A method and system for intelligent scheduling of carbon capture in a thermal power plant

Abstract

The application discloses a thermal power plant carbon capture intelligent scheduling method and system, comprising: obtaining the power generation power of each time of the generator set in the thermal power plant, and generating a power generation power time relationship diagram; according to the power generation power time relationship diagram, extracting the power mutation point of the power generation power and the corresponding mutation time in the target time period; calculating the time interval between each power mutation point and the preset power point; based on the time interval corresponding to the power mutation point of multiple target time periods, obtaining the number distribution information of the power mutation point on different time intervals; according to the number distribution information, determining the time point of power mutation as the scheduling time point of the thermal power plant carbon capture system; according to the scheduling time point, obtaining the current flue gas parameter of the coal-fired power plant generator set, and dynamically optimizing the carbon capture system operation strategy according to the current power generation power, flue gas parameter and preset power grid carbon quota data.

Description

Technical Field

[0001] This invention relates to the field of carbon capture technology, and in particular to an intelligent scheduling method and system for carbon capture in thermal power plants. Background Technology

[0002] Carbon capture technology refers to a series of technologies that separate, collect, and compress carbon dioxide generated from industrial, energy, or other emission sources for subsequent storage or utilization. It is a crucial means of mitigating climate change, playing a particularly important role in high-carbon-emission industries such as thermal power generation.

[0003] In thermal power plants, carbon capture systems (CCS) do not operate at full capacity continuously; adjustments are needed based on the plant's power generation. However, existing CCS systems can only adjust based on real-time power generation, making it impossible to anticipate and adjust accordingly, resulting in slow response times. Given the high energy consumption and significant response delay of CCS systems, they cannot be accurately and efficiently scheduled to operate at appropriate loads when coal-fired power plant loads fluctuate greatly. This leads to low utilization rates of CCS systems when capturing carbon from coal-fired power plants. Frequent operation at inappropriate loads accelerates solvent degradation and increases the risk of corrosion. Furthermore, the high energy consumption of CCS systems depletes the unit's peak-shaving capacity, preventing timely carbon capture at high loads during peak periods. Summary of the Invention

[0004] This invention provides an intelligent scheduling method and system for carbon capture in thermal power plants, which solves the technical problems of large response delays and inability to accurately and efficiently schedule carbon capture systems to operate at appropriate loads in existing technologies, resulting in low utilization rates of carbon capture systems when capturing carbon in coal-fired power plants.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide an intelligent scheduling method for carbon capture in thermal power plants, comprising:

[0006] Obtain the power generation of the generator units in the thermal power plant at each moment, and generate a power generation time relationship graph based on the power generation.

[0007] Based on the power generation time relationship diagram, extract the power abrupt change points of the power generation within the target time period, and determine the abrupt change time corresponding to each power abrupt change point;

[0008] Based on the abrupt change time, calculate the time shift interval between each power abrupt change point and the preset power point;

[0009] Based on the time shift intervals corresponding to the power mutation points in multiple target time periods, the number of power mutation points in different time shift intervals is recorded to obtain the distribution information of the number of power mutation points in different time shift intervals;

[0010] The timing of power mutations is determined based on the quantity distribution information and used as the scheduling timing of the carbon capture system in the thermal power plant.

[0011] Based on the scheduling time point, the current flue gas parameters of the coal-fired power plant generator units are obtained, and the carbon capture system operation strategy is dynamically optimized based on the current power generation, flue gas parameters, and preset grid carbon quota data.

[0012] As a preferred embodiment, the step of obtaining the power generation of the generator units in the thermal power plant at each moment and generating a power generation time relationship diagram based on the power generation specifically includes:

[0013] Real-time acquisition of the power generation capacity of generator units in thermal power plants at every moment;

[0014] Extract the power generation within the target time period and its corresponding time, and construct a power generation time relationship graph within the target time period; wherein, the horizontal axis of the power generation time relationship graph is time, the vertical axis is power generation, and the power generation corresponding to each time is fitted into a power generation curve.

[0015] As a preferred embodiment, the step of extracting power abrupt change points of the power generation within the target time period based on the power generation time relationship diagram, and determining the abrupt change time corresponding to each power abrupt change point, specifically includes:

[0016] In the power generation time relationship diagram, all power generation points within the target time period are determined, and the power slope of each power generation point on the power generation curve is calculated.

[0017] The power generation point where the absolute value of the power slope is greater than the preset value is taken as the power mutation point of the power generation within the target time period;

[0018] Extract the time point of the corresponding power change point from the power generation time relationship graph and use it as the change time.

