Micro-grid power supply system based on wind-solar-diesel storage unit-level energy storage

Abstract

The invention discloses a micro-grid power supply system based on wind-solar-diesel storage unit-level energy storage, and belongs to the technical field of intelligent micro-grids. The system analyzes power generation data and meteorological data, establishes an LSTM model, predicts wind power generation capacity and photovoltaic power generation capacity, calculates the wear degree of power generation equipment according to a prediction result, establishes an equipment efficiency analysis model, and fits a relation curve among the wear degree, maintenance times and power generation efficiency loss values of the power generation equipment. The power generation efficiency loss value of the current power generation equipment is calculated, and an effective power generation equipment maintenance evaluation system is formulated, so that a user can intuitively evaluate the wear degree of the current power generation equipment; the maintenance of the power generation equipment is judged according to the future meteorological data and the power generation efficiency loss value of the current power generation equipment, so that unnecessary resource waste is avoided, the operation and maintenance management cost of the power generation equipment is reduced, and the power generation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart microgrids, and in particular to a microgrid power supply system based on wind, solar, diesel and energy storage at the team level. Background Art

[0002] The microgrid power supply system based on wind, solar, diesel and energy storage team-level energy storage is a distributed energy system that integrates wind power generation, solar photovoltaic power generation, diesel generators and energy storage equipment; it can be connected to the external power grid or operate independently, greatly improving the flexibility and reliability of energy supply; in this system, wind power generation and solar photovoltaic power generation are the 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, but these two power generation methods are greatly affected by weather conditions; diesel generators are used to provide additional electricity when wind and solar energy are insufficient to meet 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, the increase in the length of the use cycle will cause wear and tear on the equipment itself, resulting in reduced power generation efficiency; regular maintenance can effectively extend the stability of the equipment, but frequent maintenance will lead to waste of resources, and too long a maintenance cycle may cause equipment failure; in the prior art, it is difficult to formulate an effective power generation equipment maintenance evaluation system based on existing data, resulting in increased equipment operation and maintenance costs and wear and tear, 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 and storage team-level energy storage to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a microgrid power supply system based on wind, solar, diesel and storage squadron-level energy storage, the system comprising a power generation equipment management module, a database, a model analysis and prediction module, a squadron-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 the power generation equipment and collect the power generation data and meteorological data in the power generation equipment operation equation; 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 a wind turbine, a solar photovoltaic panel and a diesel generator; 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 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;

[0010] 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;

[0011] 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 judge whether power generation equipment maintenance is needed; if necessary, 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 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.

[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, the degree of wear of power generation equipment is calculated according to the prediction results, and an equipment efficiency analysis model is established to calculate the power generation efficiency loss value of the current power generation equipment, and an effective power generation equipment maintenance evaluation system is formulated, so that users can intuitively evaluate the degree of wear of the current power generation equipment; the maintenance of power generation equipment is judged according to future meteorological data and the power generation efficiency loss value of the current power generation equipment, thereby avoiding unnecessary waste of resources, and at the same time, reducing the operation and maintenance management costs of power generation equipment and improving power generation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a structural schematic diagram of a microgrid power supply system based on wind, solar, diesel and energy storage at the team level according to the present invention. DETAILED DESCRIPTION

[0015] 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.

[0016] See also Figure 1 , the present invention provides a technical solution:

[0017] See also Figure 1 , in this embodiment: a microgrid power supply system based on wind, solar, diesel and storage team-level energy storage is provided, the system includes a power generation equipment management module, a database, a model analysis and prediction module, a team-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 the power generation equipment and collect the power generation data and meteorological data in the power generation equipment operation equation; 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 a wind turbine, 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; send the predicted power generation data to the intelligent monitoring module;

[0021] 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;

[0022] 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;

[0023] 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 judge whether power generation equipment maintenance is needed; if necessary, 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 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.

[0025] In this embodiment, the database is a cloud database, which not only stores the historical data generated by the microgrid power system itself, but also stores the historical data of other microgrid power systems. When an LSTM model is established based on historical data, the analyzed historical data includes the historical data of other microgrid power systems; and when an equipment efficiency analysis model is established based on historical data, the analyzed historical data only includes the historical data generated by the microgrid power system itself.

