Intelligent scheduling system of distributed power supply coordination device

Abstract

The invention discloses an intelligent scheduling system for a distributed power supply coordination device, and relates to the technical field of power system automation. The distributed power supply fault early warning module is used for processing according to the power supply working state data to obtain a working state abnormal evaluation value of each distributed power supply unit, and performing fault early warning according to the working state abnormal evaluation value of each distributed power supply unit; the distributed power supply data processing module is used for performing comprehensive analysis according to the power supply energy management data, the environment data and the working state abnormity evaluation value of each distributed power supply unit to obtain an operation efficiency evaluation index of each distributed power supply unit; and the distributed power supply intelligent scheduling module is used for performing intelligent scheduling on each distributed power supply unit according to the operation efficiency evaluation index of each distributed power supply unit.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and in particular to an intelligent dispatching system for a distributed power supply coordination device. Background Art

[0002] With the continuous development of the global economy and the continuous growth of population, energy demand is showing an increasing trend. In this context, the access of distributed power sources as a flexible and efficient energy supply method is also rising rapidly. However, the widespread access of this distributed energy has undoubtedly brought new challenges and tests to the safe and stable operation of the power grid.

[0003] The existing coordinated dispatching system of distributed power sources mainly relies on manual experience and traditional dispatching algorithms to ensure the stable operation of the power grid through measures such as power generation planning, real-time power adjustment, voltage and frequency monitoring, and fault response.

[0004] For example, the invention patent with announcement number CN111404195B announces a scheduling method for a microgrid containing distributed power sources based on an intelligent gateway, which includes the following steps: A) installing an intelligent gateway at the node where the target power grid is connected to the distributed power source; B) calculating the characteristic value of the next time period. If the characteristic value is less than the set threshold, the wind and solar power stations only output active power during the time period and proceed to step D); C) determining the active power and reactive power output by the wind and solar power stations; D) based on the voltage and frequency at the node, the intelligent gateway performs power control on the wind and solar power stations or energy storage stations on site.

[0005] For example, the invention patent with announcement number CN110768294B announces a distributed power random scheduling method and device, which is suitable for smart buildings containing distributed power sources, including: establishing an original random scheduling model of the smart building containing distributed power sources; obtaining the input variables and output variables of the black box random scheduling model according to the original random scheduling model; using tensor product to describe the equation relationship between the input variables and the output variables to fit the black box random scheduling model; based on Monte Carlo power sampling and random transformation schemes of scenarios, solving the optimal solution of the black box random scheduling model to obtain a random scheduling scheme.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application discovered that the above-mentioned technology has at least the following technical problems: in practical applications, due to the intermittent and volatile nature of distributed power sources, the stability and reliability of the power system may be affected, resulting in consequences such as reduced power quality and power outages. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides an intelligent scheduling system for a distributed power supply coordination device, which can effectively solve the problems involved in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a distributed power supply coordination device intelligent scheduling system, including: a distributed power supply data acquisition module, which is used to collect distributed power supply operation data in real time through a distributed power supply coordination device and monitor environmental data. The distributed power supply operation data includes power supply working status data and power supply energy management data. The collected data is preliminarily processed and integrated to form a real-time data source set.

[0009] The distributed power supply fault warning module is used to obtain the abnormal working state evaluation value of each distributed power supply unit according to the power supply working state data processing, and to issue a fault warning according to the abnormal working state evaluation value of each distributed power supply unit.

[0010] The distributed power supply data processing module is used to obtain the operating efficiency evaluation index of each distributed power supply unit through comprehensive analysis based on the power supply energy management data, environmental data and the abnormal working status evaluation value of each distributed power supply unit.

[0011] The distributed power supply intelligent scheduling module is used to intelligently schedule each distributed power supply unit according to the operation efficiency evaluation index of each distributed power supply unit.

[0012] As a further method, the environmental data includes temperature, humidity, light intensity and wind speed; the power supply working status data includes voltage, current, power generation, power factor and cumulative number of faults; and the power supply energy management data includes power generation and power consumption.

[0013] As a further method, the collected data is preliminarily processed and integrated to form a real-time data source set. The specific analysis process is: the collected distributed power supply operation data and environmental data are divided according to the collection time point to obtain the distributed power supply operation data and environmental data at each collection time point; the distributed power supply operation data and environmental data at each collection time point are integrated to obtain the real-time data source set.

[0014] As a further method, the abnormal working state evaluation value of each distributed power supply unit is obtained according to the power supply working state data processing, and the specific analysis process is: extracting the preset reference working voltage, allowable deviation working voltage, reference working current, allowable deviation working current, reference power generation power, allowable deviation power generation power, reference power factor, allowable deviation power factor and critical failure times from the distributed power supply database; according to the power supply working state data, a comprehensive analysis is performed to obtain the abnormal working state evaluation value of each distributed power supply unit, and the abnormal working state evaluation value is used to quantitatively evaluate the equipment output performance stability of the distributed power supply unit.

[0015] As a further method, a fault warning is performed according to the abnormal working state evaluation value of each distributed power supply unit. The specific analysis process is: the abnormal working state evaluation value of each distributed power supply unit is compared with the abnormal working state evaluation value threshold preset in the distributed power supply database. If the abnormal working state evaluation value of a distributed power supply unit is greater than or equal to the preset abnormal working state evaluation threshold, the working state of the distributed power supply unit is abnormal, and a fault warning is performed; if the abnormal working state evaluation value of a distributed power supply unit is less than the preset abnormal working state evaluation threshold, the working state of the distributed power supply unit is normal.

