Automatic stability control method and platform for complex working condition power system

Abstract

The invention discloses an automatic stability control method and platform for a complex working condition power system, and relates to the technical field of power system automation. Comprising the following steps: information acquisition: acquiring past information, equipment information and user basic information, wherein the past information comprises past weather information and past renewable energy trend; according to the invention, through the set matching prediction method, the predicted renewable energy trend can be predicted according to the real-time weather information, through the set matching method, the predicted power consumption trend can be predicted according to the real-time time period, and through predicting the renewable energy trend and the power consumption trend in the future time period, response and planning can be made in advance. The energy distribution is targeted, the power system can operate stably, the operation condition of the equipment is monitored in real time through the set monitoring and adjusting method, and the distributed energy is further optimized and adjusted according to the operation condition of the equipment, so that the economic benefit is ensured under the condition that the power system operates stably.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and in particular to an automated stable control method and platform for a power system under complex working conditions. Background Art

[0002] A complex operating power system refers to a power network that operates under multiple dynamic factors and uncertain conditions. These systems usually involve multiple power generation methods, different types of loads, access to renewable energy, energy storage equipment, and extensive connections to power grids. In order to cope with energy fluctuations in complex operating power systems, it is necessary to use automated stability control methods to ensure dynamic energy distribution to ensure the normal and smooth operation of equipment.

[0003] The patent publication number is CN118054480A, which is a method, device, equipment and medium for optimizing and dispatching an integrated energy and power system. The method provided by the invention uses the output power constraint information of each generator set in the integrated energy and power system to solve the first objective function, and obtains multiple objective solutions that enable the integrated energy and power system to be stable. The second objective function is solved using the multiple objective solutions to obtain the optimal objective solution among the multiple objective solutions that minimizes the operating cost of the integrated energy and power system, and the operation of the integrated energy and power system is coordinated using the optimal objective solution.

[0004] In the power supply management scenario of sewage treatment plants in urban power grids, sewage treatment plants rely on power systems to drive their pumps, agitators and other sewage treatment equipment. The power grid includes traditional thermal power and a large amount of distributed renewable energy. Due to the volatility of renewable energy generation and the dynamic changes in industrial loads within the plant, this complex working condition often leads to unstable power supply. In addition, the demand for electricity in the sewage treatment process fluctuates significantly in different time periods, especially during peak hours when the demand for electricity surges. The above-mentioned and similar methods cannot achieve advance predictive scheduling of areas where power shortages may occur during power dispatching, and are prone to sudden power shortages, which is not conducive to the stable operation of the power system. During the long-term use of the equipment, if there is a long-term power shortage, the equipment may be damaged, thereby increasing operating costs and reducing economic benefits. Therefore, the present invention is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an automated stable control method and platform for a power system under complex working conditions, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: an automatic stability control method for a complex working condition power system, the method comprising: Information acquisition: Acquisition of past information, equipment information and basic user information. Past information includes past weather information and past renewable energy trends. Basic user information is the address information of feedback information to the user. Equipment information includes equipment and operation information. Information processing: Based on the operation information, the equipment's previous power consumption time period and power consumption trend are extracted through an extraction method to obtain a target time period and a target power consumption trend, a storage library is established to store the target time period and the target power consumption trend, the correlation between the previous weather information and the previous renewable energy trend is established, the previous weather information is divided into multiple levels through a hierarchical classification method to obtain multi-level weather information, the previous energy information corresponding to the multi-level weather information is extracted based on the correlation to obtain the target energy, and a reference library is established to store the multi-level weather information and the target energy; Information matching: obtain real-time weather information and real-time time period, match the multi-level weather information corresponding to the real-time weather information in the reference library through the matching prediction method, and predict the real-time energy according to the target energy of the multi-level weather information to obtain the predicted renewable energy trend of the real-time weather information; Energy scheduling: Use the matching method to find the target time period corresponding to the real-time time period in the repository and extract the target power consumption trend corresponding to the target time period to obtain the predicted power consumption trend. Based on the predicted renewable energy trend and the predicted power consumption trend, the energy given to the equipment is scheduled and allocated through the scheduling method to obtain the allocated energy of the equipment. The scheduling method includes: dividing the power supply priority of the equipment based on the importance of the equipment, obtaining the node supplementary energy based on the relationship between the predicted renewable energy trend and the predicted electricity consumption trend, obtaining the total allocated energy by combining the predicted renewable energy trend with the node supplementary energy, allocating the total allocated energy to the equipment based on the predicted electricity consumption trend of the equipment, monitoring the operating status of the equipment in real time through the monitoring and adjustment method, further optimizing the energy allocation of the equipment, generating a work log to obtain an adjustment record, and sending the adjustment record to the user based on the user's basic information.

