Energy scheduling optimization system of self-adaptive multi-energy complementary micro-grid

Abstract

The invention relates to the technical field of micro-grid energy data processing, in particular to an adaptive multi-energy complementary micro-grid energy scheduling optimization system, which comprises a micro-grid power data acquisition module, a power generation equipment fault evaluation module, a micro-grid power scheduling platform and a micro-grid database, the micro-grid power data acquisition module is used for acquiring planned power generation data and actual power supply data of a micro-grid area, the power generation equipment fault assessment module is used for processing to obtain an abnormal operation risk assessment value of each generator equipment, and the micro-grid power dispatching platform is used for comprehensively analyzing to obtain a power load satisfaction assessment index. According to the energy dispatching optimization system for the self-adaptive multi-energy complementary micro-grid, the power supply and demand conditions of the micro-grid can be predicted more accurately, and a basis is provided for power dispatching. And the micro-grid can be managed more effectively, the power load is ensured to be satisfied, and the overall performance and economic benefit of the micro-grid are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrid energy data processing, and in particular to an energy dispatch optimization system for an adaptive multi-energy complementary microgrid. Background Art

[0002] In order to achieve clean, low-carbon and efficient energy supply, the construction of the global energy Internet has become a trend in global energy development. As the basic unit of the energy Internet, the energy dispatch optimization of microgrids is of great significance to the efficient operation of the entire energy Internet. At the same time, the development of technologies such as big data, cloud computing, and artificial intelligence provides technical support for the energy dispatch optimization of microgrids.

[0003] For example, the invention patent with publication number: CN117993271A is a microgrid day-ahead energy management method, storage medium and electronic device. The microgrid day-ahead energy management method includes: obtaining load data, photovoltaic data, time-of-use electricity price conditions and system parameters of each distributed power source obtained within a preset time period; establishing a microgrid power generation model; updating the inertia weight corresponding to each power generation unit in the microgrid power generation model; determining the fitness value of the particle; initializing the global optimal solution according to the size of the current fitness value, and taking the current fitness value as the individual optimal solution; updating the state of the particle, and determining the superior and subordinate members of the group to which the particle belongs; stopping the iteration in response to the number of iterations reaching the maximum number of iterations, or the final result of the iteration being less than the predetermined convergence accuracy.

[0004] For example, the invention patent with publication number: CN115809593A is an operation control method for an integrated energy system including a multi-energy storage device, which belongs to the field of microgrid energy management. The long short-term memory network is used to predict the wind and solar power output and the multi-energy demand of the load. The operation control is divided into two operation control scenarios based on the difference between energy output and energy demand. By formulating the scheduling sequence and scheduling strategy of electricity, heat, and hydrogen, in the case of the lack of electricity, heat, and hydrogen loads, they can be directly dispatched from the energy storage device.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it is found that the above technology has at least the following technical problems: Currently in multi-energy complementary microgrids, the integration between different energy systems is often insufficient, resulting in insufficient coordinated scheduling between different energy forms, which affects the overall efficiency of the scheduling system. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides an energy scheduling optimization system for an adaptive multi-energy complementary microgrid, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention provides an energy scheduling optimization system for an adaptive multi-energy complementary microgrid, including: a microgrid power data acquisition module, used to obtain planned power generation data and actual power supply data of the microgrid area, the planned power generation data includes planned solar power generation and planned wind power generation, and the actual power supply data includes the remaining power of the energy storage device and the operating data of each generator equipment.

[0008] The power generation equipment fault assessment module is used to obtain the abnormal operation risk assessment value of each generator equipment according to the operating data of each generator equipment through processing, perform fault assessment on the generator equipment according to the abnormal operation risk assessment value of each generator equipment, and record the number of faulty equipment.

[0009] The microgrid power dispatching platform is used to comprehensively analyze the remaining power of the energy storage system, the abnormal operation risk assessment value of each generator equipment and the number of faulty equipment to obtain the power load satisfaction assessment index, and determine whether the microgrid needs to call on the diesel engine based on the power load satisfaction assessment index.

[0010] As a further method, the operating data of each generator device includes: operating data of each wind generator device, operating data of each photovoltaic generator device and operating environment data within a preset monitoring period.

[0011] The operating data of each wind turbine device include the total operating time of the wind turbine device, the power generation of each wind turbine device within a preset monitoring period, the output power of each wind turbine device at each time monitoring point, the gear box temperature and vibration frequency, and the blade speed.

[0012] The operating data of each photovoltaic generator device include the total operating time of the photovoltaic generator device, the power generation of each photovoltaic generator device within a preset monitoring period, the output power of each photovoltaic generator device at each time monitoring point, and the voltage, current and temperature of each solar cell panel.

[0013] The operating environment data includes regional real-time wind speed and regional real-time solar radiation intensity.

[0014] As a further method, the abnormal operation risk assessment value of each generator equipment is obtained through processing based on the operating data of each generator equipment, including: extracting a reference wind speed, an allowable deviation wind speed, a reference solar radiation intensity and an allowable deviation solar radiation intensity from a microgrid database.

[0015] According to the real-time wind speed and the real-time solar radiation intensity, the characteristic values ​​of the impact of abnormal operation of wind turbine equipment and the characteristic values ​​of the impact of abnormal operation of photovoltaic generator equipment are obtained through processing.

[0016] According to the characteristic values ​​of the impact of abnormal operation of wind turbine equipment and the characteristic values ​​of the impact of abnormal operation of photovoltaic generator equipment, the characteristic factors of the impact of abnormal operation of wind turbine equipment and the characteristic factors of the impact of abnormal operation of photovoltaic generator equipment are matched to obtain.

[0017] Based on the operating data of each generator equipment, the characteristic factors affecting the abnormal operation of wind generator equipment and the characteristic factors affecting the abnormal operation of photovoltaic generator equipment, a comprehensive analysis is performed to obtain the abnormal operation risk assessment value of each photovoltaic generator equipment and the abnormal operation risk assessment value of each wind generator equipment.

[0018] The abnormal operation risk assessment value of each photovoltaic generator device and the abnormal operation risk assessment value of each wind turbine generator device are jointly marked as the abnormal operation risk assessment value of each generator device. The abnormal operation risk assessment value of each generator device is used to quantitatively assess the degree of abnormal operation risk of each generator device in the microgrid area, and provide a basis for fault assessment of the generator equipment.

[0019] As a further method, the comprehensive analysis obtains the abnormal operation risk assessment value of each photovoltaic generator equipment and the abnormal operation risk assessment value of each wind turbine equipment, including: extracting from the microgrid database the rated output power of the wind turbine equipment, the reference standard temperature of the gearbox, the rated vibration frequency of the gearbox, the reference standard speed of the blade, the allowable deviation power generation of the wind turbine equipment, the allowable deviation output power of the wind turbine equipment, the allowable deviation temperature of the gearbox, the allowable deviation vibration frequency of the gearbox and the allowable deviation speed of the blade.