[0016] As a further method, the comprehensive analysis obtains the operating efficiency evaluation index of each distributed power supply unit, and the specific analysis process is: according to the power energy management data, the energy management anomaly index of each distributed power supply unit is processed; according to the environmental data, the environmental interference index of each distributed power supply unit is processed; according to the environmental interference index of each distributed power supply unit, the energy management anomaly index of each distributed power supply unit and the working status anomaly evaluation value of each distributed power supply unit, a comprehensive analysis is performed to obtain the operating efficiency evaluation index of each distributed power supply unit.

[0017] As a further method, each distributed power supply unit is intelligently scheduled according to the operating efficiency evaluation index of each distributed power supply unit. The specific analysis process is: the operating efficiency evaluation index of each distributed power supply unit is compared with the operating efficiency evaluation index threshold preset in the distributed power supply database. If the operating efficiency evaluation index of a distributed power supply unit is greater than or equal to the operating efficiency evaluation index threshold, no additional operation is performed; if the operating efficiency evaluation index of a distributed power supply unit is less than the operating efficiency evaluation index threshold, the usage frequency of the distributed power supply unit is reduced.

[0018] As a further method, the energy management anomaly index of each distributed power supply unit is obtained by processing the power supply energy management data. The specific analysis process is: extracting a preset critical energy efficiency from a distributed power supply database; based on the power supply energy management data, a comprehensive analysis is performed to obtain the energy management anomaly index of each distributed power supply unit. The energy management anomaly index is used to quantitatively evaluate the degree of abnormality of the energy management status of the distributed power supply unit.

[0019] As a further method, the environmental interference index of each distributed power supply unit is obtained by processing according to the environmental data. The specific analysis process is: extracting the preset reference temperature, allowable deviation temperature, reference humidity, allowable deviation humidity, reference light intensity, allowable deviation light intensity, reference wind speed and allowable deviation wind speed from the distributed power supply database; according to the environmental data, a comprehensive analysis is performed to obtain the environmental interference index of each distributed power supply unit, and the environmental interference index is used to quantitatively evaluate the interference degree of the working environment of the distributed power supply unit.

[0020] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects: (1) The present invention provides an intelligent dispatching system for distributed power coordination devices, which can collect distributed power operation and environmental data in all directions and build a real-time data source set. It can effectively avoid failure risks, optimize energy distribution, improve the overall operating efficiency and reliability of the distributed power system, ensure stable power supply, enhance the grid's ability to accept distributed power, promote the efficient use of renewable energy, and meet the needs of energy transformation.

[0021] (2) The present invention constructs a scientific evaluation system to measure the abnormal evaluation value of the working state, the energy management abnormality index and the environmental interference index according to the preset threshold value, determine the operation quality of the power supply unit, and provide a reliable decision-making basis for operation and maintenance. Timely locate the hidden dangers of faults and inefficient links, reasonably adjust or maintain, ensure the stable operation of equipment, improve the level of energy management, reduce the operation and maintenance costs, extend the life of equipment, and enhance the safety and economy of system operation.

[0022] (3) The present invention dynamically adjusts the threshold of the operating efficiency evaluation index to adapt to different distributed power characteristics and complex operating conditions. It ensures that the operating status of each power unit is coordinated with the overall system goal, realizes efficient resource allocation, improves the system's ability to respond to environmental and load changes, and enhances the resilience and flexibility of the distributed power system in a complex energy landscape.

[0023] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0025] Figure 2 It is a schematic diagram of the functional relationship between the environmental interference index and the operation efficiency evaluation index of the present invention. DETAILED DESCRIPTION

[0026] 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.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0028] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent scheduling system for a distributed power supply coordination device, including: a distributed power supply data acquisition module, which is used to collect distributed power supply operation data in real time through a distributed power supply coordination device and monitor environmental data, wherein the distributed power supply operation data includes power supply working status data and power supply energy management data, and the collected data is preliminarily processed and integrated to form a real-time data source set.

[0029] Specifically, environmental data includes temperature, humidity, light intensity and wind speed; power supply working status data includes voltage, current, power generation, power factor and cumulative number of faults; power supply energy management data includes power generation and power consumption.

[0030] The distributed power coordination device intelligent dispatching system in this embodiment realizes the efficient coordination and optimized dispatching of distributed power sources through functions such as real-time monitoring, data analysis and intelligent dispatching, and provides strong support for the sustainable development of energy and the stable operation of the power system. The distributed power data acquisition module is a core component in the system, responsible for collecting and integrating data from distributed power sources. It can collect data in real time, which means that the data is collected while the power source is running, ensuring the timeliness and accuracy of the data.

[0031] It should be understood that the environmental data in this embodiment refers to external conditions that affect the operating efficiency of the power supply, such as temperature, humidity, light intensity and wind speed, which are essential for evaluating the operating status of the power supply and optimizing energy management. The power supply operating status data refers to the specific parameters of the power supply during operation, such as voltage, current, power generation, power factor and cumulative number of faults, providing a detailed view of the power supply performance, helping to identify potential problems and optimize the use of the power supply. The power supply energy management data includes power generation (the total energy generated by the power supply) and power consumption (the energy consumed by the power supply), which is essential for evaluating the energy efficiency of the power supply and formulating energy management strategies.

