A methanol generator set based on artificial intelligence

Abstract

This invention belongs to the field of methanol generator technology and relates to an artificial intelligence-based methanol generator set. By analyzing the operating status of the target methanol generator set, this invention helps to promptly detect anomalies and predict potential faults, ensuring the stable operation of the target methanol generator set. By predicting the load demand of the target methanol generator set during the predicted time period, it helps to ensure its fuel supply and avoid the risk of insufficient power generation or shutdown due to fuel shortages. By analyzing the current fuel supply matching degree of the target methanol generator set, it helps to dynamically adjust its power generation, improving its power generation efficiency and energy utilization rate. By obtaining the actual load demand of the target methanol generator set during the current time period, it helps to quickly adjust its output power and the charging and discharging strategy of the energy storage system, helping to smooth power fluctuations and ensuring the stable operation of the power system.

Description

Technical Field

[0001] This invention belongs to the field of methanol generator technology and relates to a methanol generator set based on artificial intelligence. Background Technology

[0002] A methanol generator set is a device that uses methanol as fuel to generate electricity. With the continuous growth of global energy demand and the increasing severity of environmental problems, new energy power generation systems have become a focus of attention. Methanol, as a new energy fuel, has advantages such as high calorific value, wide availability, and clean combustion. Methanol generator sets utilize methanol as fuel to generate electricity through a chemical reaction, offering advantages such as environmental friendliness, high efficiency, and sustainability. Furthermore, the operational stability of methanol generator sets is crucial for ensuring the safe and stable operation of the power system.

[0003] Existing methanol generator sets can basically meet the usage requirements, but they still have some shortcomings: On the one hand, existing methanol generator sets can generate electricity normally and meet basic load requirements. However, existing methanol generator sets lack real-time monitoring of their operation, so they cannot detect abnormalities in a timely manner, and thus cannot predict potential failures in advance, providing maintenance personnel with sufficient time for inspection and maintenance. Furthermore, existing methanol generator sets also neglect to predict load demand in future periods, thus failing to ensure sufficient fuel supply during peak power generation periods and failing to avoid the risk of insufficient power generation or shutdown due to fuel shortages.

[0004] On the other hand, existing methanol generator sets can change their fuel supply to change their power generation. However, existing methanol generator sets lack the ability to detect and analyze the matching of fuel supply and load demand. As a result, they cannot dynamically adjust their fuel supply according to the power generation demand of the methanol generator set, thus failing to avoid waste and unnecessary cost expenditures caused by fuel surplus. Furthermore, they cannot understand the real-time load status of the methanol generator set, thus failing to smooth power fluctuations and ensure the stable operation of the power system. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background technology, an artificial intelligence-based methanol generator set is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: This invention provides a methanol generator set based on artificial intelligence, including: a generator set operation detection and analysis module, a load demand prediction module, a fuel supply matching degree analysis module, a fuel supply control module, a load detection and analysis module, an energy storage scheduling control module, and an information storage database.

[0007] The generator set operation detection and analysis module is connected to the load demand prediction module, the load demand prediction module is connected to the fuel supply matching degree analysis module, the fuel supply matching degree analysis module is connected to the fuel supply control module and the load detection and analysis module respectively, the load detection and analysis module is connected to the energy storage dispatch control module, and the information reserve is connected to the generator set operation detection and analysis module and the load demand prediction module respectively.

[0008] The generator set operation detection and analysis module is used to perform real-time operation detection on the target methanol generator set, obtain the operating parameter information of the target methanol generator set, analyze the operating status of the target methanol generator set, and determine its maintenance needs.

[0009] The load demand forecasting module is used to obtain historical load data of the target methanol generator set and forecast the load demand of the target methanol generator set during the forecast period.

[0010] The fuel supply matching degree analysis module is used to obtain the current fuel supply information parameters of the target methanol generator set, analyze the current fuel supply matching degree of the target methanol generator set, and determine the fuel supply control requirements of the target methanol generator set. If the control requirements are required, the fuel supply control module is executed; otherwise, the load detection analysis module is executed.