[0019] As a preferred embodiment, the step of calculating the time shift interval between each power mutation point and a preset power point based on the mutation time specifically includes:

[0020] Based on the preset power point, power mutation points that are less than the power generation power corresponding to the preset power point are eliminated to obtain the final power mutation point;

[0021] The abrupt change times corresponding to the final power change points are statistically analyzed, and the time difference between each time point and the preset power point is calculated as the time shift interval; wherein, the preset power point is the critical power point for the carbon capture system to start.

[0022] As a preferred embodiment, the step of recording the number of power mutation points in different time shift intervals based on the power mutation points in multiple target time periods, and obtaining the distribution information of the number of power mutation points in different time shift intervals, specifically includes:

[0023] Acquire and record the time shift intervals corresponding to the power mutation points of multiple target time periods;

[0024] Based on different time shift intervals, the number of corresponding power mutation points is recorded, and each time shift interval is arranged according to a preset order to obtain the distribution information of the number of power mutation points in the time shift interval under the preset order.

[0025] As a preferred embodiment, determining the time point of power abrupt change based on the quantity distribution information as the scheduling time point of the carbon capture system of the thermal power plant specifically includes:

[0026] In the quantity distribution information, the time-shift intervals corresponding to the number of power mutation points exceeding a preset threshold are extracted to obtain the time-shift interval adjustment points;

[0027] Based on the time corresponding to the preset power point, and combined with the time difference between the time shift interval itself and the preset power point, the time corresponding to each time shift interval adjustment point is calculated, which serves as the scheduling time point for the carbon capture system of the thermal power plant.

[0028] As a preferred embodiment, the step of obtaining the current flue gas parameters of the coal-fired power plant generating units based on the scheduling time point, and dynamically optimizing the carbon capture system operation strategy based on the current power generation, flue gas parameters, and preset grid carbon quota data, specifically includes:

[0029] Based on the aforementioned scheduling time point, the current flue gas parameters and power generation of the coal-fired power plant generator units are obtained in real time.

[0030] The current power generation capacity, current flue gas parameters, and preset grid carbon quota data are input into a preset adjustment agent for optimization decision-making, and the optimized operation strategy of the carbon capture system is output.

[0031] Based on the optimized operating strategy, the carbon capture system is scheduled and adjusted.

[0032] Accordingly, the present invention also provides an intelligent scheduling system for carbon capture in thermal power plants, comprising:

[0033] The power generation module is used to acquire the power generation of the generator units in the thermal power plant at each moment, and generate a power generation time relationship diagram based on the power generation.

[0034] The mutation module is used to extract the power mutation points of the power generation within the target time period based on the power generation time relationship diagram, and to determine the mutation time corresponding to each power mutation point.

[0035] The time-shift interval module is used to calculate the time-shift interval between each power mutation point and a preset power point based on the mutation time.

[0036] The quantity distribution module is used to record the number of power mutation points in different time shift intervals based on the time shift intervals corresponding to the power mutation points in multiple target time periods, and to obtain the quantity distribution information of the power mutation points in different time shift intervals.

[0037] The scheduling timing module is used to determine the timing of power mutations based on the quantity distribution information, and to serve as the scheduling timing of the carbon capture system of the thermal power plant.

[0038] The operation strategy module is used to obtain the current flue gas parameters of the coal-fired power plant generator units according to the scheduling time point, and dynamically optimize the operation strategy of the carbon capture system based on the current power generation, flue gas parameters and preset grid carbon quota data.

[0039] Accordingly, the present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the intelligent scheduling method for carbon capture in thermal power plants as described above.

[0040] Accordingly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the intelligent scheduling method for carbon capture in thermal power plants as described above.

[0041] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0042] The technical solution of this invention obtains the power generation of generator units in a thermal power plant at each moment, extracts the power abrupt change points of the power generation within a target time period, and then calculates the time shift interval between each power abrupt change point and a preset power point. Based on the time shift intervals of multiple target time periods, it obtains the quantity distribution information of power abrupt change points in different time shift intervals. This allows the scheduling time point of the carbon capture system in the thermal power plant to be determined through the quantity distribution information. Furthermore, in subsequent adjustments, the corresponding power generation, flue gas parameters, and preset grid carbon quota data can be obtained in real time at the scheduling time point to dynamically optimize the carbon capture system's operating strategy. This invention avoids the need for existing technologies to continuously acquire current power generation data and perform related detection and calculations before optimizing the carbon capture system's scheduling. However, for coal-fired power plants with large load fluctuations, real-time data acquisition and optimization can lead to response delays. This invention, on the other hand, can determine the scheduling time point in advance, thereby directly acquiring power generation, flue gas parameters, and preset grid carbon quota data at the scheduling time point. This reduces the intermediate calculation process, improves response efficiency, reduces the computational resources required for large amounts of data, and improves the overall system's accuracy and responsiveness. As a result, the carbon capture system can be accurately and efficiently scheduled to operate at an appropriate load. Attached Figure Description

[0043] Figure 1 : A flowchart illustrating the steps of an intelligent carbon capture scheduling method for thermal power plants provided in an embodiment of the present invention;

[0044] Figure 2 : This is a structural diagram of an intelligent carbon capture and dispatching system for thermal power plants provided in an embodiment of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Example 1

[0047] Please refer to Figure 1 The present invention provides an intelligent scheduling method for carbon capture in thermal power plants, comprising the following steps S101-S106:

[0048] S101: Obtain the power generation of the generator units in the thermal power plant at each moment, and generate a power generation time relationship diagram based on the power generation.