[0032] The collected data are preliminarily processed and integrated to form a real-time data source set. The specific analysis process is as follows: the collected distributed power supply operation data and environmental data are divided according to the collection time point to obtain the distributed power supply operation data and environmental data at each collection time point; the distributed power supply operation data and environmental data at each collection time point are integrated to obtain a real-time data source set.

[0033] It should be understood that in this embodiment, the collected distributed power supply operation data and environmental data are divided according to the collection time point, and each collected data will be marked with a time point for subsequent processing and analysis. Data division helps to cut the continuous data stream into discrete data points, and each data point represents the power supply operation status and environmental conditions at a certain moment. The distributed power supply operation data and environmental data at each collection time point are integrated, and the data from different sources (such as voltage, current, temperature and humidity, etc.) are merged according to the time point to form a complete data set, creating a real-time data source set, which contains all key information and has been organized according to the time point, which is convenient for subsequent analysis and decision-making.

[0034] The distributed power supply fault warning module is used to obtain the abnormal working state evaluation value of each distributed power supply unit according to the power supply working state data processing, and to issue a fault warning according to the abnormal working state evaluation value of each distributed power supply unit.

[0035] Specifically, the abnormal working status evaluation value of each distributed power supply unit is obtained according to the power supply working status data processing. The specific analysis process is: extracting the preset reference working voltage, allowable deviation working voltage, reference working current, allowable deviation working current, reference power generation power, allowable deviation power generation power, reference power factor, allowable deviation power factor and critical fault number from the distributed power supply database.

[0036] In this embodiment, the distributed power supply fault warning module analyzes the power supply working status data, evaluates the abnormality of the working status of each distributed power supply unit, and issues a fault warning accordingly.

[0037] It should be understood that in this embodiment, preset values ​​are extracted from the distributed power supply database to evaluate whether the working state of the power supply unit is normal. The extracted reference values ​​include reference working voltage, reference working current, reference power generation, and reference power factor; the extracted allowable deviation values ​​include allowable deviation working voltage, allowable deviation working current, allowable deviation power generation, and allowable deviation power factor; in addition, the number of critical failures is extracted to determine whether the power supply unit is about to fail. These data are based on system design requirements, equipment standards, and past operating experience, and provide a benchmark for subsequent precise analysis. For example, the reference working voltage and allowable deviation working voltage range define the voltage range for normal operation of the power supply unit. Exceeding this range may cause equipment performance degradation or even damage; the reference power generation and allowable deviation power generation clarify the power generation level that the power supply unit should achieve under different working conditions, which helps to determine whether its power generation capacity is normal. The distributed power supply fault warning module compares and analyzes the real-time collected power supply working status data (including working voltage, working current, power generation, power factor and cumulative number of faults) with the extracted reference data, and comprehensively evaluates the stability of the equipment output performance of the distributed power supply unit by calculating the degree of deviation between the actual working voltage, current, power generation and power factor and the corresponding reference values, and combining the cumulative number of faults, and judging whether these deviations are within the allowable range. If the deviation exceeds the allowable range, or the power supply unit has deviations multiple times over a period of time, it indicates that the power supply unit is abnormal, and the abnormal working status assessment value is obtained. If the actual voltage frequently approaches or exceeds the allowable deviation range, it may indicate that there is a problem with the voltage regulation mechanism of the power supply unit; if the power generation power is lower than the reference power generation power for a long time and the deviation is large, it may indicate that the energy conversion efficiency of the power generation equipment is reduced or there is a fault.

[0038] According to the power supply working state data, a comprehensive analysis is performed to obtain the working state abnormality evaluation value of each distributed power supply unit, and the working state abnormality evaluation value is used to quantitatively evaluate the equipment output performance stability of the distributed power supply unit.

[0039] It should be understood that in this embodiment, the voltage is measured and obtained by a voltage transformer, the current is measured and obtained by a current transformer, the generated power is directly measured and obtained by a power analyzer, and the power factor is measured and obtained by a power factor meter.

[0040] In a specific embodiment, the abnormal working status evaluation value is obtained as follows: ; In the formula, represents the abnormal working status evaluation value of the i-th distributed power supply unit, represents the operating voltage of the i-th distributed power unit, Indicates the reference working voltage, Indicates the preset allowable deviation working voltage, represents the operating current of the i-th distributed power supply unit, Indicates the reference working current, Indicates the preset allowable deviation working current, represents the power generation of the i-th distributed power unit, Indicates the reference power generation, Indicates the preset allowable deviation power generation, represents the power factor of the i-th distributed power unit, Indicates the reference power factor, Indicates the preset allowable deviation power factor, represents the cumulative number of failures of the i-th distributed power unit, represents the number of critical failures, Indicates the abnormal impact weight of the working state corresponding to the preset working voltage, Indicates the abnormal impact weight of the working state corresponding to the preset working current, Indicates the abnormal impact weight of the working state corresponding to the preset power generation. Indicates the abnormal impact weight of the working state corresponding to the preset power factor, represents the abnormal working state impact weight corresponding to the preset number of faults, i represents the number of the distributed power supply unit, i=1, 2, 3, ..., k, k represents the total number of distributed power supply units.