[0020] Based on the operating data of each wind turbine equipment, the planned wind power generation and the characteristic factors affecting the abnormal operation of wind turbine equipment, a comprehensive analysis is conducted to obtain the abnormal operation risk assessment value of each wind turbine equipment.

[0021] The rated output power of the photovoltaic generator equipment, the rated voltage of the solar panel, the rated current of the solar panel and the reference standard temperature of the solar panel, the allowable deviation power generation of the photovoltaic generator equipment, the allowable deviation output power of the photovoltaic generator equipment, the allowable deviation voltage of the solar panel, the allowable deviation current of the solar panel and the allowable deviation temperature of the solar panel are extracted from the microgrid database.

[0022] Based on the operating data of each photovoltaic generator equipment, the planned solar power generation and the characteristic factors affecting the abnormal operation of photovoltaic generator equipment, a comprehensive analysis is conducted to obtain the abnormal operation risk assessment value of each photovoltaic generator equipment.

[0023] As a further method, the generator equipment is fault evaluated and the number of faulty equipment is recorded. The specific process is: extracting the first initial threshold value of the generator equipment operation abnormality risk assessment and the second initial threshold value of the generator equipment operation abnormality risk assessment from the microgrid database, and processing to obtain the first threshold value of the generator equipment operation abnormality risk assessment and the second threshold value of the generator equipment operation abnormality risk assessment.

[0024] The abnormal operation risk assessment value of each wind turbine equipment is compared with the first threshold value of the abnormal operation risk assessment of the generator equipment. If the abnormal operation risk assessment value of a wind turbine equipment is less than the first threshold value of the abnormal operation risk assessment of the generator equipment, the fault assessment of the wind turbine equipment is qualified, and the wind turbine equipment is marked as a normal device. If the abnormal operation risk assessment value of a wind turbine equipment is greater than or equal to the first threshold value of the abnormal operation risk assessment of the generator equipment, the fault assessment of the wind turbine equipment is unqualified, and the wind turbine equipment is marked as a faulty device.

[0025] The abnormal operation risk assessment value of each photovoltaic generator device is compared with the second threshold value of the abnormal operation risk assessment of the generator device. If the abnormal operation risk assessment value of a photovoltaic generator device is less than the second threshold value of the abnormal operation risk assessment of the generator device, the fault assessment of the photovoltaic generator device is qualified, and the photovoltaic generator device is marked as a normal device. If the abnormal operation risk assessment value of a photovoltaic generator device is greater than or equal to the second threshold value of the abnormal operation risk assessment of the generator device, the fault assessment of the photovoltaic generator device is unqualified, and the photovoltaic generator device is marked as a faulty device.

[0026] Count the number of normal devices and faulty devices.

[0027] As a further method, the comprehensive analysis obtains that the power load meets the evaluation index. The specific analysis process is: according to the abnormal operation risk assessment value of each generator equipment, the abnormal operation risk assessment value of each normal photovoltaic generator equipment and the abnormal operation risk assessment value of each normal wind generator equipment are obtained.

[0028] The critical remaining power and number of critical fault devices of the energy storage system are extracted from the microgrid database.

[0029] According to the remaining power of the energy storage system, the abnormal operation risk assessment value of each normal photovoltaic generator equipment, the abnormal operation risk assessment value of each normal wind turbine equipment and the number of faulty equipment, a comprehensive analysis is conducted to obtain the power load satisfaction assessment index, which is used to quantitatively assess the level of renewable resource energy supply in the microgrid area and provide a basis for determining whether the microgrid needs to call on diesel engines.

[0030] As a further method, the determination of whether the microgrid needs to call a diesel engine is specifically carried out as follows: extracting a power load satisfaction evaluation index threshold from a microgrid database, comparing the power load satisfaction evaluation index with the power load satisfaction evaluation index threshold; if the power load satisfaction evaluation index is higher than or equal to the power load satisfaction evaluation index threshold, then it is determined that there is no need to call the diesel engine; if the power load satisfaction evaluation index is lower than the power load satisfaction evaluation index threshold, then it is determined that the diesel engine needs to be called, and the diesel engine is called to supply power according to the power load satisfaction evaluation index.

[0031] As a further method, the abnormal operation impact characteristic value of wind turbine equipment is a quantitative evaluation data obtained by comprehensive analysis of the regional real-time wind speed, reference standard wind speed and allowable deviation wind speed, which is used to quantitatively evaluate the impact of regional wind speed on the abnormal operation of regional wind turbine equipment, and provide a basis for matching the abnormal operation impact characteristic factors of wind turbine equipment.

[0032] The photovoltaic generator equipment operation abnormality impact characteristic value is a quantitative evaluation data obtained by comprehensively analyzing the regional real-time solar radiation intensity, the reference standard solar radiation intensity and the allowable deviation solar radiation intensity, and is used to quantitatively evaluate the impact of the regional solar radiation intensity on the regional photovoltaic generator equipment operation abnormality, and provide a basis for matching the photovoltaic generator equipment operation abnormality impact characteristic factor.

[0033] As a further method, the diesel engine power supply is called according to the power load satisfying evaluation index. The specific process is: subtract the power load satisfying evaluation index from the power load satisfying evaluation index threshold to obtain the evaluation index difference, and obtain the diesel engine power supply according to the evaluation index difference.

[0034] A mapping set between the evaluation index difference and the power supplied by the diesel engine is extracted from the microgrid database, the real-time evaluation index difference is input, the corresponding power supplied by the diesel engine is obtained according to the mapping set, and the diesel engine is called to supply power.

[0035] As a further method, the power load meets the evaluation index, and the specific numerical expression is: ; In the formula, Indicates that the power load meets the evaluation index, represents the abnormal risk assessment value of the nth normal photovoltaic generator equipment operation, represents the abnormal operation risk assessment value of the zth normal wind turbine equipment, z represents the number of each normal wind turbine equipment, , j represents the total number of normal wind turbine generators, n represents the number of normal photovoltaic generators, , m represents the total number of normal photovoltaic generator equipment, Indicates the remaining power of the energy storage system. Indicates the number of faulty devices. Indicates the critical remaining power of the energy storage system. Indicates the number of critical failure devices, Indicates that the power load corresponding to the preset remaining power of the energy storage system satisfies the correction factor, Indicates that the power load corresponding to the preset number of faulty devices meets the correction factor, It indicates that the power load corresponding to the preset normal wind turbine equipment operation abnormal risk assessment value satisfies the correction factor, It indicates that the power load corresponding to the preset normal photovoltaic generator equipment operation abnormal risk assessment value satisfies the correction factor.

[0036] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides an energy dispatch optimization system for an adaptive multi-energy complementary microgrid, which comprehensively considers the remaining power of the energy storage system, the abnormal risk assessment value of normal photovoltaic and normal wind turbine equipment operation, and the number of faulty equipment. It can more accurately predict the power supply and demand of the microgrid and provide a basis for power dispatch. It can also more effectively manage the microgrid to ensure that the power load is met and improve the overall performance and economic benefits of the microgrid.