[0007] Furthermore, the monitoring and adjustment method includes: selecting a device as a monitoring object to obtain a target device, judging whether the operating information of the target device is in a normal working state, when the operating information of the target device is not in a normal working state, that is, the target device is under load, judging the importance of the target device based on the power supply priority to obtain a first priority result, acquiring devices around the target device to obtain surrounding devices, judging the importance of the surrounding devices based on the power supply priority to obtain a second priority result, eliminating the surrounding devices that exceed the first priority result in the second priority result to obtain a device to be adjusted, presetting a reduction unit, reducing the allocated energy of the device to be adjusted based on the reduction unit to obtain adjusted energy, allocating the adjusted energy to the target device, obtaining the adjusted energy and correspondingly allocating it to the device to be adjusted.

[0008] Furthermore, when the operating information of the target device is in a normal working state, the energy given to the target device is reduced based on the reduction unit, and whether the operating information of the target device is in a normal working state is judged based on the target device after the energy reduction. When the feedback is that the operating information of the target device is in a normal working state, the reduced allocated energy is further reduced based on the reduction unit until the feedback is that the operating information of the target device is not in a normal working state. When the feedback is that the operating information of the target device is not in a normal working state, the reduced allocated energy is restored by one reduction unit until the operating information of the target device is in a normal working state, and the device to be adjusted and the specific reduction unit of the device to be adjusted or the target device and the specific reduction unit of the target device are recorded to obtain an adjustment record.

[0009] Furthermore, the extraction method includes: presetting a paragraph length and a time unit, obtaining the previous power consumption time periods and the previous power consumption of the device based on the operation information, dividing the previous power consumption time into paragraphs based on the paragraph length to obtain a number of power consumption time periods, the power consumption time period being a target time period, obtaining the power consumption of a single time unit in the target time period to obtain a number of power consumptions, and constructing a function image based on the target time period and the power consumption of a single time unit in the target time period to obtain a target power consumption trend.

[0010] Furthermore, the grading method includes: presetting a time length, intercepting past weather information and past renewable energy trends based on the time length to obtain standard weather information and standard renewable energy information, obtaining factors affecting the generation of renewable energy based on the generator set that generates renewable energy to obtain target factors, extracting target factors in the standard weather information to obtain specific values, judging the relationship between the change in specific values ​​and the amount of renewable energy generated to obtain a guidance relationship, the guidance relationship includes a positive guidance or a negative guidance, presetting a division level, the division level includes a first target level, a second target level and a third target level, presetting a medium renewable energy range based on the standard renewable energy information, extracting the two endpoints of the medium renewable energy range to obtain To the first renewable energy source and the second renewable energy source, specific values ​​of target factors in the standard weather information of the first renewable energy source and the second renewable energy source are extracted based on the correlation to obtain the first information and the second information. The weather information in which the specific values ​​of the target factors in the standard weather information are between the first information and the second information is the second target level. The weather information in which the specific values ​​of the target factors in the standard weather information exceed the first information and the second information is the first target level. The weather information in which the specific values ​​of the target factors in the standard weather information do not exceed the first information and the second information is the third target level. The weather information of the first target level, the weather information of the second level and the weather information of the third level are integrated to obtain multi-level weather information.

[0011] Furthermore, the matching prediction method includes: presetting a matching frequency, updating real-time weather information based on the matching frequency, extracting specific numerical values ​​of target factors in the real-time weather information to obtain real-time values, judging the level of real-time values ​​based on multi-level weather information to obtain target level weather, selecting weather information in the target level weather that is closest to the real-time value based on the real-time value coordination and guidance relationship to obtain pre-selected weather information, and extracting standard renewable energy information corresponding to the pre-selected weather information based on correlation to obtain predicted renewable energy trends.