[0041] For example, , , , and When in use, the abnormal working state impact weights corresponding to the working voltage, working current, generated power, power factor and cumulative number of faults can be directly obtained from the distributed power supply database. The factors respectively represent the numerical values ​​of the influence of the working voltage, working current, generated power, power factor and cumulative number of faults on the abnormal working state evaluation value. The corresponding relationship can be a pre-set mapping relationship. For example, the temperature of the distributed power supply unit and the abnormal working state impact weights corresponding to the preset working voltage, working current, generated power, power factor and cumulative number of faults in the distributed power supply database form a mapping set. The temperature of the distributed power supply unit is input into the mapping set to obtain the abnormal working state impact weights corresponding to the working voltage, working current, generated power, power factor and cumulative number of faults. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0042] In this embodiment, the abnormal working state evaluation value is used to quantitatively evaluate the stability of the equipment output performance of the distributed power supply unit. The smaller the deviation between the working voltage and the reference value, or the smaller the deviation between the working current and the reference value, or the smaller the deviation between the generated power and the reference value, or the smaller the deviation between the power factor and the reference value, or the fewer the cumulative number of failures, the lower the corresponding abnormal working state evaluation value, indicating that the equipment output performance stability of the distributed power supply unit is stronger.

[0043] The algorithm of this embodiment combines the working voltage, working current, power generation, power factor and cumulative number of faults, and comprehensively analyzes to obtain the abnormal evaluation value of the working state. In this formula, the working voltage, working current, power generation, power factor and cumulative number of faults affect each other. In the circuit, voltage is the force that drives the flow of current, while current is the flow of charge. The voltage is proportional to the current. The larger the working voltage, the larger the working current; the power generation is the ability of the power supply unit to output electric energy. When the voltage or current is larger, the power generation will also be larger; the power factor is related to the quality of electric energy, reflecting the ratio between actual power and apparent power. The lower the working voltage, working current or power generation, the lower the reactive power will affect the output of active power, and the lower the power factor. The stability of the working voltage and current affects the transmission efficiency of electric energy and the operating safety of the equipment. The power generation reflects the actual power generation capacity of the power supply unit, and the power factor is related to the quality of electric energy. The smaller the deviation of the working voltage, working current, power generation and power factor from the reference value, the more stable the power supply unit is on the normal operating track and the more reliable the output performance is. When the operating voltage, operating current, power generation or power factor exceeds the allowable deviation value, the equipment failure rate will increase. The more cumulative failure times mean that the equipment has a higher frequency of problems in past operations, the worse the overall stability, and the higher the current abnormal working state assessment value. By comprehensively analyzing the operating voltage, operating current, power generation, power factor and cumulative failure times, the abnormal working state assessment value can be accurately obtained, which quantitatively reflects the degree to which the output performance of the distributed power unit deviates from the normal stable state under the current operating state.

[0044] Specifically, a fault warning is performed based on the abnormal working state evaluation value of each distributed power supply unit. The specific analysis process is: compare the abnormal working state evaluation value of each distributed power supply unit with the abnormal working state evaluation value threshold preset in the distributed power supply database. If the abnormal working state evaluation value of a distributed power supply unit is greater than or equal to the preset abnormal working state evaluation threshold, the working state of the distributed power supply unit is abnormal, and a fault warning is performed; if the abnormal working state evaluation value of a distributed power supply unit is less than the preset abnormal working state evaluation threshold, the working state of the distributed power supply unit is normal.

[0045] It should be understood that the threshold of the abnormal working state evaluation value preset in the distributed power supply database in this embodiment is directly obtained from the distributed power supply database, and is used to determine whether the working state of the distributed power supply unit is normal. The abnormal working state evaluation value of each distributed power supply unit is compared with the abnormal working state evaluation value threshold preset in the distributed power supply database. If the abnormal working state evaluation value of a distributed power supply unit is less than the preset abnormal working state evaluation threshold, the working state of the distributed power supply unit is normal; if the abnormal working state evaluation value of a distributed power supply unit is greater than or equal to the preset abnormal working state evaluation threshold, it means that the working voltage, working current, power generation and power factor of the power supply unit deviate from the preset allowable deviation by a large margin, or the cumulative number of faults has reached the critical number of faults. At this time, the working state of the distributed power supply unit is abnormal, and the early warning mechanism is triggered. The system issues a fault warning in time, which enables the operation and maintenance personnel to quickly focus on the problem and take corresponding measures. The early warning mechanism can effectively ensure the stable operation of the distributed power system. Timely fault warning can prevent small problems from gradually evolving into serious faults, and avoid economic losses caused by equipment damage and downtime, such as power loss caused by power generation interruption and increased equipment maintenance costs. For power units in normal working condition, the system can continue to perform routine monitoring, reasonably allocate resources, and ensure the efficient operation of the entire distributed power system. For example, in a wind farm containing multiple distributed power units, accurate fault warning can allow operation and maintenance personnel to give priority to abnormal units, ensure that other normal units continue to generate electricity, maintain the stability of the power output of the entire wind farm, and improve the power supply reliability of the power grid.