[0037] (2) The present invention can achieve accurate assessment and early warning of wind turbine failures by comprehensively monitoring and analyzing the power generation, output power, gearbox temperature and vibration frequency, and blade speed of wind turbine equipment, and combining the impact of regional wind speed analysis on wind turbine equipment, and provide strong support for equipment maintenance and optimization. By maintaining the equipment, equipment damage and downtime can be avoided, which is conducive to improving the reliability of the wind power generation system.

[0038] (3) The present invention can achieve accurate evaluation and early warning of photovoltaic generator failures by comprehensively monitoring and analyzing the power generation, output power, solar cell panel voltage, current and temperature of photovoltaic generator equipment, and analyzing the impact of regional solar radiation intensity on photovoltaic generator equipment. By timely discovering and processing potential failures of photovoltaic generator equipment, system shutdown or damage can be avoided, which is beneficial to improving the reliability and working continuity of the photovoltaic power generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0040] Figure 1 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0042] Reference Figure 1 As shown, the present invention provides an energy scheduling optimization system for an adaptive multi-energy complementary microgrid, including: a microgrid power data acquisition module, used to obtain planned power generation data and actual power supply data of the microgrid area, the planned power generation data includes planned solar power generation and planned wind power generation, and the actual power supply data includes the remaining power of the energy storage device and the operation data of each generator equipment.

[0043] The operating data of each generator device includes: operating data of each wind generator device, operating data of each photovoltaic generator device and operating environment data within a preset monitoring period.

[0044] The operating data of each wind turbine device include the total operating time of the wind turbine device, the power generation of each wind turbine device within a preset monitoring period, the output power of each wind turbine device at each time monitoring point, the gear box temperature and vibration frequency, and the blade speed.

[0045] It is necessary to explain that the power generation can be measured and recorded by the electric energy meter installed at the output end of the wind turbine. The output power can be monitored in real time by the power sensor installed on the output side of the generator. The operating temperature can be monitored by the sensor installed on the gearbox. The vibration data can be monitored by the vibration sensor installed on the gearbox of the wind turbine. The blade speed can be measured by the speed sensor installed on the blade.

[0046] The operating data of each photovoltaic generator device include the total operating time of the photovoltaic generator device, the power generation of each photovoltaic generator device within a preset monitoring period, the output power of each photovoltaic generator device at each time monitoring point, and the voltage, current and temperature of each solar cell panel.

[0047] It is necessary to explain that the power generated by the photovoltaic generator can be recorded by the data acquisition system. The output power can be monitored and recorded in real time by using the photovoltaic inverter. The voltage and current of each panel can be measured by the string monitor installed in the photovoltaic array. The operating temperature of the panel can be monitored by the temperature sensor installed on the back of the solar panel.

[0048] The operating environment data includes regional real-time wind speed and regional real-time solar radiation intensity.

[0049] It should be explained that the real-time wind speed can be measured by using an anemometer installed on the tower of a wind turbine, and the solar radiation intensity can be measured by using a radiometer installed in a photovoltaic power plant.

[0050] The power generation equipment fault assessment module is used to obtain the abnormal operation risk assessment value of each generator equipment according to the operating data of each generator equipment through processing, perform fault assessment on the generator equipment according to the abnormal operation risk assessment value of each generator equipment, and record the number of faulty equipment.

[0051] Specifically, according to the operation data of each generator equipment, the abnormal operation risk assessment value of each generator equipment is obtained after processing, including: extracting the reference wind speed, the allowable deviation wind speed, the reference solar radiation intensity and the allowable deviation solar radiation intensity from the microgrid database.

[0052] According to the real-time wind speed and the real-time solar radiation intensity, the characteristic values ​​of the impact of abnormal operation of wind turbine equipment and the characteristic values ​​of the impact of abnormal operation of photovoltaic generator equipment are obtained through processing.

[0053] In a specific embodiment, the numerical expression of the characteristic value of the abnormal operation of the wind turbine equipment is: ; In the formula, represents the characteristic value of abnormal operation of wind turbine equipment, t represents the time variable, , Indicates the current time point. Indicates the monitoring start time point, represents the wind speed in the area at time t, Indicates the reference standard wind speed, Indicates the allowable deviation wind speed.

[0054] It should be explained that the greater the absolute difference between the real-time wind speed and the reference standard wind speed, the greater the corresponding wind turbine equipment operation abnormality impact characteristic value, indicating that the wind turbine equipment operation abnormality is more affected by wind force.

[0055] In a specific embodiment, the numerical expression of the photovoltaic generator equipment operation abnormality impact characteristic value is: ; In the formula, Indicates the abnormal operation of photovoltaic generator equipment affecting the characteristic value. represents the solar radiation intensity of the region at time t, Indicates the reference standard solar radiation intensity, Indicates the allowable deviation of solar radiation intensity.

[0056] It needs to be explained that the greater the absolute difference between the real-time solar radiation intensity and the reference standard solar radiation intensity, the greater the corresponding photovoltaic generator equipment operation abnormality impact characteristic value, which means that the photovoltaic generator equipment operation abnormality is more affected by the solar radiation intensity.

[0057] It should be explained that the characteristic value of the impact of abnormal operation of wind turbine equipment is a quantitative evaluation data obtained by comprehensive analysis of the regional real-time wind speed, reference standard wind speed and allowable deviation wind speed. It is used to quantitatively evaluate the impact of regional wind speed on the abnormal operation of regional wind turbine equipment, and provide a basis for matching the characteristic factors affecting the abnormal operation of wind turbine equipment.

[0058] It needs to be explained that the characteristic value of the impact of abnormal operation of photovoltaic generator equipment is a quantitative evaluation data obtained by comprehensively analyzing the regional real-time solar radiation intensity, the reference standard solar radiation intensity and the allowable deviation solar radiation intensity. It is used to quantitatively evaluate the impact of regional solar radiation intensity on the abnormal operation of regional photovoltaic generator equipment, and provide a basis for matching the characteristic factors affecting the abnormal operation of photovoltaic generator equipment.

[0059] According to the characteristic values ​​of the impact of abnormal operation of wind turbine equipment and the characteristic values ​​of the impact of abnormal operation of photovoltaic generator equipment, the characteristic factors of the impact of abnormal operation of wind turbine equipment and the characteristic factors of the impact of abnormal operation of photovoltaic generator equipment are matched to obtain.

[0060] Specifically, the above matching process is: constructing a mapping set between the characteristic values ​​of abnormal operation of wind turbine equipment and the characteristic factors of abnormal operation of wind turbine equipment, obtaining the real-time characteristic values ​​of abnormal operation of wind turbine equipment and inputting them into the mapping set, and obtaining the characteristic factors of abnormal operation of wind turbine equipment according to the mapping set.

[0061] A mapping set between the photovoltaic generator equipment operation abnormality impact characteristic values ​​and the photovoltaic generator equipment operation abnormality impact characteristic factors is constructed, the real-time photovoltaic generator equipment operation abnormality impact characteristic values ​​are obtained and input into the mapping set, and the photovoltaic generator equipment operation abnormality impact characteristic factors are obtained according to the mapping set.

