteorological data to the database; send the meteorological data to the model analysis and prediction module; send the power generation data to the intelligent monitoring module and the unit-level energy storage management module; the power generation equipment includes a wind turbine generator, a solar photovoltaic panel, and a diesel generator; the power generation data includes wind power generation, photovoltaic power generation, and diesel power generation;

[0019] The database is used to store the power generation data and meteorological data sent by the power generation equipment management module as historical data;

[0020] The model analysis and prediction module is used to analyze the historical data in the database, establish an LSTM model, predict the wind power generation and photovoltaic power generation, and predict the diesel power generation according to the rated power of the diesel generator; and send the predicted power generation data to the intelligent monitoring module;

[0021] The sub - unit - level energy storage management module is used to control the charging and discharging process of the energy storage device according to the power generation data sent by the power generation equipment management module, balance the power supply and demand, and control the power generation of the power generation equipment in the power generation equipment management module;

[0022] The intelligent monitoring module is used to calculate the wear degree of the power generation equipment according to the historical power generation data in the database and the predicted power generation data in the model analysis and prediction module; establish an equipment efficiency analysis model, fit the relationship curve among the wear degree of the power generation equipment, the number of maintenance times and the power generation efficiency loss value, and determine the current wear degree of the power generation equipment and predict the power generation efficiency loss value of the current power generation equipment according to the power generation data sent by the power generation equipment management module; send the power generation efficiency loss values of the current wind turbine generator and solar photovoltaic panel to the energy - saving analysis and evaluation module, and send the power generation efficiency loss value of the current power generation equipment to the visualization display module;

[0023] The energy - saving analysis and evaluation module is used to predict the future loss of power generation according to the power generation loss alarm threshold, future meteorological data and the power generation efficiency loss values of the current wind turbine generator and solar photovoltaic panel sent by the energy - saving analysis and evaluation module, and judge whether power generation equipment maintenance is required; if so, send a maintenance signal to the visualization display module; if not, continue to judge;

[0024] The visualization display module is used to digitally display the predicted power generation efficiency loss value of the current power generation equipment in the intelligent monitoring module; among them, when receiving the maintenance signal sent by the energy - saving analysis and evaluation module, it sends the power generation equipment maintenance information to the user.

[0025] In this embodiment, the database is a cloud database, which stores not only the historical data generated by the micro - grid power system itself, but also the historical data of other micro - grid power systems. When establishing the LSTM model based on historical data, the historical data for analysis includes the historical data of other micro - grid power systems; while when establishing the equipment efficiency analysis model based on historical data, the historical data for analysis only includes the historical data generated by this micro - grid power system itself.

[0026] Furthermore, the power generation equipment management module includes a wind power generation management unit, a photovoltaic power generation management unit and a diesel power generation management unit;

[0027] The wind power generation management unit is used to convert wind energy into electrical energy through a wind turbine generator and determine the wind power generation;

[0028] The photovoltaic power generation management unit is used to convert solar energy into electrical energy through solar photovoltaic panels and determine the photovoltaic power generation amount;

[0029] The diesel power generation management unit is used to convert mechanical energy into electrical energy through a diesel generator and determine the diesel power generation amount.

[0030] Further, the model analysis and prediction module includes a model management unit, a wind power generation prediction unit, a photovoltaic power generation prediction unit, and a diesel power generation prediction unit;

[0031] The model management unit is used to establish an LSTM model, train the LSTM model based on the historical data generated by the power generation equipment in good maintenance condition, so that the LSTM model can predict the wind power generation amount and the photovoltaic power generation amount;

[0032] Among them, according to the duration since the last maintenance of the power generation equipment, the working state of the power generation equipment is divided into a good maintenance state and a worn state; determine the wear cycle duration T of the power generation equipment. When the duration since the last maintenance of the power generation equipment is less than the wear cycle duration T, it is in a good maintenance state, and when it is greater than the wear cycle duration T, it is in a worn state; the good maintenance state means that the wear of the power generation equipment has no impact on the power generation amount; the worn state means that the wear of the power generation equipment has an impact on the power generation amount; after the power generation equipment is maintained, record the maintenance times of the power generation equipment;

[0033] The wind power generation prediction unit is used to input the collected meteorological data into the LSTM model to predict the wind power generation amount;

[0034] The photovoltaic power generation prediction unit is used to input the collected meteorological data into the LSTM model to predict the photovoltaic power generation amount;

[0035] The diesel power generation prediction unit is used to predict the diesel power generation amount according to the rated power of the diesel generator.