[0011] The fuel supply control module is used to control the fuel supply to the target methanol generator set.

[0012] The load detection and analysis module is used to detect the actual load of the target methanol generator set in real time, obtain the actual load demand of the target methanol generator set in the current time period, and determine the energy storage scheduling demand of the target methanol generator set. If it is a scheduling demand, the energy storage scheduling control module is executed.

[0013] The energy storage scheduling control module is used to control the energy storage scheduling of the target methanol generator set.

[0014] The information repository is used to store historical load data of the target methanol generator set, the minimum combustion efficiency to ensure normal operation of the target methanol generator set, the standard air-methanol mixing ratio and the standard engine speed of the target methanol generator set.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. By acquiring the operating parameter information of the target methanol generator set and analyzing the operating status of the target methanol generator set, the present invention helps to promptly detect abnormal conditions of the target methanol generator set, predict potential faults in advance, provide maintenance personnel with sufficient time for inspection and maintenance, reduce the impact of sudden faults on production, and ensure the stable operation of the target methanol generator set.

[0016] 2. By predicting the load demand of the target methanol generator set during the predicted time period, this invention helps to understand the changing trend of the power generation demand of the target methanol generator set in advance, which helps to ensure that there is sufficient fuel supply during the peak power generation period and avoid the risk of insufficient power generation or shutdown due to fuel shortage.

[0017] 3. By analyzing the current fuel supply matching degree of the target methanol generator set and judging the fuel supply control requirements of the target methanol generator set, this invention is conducive to dynamically adjusting the power generation of the target methanol generator set, improving its power generation efficiency and energy utilization rate, avoiding waste and unnecessary cost expenditures caused by fuel surplus, and also reducing the reduction in power generation and economic loss caused by fuel shortage.

[0018] 4. This invention obtains the actual load demand of the target methanol generator set within the current time period, and determines the energy storage scheduling demand of the target methanol generator set accordingly. This helps to understand the real-time load status of the target methanol generator set, thereby quickly adjusting its output power and the charging and discharging strategy of the energy storage system, ensuring its supply and demand balance, avoiding power shortages or surpluses, helping to smooth power fluctuations, and ensuring the stable operation of the power system. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the system module connections of the present invention. Detailed Implementation

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0022] Please see Figure 1As shown, this invention provides an artificial intelligence-based methanol generator set, with the following module distribution: a generator set operation detection and analysis module, a load demand prediction module, a fuel supply matching degree analysis module, a fuel supply control module, a load detection and analysis module, an energy storage dispatch control module, and an information reserve database. The modules are connected as follows: the generator set operation detection and analysis module is connected to the load demand prediction module; the load demand prediction module is connected to the fuel supply matching degree analysis module; the fuel supply matching degree analysis module is connected to both the fuel supply control module and the load detection and analysis module; the load detection and analysis module is connected to the energy storage dispatch control module; and the information reserve database is connected to both the generator set operation detection and analysis module and the load demand prediction module.

[0023] The generator set operation detection and analysis module is used to perform real-time operation detection on the target methanol generator set, obtain the operating parameter information of the target methanol generator set, analyze the operating status of the target methanol generator set, and determine its maintenance needs.

[0024] As a preferred example of feasibility, the operating parameter information of the target methanol generator set includes combustion efficiency, output voltage fluctuation coefficient, air-to-methanol mixing ratio, and engine speed.

[0025] It should be further explained that the specific method for obtaining the combustion efficiency of the target methanol generator set is as follows: the methanol consumption of the target methanol generator set is detected by a flow meter installed inside the target methanol generator set to obtain the methanol consumption of the target methanol generator set within a set fixed detection period. The power generation of the target methanol generator set within the set fixed detection period is directly extracted from the target methanol generator set. Then, the power generation of the target methanol generator set within the set fixed detection period is compared with its methanol consumption, and the quotient is recorded as the combustion efficiency of the target methanol generator set.