[0049] As a preferred embodiment, the step of obtaining the power generation of the generator units in the thermal power plant at each moment and generating a power generation time relationship diagram based on the power generation specifically includes:

[0050] Real-time acquisition of the power generation capacity of generator units in thermal power plants at every moment;

[0051] Extract the power generation within the target time period and its corresponding time, and construct a power generation time relationship graph within the target time period; wherein, the horizontal axis of the power generation time relationship graph is time, the vertical axis is power generation, and the power generation corresponding to each time is fitted into a power generation curve.

[0052] In this embodiment, the power generation of the generator units in the thermal power plant at each moment can be obtained by installing high-precision power sensors in the distributed control system (DCS) or supervisory data acquisition and monitoring system (SCADA) of the thermal power plant to monitor the power generation of the generator units in real time, and preprocess the collected data, including noise removal, filling missing values, and calibrating timestamps, to ensure the accuracy and availability of the data.

[0053] In this embodiment, by extracting the power generation and its corresponding time within the target time period, and using the corresponding time as the horizontal axis and the power generation as the vertical axis, and using a mathematical fitting method, preferably cubic spline interpolation or polynomial fitting, the power generation data is fitted to generate a smooth power generation curve, thus obtaining a power generation time relationship graph within the target time period.

[0054] S102: Based on the power generation time relationship diagram, extract the power abrupt change points of the power generation within the target time period, and determine the abrupt change time corresponding to each power abrupt change point.

[0055] As a preferred embodiment, the step of extracting power abrupt change points of the power generation within the target time period based on the power generation time relationship diagram, and determining the abrupt change time corresponding to each power abrupt change point, specifically includes:

[0056] In the power generation time relationship diagram, all power generation points within the target time period are determined, and the power slope of each power generation point on the power generation curve is calculated.

[0057] The power generation point where the absolute value of the power slope is greater than the preset value is taken as the power mutation point of the power generation within the target time period;

[0058] Extract the time point of the corresponding power change point from the power generation time relationship graph and use it as the change time.

[0059] In this embodiment, all power generation points are determined from the power generation time relationship diagram. For each power generation point, its power slope on the power generation curve is calculated. The power slope can be approximated by dividing the power difference between adjacent power points by the corresponding time difference. The power slope quantifies the rate of power change. When the absolute value of the power slope exceeds a preset value, it means that a significant power change has occurred at that point. Based on the generator set where the power generation change has occurred, the corresponding carbon capture system needs to be scheduled and adjusted to determine the corresponding power change point.

[0060] Preferably, the preset value can be determined based on actual needs or the characteristics of the actual power generation system and its sensitivity to power fluctuations. All calculated power slopes are iterated through, and power generation points whose absolute values ​​are greater than the preset value are selected as power fluctuation points within the target time period. Simultaneously, after determining the power fluctuation points, their corresponding fluctuation times are obtained for further analysis and processing.

[0061] Preferably, the target time period can be half a day, i.e., 0:00-12:00 or 12:00-24:00, or the target time period can be 0:00-24:00 of a day.

[0062] S103: Based on the abrupt change time, calculate the time shift interval between each power abrupt change point and the preset power point.

[0063] As a preferred embodiment, the step of calculating the time shift interval between each power mutation point and a preset power point based on the mutation time specifically includes:

[0064] Based on the preset power point, power mutation points that are less than the power generation power corresponding to the preset power point are eliminated to obtain the final power mutation point;

[0065] The abrupt change times corresponding to the final power change points are statistically analyzed, and the time difference between each time point and the preset power point is calculated as the time shift interval; wherein, the preset power point is the critical power point for the carbon capture system to start.

[0066] In this embodiment, the preset power point is determined based on the critical power requirement for the carbon capture system to start up, i.e., the minimum power generation threshold at which the carbon capture system can start up normally and operate effectively. This needs to be precisely set according to the specific technical parameters and operational requirements of the carbon capture system. Typically, there will be one, two, or more preset power points, meaning that the carbon capture system may start up multiple times within the target time period. When there are two or more preset power points, the power point corresponding to the first start-up time is designated as the preset power point, while the other preset power points are marked as start-up points. The identification of these start-up time points is then incorporated into the subsequent dynamic optimization strategy for the carbon capture system's operation.