[0046] The distributed power supply data processing module is used to obtain the operating efficiency evaluation index of each distributed power supply unit through comprehensive analysis based on the power supply energy management data, environmental data and the abnormal working status evaluation value of each distributed power supply unit.

[0047] Specifically, the operation efficiency evaluation index of each distributed power supply unit is obtained through comprehensive analysis. The specific analysis process is: according to the power supply energy management data, the energy management abnormality index of each distributed power supply unit is obtained through processing.

[0048] It should be understood that in this embodiment, the power generation is obtained by the substation measurement equipment, and the power consumption is measured and obtained in the distribution box or distribution cabinet.

[0049] In a specific embodiment, the energy management abnormality index is obtained as follows: ; In the formula, represents the energy management anomaly index of the i-th distributed power unit, represents the power generation of the ith distributed power unit at the tth time point, represents the power consumption of the i-th distributed power unit at the t-th time point, represents the average energy efficiency of the i-th distributed power unit, represents the preset critical energy efficiency, represents the energy management abnormality impact weight corresponding to the preset energy efficiency, i represents the number of the distributed power supply unit, i=1, 2, 3, ..., k, k represents the total number of distributed power supply units, t represents the number of the distributed power supply unit, t=1, 2, 3, ..., m, m represents the total number of distributed power supply units.

[0050] For example, When in use, the energy management abnormality impact weight corresponding to the energy efficiency can be directly obtained from the distributed power supply database. The factor represents the numerical value of the influence degree of energy efficiency on the energy management abnormality index, and the corresponding relationship can be a pre-set mapping relationship. For example, the temperature of the distributed power supply unit and the energy management abnormality impact weight corresponding to the energy efficiency in the distributed power supply database form a mapping set, and the temperature of the distributed power supply unit is input into the mapping set to obtain the energy management abnormality impact weight corresponding to the energy efficiency. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0051] In this embodiment, the energy management abnormality index is used to quantitatively evaluate the abnormality of the energy management status of the distributed power supply unit. The higher the energy efficiency, the lower the corresponding energy management abnormality index, indicating that the energy management status of the distributed power supply unit is better.

[0052] The algorithm of this embodiment combines power generation and power consumption, and comprehensively analyzes to obtain the energy management anomaly index. In this formula, power generation and power consumption influence each other. Power generation reflects the energy production capacity of the power supply unit, and power consumption reflects the energy consumption demand. When the power generation can efficiently meet the power demand and minimize waste, the higher the energy utilization efficiency, the better the energy management of the power supply unit. By comprehensively analyzing the power generation and power consumption, the energy management anomaly index can be accurately obtained, which quantitatively reflects the rationality of the distributed power supply unit for energy utilization.

[0053] According to the environmental data, the environmental interference index of each distributed power supply unit is obtained through processing.

[0054] It should be understood that, in this embodiment, the temperature is measured and obtained by an infrared temperature sensor, the humidity is measured and obtained by a resistive humidity sensor, the light intensity is measured and obtained by a silicon photocell sensor, and the wind speed is measured and obtained by an ultrasonic anemometer.

[0055] In a specific embodiment, the environmental interference index is obtained in the following manner: ; In the formula, represents the environmental interference index of the i-th distributed power unit, represents the temperature of the i-th distributed power unit, represents the reference temperature, Indicates the preset allowable deviation temperature, represents the humidity of the i-th distributed power unit, represents the reference humidity, Indicates the preset allowable deviation humidity, represents the light intensity of the i-th distributed power unit, represents the reference light intensity, Indicates the preset allowable deviation light intensity, represents the wind speed of the i-th distributed power unit, represents the reference wind speed, Indicates the preset allowable deviation wind speed, Indicates the operating status impact weight corresponding to the preset temperature. Indicates the operating status impact weight corresponding to the preset humidity. Indicates the operating status impact weight corresponding to the preset light intensity. represents the operating state influence weight corresponding to the preset wind speed, i represents the number of the distributed power supply unit, i=1, 2, 3, ..., k, k represents the total number of distributed power supply units.

[0056] For example, , , and When in use, the operating status impact weights corresponding to the temperature, humidity, light intensity and wind speed can be directly obtained from the distributed power supply database. The factors respectively represent the numerical values ​​of the influence of the temperature, humidity, light intensity and wind speed on the operating status evaluation value, and the corresponding relationship can be a pre-set mapping relationship. For example, the temperature of the distributed power supply unit and the operating status impact weights corresponding to the temperature, humidity, light intensity and wind speed preset in the distributed power supply database form a mapping set, and the temperature of the distributed power supply unit is input into the mapping set to obtain the operating status impact weights corresponding to the temperature, humidity, light intensity and wind speed. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0057] In this embodiment, the environmental interference index is used to quantitatively evaluate the interference degree of the working environment of the distributed power supply unit. The smaller the deviation between the temperature and the reference value, or the smaller the deviation between the humidity and the reference value, or the smaller the deviation between the light intensity and the reference value, or the smaller the deviation between the wind speed and the reference value, the lower the corresponding environmental interference index, indicating that the environmental adaptability and performance impact of the distributed power supply unit are stronger.