[0026] The specific method for obtaining the output voltage fluctuation coefficient of the target methanol generator set is as follows: the output voltage of the target methanol generator set is detected using deployed voltmeters, and the output voltage of the target methanol generator set at each detection is obtained. ,in , The corresponding number for each test. The number of tests, according to the analysis formula. ,in The set permissible fluctuation value for the output voltage.

[0027] The specific method for obtaining the air-to-methanol mixing ratio of the target methanol generator set is as follows: the air-to-methanol mixing ratio of the target methanol generator set is extracted from the maintenance record table of the target methanol generator set.

[0028] The specific method for obtaining the engine speed of the target methanol generator set is as follows: the engine speed of the target methanol generator set is directly measured using deployed speed sensors.

[0029] As a preferred feasibility example, the analysis of the target methanol generator set's operation requires constructing an operation evaluation coefficient. The specific analysis method includes extracting the target methanol generator set's combustion efficiency, output voltage fluctuation coefficient, air-to-methanol mixing ratio, and engine speed, respectively denoted as... Analyze the operational evaluation coefficients of the target methanol generator set. ,in The minimum combustion efficiency required to ensure the normal operation of the target methanol generator set is extracted from the information reserve. The target methanol generator set's output voltage fluctuation coefficient threshold is set. To extract the standard air-to-methanol mixing ratio and standard engine speed of the target methanol generator set from the information reserve, The permissible difference between the set air-to-methanol mixing ratio and the standard air-to-methanol mixing ratio, and the permissible difference between the engine speed and its standard speed.

[0030] The operation evaluation coefficient of the target methanol generator set is compared with the set operation evaluation coefficient threshold. If the operation evaluation coefficient of the target methanol generator set is less than the operation evaluation coefficient threshold, the maintenance requirement of the target methanol generator set is recorded as a maintenance requirement; otherwise, the maintenance requirement of the target methanol generator set is recorded as a maintenance requirement.

[0031] It should be further explained that the maintenance requirement for the target methanol generator set is that maintenance is required when necessary.

[0032] Specifically, (1) Regularly inspect and clean burner components such as nozzles, flexible couplings, and flame detectors.

[0033] (2) Keep the fuel system clean and clean the fuel tank and fuel filter regularly.

[0034] (3) Check the tightness of the electrical connections to ensure there is no looseness or corrosion.

[0035] (4) Regularly clean the dust and oil stains on the surface and inside of the generator set.

[0036] This invention obtains the operating parameter information of the target methanol generator set and analyzes its operating status, which helps to promptly detect abnormalities in the target methanol generator set, predict potential faults in advance, provide maintenance personnel with sufficient time for inspection and maintenance, reduce the impact of sudden faults on production, and ensure the stable operation of the target methanol generator set.

[0037] The load demand forecasting module is used to obtain historical load data of the target methanol generator set and forecast the load demand of the target methanol generator set during the forecast period.

[0038] As a preferred example of feasibility, the historical load data of the target methanol generator set includes the load demand for each time period corresponding to each historical date.

[0039] As a preferred feasible example, the specific method for obtaining the predicted time period in the load demand of the target methanol generator set includes: extracting the load demand of each historical date corresponding to each time period of the target methanol generator set, determining the load demand of each historical date corresponding to each time period of the target methanol generator set that corresponds to the current date, and recording it as the load demand of each historical reference date corresponding to each time period of the target methanol generator set.

[0040] The current time point is recorded as the reference starting time point. Further, from the load demand of each historical reference date corresponding to each time period of the target methanol generator set, the continuous time periods corresponding to the historical reference dates of the target methanol generator set with the reference starting time point as the starting time point and the load demand are determined, and these are recorded as the reference continuous time periods corresponding to the historical reference dates of the target methanol generator set.

[0041] The overlapping time periods in the reference continuous time period corresponding to each historical reference date of the target methanol generator set are recorded as the prediction time period of the target methanol generator set.