[0012] Furthermore, the matching method includes: extracting a target time period corresponding to the real-time time period in the storage repository to obtain a number of reference time periods, determining the date features of the real-time time period and the reference time period to obtain a feature result, determining whether there is a reference time period whose feature result is consistent with the real-time time period, and when there is a reference time period whose feature result is consistent with the real-time time period, extracting the reference time period whose feature result is consistent with the real-time time period to obtain a selected time period, extracting a target power consumption trend in the storage repository based on the selected time period to obtain a predicted power consumption trend, and when there is no reference time period whose feature result is consistent with the real-time time period, extracting a target power consumption trend in the storage repository based on the reference time period and averaging the target power consumption trend to obtain a predicted power consumption trend.

[0013] An automatic stability control platform for a power system under complex working conditions uses the above-mentioned automatic stability control method for a power system under complex working conditions.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The automated stable control method and platform for complex working condition power systems can predict the renewable energy trend based on real-time weather information through a set matching prediction method, and can predict the electricity consumption trend based on real-time time period prediction through a set matching method. By predicting the renewable energy trend and electricity consumption trend in future time periods, responses and plans can be made in advance, so that energy allocation is targeted and the power system can operate stably. The operating status of the equipment is monitored in real time through the set monitoring and adjustment method, and the allocated energy is further optimized and adjusted according to the operating status of the equipment, so as to ensure economic benefits under the condition of stable operation of the power system.

[0015] At the same time, in the monitoring and adjustment method, when it is found that the operating information of the target device is not in a normal working state, the regulated energy of the device with a lower priority than the target device is reduced, and the regulated energy is allocated to the target device to ensure the normal operation of the target device. When the allocated energy to the target device reaches the highest power and there is still a load, an error is reported and fed back to the user. By reducing the energy of the target device in a normal working state and monitoring whether it is in a normal working state, it can save resources and improve economic benefits. In the matching prediction method, by presetting the matching frequency, the real-time weather information can be updated to improve the accuracy of energy scheduling, thereby improving the economic benefits and the stability of the power system. Through the guiding relationship, the selected predicted renewable energy trend can be combined with the node to supplement the energy to have redundancy to cope with transmission losses, which is conducive to ensuring the stable operation of the equipment.

[0016] At the same time, the multi-level weather information is divided into multiple levels through the set level division method to obtain multi-level weather information. The level division is used to facilitate the subsequent real-time weather matching, so as to reduce the matching calculation amount, reduce system occupancy, and improve matching efficiency. The power supply priority of the equipment is divided based on the importance of the equipment. Through priority division, important equipment is given priority in energy scheduling to ensure the efficiency of sewage treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the structure of the information processing and information matching stages of the present invention; Figure 2 It is a schematic diagram of the structure of the energy dispatching stage of the present invention; Figure 3 It is a schematic diagram of the structure of the scheduling method of the present invention; Figure 4 It is a schematic diagram of the structure of predicting renewable energy trend and predicting electricity consumption trend of the present invention; Figure 5 This is a schematic diagram of the node energy supplement structure of the present invention; Figure 6 It is a schematic diagram of the hierarchical structure of the present invention. DETAILED DESCRIPTION

[0018] 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.

[0019] During the sewage treatment process, in order to ensure the efficiency of sewage treatment and extend the service life of equipment, it is necessary to ensure the stable operation of the power system. By allocating the energy of the equipment on demand in real time, the stable operation of the system can be guaranteed and the operating costs can be reduced while ensuring economic benefits.