[0067] In this embodiment, among the identified power mutation points, a preset power point is used for screening. Preferably, the power generation power corresponding to each power mutation point is compared with the preset power point, and those power mutation points with power generation power less than the preset power point are eliminated. Thus, the final power mutation points selected are all power mutations that occur when the power generation power reaches or exceeds the critical power point for the carbon capture system to start. Power mutation points with power generation power less than the carbon capture system in the off-state state are of no practical significance to the carbon capture system.

[0068] In this embodiment, the abrupt change times corresponding to the final power abrupt change points are statistically analyzed and recorded. Then, the time difference between each abrupt change time and the preset power point is calculated, and the time difference is used as the time shift interval corresponding to the abrupt change time.

[0069] Understandably, calculating the time shift between the final power mutation point and the preset power point can provide an important reference for determining the optimal start-up time of the carbon capture system. By analyzing the time shift, we can understand how long it takes to reach the critical power point for the carbon capture system to start up after the power mutation, thereby rationally arranging the start-up time of the carbon capture system, ensuring that it can start up under appropriate power conditions, improving the operating efficiency and reliability of the carbon capture system, and reducing energy waste and equipment wear caused by improper start-up timing.

[0070] S104: Based on the time shift intervals corresponding to the power mutation points in multiple target time periods, record the number of power mutation points in different time shift intervals to obtain the distribution information of the number of power mutation points in different time shift intervals.

[0071] As a preferred embodiment, the step of recording the number of power mutation points in different time shift intervals based on the power mutation points in multiple target time periods, and obtaining the distribution information of the number of power mutation points in different time shift intervals, specifically includes:

[0072] Acquire and record the time shift intervals corresponding to the power mutation points of multiple target time periods;

[0073] Based on different time shift intervals, the number of corresponding power mutation points is recorded, and each time shift interval is arranged according to a preset order to obtain the distribution information of the number of power mutation points in the time shift interval under the preset order.

[0074] In this embodiment, multiple target time periods are determined. Preferably, a target time period can be one day, so multiple target time periods refer to data from multiple days. This involves recording the time shift intervals corresponding to power abrupt change points over several days, thereby obtaining the number of power abrupt change points within any given time shift interval over those several days. The number of power abrupt change points belonging to that time shift interval over those several days is then statistically analyzed to obtain the total number of power abrupt change points corresponding to that time shift interval. The number of power abrupt change points corresponding to other time shift intervals is also statistically analyzed using the same method.

[0075] In this embodiment, it is also necessary to determine the preset order of the time-shift intervals. This order can be based on chronological order or other specific sorting rules, such as ascending or descending order. For each time-shift interval, the number of corresponding power abrupt change points is counted. This can be achieved by traversing all power abrupt change points and their corresponding time-shift interval data, classifying each power abrupt change point into its corresponding time-shift interval, and counting the number of power abrupt change points within each interval. Each time-shift interval and its corresponding number of power abrupt change points are then arranged in a preset order to form complete power abrupt change point distribution information.

[0076] S105: Determine the moment of power mutation based on the quantity distribution information, and use it as the scheduling moment of the carbon capture system of the thermal power plant.

[0077] As a preferred embodiment, determining the time point of power abrupt change based on the quantity distribution information as the scheduling time point of the carbon capture system of the thermal power plant specifically includes:

[0078] In the quantity distribution information, the time-shift intervals corresponding to the number of power mutation points exceeding a preset threshold are extracted to obtain the time-shift interval adjustment points;

[0079] Based on the time corresponding to the preset power point, and combined with the time difference between the time shift interval itself and the preset power point, the time corresponding to each time shift interval adjustment point is calculated, which serves as the scheduling time point for the carbon capture system of the thermal power plant.

[0080] In this embodiment, based on actual needs and experience, a threshold for the number of power abrupt change points is set to filter out time-shift intervals with significant magnitudes, corresponding to significant changes in power generation. From the distribution information of power abrupt change points, time-shift intervals with the number of power abrupt change points exceeding the preset threshold are identified and extracted as time-shift interval adjustment points. These time-shift interval adjustment points represent periods where power abrupt changes are frequent or significant, potentially having a substantial impact on the operation of the carbon capture system.

[0081] In this embodiment, based on the time corresponding to the preset power point, that is, the time point corresponding to the critical power point for the start-up of the carbon capture system, for each time shift interval adjustment point, the scheduling time point corresponding to each time shift interval adjustment point is determined by combining its own time difference with the preset power point.

[0082] S106: Based on the scheduling time point, obtain the current flue gas parameters of the coal-fired power plant generator unit, and dynamically optimize the carbon capture system operation strategy based on the current power generation, flue gas parameters and preset grid carbon quota data.