[0042] As a preferred feasibility example, the specific method for predicting the load demand of the target methanol generator set during the forecast period includes: extracting the load demand of the target methanol generator set for each historical date corresponding to each time period, and extracting the load demand of the target methanol generator set for each historical reference date corresponding to the forecast period. ,in , The corresponding number for each historical reference date. The quantity corresponding to the historical reference date, according to the analysis formula. Obtain the load demand of the target methanol generator set during the predicted time period. ,in The compensation value corresponds to the load demand of the target methanol generator set.

[0043] As a preferred feasible example, the specific method for obtaining the compensation value corresponding to the load demand of the target methanol generator set includes: extracting the load demand of the target methanol generator set corresponding to the predicted time period for each historical date from the load demand of each historical date corresponding to each time period of the target methanol generator set, using the load demand of the target methanol generator set corresponding to the predicted time period for each historical reference date as the reference date, and extracting the load demand of the target methanol generator set corresponding to the predicted time period for each historical date corresponding to the historical compensation date of the target methanol generator set for a set number of days in advance and backward, and recording it as the load demand of the target methanol generator set corresponding to the predicted time period for each historical compensation date. ,in , For each historical compensation date, The number of historical compensation dates, according to the analysis formula Obtain the compensation value corresponding to the load demand of the target methanol generator set. .

[0044] This invention helps to understand the changing trend of the power generation demand of the target methanol generator set in advance by predicting the load demand of the target methanol generator set during the predicted period. This helps to ensure that there is sufficient fuel supply during the peak power generation period and avoid the risk of insufficient power generation or shutdown due to fuel shortage.

[0045] The fuel supply matching degree analysis module is used to obtain the current fuel supply information parameters of the target methanol generator set, analyze the current fuel supply matching degree of the target methanol generator set, and determine the fuel supply control requirements of the target methanol generator set. If the control requirements are required, the fuel supply control module is executed; otherwise, the load detection analysis module is executed.

[0046] As a preferred example of feasibility, the fuel supply information parameters of the target methanol generator set include the methanol supply amount and the temperature and pressure of the combustion chamber.

[0047] It should be further explained that the methanol supply, combustion chamber temperature and pressure of the target methanol generator set are obtained by directly detecting the methanol supply, combustion chamber temperature and pressure of the target methanol generator set from the flow meter of the target methanol generator set and the temperature sensor and pressure gauge installed in the combustion chamber.

[0048] As a preferred feasibility example, the specific method for determining the fuel supply control demand of the target methanol generator set includes: matching the load demand of the target methanol generator set during the predicted time period with the reference methanol supply, reference temperature, and reference pressure of the combustion chamber corresponding to each load demand in the information reserve, to obtain the reference methanol supply, reference temperature, and reference pressure of the combustion chamber for the target methanol generator set, denoted as […]. .

[0049] The methanol supply, combustion chamber temperature, and pressure of the target methanol generator set are extracted and denoted as follows: Analyze the current fuel supply matching degree of the target methanol generator set. ,in These are the permissible differences between the set methanol supply and the reference methanol supply, the permissible differences between the combustion chamber temperature and its reference temperature, and the permissible differences between the combustion chamber pressure and its reference pressure, respectively.

[0050] The current fuel supply matching degree of the target methanol generator set is compared with the set fuel supply matching degree threshold. If the current fuel supply matching degree of the target methanol generator set is less than the fuel supply matching degree threshold, the fuel supply control demand of the target methanol generator set is a control demand; otherwise, the fuel supply control demand of the target methanol generator set is a control demand.

[0051] The fuel supply control module is used to control the fuel supply to the target methanol generator set.

[0052] As a preferred example of feasibility, the specific operation of controlling the fuel supply of the target methanol generator set includes: obtaining the current load demand of the target methanol generator set, subtracting it from the load demand of the target methanol generator set during the predicted time period, and obtaining the difference between the current load demand of the target methanol generator set and the load demand during the predicted time period. .