[0020] like Figure 1-Figure 6 As shown, the present invention provides a technical solution: an automatic stability control method for a complex working condition power system, the method comprising: Information acquisition: Acquisition of past information, equipment information and basic user information. Past information includes past weather information and past renewable energy trends. Basic user information is the address information of feedback information to the user. Equipment information includes equipment and operation information. Information processing: Based on the operation information, the equipment's previous power consumption time period and power consumption trend are extracted through an extraction method to obtain a target time period and a target power consumption trend, a storage library is established to store the target time period and the target power consumption trend, the correlation between the previous weather information and the previous renewable energy trend is established, the previous weather information is divided into multiple levels through a hierarchical classification method to obtain multi-level weather information, the previous energy information corresponding to the multi-level weather information is extracted based on the correlation to obtain the target energy, and a reference library is established to store the multi-level weather information and the target energy; Information matching: obtain real-time weather information and real-time time period, match the multi-level weather information with the highest similarity to the real-time weather information in the reference library through the matching prediction method, and predict the real-time energy according to the target energy of the multi-level weather information to obtain the predicted renewable energy trend of the real-time weather information; Energy scheduling: Use the matching method to find the target time period corresponding to the real-time time period in the repository and extract the target power consumption trend corresponding to the target time period to obtain the predicted power consumption trend. Based on the predicted renewable energy trend and the predicted power consumption trend, the energy given to the equipment is scheduled and allocated through the scheduling method to obtain the allocated energy of the equipment. It should be noted that, in the information acquisition stage, past weather information can be obtained by querying the previous weather forecast of the area according to the location of the sewage treatment plant. At the same time, before the method is put into use, the staff can also record weather samples. The accuracy of past weather information is required. The more accurate the past weather information is, the higher the subsequent energy scheduling efficiency and the higher the economic benefits will be. Past renewable energy trends can be directly obtained through the operating data of the generator sets in the sewage treatment plant. Equipment information can be obtained by the staff querying the operating data and model of the equipment. User basic information includes but is not limited to the user's IP address, telephone number and email address. In the information processing stage, based on the operating information of the equipment, the set extraction method is used to extract the equipment's past power consumption time period and power consumption trend to obtain the target time period and target power consumption trend. The target time period corresponds to the target power consumption trend. Past weather information is associated with past renewable energy trends. The set level division method is used to divide the past weather information into multiple levels to obtain multi-level weather information. The levels are divided to facilitate subsequent real-time weather processing. Matching is performed to reduce the amount of matching calculations, reduce system occupancy, and improve matching efficiency. The reference library is set to store multi-level weather and target energy for subsequent matching. Multi-level weather includes past weather information. Multi-level weather is the result of classifying past weather information. The target energy is consistent with the past energy information. In the information matching stage, real-time weather information is obtained by obtaining the real-time weather at the location of the sewage treatment plant. The real-time time period is determined according to usage requirements. The specific time interval can be 1 hour, for example, the real-time time period is 1:00-2:00. Through the set matching prediction method, multi-level weather information corresponding to the real-time weather information is found in the reference library, and the real-time energy is predicted according to the target energy of the multi-level weather information to obtain the predicted renewable energy trend of the real-time weather information. In the energy scheduling stage, through the set matching method, the target time period corresponding to the real-time time period is found in the storage library and the target power consumption trend of the target time period is extracted to obtain the predicted power consumption trend. The equipment is energy scheduled according to the predicted renewable energy trend and the predicted power consumption trend through the set scheduling method.

[0021] like Figure 4 and Figure 5 As shown, the scheduling method includes: dividing the power supply priority of the equipment based on the importance of the equipment, obtaining the node supplementary energy based on the relationship between the predicted renewable energy trend and the predicted power consumption trend, obtaining the total allocated energy by combining the predicted renewable energy trend with the node supplementary energy, allocating the total allocated energy to the equipment based on the predicted power consumption trend of the equipment, monitoring the operating status of the equipment in real time through the monitoring and adjustment method, further optimizing the energy allocation of the equipment, generating a work log to obtain an adjustment record, and sending the adjustment record to the user based on the user's basic information.

[0022] It should be noted that the process of dividing the power supply priority of equipment based on the importance of the equipment is to ensure that important equipment is given priority in energy scheduling through priority division to ensure the efficiency of sewage treatment. The specific division can be divided according to actual usage needs, for example: high-priority equipment: sewage pumps, fans and other key equipment should be given priority in power supply at any time period, low-priority equipment: lighting, heating and other non-critical equipment can be adjusted or temporarily shut down during peak hours, the time unit of the predicted renewable energy trend is the same as the predicted electricity consumption trend, specifically a time segment, and the node supplementary energy can be obtained by judging the relationship between the predicted renewable energy trend and the predicted electricity consumption trend. The node supplementary energy is the node where the renewable energy generated by the generator set cannot meet the predicted electricity consumption trend. Refers to a certain point in time when the predicted renewable energy trend is greater than or equal to the predicted electricity consumption trend. At this time, the node supplementary energy is 0. The total allocated energy is obtained by combining the predicted renewable energy trend with the node supplementary energy. In this process, the node supplementary energy is consistent with the node that cannot meet the predicted electricity consumption trend in the predicted renewable energy trend. By supplementing the node supplementary energy, the total allocated energy can meet the predicted electricity consumption trend. The total allocated energy distributes energy to the equipment according to the predicted electricity consumption trend, and then monitors the operating status of the equipment in real time through the set monitoring and adjustment method, and further optimizes and adjusts the allocated energy according to the operating status of the equipment, so as to ensure economic benefits under the condition of stable operation of the power system. By generating adjustment records and feeding back to users, users can understand the optimized units. Figure 4 Figure a is a schematic diagram of the structure for predicting electricity consumption trends. Figure 4 Figure b is a schematic diagram of the structure for predicting renewable energy trends. Figure 5 For combination Figure 4 a and b in the figure are schematic diagrams of node energy supplement structure.