[0062] Based on the operating data of each generator equipment, the characteristic factors affecting the abnormal operation of wind generator equipment and the characteristic factors affecting the abnormal operation of photovoltaic generator equipment, a comprehensive analysis is performed to obtain the abnormal operation risk assessment value of each photovoltaic generator equipment and the abnormal operation risk assessment value of each wind generator equipment.

[0063] The abnormal operation risk assessment value of each photovoltaic generator device and the abnormal operation risk assessment value of each wind turbine generator device are jointly marked as the abnormal operation risk assessment value of each generator device. The abnormal operation risk assessment value of each generator device is used to quantitatively assess the degree of abnormal operation risk of each generator device in the microgrid area, and provide a basis for fault assessment of the generator equipment.

[0064] Furthermore, a comprehensive analysis is performed to obtain the abnormal operation risk assessment value of each photovoltaic generator device and the abnormal operation risk assessment value of each wind turbine device, including: extracting from the microgrid database the rated output power of the wind turbine device, the reference standard temperature of the gearbox, the rated vibration frequency of the gearbox, the reference standard speed of the blade, the allowable deviation power generation of the wind turbine device, the allowable deviation output power of the wind turbine device, the allowable deviation temperature of the gearbox, the allowable deviation vibration frequency of the gearbox and the allowable deviation speed of the blade.

[0065] Based on the operating data of each wind turbine equipment, the planned wind power generation and the characteristic factors affecting the abnormal operation of wind turbine equipment, a comprehensive analysis is conducted to obtain the abnormal operation risk assessment value of each wind turbine equipment.

[0066] The rated output power of the photovoltaic generator equipment, the rated voltage of the solar panel, the rated current of the solar panel and the reference standard temperature of the solar panel, the allowable deviation power generation of the photovoltaic generator equipment, the allowable deviation output power of the photovoltaic generator equipment, the allowable deviation voltage of the solar panel, the allowable deviation current of the solar panel and the allowable deviation temperature of the solar panel are extracted from the microgrid database.

[0067] Based on the operating data of each photovoltaic generator equipment, the planned solar power generation and the characteristic factors affecting the abnormal operation of photovoltaic generator equipment, a comprehensive analysis is conducted to obtain the abnormal operation risk assessment value of each photovoltaic generator equipment.

[0068] In a specific embodiment, the numerical expression of the abnormal operation risk assessment value of each wind turbine equipment is: ; In the formula, represents the risk assessment value of abnormal operation of the rth wind turbine equipment, e represents a natural constant, r represents the number of each wind turbine equipment, , h represents the total number of wind turbine equipment, represents the power generation of the rth wind turbine device within the preset monitoring period, represents the output power of the rth wind turbine at the i-th time monitoring point, represents the gearbox temperature of the rth wind turbine equipment at the i-th time monitoring point, represents the vibration frequency of the rth wind turbine equipment at the i-th time monitoring point, represents the blade speed of the rth wind turbine at the i-th time monitoring point, represents the planned wind power generation, Indicates the rated output power of wind turbine equipment. Indicates the gearbox reference standard temperature, Indicates the rated vibration frequency of the gearbox, Indicates the blade reference standard speed, Indicates the allowable deviation power generation of wind turbine equipment. Indicates the allowable deviation output power of the wind turbine equipment. Indicates the allowable deviation temperature of the gearbox. Indicates the allowable deviation vibration frequency of the gearbox, Indicates the allowable deviation speed of the blade. Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset power generation, Indicates the risk factor of abnormal operation of wind turbine equipment corresponding to the preset output power, Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset gearbox temperature, Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset gearbox vibration frequency, Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset blade speed, It represents the characteristic factors affecting abnormal operation of wind turbine equipment.

[0069] It needs to be explained that the greater the absolute difference between the power generation, output power, gearbox temperature and vibration frequency, and blade speed of each wind turbine equipment and the rated power generation, rated output power, reference standard gearbox temperature, reference standard gearbox vibration frequency and reference standard blade speed, the greater the characteristic factor affecting the abnormal operation of the wind turbine equipment, the greater the corresponding wind turbine equipment operation abnormality risk assessment value, indicating that the risk of abnormal operation of the wind turbine equipment is greater.

[0070] It should be explained that in this embodiment Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset power generation, Indicates the risk factor of abnormal operation of wind turbine equipment corresponding to the preset output power, Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset gearbox temperature, Indicates the risk influencing factor of abnormal operation of wind turbine equipment corresponding to the preset gearbox vibration frequency, Indicates the wind turbine equipment abnormal operation risk influencing factors corresponding to the preset blade speed, and the values ​​of these influencing factors respectively represent the influence degree of the wind turbine equipment's power generation, output power, gearbox temperature, gearbox vibration frequency and blade speed unit value on the wind turbine equipment's abnormal operation. When used, these influencing factors can be directly obtained from the microgrid database. The values ​​of these influencing factors are preset in the microgrid database. For example, the wind turbine equipment's power generation, output power, gearbox temperature, gearbox vibration frequency and blade speed form a mapping set with the preset influencing factors in the microgrid database. The real-time wind turbine equipment's power generation, output power, gearbox temperature, gearbox vibration frequency and blade speed are input into the mapping set to obtain the corresponding wind turbine equipment abnormal operation risk influencing factors. These mapping relationships can be one-to-one or many-to-one. The value range of all influencing factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0071] It should be explained that power generation is the accumulation of output power over time. In the preset monitoring period, the integral value of output power is the power generation. Therefore, the size and stability of output power directly affect power generation. When the wind speed is low, the output power increases with the increase of wind speed; when the wind speed reaches the rated wind speed, the output power reaches the maximum value, that is, the rated power; thereafter, as the wind speed continues to increase, the output power may decrease or remain unchanged due to the protection mechanism of the wind turbine. The temperature and vibration frequency of the gearbox are indirect factors affecting the output power. Temperatures higher than the reference standard or abnormal vibration frequencies may cause gearbox failures, thereby affecting the stability and reliability of the output power. The blade speed increases with the increase of wind speed. The increase in blade speed helps to increase the output power, but is limited by the mechanical and electrical limitations of the wind turbine. At the same time, the increase in output power is also affected by the blade speed. Temperatures higher than the reference standard may cause the gearbox material to expand and the lubrication performance to decrease, thereby increasing the vibration frequency; and abnormal vibration frequencies may also cause the gearbox to wear more and the temperature to rise.

[0072] It should be explained that this embodiment can achieve accurate assessment and early warning of wind turbine failures by comprehensively monitoring and analyzing the power generation of each wind turbine device within a preset monitoring period, the output power at each time monitoring point, the gearbox temperature and vibration frequency, and the blade speed, and combining the impact of regional wind speed analysis on wind turbine devices, and provide strong support for equipment maintenance and optimization. By maintaining the equipment, equipment damage and downtime can be avoided, which is conducive to improving the reliability and economic benefits of the wind power generation system.