[0083] As a preferred embodiment, the step of obtaining the current flue gas parameters of the coal-fired power plant generating units based on the scheduling time point, and dynamically optimizing the carbon capture system operation strategy based on the current power generation, flue gas parameters, and preset grid carbon quota data, specifically includes:

[0084] Based on the aforementioned scheduling time point, the current flue gas parameters and power generation of the coal-fired power plant generator units are obtained in real time.

[0085] The current power generation capacity, current flue gas parameters, and preset grid carbon quota data are input into a preset adjustment agent for optimization decision-making, and the optimized operation strategy of the carbon capture system is output.

[0086] Based on the optimized operating strategy, the carbon capture system is scheduled and adjusted.

[0087] In this embodiment, the efficient operation of the carbon capture system in a thermal power plant is achieved through real-time data acquisition, intelligent optimization decision-making, and system scheduling adjustments. The principle is to utilize real-time acquired power generation and flue gas parameters, combined with preset grid carbon quota data, to perform optimization decisions through a preset adjustment agent. This generates an optimized operation strategy for the carbon capture system, and based on this strategy, the carbon capture system is scheduled and adjusted to maximize carbon capture efficiency and minimize operating costs.

[0088] In this embodiment, data is collected at the scheduling time point calculated in the preceding steps. That is, the current power generation and flue gas parameters of the coal-fired power plant generator units are acquired in real time through sensors and monitoring equipment. The power generation can be obtained through the generator unit's power monitoring system, and the flue gas parameters (such as carbon dioxide concentration, temperature, flow rate, etc.) can be obtained through sensors installed in the flue.

[0089] In this embodiment, the preset adjustment agent is an optimization model based on artificial intelligence or machine learning algorithms. It can perform complex optimization calculations based on the input real-time data and preset grid carbon quota data, and output an optimized operating strategy. Preferably, the preset agent can be constructed based on a deep reinforcement learning (DRL) model using a dual-delay deep deterministic policy gradient, where execution and constraints are determined, and a reward feedback is constructed before training to obtain the corresponding preset agent.

[0090] Preferably, the training method for the pre-defined agent first involves determining that the input data includes power generation, flue gas parameters, and pre-defined grid carbon quota data. Specifically, the flue gas parameters include main steam pressure, valve opening, temperature, flow rate, and CO2 volume fraction. The pre-defined grid carbon quota data includes real-time carbon quota prices and electricity prices. The above raw data is encoded and abstracted into a multi-dimensional vector to ensure consistent DRL input scale for the agent. Then, the gradient of the dual-delay deep deterministic policy is determined, i.e., by determining the Actor network and the Critic dual network. The Actor network takes a multi-dimensional vector as input and outputs the flue gas bypass damper opening, reboiler steam valve opening, and lean liquor pump frequency, while the Critic dual network is used to suppress overestimation. Then, corresponding execution and constraints are established, such as: minimum technical output of the unit ≥ 40% of rated capacity, reboiler temperature ≤ 125 ℃ (anti-degradation), and daily average capture rate ≥ 90% (compliance baseline). A reward function is set according to economic cost, carbon emissions, and safety, thereby training a pre-defined agent that can automatically fit the optimal policy.

[0091] Furthermore, based on the preset optimized operation strategy output by the intelligent agent, the carbon capture system is scheduled and adjusted. This can be achieved through an automated control system, directly translating the optimized operation strategy into control commands for the equipment, adjusting the operating parameters and operating status of the carbon capture system. Preferably, during the execution of the optimized operation strategy, the operating status and effectiveness of the carbon capture system are monitored in real time to ensure the effective implementation of the optimized strategy. If deviations are found between the actual operating conditions and the optimized strategy, the optimized strategy can be adjusted promptly for dynamic optimization.

[0092] In this embodiment, when the preset power point is greater than or equal to 2, it is also necessary to add the time corresponding to the subsequent power points other than the first preset power point to dynamically optimize the carbon capture system operation strategy. Similarly, at the time of reaching this preset power point, the current flue gas parameters and power generation of the coal-fired power plant generator unit are obtained, and combined with the preset grid carbon quota data, the data is input into the preset adjustment agent for optimization decision-making, and the optimized operation strategy of the carbon capture system corresponding to the current preset power point is output.