[0036] It should be noted that through the wind power generation prediction unit, the photovoltaic power generation prediction unit, and the diesel power generation prediction unit, the predicted wind power generation amount the predicted photovoltaic power generation amount and the predicted diesel power generation amount

[0037] It should be noted that the meteorological data represents environmental parameters such as the wind speed, light intensity, air pressure, radiation amount, temperature, and relative air humidity around the power generation equipment that affect the wind power generation amount and the photovoltaic power generation amount.

[0038] It should be noted that by analyzing the historical data generated by power generation equipment in good maintenance condition, the LSTM model can more accurately predict the power generation of power generation equipment in normal working condition, improving the accuracy of data analysis. Among them, the shorter the wear cycle duration T, the more accurate the prediction result of the trained LSTM model. In this implementation, the wear cycle duration of wind turbines and solar photovoltaic panels is 15 days, and the wear cycle duration of diesel generators is 72 hours.

[0039] It should be noted that based on the historical data generated by power generation equipment in good maintenance condition, the method for training the LSTM model and predicting wind power generation and photovoltaic power generation respectively is as follows: Obtain historical power generation data and historical meteorological data under the same time series, select model features and divide them into a training set and a validation set, use the training data set to train the LSTM model, optimize the model parameters through the backpropagation algorithm, and use the training set to verify the performance of the LSTM model, so that the LSTM model can predict wind power generation and photovoltaic power generation. Among them, in this implementation, the surrounding wind speed, air pressure, temperature, relative air humidity in historical meteorological data and wind power generation in historical power generation data are used as model features for predicting wind power generation; the surrounding light intensity, radiation amount, temperature, relative air humidity in historical meteorological data and photovoltaic power generation in historical power generation data are used as model features for predicting photovoltaic power generation.

[0040] Furthermore, the sub - unit - level energy storage management module includes a supply - demand management unit and an energy storage management unit;

[0041] The supply - demand management unit is used to connect with the power - consuming equipment at the supply - demand end to determine the required power consumption at the supply - demand end;

[0042] The energy storage management unit is used to store the power of the power generation equipment management module, and control the charging and discharging process of the energy storage device according to the power generation data in the power generation equipment management module and the required power consumption at the supply - demand end determined by the supply - demand management unit to balance the power supply and demand.

[0043] In this embodiment, determine the wind power generation X 1 、photovoltaic power generation X 2 and the required power consumption W at the supply - demand end; when X 1 +X 2 ≥W, control the wind power generation management unit and the wind power generation management unit to supply power to the supply - demand end, and control the remaining power to charge the energy storage device; when X 1 +X 2 <W, control the wind power generation management unit, the wind power generation management unit and the energy storage device to supply power to the supply - demand end; when X 1 +X 2When <W and the power of the energy storage device is insufficient, the diesel generator is started at this time, and the wind power generation management unit, the wind power generation management unit, and the diesel power generation management unit are controlled to supply power to the supply and demand end.

[0044] Further, the intelligent monitoring module includes a wear degree calculation unit, a device efficiency analysis unit, and a device efficiency calculation unit;

[0045] The wear degree calculation unit calculates the wear degree of the power generation equipment according to the historical power generation data in the database and the predicted power generation data in the model analysis prediction module at the corresponding time stamp, and sends the calculation result to the device efficiency analysis unit; among them, according to the historical power generation data, the wind power generation at different time stamps t is determined respectively Photovoltaic power generation And diesel power generation According to the predicted power generation data, the predicted wind power generation at different time stamps t is determined respectively Predicted photovoltaic power generation And predicted diesel power generation Calculate the wear degree of the wind turbine generator, solar photovoltaic panel and diesel generator at different time stamps t respectively And

[0046]

[0047] Among them, t represents the time stamp; Represents the wear degree of the i-th power generation equipment at time t calculated; Represents the power generation of the i-th power generation equipment at time ε; Represents the predicted power generation of the i-th power generation equipment at time ε; i = 1, 2, 3; ε represents the integral variable of time; t 0 ≤ε≤t; t in the integral 0 The initial time represents the time stamp corresponding to after the power generation equipment is maintained;

[0048] The device efficiency analysis unit establishes a device efficiency analysis model according to the wear degree of the power generation equipment calculated by the wear degree calculation unit; takes the wear degree S and the maintenance times M of the power generation equipment as independent variables, and the power generation efficiency loss value As the dependent variable, a relationship curve about S, M and Is obtained:

[0049]

[0050] Among them, X t Represents the power generation of the power generation equipment at time t; Y t Represents the predicted power generation of the power generation equipment at time t; S tRepresents the wear degree of the power generation equipment at time t; ΔS j Represents the wear degree of the power generation equipment within the jth maintenance cycle; M t Represents the number of maintenance times of the power generation equipment at time t; h represents the wear recovery value after the power generation equipment is maintained; β 1 and β 2 Both represent the attenuation constant;

[0051] Among them, according to the historical power generation data, the predicted power generation data at the corresponding timestamp, and the calculated wear degree of the power generation equipment, h and β are determined 1 and β 2 values;

[0052] It should be noted that the maintenance cycle refers to the cycle duration experienced by the power generation equipment from the current maintenance to the next maintenance; the first, second, and third types of power generation equipment refer to wind turbine generators, solar photovoltaic panels, and diesel generators respectively; by establishing an equipment efficiency analysis model, a relationship curve between the wear degree, the number of maintenance times, and the power generation efficiency loss value of the power generation equipment is fitted; the wear degrees corresponding to the wind turbine generator, solar photovoltaic panel, and diesel generator are respectively and As the independent variable S t , the corresponding number of maintenance times and As the independent variable M t , according to the wind power generation photovoltaic power generation diesel power generation predicted wind power generation predicted photovoltaic power generation and predicted diesel power generation respectively determine the power generation efficiency loss values of the wind turbine generator, solar photovoltaic panel, and diesel generator and and use them as the dependent variable Among them, according to the timestamps corresponding to the maintenance cycles of the power generation equipment, the and in the wind turbine generator, solar photovoltaic panel, and diesel generator are respectively determined; these data are used as training data and substituted into the established equipment efficiency analysis model, and finally the fitted parameters are obtained to determine the values of h, β 1 and β 2 values; in this implementation, the wear recovery value h corresponding to each maintenance of the power generation equipment is fixed.

[0053] The device efficiency calculation unit is used to determine the wear degree and maintenance times of the current power generation device, and predict the power generation efficiency loss value of the current power generation device according to the device efficiency analysis model established in the device efficiency analysis unit. According to the calculation formula:

[0054]

[0055] t x represents the current timestamp; represents the wear degree of the power generation device at time t x ; represents the maintenance times of the power generation device at time t x ; represents the power generation efficiency loss value of the power generation device at time t x .

[0056] Furthermore, the energy-saving analysis and evaluation module includes a network meteorological data acquisition unit, a power loss prediction unit, and an intelligent judgment and control unit;

[0057] The network meteorological data acquisition unit is used to obtain future meteorological data through the Internet;

[0058] The power loss prediction unit is used to predict the future wind power generation and photovoltaic power generation according to the future meteorological data obtained by the network meteorological data acquisition unit through the LSTM model established in the model management unit, and predict the future power loss X Fu according to the calculation formula:

[0059]

[0060] where, represents the power generation efficiency loss value of the wind turbine at time t x ; represents the power generation efficiency loss value of the solar photovoltaic panel at time t x ; and send the predicted future power loss X Fu to the intelligent judgment and control unit;

[0061] The intelligent judgment and control unit is used to determine the power generation loss alarm threshold X max , compare X max with X Fu to judge whether power generation equipment maintenance is required; when X Fu <X max , power generation equipment maintenance is not required at this time, and continue to judge; when X Fu ≥X maxWhen it is time to perform maintenance on the power generation equipment, a maintenance signal is sent to the visual display module.

[0062] It should be noted that the power generation loss alarm threshold represents the allowable power generation loss of the power generation equipment due to wear under future meteorological data; the future meteorological data represents the meteorological data of the microgrid power system within the next day; by combining with the future meteorological data, the power generation loss within the next day is predicted. When the power generation loss is excessive, the maintenance of the power generation equipment is carried out in advance, thereby reducing the operation and maintenance management cost of the power generation equipment and improving the power generation efficiency.

[0063] In this embodiment:

[0064] When maintenance of the power generation equipment is required, the user combines the future meteorological data with the power generation efficiency loss values of the current wind turbine, solar photovoltaic panel, and diesel generator displayed in the visual display module, and according to and determines whether the future power generation loss is wind power generation or photovoltaic power generation, so as to perform selective maintenance on the power generation equipment; for example, when is too large, the user controls the wind turbine to stop working through the wind power generation management unit and performs maintenance on the wind turbine. During the maintenance process, other units work normally.