[0073] In a specific embodiment, the numerical expression of the abnormal operation risk assessment value of each photovoltaic generator device is: ; In the formula, represents the risk assessment value of abnormal operation of the vth photovoltaic generator equipment, v represents the number of each photovoltaic generator equipment, , k represents the total number of photovoltaic generator devices, represents the power generation of the vth photovoltaic generator device within the preset monitoring period, represents the output power of the vth photovoltaic generator device at the i-th time monitoring point, represents the voltage of the qth solar panel of the vth photovoltaic generator device at the i-th time monitoring point, q represents the number of each solar panel, , p represents the total number of solar panels, represents the current of the qth solar panel of the vth photovoltaic generator device at the i-th time monitoring point, represents the temperature of the qth solar panel of the vth photovoltaic generator device at the i-th time monitoring point, represents the planned solar power generation, Indicates the rated output power of the photovoltaic generator equipment. Indicates the rated voltage of the solar panel, Indicates the rated current of the solar panel, Indicates the reference standard temperature of the solar panel. Indicates the allowable deviation power generation of photovoltaic generator equipment. Indicates the allowable deviation output power of the photovoltaic generator equipment. Indicates the allowable deviation voltage of the solar panel. Indicates the allowable deviation current of the solar panel. Indicates the allowable deviation temperature of the solar panel. Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset power generation. Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset output power, Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset solar panel voltage, Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset solar panel current, Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset solar panel temperature, Indicates the characteristic factors affecting the abnormal operation of photovoltaic generator equipment.

[0074] It needs to be explained that when the absolute difference between the power generation, output power, solar panel voltage, solar panel current and solar panel temperature of each photovoltaic generator equipment and the rated power generation, rated output power, rated solar panel voltage, rated solar panel current and reference standard solar panel temperature is greater, and the abnormal operation influencing characteristic factor of the photovoltaic generator equipment is also greater, the corresponding photovoltaic generator equipment abnormal operation risk assessment value is greater, indicating that the risk degree of abnormal operation of the photovoltaic generator equipment is greater.

[0075] It should be explained that in this embodiment Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset power generation. Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset output power, Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset solar panel voltage, Indicates the risk factor of abnormal operation of photovoltaic generator equipment corresponding to the preset solar panel current, The photovoltaic generator equipment abnormal operation risk influencing factors corresponding to the preset solar panel temperature are represented. The values ​​of these influencing factors respectively represent the degree of influence of the power generation, output power, solar panel voltage, solar panel current and solar panel temperature of the photovoltaic generator equipment on the abnormal operation of the photovoltaic generator equipment. When used, these influencing factors can be directly obtained from the microgrid database. The values ​​of these influencing factors are preset in the microgrid database. For example, the power generation, output power, solar panel voltage, solar panel current and solar panel temperature of the photovoltaic generator equipment are respectively mapped with the preset influencing factors in the microgrid database. The power generation, output power, solar panel voltage, solar panel current and solar panel temperature of the real-time photovoltaic generator equipment are input into the mapping set to obtain the corresponding photovoltaic generator equipment abnormal operation risk influencing factors. These mapping relationships can be one-to-one or many-to-one. The value range of all influencing factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0076] It needs to be explained that photovoltaic power generation refers to the total amount of electricity generated by solar panels over a period of time, usually expressed in kWh. Photovoltaic power output power refers to the output power of the panel per unit time, usually expressed in W. Photovoltaic power output power is positively correlated with power generation, that is, the higher the power, the greater the power generation. Under the same solar panel area, the higher the photovoltaic power output power, the higher the power generation of a single solar panel under the same conditions. There is a direct relationship between photovoltaic power output power (P) and the voltage (V) and current (I) of the solar panel, which can be expressed by the formula P=V×I. This means that changes in the voltage and current of the solar panel will directly affect the size of the output power. The voltage of the solar panel will increase with the increase in solar radiation intensity, but the rate of increase will gradually slow down. When the solar radiation intensity reaches a certain level, the voltage will tend to stabilize. The current of the solar panel is proportional to the solar radiation intensity, that is, the higher the solar radiation intensity, the greater the current. The temperature of the solar panel will increase with the increase in solar radiation intensity. However, the increase in temperature will cause the open circuit voltage of the solar panel to decrease, while the current will increase slightly with the increase in temperature. Generally speaking, the power of solar cells decreases with increasing temperature. Regional solar radiation intensity is one of the key factors affecting photovoltaic power generation. The higher the solar radiation, the higher the photovoltaic power generation. There are differences in the intensity and duration of sunshine in different regions, which directly affect the power generation of photovoltaic systems. For example, in high-latitude areas, the sunshine duration is short in winter, and the power generation is relatively low.

[0077] It should be explained that when the power generation drops significantly and the output power fluctuates, it may indicate that there is a fault in the solar panel or inverter. When the voltage or current of the solar panel is abnormal, there may be dirt, shadows or damage on the surface of the panel, and the inverter or connecting cable may be faulty. When the temperature of the solar panel rises abnormally, its heat dissipation system may fail. This embodiment comprehensively monitors and analyzes the power generation of each photovoltaic generator device within a preset monitoring period, the output power at each time monitoring point, the voltage, current and temperature of each solar panel, and combines the regional solar radiation intensity to analyze the impact on the photovoltaic generator device. It can achieve accurate assessment and early warning of photovoltaic generator failures. By timely discovering and processing potential equipment failures, system shutdown or damage can be avoided, which is beneficial to improving the reliability and economic benefits of the photovoltaic power generation system.

[0078] Furthermore, a fault assessment is performed on the generator equipment, and the number of faulty equipment is recorded. The specific process is: extracting the first initial threshold value of the generator equipment operation abnormality risk assessment and the second initial threshold value of the generator equipment operation abnormality risk assessment from the microgrid database, and processing to obtain the first threshold value of the generator equipment operation abnormality risk assessment and the second threshold value of the generator equipment operation abnormality risk assessment.

[0079] The abnormal operation risk assessment value of each wind turbine equipment is compared with the first threshold value of the abnormal operation risk assessment of the generator equipment. If the abnormal operation risk assessment value of a wind turbine equipment is less than the first threshold value of the abnormal operation risk assessment of the generator equipment, the fault assessment of the wind turbine equipment is qualified, and the wind turbine equipment is marked as a normal device. If the abnormal operation risk assessment value of a wind turbine equipment is greater than or equal to the first threshold value of the abnormal operation risk assessment of the generator equipment, the fault assessment of the wind turbine equipment is unqualified, and the wind turbine equipment is marked as a faulty device.

[0080] The abnormal operation risk assessment value of each photovoltaic generator device is compared with the second threshold value of the abnormal operation risk assessment of the generator device. If the abnormal operation risk assessment value of a photovoltaic generator device is less than the second threshold value of the abnormal operation risk assessment of the generator device, the fault assessment of the photovoltaic generator device is qualified, and the photovoltaic generator device is marked as a normal device. If the abnormal operation risk assessment value of a photovoltaic generator device is greater than or equal to the second threshold value of the abnormal operation risk assessment of the generator device, the fault assessment of the photovoltaic generator device is unqualified, and the photovoltaic generator device is marked as a faulty device.