[0093] Implementing the above embodiments has the following effects:

[0094] The technical solution of this invention obtains the power generation of generator units in a thermal power plant at each moment, extracts the power abrupt change points of the power generation within a target time period, and then calculates the time shift interval between each power abrupt change point and a preset power point. Based on the time shift intervals of multiple target time periods, it obtains the quantity distribution information of power abrupt change points in different time shift intervals. This allows the scheduling time point of the carbon capture system in the thermal power plant to be determined through the quantity distribution information. Furthermore, in subsequent adjustments, the corresponding power generation, flue gas parameters, and preset grid carbon quota data can be obtained in real time at the scheduling time point to dynamically optimize the carbon capture system's operating strategy. This invention avoids the need for existing technologies to continuously acquire current power generation data and perform related detection and calculations before optimizing the carbon capture system's scheduling. However, for coal-fired power plants with large load fluctuations, real-time data acquisition and optimization can lead to response delays. This invention, on the other hand, can determine the scheduling time point in advance, thereby directly acquiring power generation, flue gas parameters, and preset grid carbon quota data at the scheduling time point. This reduces the intermediate calculation process, improves response efficiency, reduces the computational resources required for large amounts of data, and improves the overall system's accuracy and responsiveness. As a result, the carbon capture system can be accurately and efficiently scheduled to operate at an appropriate load.

[0095] Example 2

[0096] Please see Figure 2 The present invention provides an intelligent scheduling system for carbon capture in thermal power plants, comprising:

[0097] The power generation module 201 is used to acquire the power generation of the generator set in the thermal power plant at each moment, and generate a power generation time relationship diagram based on the power generation.

[0098] The mutation module 202 is used to extract the power mutation points of the power generation within the target time period according to the power generation time relationship diagram, and to determine the mutation time corresponding to each power mutation point.

[0099] The time-shift interval module 203 is used to calculate the time-shift interval between each power mutation point and a preset power point based on the mutation time.

[0100] The quantity distribution module 204 is used to record the number of power mutation points in different time shift intervals based on the time shift intervals corresponding to the power mutation points in multiple target time periods, and to obtain the quantity distribution information of the power mutation points in different time shift intervals.

[0101] The scheduling timing module 205 is used to determine the timing of power mutation based on the quantity distribution information, and use it as the scheduling timing of the carbon capture system of the thermal power plant.

[0102] The operation strategy module 206 is used to obtain the current flue gas parameters of the coal-fired power plant generator unit according to the scheduling time point, and dynamically optimize the operation strategy of the carbon capture system based on the current power generation, flue gas parameters and preset grid carbon quota data.

[0103] As a preferred embodiment, the step of obtaining the power generation of the generator units in the thermal power plant at each moment and generating a power generation time relationship diagram based on the power generation specifically includes:

[0104] Real-time acquisition of the power generation capacity of generator units in thermal power plants at every moment;

[0105] Extract the power generation within the target time period and its corresponding time, and construct a power generation time relationship graph within the target time period; wherein, the horizontal axis of the power generation time relationship graph is time, the vertical axis is power generation, and the power generation corresponding to each time is fitted into a power generation curve.

[0106] As a preferred embodiment, the step of extracting power abrupt change points of the power generation within the target time period based on the power generation time relationship diagram, and determining the abrupt change time corresponding to each power abrupt change point, specifically includes:

[0107] In the power generation time relationship diagram, all power generation points within the target time period are determined, and the power slope of each power generation point on the power generation curve is calculated.

[0108] The power generation point where the absolute value of the power slope is greater than the preset value is taken as the power mutation point of the power generation within the target time period;

[0109] Extract the time point of the corresponding power change point from the power generation time relationship graph and use it as the change time.

[0110] As a preferred embodiment, the step of calculating the time shift interval between each power mutation point and a preset power point based on the mutation time specifically includes:

[0111] Based on the preset power point, power mutation points that are less than the power generation power corresponding to the preset power point are eliminated to obtain the final power mutation point;

[0112] The abrupt change times corresponding to the final power change points are statistically analyzed, and the time difference between each time point and the preset power point is calculated as the time shift interval; wherein, the preset power point is the critical power point for the carbon capture system to start.

[0113] As a preferred embodiment, the step of recording the number of power mutation points in different time shift intervals based on the power mutation points in multiple target time periods, and obtaining the distribution information of the number of power mutation points in different time shift intervals, specifically includes:

[0114] Acquire and record the time shift intervals corresponding to the power mutation points of multiple target time periods;

[0115] Based on different time shift intervals, the number of corresponding power mutation points is recorded, and each time shift interval is arranged according to a preset order to obtain the distribution information of the number of power mutation points in the time shift interval under the preset order.

[0116] As a preferred embodiment, determining the time point of power abrupt change based on the quantity distribution information as the scheduling time point of the carbon capture system of the thermal power plant specifically includes:

[0117] In the quantity distribution information, the time-shift intervals corresponding to the number of power mutation points exceeding a preset threshold are extracted to obtain the time-shift interval adjustment points;

[0118] Based on the time corresponding to the preset power point, and combined with the time difference between the time shift interval itself and the preset power point, the time corresponding to each time shift interval adjustment point is calculated, which serves as the scheduling time point for the carbon capture system of the thermal power plant.