[0053] when At the same time, reduce the methanol supply to the target methanol generator set or lower the temperature and pressure of the combustion chamber of the target methanol generator set.

[0054] It should be further explained that the specific operation of reducing the methanol supply of the target methanol generator set or reducing the temperature and pressure of the combustion chamber of the target methanol generator set is as follows: reduce the methanol supply of the target methanol generator set to its minimum methanol supply, calculate the difference between the current load demand of the target methanol generator set and the predicted time period, and if it is still greater than zero, further reduce the temperature and pressure of the combustion chamber of the target methanol generator set until the difference between the current load demand of the target methanol generator set and the predicted time period is equal to zero.

[0055] when At the same time, the methanol supply to the target methanol generator set, as well as the temperature and pressure of the combustion chamber, are kept constant.

[0056] when At the same time, increase the methanol supply to the target methanol generator set or increase the temperature and pressure of the combustion chamber of the target methanol generator set.

[0057] It should be further explained that the specific operation of increasing the methanol supply of the target methanol generator set or increasing the temperature and pressure of the combustion chamber of the target methanol generator set is as follows: increase the methanol supply of the target methanol generator set to its maximum methanol supply, calculate the difference between the current load demand of the target methanol generator set and the predicted time period, and if it is still less than zero, further increase the temperature and pressure of the combustion chamber of the target methanol generator set until the difference between the current load demand of the target methanol generator set and the predicted time period is equal to zero.

[0058] This invention analyzes the current fuel supply matching degree of the target methanol generator set and determines the fuel supply control requirements of the target methanol generator set. This helps to dynamically adjust the power generation of the target methanol generator set, improve its power generation efficiency and energy utilization, avoid waste and unnecessary cost expenditures caused by fuel surplus, and reduce the reduction in power generation and economic loss caused by fuel shortage.

[0059] The load detection and analysis module is used to detect the actual load of the target methanol generator set in real time, obtain the actual load demand of the target methanol generator set in the current time period, and determine the energy storage scheduling demand of the target methanol generator set. If it is a scheduling demand, the energy storage scheduling control module is executed.

[0060] As a preferred feasibility example, the specific method for determining the energy storage dispatch demand of the target methanol generator set includes: extracting the actual load demand of the target methanol generator set in the current time period, subtracting it from the load demand of the target methanol generator set in the predicted time period, and obtaining the difference between the load demand of the target methanol generator set in the current time period and the predicted time period. .

[0061] If the difference between the load demand of the target methanol generator set in the current time period and the predicted time period is 0, then the energy storage dispatch demand of the target methanol generator set is recorded as no dispatch demand; otherwise, the energy storage dispatch demand of the target methanol generator set is recorded as dispatch demand.

[0062] The energy storage scheduling control module is used to control the energy storage scheduling of the target methanol generator set.

[0063] As a preferred feasible example, the energy storage scheduling of the controlled target methanol generator set specifically includes the following operations: when When necessary, dispatching is carried out from the energy storage system of the target methanol generator set. The load.

[0064] when At that time, storage will be performed in the energy storage system of the target methanol generator set. The load.

[0065] The information storage database is used to store historical load data of the target methanol generator set, the minimum combustion efficiency to ensure normal operation of the target methanol generator set, the standard air-methanol mixing ratio and the standard engine speed of the target methanol generator set.

[0066] This invention obtains the actual load demand of the target methanol generator set within the current time period, and determines the energy storage scheduling demand of the target methanol generator set accordingly. This helps to understand the real-time load status of the target methanol generator set, thereby quickly adjusting its output power and the charging and discharging strategy of the energy storage system, ensuring its supply and demand balance, avoiding power shortages or surpluses, helping to smooth power fluctuations, and ensuring the stable operation of the power system.