[0081] Count the number of normal devices and faulty devices.

[0082] Specifically, the process of obtaining the first threshold value of the abnormal operation risk assessment of the generator equipment and the second threshold value of the abnormal operation risk assessment of the generator equipment is as follows: according to the total operating time of the wind turbine equipment, the first initial threshold correction parameter of the abnormal operation risk assessment of the generator equipment is matched, and the first initial threshold correction parameter of the abnormal operation risk assessment of the generator equipment is added to the first initial threshold value of the abnormal operation risk assessment of the generator equipment to obtain the first threshold value of the abnormal operation risk assessment of the generator equipment.

[0083] According to the total operating time of the photovoltaic generator equipment, the second initial threshold correction parameter of the generator equipment abnormal operation risk assessment is matched, and the second initial threshold correction parameter of the generator equipment abnormal operation risk assessment is added to the second initial threshold of the generator equipment abnormal operation risk assessment to obtain the second threshold of the generator equipment abnormal operation risk assessment.

[0084] Furthermore, the above matching process is: extracting from the microgrid database a mapping set between the total operating time of the wind turbine equipment and the first initial threshold correction parameter of the generator equipment operation abnormality risk assessment, and a mapping set between the total operating time of the photovoltaic generator equipment and the second initial threshold correction parameter of the generator equipment operation abnormality risk assessment.

[0085] The real-time total operating time of the wind turbine equipment and the total operating time of the photovoltaic generator equipment are input, and the first initial threshold correction parameter for the abnormal operation risk assessment of the generator equipment and the second initial threshold correction parameter for the abnormal operation risk assessment of the generator equipment are obtained according to the mapping set.

[0086] The microgrid power dispatching platform is used to comprehensively analyze the remaining power of the energy storage system, the abnormal operation risk assessment value of each generator equipment and the number of faulty equipment to obtain the power load satisfaction assessment index, and determine whether the microgrid needs to call on the diesel engine based on the power load satisfaction assessment index.

[0087] Specifically, a comprehensive analysis is performed to determine whether the power load meets the evaluation index. The specific analysis process is as follows: based on the abnormal operation risk assessment value of each generator equipment, the abnormal operation risk assessment value of each normal photovoltaic generator equipment and the abnormal operation risk assessment value of each normal wind turbine generator equipment are obtained.

[0088] The critical remaining power and number of critical fault devices of the energy storage system are extracted from the microgrid database.

[0089] According to the remaining power of the energy storage system, the abnormal operation risk assessment value of each normal photovoltaic generator equipment, the abnormal operation risk assessment value of each normal wind turbine equipment and the number of faulty equipment, a comprehensive analysis is conducted to obtain the power load satisfaction assessment index, which is used to quantitatively evaluate the level of renewable resource energy supply in the microgrid area and provide a basis for determining whether the microgrid needs to call on diesel engines.

[0090] In a specific embodiment, the numerical expression of the power load satisfying the evaluation index is: ; In the formula, Indicates that the power load meets the evaluation index, represents the abnormal risk assessment value of the nth normal photovoltaic generator equipment operation, represents the abnormal operation risk assessment value of the zth normal wind turbine equipment, z represents the number of each normal wind turbine equipment, , j represents the total number of normal wind turbine generators, n represents the number of normal photovoltaic generators, , m represents the total number of normal photovoltaic generator equipment, Indicates the remaining power of the energy storage system. Indicates the number of faulty devices. Indicates the critical remaining power of the energy storage system. Indicates the number of critical failure devices, Indicates that the power load corresponding to the preset remaining power of the energy storage system satisfies the correction factor, Indicates that the power load corresponding to the preset number of faulty devices meets the correction factor, It indicates that the power load corresponding to the preset normal wind turbine equipment operation abnormal risk assessment value satisfies the correction factor, It indicates that the power load corresponding to the preset normal photovoltaic generator equipment operation abnormal risk assessment value satisfies the correction factor.

[0091] It needs to be explained that when the remaining power of the energy storage system is larger, the abnormal operation risk assessment value of each normal photovoltaic generator equipment, the abnormal operation risk assessment value of each normal wind turbine equipment and the number of faulty equipment are smaller, the corresponding power load meets the greater the assessment index, indicating that the level of renewable resource energy supply in the microgrid area is higher.

[0092] It should be explained that in this embodiment Indicates that the power load corresponding to the preset remaining power of the energy storage system satisfies the correction factor, Indicates that the power load corresponding to the preset number of faulty devices meets the correction factor, It indicates that the power load corresponding to the preset normal wind turbine equipment operation abnormal risk assessment value satisfies the correction factor, It indicates the power load satisfaction correction factor corresponding to the preset normal photovoltaic generator equipment operation abnormal risk assessment value. The values ​​of these correction factors respectively represent the influence of the remaining power of the energy storage system, the number of faulty equipment, the normal wind turbine equipment operation abnormal risk assessment value and the normal photovoltaic generator equipment operation abnormal risk assessment value unit value on the regional power load satisfaction. When used, these correction factors can be directly obtained from the microgrid database. The values ​​of these influencing factors are preset in the microgrid database. For example, the remaining power of the energy storage system, the number of faulty equipment, the normal wind turbine equipment operation abnormal risk assessment value and the normal photovoltaic generator equipment operation abnormal risk assessment value form a mapping set with the correction factors preset in the microgrid database. The real-time remaining power of the energy storage system, the number of faulty equipment, the normal wind turbine equipment operation abnormal risk assessment value and the normal photovoltaic generator equipment operation abnormal risk assessment value are input into the mapping set to obtain the corresponding power load satisfaction correction factor. These mapping relationships can be one-to-one or many-to-one. The value range of all correction factors is between 0 and 1, indicating the degree from no impact to maximum impact.

[0093] It should be noted that when the risk assessment values of wind power generation equipment and photovoltaic power generation equipment increase, it means that they may not be able to operate normally or output the expected electrical energy. This will cause the energy storage system to need to supplement more energy to meet the load demand, which may lead to a decrease in the remaining power of the energy storage system. On the contrary, if the operating status of these devices is good and the assessment value is low, they can stably charge the energy storage system or directly supply power to the load, which helps to maintain the power level of the energy storage system. An increase in the number of faulty devices usually means a decrease in the number of power generation devices that can work properly, which will directly affect the charge-discharge balance of the energy storage system. If there are many faulty devices, the energy storage system may need to discharge faster to compensate for the power shortage, resulting in a rapid decrease in the remaining power. If the faulty devices are repaired in time, the power of the energy storage system can be better maintained. The risk assessment value of equipment operation anomalies can predict potential equipment failures. If the assessment value of a certain device is very high, then the possibility of its failure is also high, which may lead to an increase in the number of faulty devices. When the assessment values of multiple devices are relatively high, the reliability of the entire power generation system decreases, and the number of faulty devices may increase accordingly.