[0119] As a preferred embodiment, the step of obtaining the current flue gas parameters of the coal-fired power plant generating units based on the scheduling time point, and dynamically optimizing the carbon capture system operation strategy based on the current power generation, flue gas parameters, and preset grid carbon quota data, specifically includes:

[0120] Based on the aforementioned scheduling time point, the current flue gas parameters and power generation of the coal-fired power plant generator units are obtained in real time.

[0121] The current power generation capacity, current flue gas parameters, and preset grid carbon quota data are input into a preset adjustment agent for optimization decision-making, and the optimized operation strategy of the carbon capture system is output.

[0122] Based on the optimized operating strategy, the carbon capture system is scheduled and adjusted.

[0123] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0124] Implementing the above embodiments has the following effects:

[0125] The technical solution of this invention obtains the power generation of generator units in a thermal power plant at each moment, extracts the power abrupt change points of the power generation within a target time period, and then calculates the time shift interval between each power abrupt change point and a preset power point. Based on the time shift intervals of multiple target time periods, it obtains the quantity distribution information of power abrupt change points in different time shift intervals. This allows the scheduling time point of the carbon capture system in the thermal power plant to be determined through the quantity distribution information. Furthermore, in subsequent adjustments, the corresponding power generation, flue gas parameters, and preset grid carbon quota data can be obtained in real time at the scheduling time point to dynamically optimize the carbon capture system's operating strategy. This invention avoids the need for existing technologies to continuously acquire current power generation data and perform related detection and calculations before optimizing the carbon capture system's scheduling. However, for coal-fired power plants with large load fluctuations, real-time data acquisition and optimization can lead to response delays. This invention, on the other hand, can determine the scheduling time point in advance, thereby directly acquiring power generation, flue gas parameters, and preset grid carbon quota data at the scheduling time point. This reduces the intermediate calculation process, improves response efficiency, reduces the computational resources required for large amounts of data, and improves the overall system's accuracy and responsiveness. As a result, the carbon capture system can be accurately and efficiently scheduled to operate at an appropriate load.

[0126] Example 3

[0127] Accordingly, the present invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the intelligent scheduling method for carbon capture in thermal power plants as described in any of the above embodiments.

[0128] The terminal device in this embodiment includes a processor, a memory, and a computer program and computer instructions stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps described in Embodiment 1 above, for example... Figure 1 The steps S101 to S106 are shown. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above device embodiment, such as the operation strategy module 206.

[0129] For example, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device. For example, the operation strategy module 206 is used to obtain the current flue gas parameters of the coal-fired power plant generator unit according to the scheduling time point, and dynamically optimize the carbon capture system operation strategy based on the current power generation, flue gas parameters, and preset grid carbon quota data.

[0130] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the schematic diagram is merely an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, buses, etc.

[0131] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0132] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile terminal, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital card (SD card), flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0133] Wherein, if the modules / units integrated in the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. Wherein, the computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0134] Example 4

[0135] Accordingly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the intelligent scheduling method for carbon capture in thermal power plants as described in any of the above embodiments.

[0136] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for intelligent scheduling of carbon capture in a thermal power plant, characterized in that, The method comprises the following steps: acquiring the power generation of each time point of the generator set in the thermal power plant, and generating a power generation time point relationship diagram according to the power generation; extracting the power mutation points of the power generation in a target time period according to the power generation time point relationship diagram, and determining the mutation time points corresponding to each power mutation point; wherein, in the power generation time point relationship diagram, all power generation points in the target time period are determined, and the power slope of each power generation point on the power generation curve is calculated; the power generation point with an absolute value of the power slope greater than a preset value is taken as the power mutation point of the power generation in the target time period; the time point corresponding to the power mutation point in the power generation time point relationship diagram is extracted as the mutation time point; calculating the time interval between each power mutation point and a preset power point according to the mutation time point; based on the time intervals of the power mutation points of multiple target time periods, recording the number of power mutation points in different time intervals, and obtaining the number distribution information of the power mutation points in different time intervals; wherein, the time intervals of the power mutation points of multiple target time periods are acquired and recorded; based on different time intervals, the number of corresponding power mutation points is recorded, and each time interval is arranged according to a preset order, so that the number distribution information of the power mutation points in the preset order is obtained; determining the time point of power mutation according to the number distribution information as the scheduling time point of the carbon capture system of the thermal power plant; acquiring the current flue gas parameters of the generator set of the coal-fired power plant according to the scheduling time point, and dynamically optimizing the operation strategy of the carbon capture system according to the current power generation, flue gas parameters and preset power grid carbon quota data.