[0023] like Figure 3 As shown, the monitoring and adjustment method includes: selecting a device as a monitoring object to obtain a target device, judging whether the operating information of the target device is in a normal working state, when the operating information of the target device is not in a normal working state, that is, the target device is under load, judging the importance of the target device based on the power supply priority to obtain a first priority result, acquiring devices around the target device to obtain surrounding devices, judging the importance of the surrounding devices based on the power supply priority to obtain a second priority result, eliminating the surrounding devices that exceed the first priority result in the second priority result to obtain a device to be adjusted, presetting a reduction unit, reducing the allocated energy of the device to be adjusted based on the reduction unit to obtain an adjusted energy, allocating the adjusted energy to the target device, and obtaining the adjusted energy and correspondingly allocating it to the device to be adjusted.

[0024] It should be noted that in the process of selecting equipment as the monitoring object to obtain the target equipment, the equipment can be randomly selected or all equipment can be monitored at the same time. Random selection can reduce system occupancy, but the effect of optimizing the equipment and generating economic benefits is not very good. Monitoring all equipment at the same time will occupy a large system, but the effect of optimizing the equipment and generating emergency benefits is good. It can be selected according to the actual usage. In the process of judging whether the operation information of the target equipment is in a normal working state, the target equipment can be judged based on the operation information of the previous target equipment. At the same time, the operating current of the equipment motor is also monitored by the current sensor. Usually, the current should be within the rated range. If the current is significantly higher than the normal value, it may indicate that the equipment is overloaded; if the current is lower than the normal range, it may indicate that the equipment is not loaded or a fault occurs. For example, for a sewage pump, the load can be judged in the following ways: high current + high flow = normal load: the current and flow of the pump are both higher than the baseline value; low current + low flow = no load: the current and flow of the pump are both lower than the baseline value; High current + low flow = overload or failure: The pump has high current but low flow, and the pump may be blocked or damaged. The importance of the target device is determined based on the power supply priority to obtain the second priority result, and then the power supply priority of the devices around the target device is obtained to obtain the second priority result. When the target device is loaded, the regulated energy of the devices with a lower priority than the target device is reduced according to the power supply priority, and the regulated energy is allocated to the target device to ensure the normal operation of the target device. For example, based on the reduction unit, the energy of non-critical equipment such as lighting and heating is reduced, and the energy is allocated to critical equipment such as sewage pumps and fans. By reducing the energy of the surrounding equipment and allocating time to reduce the load of the target equipment, it is beneficial to ensure the operation of important equipment to improve the overall operation stability. The reduction unit can be formulated according to the actual usage, specifically to reduce the energy of a specific value. At the same time, the regulated energy is obtained and allocated to the adjustment equipment accordingly to ensure the normal operation of the adjustment equipment and facilitate use. When the allocated energy to the target device reaches the highest power and there is still load, an error is reported and fed back to the user.

[0025] When the operating information of the target device is in a normal working state, the energy given to the target device is reduced based on the reduction unit, and whether the operating information of the target device is in a normal working state is judged based on the target device after the energy reduction. When the feedback is that the operating information of the target device is in a normal working state, the reduced allocated energy is further reduced based on the reduction unit until the feedback is that the operating information of the target device is not in a normal working state. When the feedback is that the operating information of the target device is not in a normal working state, the reduced allocated energy is restored by one reduction unit until the operating information of the target device is in a normal working state, and the device to be adjusted and the specific reduction unit of the device to be adjusted or the target device and the specific reduction unit of the target device are recorded to obtain an adjustment record.

[0026] It should be noted that by reducing the energy of the target device in normal working state and monitoring whether it is in normal working state, it can save resources and improve economic benefits. By continuously reducing the energy given to the target device based on the reduction unit until the operating information of the target device is not in normal working state, and restoring a reduction unit after the operating information of the target device is not in normal working state, it can reduce energy consumption and save resources while ensuring the stable operation of the target device. By recording the specific reduction units of the device to be adjusted and the device to be adjusted or the target device and the specific reduction units of the target device to obtain the adjustment record, it can be convenient for users to understand the adjustment process and facilitate use.