[0026] Further, 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 the wind turbine generator set 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;

[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, 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;

[0032] 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;

[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;

[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;

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

[0036] It should be noted that the predicted wind power generation at different timestamps t is determined by the wind power generation prediction unit, the photovoltaic power generation prediction unit and the diesel power generation prediction unit. Forecasted photovoltaic power generation and forecast diesel generation

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

[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 the wind turbine generator and the solar photovoltaic panel is 15 days, and the wear cycle duration of the diesel generator 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 training sets and validation sets, 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 the historical meteorological data and the wind power generation in the historical power generation data are used as the model features for predicting wind power generation; the surrounding light intensity, radiation amount, temperature, relative air humidity in the historical meteorological data and the photovoltaic power generation in the historical power generation data are used as the 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 be connected to the supply - demand side electrical equipment and determine the electricity consumption required by the supply - demand side;

[0042] The energy storage management unit is used to store the electricity 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 electricity consumption required by the supply - demand side determined by the supply - demand management unit, so as to balance the power supply and demand.

[0043] In this embodiment, determine the wind power generation Z 1 , the photovoltaic power generation X 2 and the electricity consumption required by the supply - demand side W; 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 side, and control the remaining electricity 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 side; 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] Furthermore, 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 and 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; t0 ≤ ε ≤ t; the initial time t0 in the integral 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 in the wear degree calculation unit; uses 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, obtain the relationship curve about S, M, and :

[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 t Represents the wear degree of the power generation equipment at time t; ΔSj 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;

[0051] 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;

[0052] It should be noted that the maintenance cycle refers to the length of the cycle from the current maintenance of the power generation equipment to the next maintenance; the first, second and third power generation equipment refer to wind turbines, solar photovoltaic panels and diesel generators respectively; by establishing an equipment efficiency analysis model, a relationship curve between the degree of wear, maintenance times and power generation efficiency loss value of the power generation equipment is fitted; the degree of wear corresponding to the wind turbines, solar photovoltaic panels and diesel generators is calculated respectively. and As the independent variable S t , the corresponding maintenance times and As the independent variable M t , based on wind power generation Photovoltaic power generation Diesel power generation Forecasted wind power generation Forecasted photovoltaic power generation and forecast diesel generation Determine the power generation efficiency loss values ​​of wind turbines, solar photovoltaic panels and diesel generators respectively and and as the dependent variable Among them, according to the corresponding timestamps in the maintenance cycle of the power generation equipment, the wind turbine, solar photovoltaic panels and diesel generators are determined respectively. and These data are used as training data to establish the equipment efficiency analysis model, and finally the fitting parameters are obtained to determine the values ​​of h, β1 and β2; in this implementation, the wear recovery value h corresponding to each maintenance of the power generation equipment is fixed.

[0053] 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:

[0054]

[0055] 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 Maintenance times at all times; Indicates that the power generation equipment is at t x The power generation efficiency loss value at the moment.

[0056] Furthermore, 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;

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

[0058] 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:

[0059]

[0060] 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 power generation loss X Fu Send to the intelligent judgment control unit;

[0061] 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.

[0062] It should be noted that the power generation loss alarm threshold represents the amount of power generation that is allowed to be lost due to wear and tear of power generation equipment under future meteorological data; the future meteorological data represents the meteorological data of the microgrid power system in the next day; by combining with future meteorological data, the power generation loss in the next day is predicted, and when the power generation loss is too much, the power generation equipment is maintained in advance, thereby reducing the operation and maintenance management costs of the power generation equipment and improving the power generation efficiency.

[0063] In this embodiment:

[0064] When power generation equipment maintenance is required, users can use the current power generation efficiency loss values ​​of wind turbines, solar photovoltaic panels and diesel generators displayed in the visualization module, combined with future meteorological data, to determine the maintenance efficiency of the power generation equipment. and Determine whether the power generation lost in the future is wind power generation or photovoltaic power generation, so as to selectively maintain the power generation equipment; for example, when When it is too large, the user controls the wind turbine generator set to stop working through the wind power generation management unit and performs maintenance on the wind turbine generator set. During the maintenance process, other units work normally.

[0065] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in 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 in the power generation equipment operation equation; 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 a wind turbine, a solar photovoltaic panel and a diesel generator; 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 Where 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; j = 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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