[0065] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A microgrid power supply system based on wind, solar, diesel and storage team-level energy storage, characterized by: The system includes power generation equipment management module, database, model analysis and prediction module, squadron-level energy storage management module, intelligent monitoring module, energy-saving analysis and evaluation module and visualization display module; The power generation equipment management module is used to control the power generation of the power generation equipment and collect the power generation data and meteorological data during the operation of the power generation equipment; send the power generation data and meteorological data to the database; send the meteorological data to the model analysis and prediction module; send the power generation data to the intelligent monitoring module and the squadron-level energy storage management module; the power generation equipment includes wind turbines, solar photovoltaic panels and diesel generators; the power generation data includes wind power generation, photovoltaic power generation and diesel power generation; The database is used to store the power generation data and meteorological data sent by the power generation equipment management module as historical data; The model analysis and prediction module is used to analyze the historical data in the database, establish an LSTM model, predict the wind power generation and photovoltaic power generation, and predict the diesel power generation according to the rated power of the diesel generator; send the predicted power generation data to the intelligent monitoring module; The squadron-level energy storage management module is used to control the charging and discharging process of the energy storage device, balance the supply and demand of electricity, and control the power generation of the power generation equipment in the power generation equipment management module according to the power generation data sent by the power generation equipment management module; The intelligent monitoring module is used to calculate the degree of wear of the power generation equipment based on the historical power generation data in the database and the power generation data predicted in the model analysis and prediction module; establish an equipment efficiency analysis model to fit the relationship curve between the degree of wear of the power generation equipment, the number of maintenance times and the power generation efficiency loss value, and determine the degree of wear of the current power generation equipment based on the power generation data sent by the power generation equipment management module, and predict the power generation efficiency loss value of the current power generation equipment; send the power generation efficiency loss value of the current wind turbine and solar photovoltaic panel to the energy-saving analysis and evaluation module, and send the power generation efficiency loss value of the current power generation equipment to the visualization display module; The energy-saving analysis and evaluation module is used to predict the future loss of power generation based on the power generation loss alarm threshold, future meteorological data and the power generation efficiency loss value of the current wind turbine generator set and solar photovoltaic panel sent by the energy-saving analysis and evaluation module, and determine whether power generation equipment maintenance is required; if necessary, send a maintenance signal to the visualization display module; If not, continue to judge; The visualization display module is used to digitally display the power generation efficiency loss value of the current power generation equipment predicted in the intelligent monitoring module; when a maintenance signal sent by the energy-saving analysis and evaluation module is received, the power generation equipment maintenance information is sent to the user.

2. A microgrid power supply system based on wind, solar, diesel and energy storage at the team level according to claim 1, characterized in that: The power generation equipment management module includes a wind power generation management unit, a photovoltaic power generation management unit and a diesel power generation management unit; The wind power generation management unit is used to convert wind energy into electrical energy through the wind turbine generator set and determine the wind power generation; The photovoltaic power generation management unit is used to convert solar energy into electrical energy through solar photovoltaic panels and determine the photovoltaic power generation; The diesel power generation management unit is used to convert mechanical energy into electrical energy through a diesel generator and determine the diesel power generation amount.

3. A microgrid power supply system based on wind, solar, diesel and energy storage at the team level according to claim 2, characterized in that: The model analysis and prediction module includes a model management unit, a wind power generation prediction unit, a photovoltaic power generation prediction unit and a diesel power generation prediction unit; The model management unit is used to establish an LSTM model, and train the LSTM model based on historical data generated by power generation equipment in a well-maintained state, so that the LSTM model can predict wind power generation and photovoltaic power generation; Among them, according to the time since the last maintenance of the power generation equipment, the working state of the power generation equipment is divided into a good maintenance state and a wear state; the wear cycle time T of the power generation equipment is determined, when the time since the last maintenance of the power generation equipment is less than the wear cycle time T, it is in a good maintenance state, and when it is greater than the wear cycle time T, it is in a wear state; the good maintenance state means that the wear of the power generation equipment has no effect on the power generation; the wear state means that the wear of the power generation equipment has an effect on the power generation; after the power generation equipment is maintained, the number of maintenance times of the power generation equipment is recorded; The wind power generation prediction unit is used to input the collected meteorological data into the LSTM model to predict the wind power generation; The photovoltaic power generation prediction unit is used to input the collected meteorological data into the LSTM model to predict the photovoltaic power generation; The diesel power generation prediction unit is used to predict the diesel power generation according to the rated power of the diesel generator.