[0027] like Figure 2 As shown, the extraction method includes: presetting a paragraph length and a time unit, acquiring the previous power consumption time period and the previous power consumption of the equipment based on the operation information, dividing the previous power consumption time into paragraphs based on the paragraph length to obtain a number of power consumption time periods, the power consumption time period being a target time period, obtaining the power consumption of a single time unit in the target time period to obtain a number of power consumptions, and constructing a function image based on the target time period and the power consumption of a single time unit in the target time period to obtain a target power consumption trend.

[0028] It should be noted that the paragraph length is determined according to actual usage, and the time unit is determined according to actual usage needs, specifically the unit of expressing time, such as seconds, minutes and hours. The paragraph length can be consistent with the real-time time period, and the previous power consumption time period and previous power consumption of the equipment are obtained through operating information. The previous power consumption time is divided into paragraphs based on the paragraph length to obtain several power consumption time periods consistent with the paragraph length. The power consumption of a single time unit in the past power consumption is obtained by combining the target time period with the time unit, and several power consumptions can be obtained. The target power consumption trend can be obtained by constructing a function image based on the power consumption of the target time period and the time unit.

[0029] like Figure 1 and Figure 6As shown, the grading method includes: presetting a time length, intercepting past weather information and past renewable energy trends based on the time length to obtain standard weather information and standard renewable energy information, obtaining factors affecting the generation of renewable energy based on the generator set that generates renewable energy to obtain target factors, extracting target factors in the standard weather information to obtain specific values, judging the relationship between the change of specific values ​​and the amount of renewable energy generated to obtain a guiding relationship, the guiding relationship includes a positive guiding relationship or a negative guiding relationship, presetting a grading level, the grading level includes a first target level, a second target level and a third target level, presetting a medium renewable energy range based on the standard renewable energy information, extracting two endpoints of the medium renewable energy range to obtain the first renewable energy and the second renewable energy, extracting specific values ​​of target factors in the standard weather information of the first renewable energy and the second renewable energy based on the correlation to obtain the first information and the second information, the weather information whose specific values ​​of the target factors in the standard weather information are between the first information and the second information is the second target level, the weather information whose specific values ​​of the target factors in the standard weather information exceed the first information and the second information is the first target level, the weather information whose specific values ​​of the target factors in the standard weather information do not exceed the first information and the second information is the third target level, and integrating the weather information of the first target level, the weather information of the second level and the weather information of the third level to obtain multi-level weather information.

[0030] It should be noted that the time length is consistent with the paragraph length. The process of obtaining the factors affecting the generation of renewable energy based on the generator set that generates renewable energy to obtain the target factor is obtained according to the use demand of the generator set. For example, the target factor of the wind generator set is wind power, and the target factor of the solar generator set is solar energy. The relationship between the change in specific value and the amount of renewable energy generated is judged to obtain the guiding relationship. The guiding relationship is how the renewable energy generated by the generator set will change when the specific value increases or decreases. The guiding relationship includes positive guidance or negative guidance. The positive guidance is that if the specific value increases, the renewable energy generated by the generator set will increase, and if the specific value decreases, the renewable energy generated by the generator set will decrease. The negative guidance is that if the specific value decreases, the renewable energy generated by the generator set will increase, and if the specific value increases, the renewable energy generated by the generator set will decrease. Through the preset classification level, all past weather information can be graded to reduce the system occupancy of subsequent matching and facilitate use. The process of presetting the medium renewable energy range based on the standard renewable energy information, the medium renewable energy range can be selected according to the range in the middle of all standard renewable energy information.

[0031] like Figure 1As shown, the matching prediction method includes: presetting a matching frequency, updating real-time weather information based on the matching frequency in real time, extracting specific values ​​of target factors in the real-time weather information to obtain real-time values, judging the level of the real-time value based on multi-level weather information to obtain target level weather, selecting weather information in the target level weather that is closest to the real-time value based on the real-time value coordination and guidance relationship to obtain pre-selected weather information, and extracting standard renewable energy information corresponding to the pre-selected weather information based on the correlation to obtain predicted renewable energy trends.