[0058] The algorithm of this embodiment combines temperature, humidity, light intensity and wind speed, and comprehensively analyzes to obtain the abnormal working state evaluation value. In this formula, temperature, humidity, light intensity and wind speed affect each other. Compared with the reference temperature, too high or too low temperature will cause changes in the performance of electronic components inside the device, such as affecting the conductivity of semiconductor devices and reducing the charging and discharging efficiency of batteries. The lower the temperature, the higher the humidity of the air, which will cause the device to get damp, and then cause short circuit or corrosion, affecting the electrical insulation performance and mechanical structure stability of the device. The light intensity directly affects the power generation efficiency of distributed power sources that rely on light (such as solar photovoltaic power sources). The stronger the light intensity, the higher the temperature and the lower the humidity of the air. Compared with the reference light intensity, too strong light will cause the device to overheat, while too weak light will not provide enough energy to drive the device. Changes in light intensity will affect the photoelectric conversion efficiency of the device, and thus affect its output performance. Compared with the reference wind speed, a wind speed that is too high will exceed the design range of the equipment, resulting in damage to the mechanical structure, such as blade fatigue and tower vibration; a wind speed that is too low will not reach the rated power generation of the equipment, thus affecting its economic benefits and operational stability. By comprehensively analyzing temperature, humidity, light intensity and wind speed, the abnormal working state assessment value can be accurately obtained, which quantitatively reflects the comprehensive interference degree of the environmental conditions of the distributed power unit on its performance stability under normal operating conditions and the unit's adaptability to the environment.

[0059] According to the environmental interference index of each distributed power unit, the energy management abnormality index of each distributed power unit and the working status abnormality evaluation value of each distributed power unit, a comprehensive analysis is performed to obtain the operation efficiency evaluation index of each distributed power unit.

[0060] In a specific embodiment, the operation efficiency evaluation index is obtained as follows: ; In the formula, represents the operating efficiency evaluation index of the i-th distributed power unit, represents the environmental interference index of the i-th distributed power unit, represents the energy management anomaly index of the i-th distributed power unit, represents the abnormal working status evaluation value of the i-th distributed power supply unit, Indicates the impact weight of the operation efficiency evaluation corresponding to the preset environmental interference index. Indicates the impact weight of the operation efficiency assessment corresponding to the preset energy management abnormality index. represents the operating efficiency assessment impact weight corresponding to the preset working state abnormality assessment value, i represents the number of the distributed power supply unit, i=1, 2, 3, ..., k, k represents the total number of distributed power supply units.

[0061] In a specific embodiment, Figure 2 As shown, =0.2, =0.3, = 0.5, when =0.5, the functional relationship between the environmental interference index and the operating efficiency evaluation index is shown in curve a; when =0.8, the functional relationship between the environmental interference index and the operating efficiency evaluation index is shown in curve b; when =1.2, the functional relationship between the environmental interference index and the operation efficiency evaluation index is shown in curve c.

[0062] For example, , and When in use, the operating efficiency assessment influence weights corresponding to the environmental interference index, energy management abnormality index and working state abnormality evaluation value can be directly obtained from the distributed power supply database. The factors respectively represent the numerical values ​​of the influence of the environmental interference index, energy management abnormality index and working state abnormality evaluation value on the operating efficiency evaluation index. The corresponding relationship can be a pre-set mapping relationship. For example, the temperature of the distributed power supply unit and the operating efficiency assessment influence weights corresponding to the environmental interference index, energy management abnormality index and working state abnormality evaluation value preset in the distributed power supply database form a mapping set. The temperature of the distributed power supply unit is input into the mapping set to obtain the operating efficiency assessment influence weights corresponding to the environmental interference index, energy management abnormality index and working state abnormality evaluation value. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0063] In this embodiment, the operation efficiency evaluation index is used to quantitatively evaluate the overall operation status and performance level of the distributed power supply unit. The smaller the environmental interference index and the energy management abnormality index, the lower the abnormal evaluation value of the working state, and the higher the corresponding operation efficiency evaluation index, indicating that the overall operation status and performance level of the distributed power supply unit are higher.

[0064] The algorithm of this embodiment combines the environmental interference index, the energy management abnormality index and the working state abnormality evaluation value, and comprehensively analyzes to obtain the operation efficiency evaluation index. In this formula, the environmental interference index, the energy management abnormality index and the working state abnormality evaluation value affect each other. Changes in environmental factors will directly affect the working state of the equipment. For example, the higher the temperature, the lower the performance of the electronic components inside the equipment, and thus the greater the working state abnormality evaluation value. When the environmental interference index is smaller, it means that the negative impact of environmental factors such as temperature, humidity, light intensity and wind speed on its operation is smaller, and the energy utilization efficiency of the equipment is higher. Then, the lower the energy management abnormality index, the equipment can continue to operate stably under relatively stable environmental conditions, and the corresponding operation efficiency is higher. The smaller the energy management abnormality index, the more reasonable the power generation and power consumption are, the more efficient the energy utilization is, the fewer equipment failures and abnormal states are, the lower the working state abnormality evaluation value is, and the higher the corresponding operation efficiency is. The lower the working state abnormality evaluation value is, the stronger the reliability of the core components and the overall system of the equipment is, and the higher the overall operation status and performance level of the power supply unit is. By comprehensively analyzing the environmental interference index, energy management abnormality index and working status abnormality evaluation value, the operation efficiency evaluation index can be accurately obtained, which quantitatively reflects the all-round operation quality and comprehensive performance of the distributed power supply unit in a complex operating environment.