4. A microgrid power supply system based on wind, solar, diesel and energy storage at the team level according to claim 2, characterized in that: The squadron-level energy storage management module includes a supply and demand management unit and an energy storage management unit; The supply and demand management unit is used to interconnect with the power consumption equipment on the supply and demand sides to determine the power consumption required by the supply and demand sides; The energy storage management unit is used to store the electricity of the power generation equipment management module, control the charging and discharging process of the energy storage device according to the power generation data in the power generation equipment management module and the power consumption required by the supply and demand side determined in the supply and demand side management unit, and balance the power supply and demand.

5. A microgrid power supply system based on wind, solar, diesel and energy storage at the team level according to claim 3, characterized in that: The intelligent monitoring module includes a wear degree calculation unit, an equipment efficiency analysis unit, and an equipment efficiency calculation unit; The wear degree calculation unit calculates the wear degree of the power generation equipment according to the historical power generation data in the database and the power generation data predicted in the model analysis and prediction module at the corresponding timestamp, and sends the calculation result to the equipment efficiency analysis unit; wherein, according to the historical power generation data, the wind power generation at different timestamps t is determined respectively. Photovoltaic power generation and diesel power generation According to the predicted power generation data, the predicted wind power generation at different timestamps t is determined respectively. Forecasted photovoltaic power generation and forecast diesel generation Calculate the wear degree of wind turbines, solar photovoltaic panels and diesel generators at different time stamps t and Wherein, t represents the timestamp; It represents the calculated wear degree of the i-th power generation equipment at time t; represents the power generation of the i-th power generation equipment at time ε; represents the predicted power generation of the i-th power generation equipment at time ε; i = 1, 2, 3; ε represents the integral variable at the time; t0≤ε≤t; the initial time t0 in the integral represents the timestamp corresponding to the maintenance of the power generation equipment; The equipment efficiency analysis unit establishes an equipment efficiency analysis model according to the degree of wear of the power generation equipment calculated in the wear degree calculation unit; takes the degree of wear S and the number of maintenance times M of the power generation equipment as independent variables, and the power generation efficiency loss value As the dependent variable, we get the information about S, M and The relationship curve: Among them, X t represents the power generation of the power generation equipment at time t; Y t S represents the predicted power generation of the power generation equipment at time t; t Indicates the degree of wear of the power generation equipment at time t; ΔS j Indicates the degree of wear of the power generation equipment during the jth maintenance cycle; M t represents the number of maintenance times of the power generation equipment at time t; h represents the wear recovery value of the power generation equipment after maintenance; β1 and β2 both represent attenuation constants; Among them, the values ​​of h, β1 and β2 are determined according to the historical power generation data, the predicted power generation data at the corresponding timestamp, and the calculated degree of wear of the power generation equipment; The equipment efficiency calculation unit is used to determine the wear degree and maintenance times of the current power generation equipment, and predict the power generation efficiency loss value of the current power generation equipment according to the equipment efficiency analysis model established in the equipment efficiency analysis unit, according to the calculation formula: t x Indicates the current timestamp; Indicates that the power generation equipment is at t x The degree of wear and tear at the moment; Indicates that the power generation equipment is at t x The number of maintenance times at a time; Indicates that the power generation equipment is at t x The power generation efficiency loss value at the moment.

6. A microgrid power supply system based on wind, solar, diesel and energy storage at the team level according to claim 5, characterized in that: The energy-saving analysis and evaluation module includes a network meteorological data acquisition unit, a power consumption prediction unit and an intelligent judgment control unit; The network meteorological data acquisition unit is used to acquire future meteorological data through the Internet; The power loss prediction unit is used to predict the future wind power generation through the LSTM model established in the model management unit according to the future meteorological data obtained by the network meteorological data acquisition unit. and photovoltaic power generation And according to the power generation efficiency loss value of the current power generation equipment, predict the future loss of power generation X Fu , according to the calculation formula: in, Indicates that the wind turbine generator set is at t x The power generation efficiency loss value at the moment; The solar photovoltaic panel is x The power generation efficiency loss value at the moment; the predicted future loss power generation X Fu Send to the intelligent judgment control unit; The intelligent judgment control unit is used to determine the power generation loss alarm threshold value X max , X max With X Fu Compare and judge whether power generation equipment maintenance is needed; when X Fu <X max When X Fu ≥X max When the power generation equipment needs to be maintained, a maintenance signal is sent to the visualization display module.

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