[0094] It should be noted that in this embodiment, by monitoring the remaining power of the energy storage system, the power reserve situation of the microgrid can be understood in real time, ensuring that the stable operation of the grid can still be maintained when the power generation equipment fails or the power generation is insufficient. Analyzing the risk assessment value of equipment operation anomalies helps to identify potential failure risks in advance and take preventive measures, thereby reducing the possibility of sudden power outages. By analyzing the remaining power of the energy storage system and the operating status of the power generation equipment, the dispatching strategy can be optimized, such as storing electrical energy when the electricity price is low and releasing electrical energy during peak electricity prices or when the power generation is insufficient. By monitoring the number of faulty devices, the vulnerability of the microgrid can be evaluated, and repairs or replacements can be carried out in a timely manner to enhance the anti-interference ability of the system. When power generation equipment fails due to extreme weather or emergencies, the energy storage system can play a buffering role to ensure the power supply of critical loads. Assessing the risk of equipment operation anomalies helps to achieve predictive maintenance, reduce unplanned downtime and related maintenance costs. It is beneficial to extend the equipment life and reduce the frequency and cost of replacing equipment. By optimizing the power load satisfaction, it helps to promote the utilization of renewable energy, reduce the dependence on fossil energy, and achieve green and sustainable development.

[0095] It should be noted that in this embodiment, by comprehensively considering the remaining power of the energy storage system, the risk assessment values of the operation anomalies of normal photovoltaic and normal wind turbine equipment, and the number of faulty devices, the power supply and demand situation of the microgrid can be predicted more accurately, providing a basis for power dispatching. It can also manage the microgrid more effectively, ensure that the power load is met, and improve the overall performance and economic benefits of the microgrid.

[0096] Furthermore, it is determined whether the microgrid needs to call the diesel engine. The specific judgment process is: extract the power load satisfaction evaluation index threshold from the microgrid database, compare the power load satisfaction evaluation index with the power load satisfaction evaluation index threshold, if the power load satisfaction evaluation index is higher than or equal to the power load satisfaction evaluation index threshold, then it is determined that there is no need to call the diesel engine, if the power load satisfaction evaluation index is lower than the power load satisfaction evaluation index threshold, then it is determined that the diesel engine needs to be called, and the diesel engine is called to supply power according to the power load satisfaction evaluation index.

[0097] Furthermore, the diesel engine is called to supply power according to the power load satisfying evaluation index. The specific process is: subtract the power load satisfying evaluation index from the power load satisfying evaluation index threshold to obtain the evaluation index difference, and obtain the diesel engine supply power according to the matching of the evaluation index difference.

[0098] Specifically, a mapping set between the evaluation index difference and the power supplied by the diesel engine is extracted from the microgrid database, the real-time evaluation index difference is input, and the corresponding power supplied by the diesel engine is obtained according to the mapping set.

[0099] In a specific embodiment, the microgrid database is used to store relevant data in the process of evaluating the microgrid power load satisfaction, including wind turbine equipment operation abnormality risk impact factor corresponding to power generation, wind turbine equipment operation abnormality risk impact factor corresponding to output power, wind turbine equipment operation abnormality risk impact factor corresponding to gearbox temperature, wind turbine equipment operation abnormality risk impact factor corresponding to gearbox vibration frequency, wind turbine equipment operation abnormality risk impact factor corresponding to blade speed, critical remaining power, number of critical fault devices, generator equipment operation abnormality risk assessment first threshold and generator equipment operation abnormality risk assessment second threshold, and data extracted from the microgrid database in the above embodiment can be collected in real time through sensors and monitoring devices equipped with various components in the microgrid (such as photovoltaic panels, wind turbines, energy storage systems, loads, etc.), power generation, consumption, storage and system status data, and then the data is transmitted to the database through a communication network, and can also be connected to a data acquisition system (SCADA, EMS, etc.) through standard communication interfaces equipped with microgrid components, such as Modbus, OPC UA, IEC 61850, etc., to remotely obtain relevant data, and can also view relevant data by logging into the microgrid open data platform.

[0100] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid is characterized by: include: A microgrid power data acquisition module is used to acquire the planned power generation data and actual power supply data of the microgrid area, wherein the planned power generation data includes the planned solar power generation and the planned wind power generation, and the actual power supply data includes the remaining power of the energy storage device and the operation data of each generator device; The power generation equipment fault assessment module is used to obtain the abnormal operation risk assessment value of each power generation equipment according to the operation data of each power generation equipment through processing, conduct fault assessment on the power generation equipment according to the abnormal operation risk assessment value of each power generation equipment, and record the number of faulty equipment; The microgrid power dispatching platform is used to comprehensively analyze the remaining power of the energy storage system, the abnormal operation risk assessment value of each generator equipment and the number of faulty equipment to obtain the power load satisfaction assessment index, and determine whether the microgrid needs to call on the diesel engine based on the power load satisfaction assessment index.

2. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 1 is characterized in that: The operating data of each generator device includes: operating data of each wind turbine generator device, operating data of each photovoltaic generator device and operating environment data within a preset monitoring period; The operation data of each wind turbine device include the total operation time of the wind turbine device, the power generation of each wind turbine device within a preset monitoring period, the output power of each wind turbine device at each time monitoring point, the gear box temperature and vibration frequency, and the blade speed; The operation data of each photovoltaic generator device includes the total operation time of the photovoltaic generator device, the power generation of each photovoltaic generator device within a preset monitoring period, the output power of each photovoltaic generator device at each time monitoring point, and the voltage, current and temperature of each solar panel; The operating environment data includes regional real-time wind speed and regional real-time solar radiation intensity.

3. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 2 is characterized in that: The abnormal operation risk assessment value of each generator device is obtained by processing the operation data of each generator device, including: The reference wind speed, the allowable deviation wind speed, the reference solar radiation intensity and the allowable deviation solar radiation intensity are extracted from the microgrid database; According to the real-time wind speed and the real-time solar radiation intensity, the characteristic value of the impact of abnormal operation of the wind turbine equipment and the characteristic value of the impact of abnormal operation of the photovoltaic generator equipment are obtained through processing; According to the characteristic values ​​of the impact of abnormal operation of wind turbine equipment and the characteristic values ​​of the impact of abnormal operation of photovoltaic generator equipment, the characteristic factors of the impact of abnormal operation of wind turbine equipment and the characteristic factors of the impact of abnormal operation of photovoltaic generator equipment are matched; Based on the operation data of each generator equipment, the characteristic factors affecting the abnormal operation of wind generator equipment and the characteristic factors affecting the abnormal operation of photovoltaic generator equipment, a comprehensive analysis is performed to obtain the abnormal operation risk assessment value of each photovoltaic generator equipment and the abnormal operation risk assessment value of each wind generator equipment; The abnormal operation risk assessment value of each photovoltaic generator device and the abnormal operation risk assessment value of each wind turbine generator device are jointly marked as the abnormal operation risk assessment value of each generator device. The abnormal operation risk assessment value of each generator device is used to quantitatively assess the degree of abnormal operation risk of each generator device in the microgrid area, and provide a basis for fault assessment of the generator equipment.

4. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 3 is characterized by: The comprehensive analysis obtains the abnormal operation risk assessment value of each photovoltaic generator device and the abnormal operation risk assessment value of each wind turbine device, including: Extract from the microgrid database the rated output power of the wind turbine equipment, the reference standard temperature of the gearbox, the rated vibration frequency of the gearbox, the reference standard speed of the blades, the allowable deviation power generation of the wind turbine equipment, the allowable deviation output power of the wind turbine equipment, the allowable deviation temperature of the gearbox, the allowable deviation vibration frequency of the gearbox and the allowable deviation speed of the blades; Based on the operation data of each wind turbine equipment, the planned wind power generation and the characteristic factors affecting the abnormal operation of wind turbine equipment, a comprehensive analysis is conducted to obtain the abnormal operation risk assessment value of each wind turbine equipment; Extract the rated output power of photovoltaic generator equipment, the rated voltage of solar panels, the rated current of solar panels and the reference standard temperature of solar panels, the allowable deviation power generation of photovoltaic generator equipment, the allowable deviation output power of photovoltaic generator equipment, the allowable deviation voltage of solar panels, the allowable deviation current of solar panels and the allowable deviation temperature of solar panels from the microgrid database; Based on the operating data of each photovoltaic generator equipment, the planned solar power generation and the characteristic factors affecting the abnormal operation of photovoltaic generator equipment, a comprehensive analysis is conducted to obtain the abnormal operation risk assessment value of each photovoltaic generator equipment.

5. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 4 is characterized in that: The specific process of performing fault assessment on the generator equipment and recording the number of faulty equipment is as follows: Extracting a first initial threshold value for abnormal operation risk assessment of generator equipment and a second initial threshold value for abnormal operation risk assessment of generator equipment from a microgrid database, and processing to obtain a first threshold value for abnormal operation risk assessment of generator equipment and a second threshold value for abnormal operation risk assessment of generator equipment; Compare the abnormal operation risk assessment value of each wind turbine equipment with the first threshold value of abnormal operation risk assessment of the generator equipment; if the abnormal operation risk assessment value of a certain wind turbine equipment is less than the first threshold value of abnormal operation risk assessment of the generator equipment, then the fault assessment of the wind turbine equipment is qualified, and the wind turbine equipment is marked as a normal device; if the abnormal operation risk assessment value of a certain wind turbine equipment is greater than or equal to the first threshold value of abnormal operation risk assessment of the generator equipment, then the fault assessment of the wind turbine equipment is unqualified, and the wind turbine equipment is marked as a faulty device; Compare the abnormal operation risk assessment value of each photovoltaic generator device with the second threshold value of the abnormal operation risk assessment of the generator device. If the abnormal operation risk assessment value of a photovoltaic generator device is less than the second threshold value of the abnormal operation risk assessment of the generator device, the fault assessment of the photovoltaic generator device is qualified, and the photovoltaic generator device is marked as a normal device. If the abnormal operation risk assessment value of a photovoltaic generator device is greater than or equal to the second threshold value of the abnormal operation risk assessment of the generator device, the fault assessment of the photovoltaic generator device is unqualified, and the photovoltaic generator device is marked as a faulty device. Count the number of normal devices and faulty devices.

6. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 4 is characterized by: The comprehensive analysis shows that the power load meets the evaluation index. The specific analysis process is as follows: According to the abnormal operation risk assessment value of each generator equipment, the abnormal operation risk assessment value of each normal photovoltaic generator equipment and the abnormal operation risk assessment value of each normal wind turbine generator equipment are obtained; Extract the critical remaining power of the energy storage system and the number of critical fault devices from the microgrid database; According to the remaining power of the energy storage system, the abnormal operation risk assessment value of each normal photovoltaic generator equipment, the abnormal operation risk assessment value of each normal wind turbine equipment and the number of faulty equipment, a comprehensive analysis is conducted to obtain the power load satisfaction assessment index, which is used to quantitatively assess the level of renewable resource energy supply in the microgrid area and provide a basis for determining whether the microgrid needs to call on diesel engines.

7. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 6 is characterized by: The specific process of judging whether the microgrid needs to call a diesel engine is as follows: The power load meets the evaluation index threshold value extracted from the microgrid database, and the power load meets the evaluation index and the power load meets the evaluation index threshold value are compared. If the power load meets the evaluation index higher than or equal to the power load meets the evaluation index threshold value, it is determined that there is no need to call the diesel engine. If the power load meets the evaluation index lower than the power load meets the evaluation index threshold value, it is determined that the diesel engine needs to be called, and the diesel engine is called to supply power according to the power load meets the evaluation index.

8. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 3 is characterized by: The wind turbine equipment operation abnormality impact characteristic value is a quantitative evaluation data obtained by comprehensive analysis of the regional real-time wind speed, the reference standard wind speed and the allowable deviation wind speed, and is used to quantitatively evaluate the impact of the regional wind speed on the regional wind turbine equipment operation abnormality, and provide a basis for matching the wind turbine equipment operation abnormality impact characteristic factor; The photovoltaic generator equipment operation abnormality impact characteristic value is a quantitative evaluation data obtained by comprehensively analyzing the regional real-time solar radiation intensity, the reference standard solar radiation intensity and the allowable deviation solar radiation intensity, and is used to quantitatively evaluate the impact of the regional solar radiation intensity on the regional photovoltaic generator equipment operation abnormality, and provide a basis for matching the photovoltaic generator equipment operation abnormality impact characteristic factor.

9. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 7 is characterized by: The specific process of calling the diesel engine to supply electricity according to the power load meeting the evaluation index is as follows: Subtract the power load satisfaction evaluation index from the power load satisfaction evaluation index threshold to obtain the evaluation index difference, and obtain the diesel engine supply power according to the evaluation index difference; A mapping set between the evaluation index difference and the power supplied by the diesel engine is extracted from the microgrid database, the real-time evaluation index difference is input, the corresponding power supplied by the diesel engine is obtained according to the mapping set, and the diesel engine is called to supply power.

10. The energy dispatch optimization system of the adaptive multi-energy complementary microgrid according to claim 6 is characterized by: The power load meets the evaluation index, and the specific numerical expression is: ； In the formula, Indicates that the power load meets the evaluation index, represents the abnormal risk assessment value of the nth normal photovoltaic generator equipment operation, represents the abnormal operation risk assessment value of the zth normal wind turbine equipment, z represents the number of each normal wind turbine equipment, , j represents the total number of normal wind turbine generators, n represents the number of normal photovoltaic generators, , m represents the total number of normal photovoltaic generator equipment, Indicates the remaining power of the energy storage system. Indicates the number of faulty devices. Indicates the critical remaining power of the energy storage system. Indicates the number of critical failure devices, Indicates that the power load corresponding to the preset remaining power of the energy storage system satisfies the correction factor, Indicates that the power load corresponding to the preset number of faulty devices meets the correction factor, It indicates that the power load corresponding to the preset normal wind turbine equipment operation abnormal risk assessment value satisfies the correction factor, It indicates that the power load corresponding to the preset normal photovoltaic generator equipment operation abnormal risk assessment value satisfies the correction factor.

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