[0065] The distributed power supply intelligent scheduling module is used to intelligently schedule each distributed power supply unit according to the operation efficiency evaluation index of each distributed power supply unit.

[0066] Specifically, each distributed power supply unit is intelligently scheduled according to its operating efficiency evaluation index. The specific analysis process is: the operating efficiency evaluation index of each distributed power supply unit is compared with the operating efficiency evaluation index threshold preset in the distributed power supply database. If the operating efficiency evaluation index of a distributed power supply unit is greater than or equal to the operating efficiency evaluation index threshold, no additional operation is performed; if the operating efficiency evaluation index of a distributed power supply unit is less than the operating efficiency evaluation index threshold, the usage frequency of the distributed power supply unit is reduced.

[0067] It should be understood that the preset operating efficiency evaluation index threshold in this embodiment is directly obtained from the distributed power supply database, and is a key boundary for distinguishing whether the operating status of the power supply unit is up to standard. The operating efficiency evaluation index of each distributed power supply unit is compared with the operating efficiency evaluation index threshold preset in the distributed power supply database to determine the scheduling operation. If the operating efficiency evaluation index of a distributed power supply unit is greater than or equal to the operating efficiency evaluation index threshold, it indicates that the power supply unit operates well under the current working conditions, has excellent performance in all aspects, efficient energy management, strong environmental adaptability, and stable and reliable equipment, and can continuously and stably supply power, so no additional intervention is required. Maintaining its normal operation can ensure the stability of system power supply and energy utilization efficiency. On the contrary, if the operating efficiency evaluation index of a distributed power supply unit is less than the operating efficiency evaluation index threshold, it means that the power supply unit has deficiencies in energy conversion, environmental adaptation or equipment stability. Reducing its use frequency can prevent inefficient operation units from affecting the overall performance of the system, avoid the possible spread of fault risks, ensure that the system operates in the optimal performance state, improve the overall operating reliability and energy supply quality, and realize resource optimization configuration and intelligent scheduling management.

[0068] Specifically, based on the power supply energy management data, the energy management anomaly index of each distributed power supply unit is processed and obtained. The specific analysis process is: extracting the preset critical energy efficiency from the distributed power supply database; based on the power supply energy management data, a comprehensive analysis is performed to obtain the energy management anomaly index of each distributed power supply unit. The energy management anomaly index is used to quantitatively evaluate the degree of abnormality of the energy management status of the distributed power supply unit.

[0069] It should be understood that in this embodiment, the critical energy efficiency is directly obtained from the distributed power supply database and is used to construct a key reference system for evaluating the energy management status of distributed power supply units. If the energy efficiency is higher than the critical value, the energy management anomaly index decreases, indicating that energy utilization is scientific and management is efficient; conversely, when the energy efficiency is lower than the critical value, the energy management anomaly index increases, warning that there may be problems such as excessive energy loss, imbalance in power generation and use, or failure of management and control strategies in the energy management link. Through power supply energy management data, the operation and maintenance team can keenly identify weak links in energy management, optimize energy allocation strategies, accurately control equipment operating parameters, promptly check and correct sources of energy waste, improve the overall energy management level, and ensure that the distributed power supply system maintains efficient, economical, and reliable operation for a long time, which is in line with the strategic demands of sustainable energy development and the competitive needs of the energy market.

[0070] Specifically, according to the environmental data, the environmental interference index of each distributed power supply unit is obtained by processing, and the specific analysis process is: extracting the preset reference temperature, allowable deviation temperature, reference humidity, allowable deviation humidity, reference light intensity, allowable deviation light intensity, reference wind speed and allowable deviation wind speed from the distributed power supply database; according to the environmental data, a comprehensive analysis is performed to obtain the environmental interference index of each distributed power supply unit, and the environmental interference index is used to quantitatively evaluate the interference degree of the working environment of the distributed power supply unit.

[0071] It should be understood that the reference temperature, allowable deviation temperature, reference humidity, allowable deviation humidity, reference light intensity, allowable deviation light intensity, reference wind speed and allowable deviation wind speed preset in this embodiment are directly obtained from the distributed power supply database.

[0072] The distributed power database is used to store various information related to distributed power, including critical energy efficiency, reference temperature, allowable deviation temperature, reference humidity, allowable deviation humidity, critical light intensity, critical wind speed and critical abnormal interruption times. The data in the distributed power database can be obtained from channels such as smart grid management systems, renewable energy power station monitoring systems, and professional distributed power measurement and sensing equipment.

[0073] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. Intelligent dispatching system for distributed power coordination device, characterized by: include: A distributed power supply data acquisition module is used to collect distributed power supply operation data in real time through a distributed power supply coordination device and monitor environmental data. The distributed power supply operation data includes power supply working status data and power supply energy management data. The collected data is preliminarily processed and integrated to form a real-time data source set. A distributed power supply fault warning module is used to obtain an abnormal working state evaluation value of each distributed power supply unit according to the power supply working state data processing, and to issue a fault warning according to the abnormal working state evaluation value of each distributed power supply unit; The distributed power supply data processing module is used to obtain the operating efficiency evaluation index of each distributed power supply unit through comprehensive analysis based on the power supply energy management data, environmental data and the abnormal working status evaluation value of each distributed power supply unit; The distributed power supply intelligent scheduling module is used to intelligently schedule each distributed power supply unit according to the operation efficiency evaluation index of each distributed power supply unit.