[0032] It should be noted that the matching frequency can be set according to actual usage and can be consistent with the time length. The weather will change over time. By presetting the matching frequency, the real-time weather information can be updated to improve the accuracy of energy scheduling, thereby improving the economic benefits and stability of the power system. Based on the real-time value and the guiding relationship, the weather information closest to the real-time value in the target level weather is selected to obtain the pre-selected weather information. When the guiding relationship is positive, the closest weather information lower than the real-time value is selected to obtain the pre-selected weather information. When the guiding relationship is negative, the closest weather information higher than the real-time value is selected to obtain the pre-selected weather information. Based on the correlation, the standard renewable energy information corresponding to the pre-selected weather information is extracted to obtain the predicted renewable energy trend.

[0033] like Figure 2 As shown, the matching method includes: extracting a target time period corresponding to the real-time time period in a storage repository to obtain a number of reference time periods, judging the date features of the real-time time period and the reference time period to obtain a feature result, judging whether there is a reference time period with a feature result consistent with the real-time time period, when there is a reference time period with a feature result consistent with the real-time time period, extracting the reference time period with a feature result consistent with the real-time time period to obtain a selected time period, extracting a target power consumption trend corresponding to the selected time period in the storage repository to obtain a predicted power consumption trend, and when there is no reference time period with a feature result consistent with the real-time time period, extracting a target power consumption trend corresponding to the reference time period in the storage repository and averaging the target power consumption trend to obtain a predicted power consumption trend.

[0034] It should be noted that the process of determining the date characteristics of the real-time time period and the reference time period to obtain the characteristic results is to obtain two characteristic results by analyzing the date characteristics of the real-time time period and the date characteristics of the reference time period, compare the characteristic results and select the corresponding reference time period to obtain the selected time period. Specifically, the process of determining the date characteristics is to analyze whether the dates of the real-time time period and the reference time period are on working days or holidays, etc.

[0035] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. An automatic stability control method for a complex working condition power system, characterized by: The method comprises: Information acquisition: Acquisition of past information, equipment information and basic user information. Past information includes past weather information and past renewable energy trends. Basic user information is the address information of feedback information to the user. Equipment information includes equipment and operation information. Information processing: Based on the operation information, the equipment's previous power consumption time period and power consumption trend are extracted through an extraction method to obtain a target time period and a target power consumption trend, a storage library is established to store the target time period and the target power consumption trend, the correlation between the previous weather information and the previous renewable energy trend is established, the previous weather information is divided into multiple levels through a hierarchical classification method to obtain multi-level weather information, the previous energy information corresponding to the multi-level weather information is extracted based on the correlation to obtain the target energy, and a reference library is established to store the multi-level weather information and the target energy; Information matching: obtain real-time weather information and real-time time period, match the multi-level weather information corresponding to the real-time weather information in the reference library through the matching prediction method, and predict the real-time energy according to the target energy of the multi-level weather information to obtain the predicted renewable energy trend of the real-time weather information; Energy scheduling: Use the matching method to find the target time period corresponding to the real-time time period in the repository and extract the target power consumption trend corresponding to the target time period to obtain the predicted power consumption trend. Based on the predicted renewable energy trend and the predicted power consumption trend, the energy given to the equipment is scheduled and allocated through the scheduling method to obtain the allocated energy of the equipment. The scheduling method includes: dividing the power supply priority of the equipment based on the importance of the equipment, obtaining the node supplementary energy based on the relationship between the predicted renewable energy trend and the predicted electricity consumption trend, obtaining the total allocated energy by combining the predicted renewable energy trend with the node supplementary energy, allocating the total allocated energy to the equipment based on the predicted electricity consumption trend of the equipment, monitoring the operating status of the equipment in real time through the monitoring and adjustment method, further optimizing the energy allocation of the equipment, generating a work log to obtain an adjustment record, and sending the adjustment record to the user based on the user's basic information.

2. The method for automatic stability control of a power system under complex working conditions according to claim 1, characterized in that: The monitoring and adjustment method includes: selecting a device as a monitoring object to obtain a target device, judging whether the operation information of the target device is in a normal working state, when the operation information of the target device is not in a normal working state, that is, the target device is under load, judging the importance of the target device based on the power supply priority to obtain a first priority result, acquiring devices around the target device to obtain surrounding devices, judging the importance results of the surrounding devices based on the power supply priority to obtain a second priority result, eliminating the surrounding devices that exceed the first priority results in the second priority results to obtain a device to be adjusted, presetting a reduction unit, reducing the allocated energy of the device to be adjusted based on the reduction unit to obtain an adjusted energy, allocating the adjusted energy to the target device, and acquiring the adjusted energy and correspondingly allocating it to the device to be adjusted.