2. The method of intelligent scheduling of carbon capture in a thermal power plant of claim 1, wherein, The method comprises the following steps: real-time acquisition of the power generation of each time point of the generator set in the thermal power plant; extracting the power generation and its corresponding time point in the target time period to construct the power generation time point relationship diagram in the target time period; wherein, the horizontal axis of the power generation time point relationship diagram is the time point, the vertical axis is the power generation, and the power generation corresponding to each time point is fitted into a power generation curve.

3. The method of intelligent scheduling of carbon capture in a thermal power plant of claim 2, wherein, The method comprises the following steps: according to the preset power point, eliminating the power mutation points less than the corresponding power generation of the preset power point to obtain the final power mutation points; statistically analyzing the mutation time points corresponding to the final power mutation points to calculate the time difference between each preset power point as the time interval; wherein, the preset power point is the critical power point of the start of the carbon capture system.

4. The method of intelligent scheduling of carbon capture of a thermal power plant of claim 3, wherein, The method comprises the following steps: in the number distribution information, extracting the time interval corresponding to the power mutation point whose number exceeds the preset threshold to obtain the time interval adjustment point; According to the moment corresponding to the preset power point, the time difference between the time shift interval itself and the preset power point is combined to calculate the moment corresponding to each time shift interval adjustment point, as the scheduling moment point of the carbon capture system of the thermal power plant.

5. The method of intelligent scheduling of carbon capture of a thermal power plant of claim 4, wherein, According to the scheduling moment point, the current flue gas parameters of the coal-fired power plant generator set are obtained, and the carbon capture system operation strategy is dynamically optimized according to the current power generation power, flue gas parameters and preset power grid carbon quota data, specifically including: According to the scheduling moment point, the current flue gas parameters of the coal-fired power plant generator set are obtained, and the carbon capture system operation strategy is dynamically optimized according to the current power generation power, flue gas parameters and preset power grid carbon quota data, specifically including: According to the scheduling moment point, the current flue gas parameters of the coal-fired power plant generator set are obtained, and the carbon capture system operation strategy is dynamically optimized according to the current power generation power, flue gas parameters and preset power grid carbon quota data, specifically including: According to the scheduling moment point, the current flue gas parameters of the coal-fired power plant generator set are obtained, and the carbon capture system operation strategy is dynamically optimized according to the current power generation power, flue gas parameters and preset power grid carbon quota data, specifically including:

6. A carbon capture intelligent scheduling system for a thermal power plant, characterized in that, Including: The power generation power module is used to obtain the power generation power of the generator set in the thermal power plant at each moment, and generate a power generation power moment relationship diagram according to the power generation power; The mutation module is used to extract the power mutation point of the power generation power in the target time period according to the power generation power moment relationship diagram, and determine the mutation moment corresponding to each power mutation point; wherein, in the power generation power moment relationship diagram, all power generation power points in the target time period are determined, and the power slope of each power generation power point on the power generation power curve is calculated; the power generation power point with an absolute value of the power slope greater than a preset value is taken as the power mutation point of the power generation power in the target time period; the moment point corresponding to the power mutation point in the power generation power moment relationship diagram is extracted as the mutation moment; The time shift interval module is used to calculate the time shift interval between each power mutation point and the preset power point according to the mutation moment; The quantity distribution module is used to record the number of power mutation points in different time shift intervals based on the time shift intervals corresponding to the power mutation points of multiple target time periods, and obtain the quantity distribution information of the power mutation points in different time shift intervals; wherein, the time shift intervals corresponding to the power mutation points of multiple target time periods are obtained and recorded; based on different time shift intervals, the number of power mutation points corresponding to each time shift interval is recorded, and each time shift interval is arranged according to a preset order, so that the quantity distribution information of the power mutation points in the time shift intervals in the preset order is obtained; The scheduling moment module is used to determine the moment of power mutation as the scheduling moment point of the carbon capture system of the thermal power plant according to the quantity distribution information; The operation strategy module is used to obtain the current flue gas parameters of the coal-fired power plant generator set according to the scheduling moment point, and dynamically optimize the carbon capture system operation strategy according to the current power generation power, flue gas parameters and preset power grid carbon quota data.

7. A terminal device, characterized by comprising: The processor, the memory and the computer program stored in the memory and configured to be executed by the processor are included, and the processor implements the thermal power plant carbon capture intelligent scheduling method in any one of claims 1 to 5 when the computer program is executed. The processor, the memory and the computer program stored in the memory and configured to be executed by the processor are included, and the processor implements the thermal power plant carbon capture intelligent scheduling method in any one of claims 1 to 5 when the computer program is executed.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored computer program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to execute the method for intelligent scheduling of carbon capture in a thermal power plant according to any one of claims 1 to 5 when the computer program is running.

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