2. According to claim 1, the intelligent dispatching system for distributed power coordination device is characterized by: The environmental data include temperature, humidity, light intensity and wind speed; Power supply working status data includes voltage, current, power generation, power factor and cumulative fault times; Power energy management data includes power generation and power consumption.

3. According to claim 1, the intelligent dispatching system for distributed power coordination device is characterized by: The collected data is preliminarily processed and integrated to form a real-time data source set. The specific analysis process is as follows: The collected distributed power supply operation data and environmental data are divided according to the collection time point to obtain the distributed power supply operation data and environmental data at each collection time point; The distributed power supply operation data and environmental data at each collection time point are integrated to obtain a real-time data source set.

4. According to claim 1, the intelligent dispatching system for distributed power coordination device is characterized by: The abnormal working state evaluation value of each distributed power supply unit is obtained by processing the power supply working state data. The specific analysis process is as follows: Extracting preset reference working voltage, allowable deviation working voltage, reference working current, allowable deviation working current, reference power generation, allowable deviation power generation, reference power factor, allowable deviation power factor and critical fault times from a distributed power database; According to the power supply working state data, a comprehensive analysis is performed to obtain the working state abnormality evaluation value of each distributed power supply unit, and the working state abnormality evaluation value is used to quantitatively evaluate the equipment output performance stability of the distributed power supply unit.

5. According to claim 1, the intelligent dispatching system for distributed power coordination device is characterized by: The fault warning is performed according to the abnormal evaluation value of the working state of each distributed power supply unit, and the specific analysis process is as follows: Compare the abnormal working state evaluation value of each distributed power supply unit with the abnormal working state evaluation value threshold preset in the distributed power supply database. If the abnormal working state evaluation value of a distributed power supply unit is greater than or equal to the preset abnormal working state evaluation threshold, the working state of the distributed power supply unit is abnormal, and a fault warning is issued. If the working state abnormality assessment value of a distributed power supply unit is less than a preset working state abnormality assessment threshold, the working state of the distributed power supply unit is normal.

6. The intelligent dispatching system for distributed power coordination device according to claim 1, characterized in that: The comprehensive analysis obtains the operating efficiency evaluation index of each distributed power supply unit. The specific analysis process is as follows: According to the power supply energy management data, the energy management abnormality index of each distributed power supply unit is obtained; According to the environmental data, the environmental interference index of each distributed power supply unit is obtained by processing; According to the environmental interference index of each distributed power unit, the energy management abnormality index of each distributed power unit and the working status abnormality evaluation value of each distributed power unit, a comprehensive analysis is performed to obtain the operation efficiency evaluation index of each distributed power unit.

7. The intelligent dispatching system for distributed power coordination device according to claim 1, characterized in that: The intelligent scheduling of each distributed power supply unit is performed according to the operation efficiency evaluation index of each distributed power supply unit. The specific analysis process is as follows: The operating efficiency evaluation index of each distributed power supply unit is compared with the operating efficiency evaluation index threshold preset in the distributed power supply database. If the operating efficiency evaluation index of a distributed power supply unit is greater than or equal to the operating efficiency evaluation index threshold, no additional operation is performed; if the operating efficiency evaluation index of a distributed power supply unit is less than the operating efficiency evaluation index threshold, the usage frequency of the distributed power supply unit is reduced.

8. The distributed power coordination device intelligent dispatching system according to claim 1, characterized in that: The operation efficiency evaluation index of each distributed power supply unit is obtained as follows: ； In the formula, represents the operating efficiency evaluation index of the i-th distributed power unit, represents the environmental interference index of the i-th distributed power unit, represents the energy management anomaly index of the i-th distributed power unit, represents the abnormal working status evaluation value of the i-th distributed power supply unit, Indicates the impact weight of the operation efficiency assessment corresponding to the preset environmental interference index. Indicates the impact weight of the operation efficiency assessment corresponding to the preset energy management abnormality index. represents the operating efficiency assessment impact weight corresponding to the preset working state abnormality assessment value, i represents the number of the distributed power supply unit, i=1, 2, 3, ..., k, k represents the total number of distributed power supply units.

9. The distributed power supply coordination device intelligent dispatching system according to claim 6, characterized in that: According to the power supply energy management data, the energy management abnormality index of each distributed power supply unit is obtained by processing, and the specific analysis process is as follows: Extracting preset critical energy efficiency from distributed power database; According to the power supply energy management data, the energy management abnormality index of each distributed power supply unit is obtained through comprehensive analysis. The energy management abnormality index is used to quantitatively evaluate the abnormality degree of the energy management status of the distributed power supply unit.

10. The distributed power supply coordination device intelligent dispatching system according to claim 6, characterized in that: According to the environmental data, the environmental interference index of each distributed power supply unit is obtained by processing, and the specific analysis process is as follows: Extracting preset reference temperature, allowable deviation temperature, reference humidity, allowable deviation humidity, reference light intensity, allowable deviation light intensity, reference wind speed and allowable deviation wind speed from a distributed power supply database; According to the environmental data, an environmental interference index of each distributed power supply unit is obtained through comprehensive analysis, and the environmental interference index is used to quantitatively evaluate the interference degree of the working environment of the distributed power supply unit.

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