3. The method for automatic stability control of a power system under complex working conditions according to claim 2 is characterized in that: When the operating information of the target device is in a normal working state, the energy given to the target device is reduced based on the reduction unit, and whether the operating information of the target device is in a normal working state is judged based on the target device after the energy reduction. When the feedback is that the operating information of the target device is in a normal working state, the reduced allocated energy is further reduced based on the reduction unit until the feedback is that the operating information of the target device is not in a normal working state. When the feedback is that the operating information of the target device is not in a normal working state, the reduced allocated energy is restored by one reduction unit until the operating information of the target device is in a normal working state, and the device to be adjusted and the specific reduction unit of the device to be adjusted or the target device and the specific reduction unit of the target device are recorded to obtain an adjustment record.

4. The method for automatic stability control of a power system under complex working conditions according to claim 1, characterized in that: The extraction method includes: presetting a paragraph length and a time unit, acquiring the previous power consumption time period and the previous power consumption of the device based on the operation information, dividing the previous power consumption time into paragraphs based on the paragraph length to obtain a plurality of power consumption time periods, the power consumption time period being a target time period, obtaining the power consumption of a single time unit in the target time period to obtain a plurality of power consumptions, and constructing a function image based on the target time period and the power consumption of a single time unit in the target time period to obtain a target power consumption trend.

5. The method for automatic stability control of a power system under complex working conditions according to claim 1 is characterized in that: The grading method includes: presetting a time length, intercepting past weather information and past renewable energy trends based on the time length to obtain standard weather information and standard renewable energy information, obtaining factors affecting the generation of renewable energy based on the generator set that generates renewable energy to obtain target factors, extracting target factors in the standard weather information to obtain specific values, judging the relationship between the change of specific values ​​and the amount of renewable energy generated to obtain a guiding relationship, wherein the guiding relationship includes a positive guiding relationship or a negative guiding relationship, presetting a grading level, wherein the grading level includes a first target level, a second target level, and a third target level, presetting a medium renewable energy range based on the standard renewable energy information, extracting two endpoints of the medium renewable energy range to obtain the first renewable energy and the second renewable energy, extracting specific values ​​of target factors in the standard weather information of the first renewable energy and the second renewable energy based on correlation to obtain the first information and the second information, weather information whose specific values ​​of the target factors in the standard weather information are between the first information and the second information is the second target level, weather information whose specific values ​​of the target factors in the standard weather information exceed the first information and the second information is the first target level, weather information whose specific values ​​of the target factors in the standard weather information do not exceed the first information and the second information is the third target level, and integrating the weather information of the first target level, the weather information of the second level, and the weather information of the third level to obtain multi-level weather information.

6. The method for automatic stability control of a power system under complex working conditions according to claim 5, characterized in that: The matching prediction method includes: presetting a matching frequency, updating real-time weather information in real time based on the matching frequency, extracting specific values ​​of target factors in the real-time weather information to obtain real-time values, judging the level of the real-time values ​​based on multi-level weather information to obtain target level weather, selecting weather information in the target level weather that is closest to the real-time value based on the real-time value coordination and guidance relationship to obtain pre-selected weather information, and extracting standard renewable energy information corresponding to the pre-selected weather information based on correlation to obtain predicted renewable energy trends.

7. The method for automatic stability control of a power system under complex working conditions according to claim 1, characterized in that: The matching method includes: extracting a target time period corresponding to a real-time time period in a storage repository to obtain a plurality of reference time periods, determining date features of the real-time time period and the reference time period to obtain a feature result, determining whether there is a reference time period whose feature result is consistent with the real-time time period, and when there is a reference time period whose feature result is consistent with the real-time time period, extracting the reference time period whose feature result is consistent with the real-time time period to obtain a selected time period, extracting a target power consumption trend corresponding to the selected time period in the storage repository to obtain a predicted power consumption trend, and when there is no reference time period whose feature result is consistent with the real-time time period, extracting a target power consumption trend corresponding to the reference time period in the storage repository and averaging the target power consumption trends to obtain a predicted power consumption trend.

8. An automated stable control platform for complex working condition power systems, characterized by: An automated stability control method for a power system under complex operating conditions as described in any one of claims 1 to 7 is used.

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