[0067] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A methanol generator set based on artificial intelligence, characterized in that: include: The generator set operation detection and analysis module is used to perform real-time operation detection of the target methanol generator set, obtain the operating parameter information of the target methanol generator set, analyze the operating status of the target methanol generator set, and determine its maintenance needs. The load demand forecasting module is used to acquire historical load data of the target methanol generator set and forecast the load demand of the target methanol generator set during the forecast period. The fuel supply matching degree analysis module is used to obtain the current fuel supply information parameters of the target methanol generator set, analyze the current fuel supply matching degree of the target methanol generator set, and determine the fuel supply control requirements of the target methanol generator set. If the control requirements are required, the fuel supply control module is executed; otherwise, the load detection analysis module is executed. The fuel supply control module is used to control the fuel supply to the target methanol generator set. The load detection and analysis module is used to detect the actual load of the target methanol generator set in real time, obtain the actual load demand of the target methanol generator set in the current time period, and determine the energy storage scheduling demand of the target methanol generator set. If it is a scheduling demand, the energy storage scheduling control module is executed. The energy storage dispatch control module is used to control the energy storage dispatch of the target methanol generator set; The information storage database is used to store historical load data of the target methanol generator set, the minimum combustion efficiency to ensure normal operation of the target methanol generator set, the standard air-methanol mixing ratio and the standard engine speed of the target methanol generator set. The operating parameters of the target methanol generator set include combustion efficiency, output voltage fluctuation coefficient, air-to-methanol mixing ratio, and engine speed. The historical load data of the target methanol generator set includes the load demand for each historical date and time period. The fuel supply information parameters of the target methanol generator set include the methanol supply amount and the temperature and pressure of the combustion chamber.

2. The methanol generator set based on artificial intelligence according to claim 1, characterized in that: The analysis of the target methanol generator set's operation requires the construction of an operation evaluation coefficient, the specific analysis methods of which include: The combustion efficiency, output voltage fluctuation coefficient, air-to-methanol mixing ratio, and engine speed of the target methanol generator set were extracted and denoted as follows: Analyze the operational evaluation coefficients of the target methanol generator set. ,in The minimum combustion efficiency required to ensure the normal operation of the target methanol generator set is extracted from the information reserve. The target methanol generator set's output voltage fluctuation coefficient threshold is set. To extract the standard air-to-methanol mixing ratio and standard engine speed of the target methanol generator set from the information reserve, The permissible difference between the set air-to-methanol mixing ratio and the standard air-to-methanol mixing ratio, and the permissible difference between the engine speed and its standard speed; The operation evaluation coefficient of the target methanol generator set is compared with the set operation evaluation coefficient threshold. If the operation evaluation coefficient of the target methanol generator set is less than the operation evaluation coefficient threshold, the maintenance requirement of the target methanol generator set is recorded as a maintenance requirement; otherwise, the maintenance requirement of the target methanol generator set is recorded as a maintenance requirement.

3. The methanol generator set based on artificial intelligence according to claim 1, characterized in that: The specific methods for obtaining the predicted time period from the load demand of the target methanol generator set include: Extract the load demand of each historical date corresponding to each time period of the target methanol generator set, and determine the load demand of each historical date corresponding to each time period of the target methanol generator set that corresponds to the current date. Record these as the load demand of each historical reference date corresponding to each time period of the target methanol generator set. The current time point is recorded as the reference starting time point. Further, from the load demand of each historical reference date corresponding to each time period of the target methanol generator set, the continuous time period corresponding to each historical reference date of the target methanol generator set with the reference starting time point as the starting time point and the load demand is consistent, is determined and recorded as the reference continuous time period corresponding to each historical reference date of the target methanol generator set. The overlapping time periods in the reference continuous time period corresponding to each historical reference date of the target methanol generator set are recorded as the prediction time period of the target methanol generator set.

4. A methanol generator set based on artificial intelligence according to claim 3, characterized in that: The specific prediction method for the load demand of the target methanol generator set during the predicted time period includes: Extract the load demand for each historical date corresponding to each time period of the target methanol generator set, and then extract the load demand for each historical reference date corresponding to the predicted time period of the target methanol generator set. ,in , The corresponding number for each historical reference date. The quantity corresponding to the historical reference date, according to the analysis formula. Obtain the load demand of the target methanol generator set during the predicted time period. ,in The compensation value corresponds to the load demand of the target methanol generator set.

5. A methanol generator set based on artificial intelligence according to claim 4, characterized in that: The specific methods for obtaining the compensation value corresponding to the load demand of the target methanol generator set include: The load demand for each historical date corresponding to each time period of the target methanol generator set is extracted from the load demand for each historical reference date corresponding to the predicted time period of the target methanol generator set, using the load demand for each historical reference date corresponding to the predicted time period of the target methanol generator set as the reference date. The load demand for each historical date corresponding to the predicted time period of the target methanol generator set is extracted forward and backward by a set number of days, and recorded as the load demand for each historical compensation date corresponding to the predicted time period of the target methanol generator set. ,in , For each historical compensation date, The number of historical compensation dates, according to the analysis formula Obtain the compensation value corresponding to the load demand of the target methanol generator set. .

6. A methanol generator set based on artificial intelligence according to claim 4, characterized in that: The specific methods for determining the fuel supply control requirements of the target methanol generator set include: The load demand of the target methanol generator set during the predicted time period is matched with the reference methanol supply, combustion chamber temperature, and reference pressure corresponding to each load demand in the information reserve to obtain the reference methanol supply, combustion chamber temperature, and reference pressure of the target methanol generator set, denoted as [reference values ​​would be inserted here]. ; The methanol supply, combustion chamber temperature, and pressure of the target methanol generator set are extracted and denoted as follows: Analyze the current fuel supply matching degree of the target methanol generator set. ,in These are the permissible differences between the set methanol supply and the reference methanol supply, the permissible differences between the combustion chamber temperature and its reference temperature, and the permissible differences between the combustion chamber pressure and its reference pressure, respectively. The current fuel supply matching degree of the target methanol generator set is compared with the set fuel supply matching degree threshold. If the current fuel supply matching degree of the target methanol generator set is less than the fuel supply matching degree threshold, the fuel supply control demand of the target methanol generator set is a control demand; otherwise, the fuel supply control demand of the target methanol generator set is a control demand.

7. A methanol generator set based on artificial intelligence according to claim 6, characterized in that: The specific operations of controlling the fuel supply of the target methanol generator set include: Obtain the current load demand of the target methanol generator set, and subtract it from the load demand of the target methanol generator set during the predicted time period to obtain the difference between the current and predicted load demand of the target methanol generator set. ; when At the same time, reduce the methanol supply to the target methanol generator set or lower the temperature and pressure of the combustion chamber of the target methanol generator set; when At the same time, maintain the methanol supply of the target methanol generator set and the temperature and pressure of the combustion chamber at a constant level; when At the same time, increase the methanol supply to the target methanol generator set or increase the temperature and pressure of the combustion chamber of the target methanol generator set.

8. A methanol generator set based on artificial intelligence according to claim 7, characterized in that: The specific methods for determining the energy storage dispatch requirements of the target methanol generator set include: Extract the actual load demand of the target methanol generator set for the current time period, and subtract it from the load demand of the target methanol generator set for the predicted time period to obtain the load demand difference between the current and predicted time periods. ; If the difference between the load demand of the target methanol generator set in the current time period and the predicted time period is 0, then the energy storage dispatch demand of the target methanol generator set is recorded as no dispatch demand; otherwise, the energy storage dispatch demand of the target methanol generator set is recorded as dispatch demand.

9. A methanol generator set based on artificial intelligence according to claim 8, characterized in that: The specific operations of the energy storage scheduling of the controlled target methanol generator set include: when When necessary, dispatching is carried out from the energy storage system of the target methanol generator set. The load; when At that time, storage will be performed in the energy storage system of the target methanol generator set. The load.

Images