CN117477655A - Real-time control system and method for power generation efficiency of power plant - Google Patents
Real-time control system and method for power generation efficiency of power plant Download PDFInfo
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Abstract
The invention relates to the field of intelligent algorithms, in particular to a real-time control system and method for generating efficiency of a power plant, wherein the system comprises a data acquisition module, an algorithm calculation and analysis module and a control module; the data acquisition module is used for acquiring operation data generated in the operation process of the power plant and screening target operation data from the operation data based on a preset rule; the algorithm calculation analysis module is used for predicting the power generation efficiency of the power plant in a preset time period according to the target operation data; if the power generation efficiency is determined to be lower than the threshold value, determining a regulation scheme according to the target operation data; the control module is used for determining control parameters according to the regulation and control scheme and regulating and controlling the power plant according to the determined control parameters. According to the invention, the regulation and control scheme of the power plant is determined according to the target operation data, and the power plant data is automatically regulated and corrected according to the regulation and control scheme, so that the power generation efficiency of the power plant is in an optimal state, the working efficiency of the power plant is improved, the energy is saved, and the generated energy is improved.
Description
Technical Field
The invention relates to the field of intelligent power generation efficiency control algorithms, in particular to a real-time control system and method for power generation efficiency of a power plant.
Background
In the prior art, the control system of the thermal power plant and the rear control platform are mostly one-to-one, namely, one control system of the power plant corresponds to one control platform; the control system is controlled and regulated by a rear platform staff through a rear control platform, and the manual rear platform regulation mode has high requirements on the rear platform operation control of the rear platform staff and is regulated by completely depending on the experience of the rear platform staff.
In conclusion, the adjusting speed of the adjusting control system adjusted manually is generally high, the labor cost is high, the personnel level of the operation and maintenance platform behind the power plant is different, and the training cost is high.
Disclosure of Invention
The embodiment of the invention provides a real-time control system for generating efficiency of a power plant, which is used for improving the generating efficiency and the running speed of a background, reducing the labor cost, improving the running efficiency of control of a complex large-scale energy system, enabling a plurality of power plants to synchronously improve the running and maintenance control generating level and achieving the purpose of saving a large amount of energy sources for generating power.
In a first aspect, an embodiment of the present invention provides a real-time control system for generating efficiency of a power plant, including a data acquisition module, an algorithm calculation analysis module, and a control module;
the data acquisition module is used for acquiring operation data generated in the operation process of the power plant; screening target operation data from the operation data based on a preset rule; the operation data comprise operation parameters of each device and operation state data of each device in the operation process of the power plant;
The algorithm calculation analysis module is used for predicting the power generation efficiency of the power plant in a preset duration according to the target operation data; if the power generation efficiency is determined to be lower than a threshold value, determining a regulation scheme for regulating equipment in the power plant according to the target operation data;
and the control module is used for determining control parameters which need to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameters.
Optionally, the algorithm calculation and analysis module is specifically configured to:
determining a regulation scheme for regulating equipment in the power plant according to the target operation data and a predefined basic algorithm; or,
and inputting the target operation data into a trained data analysis model, and acquiring a regulation scheme which is output by the trained data analysis model and used for regulating equipment in the power plant.
Optionally, the control module is specifically configured to:
determining control parameters and a control period for controlling equipment in the power plant according to the control scheme and a predefined control algorithm;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
Optionally, the control module is specifically configured to:
inputting the regulation scheme into a trained control model, and acquiring control parameters and regulation periods which are output by the trained control model and are required to regulate equipment in the power plant;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
Optionally, the system further comprises a super computing module;
the super computing module is used for training the data analysis model in the algorithm computing and analyzing module according to a first sample set to obtain the trained data analysis model; and/or training the control model in the control module according to a second sample set to obtain the trained control model.
Optionally, the system further comprises a data storage module and a user input module;
the user input module is used for acquiring a regulation scheme input by a user for regulating equipment in the power plant; or a control parameter and a regulation period which are input by a user and need to regulate equipment in the power plant;
the data storage module is used for storing the historical operation data generated in the operation process of the power plant, which is acquired by the data acquisition module, and storing a regulation and control scheme input by a user through the user input module or storing control parameters and a regulation and control period input by the user through the user input module;
The super computing module is specifically configured to: acquiring the first sample set from the data storage module; the first sample set comprises sample operation data and a sample regulation and control scheme corresponding to the sample operation data; inputting the sample operation data into the data analysis model to acquire a reference regulation and control scheme output by the data analysis model; adjusting model parameters of the data analysis model according to the sample regulation and control scheme and the reference regulation and control scheme until a trained data analysis model is obtained; and/or obtaining the second sample set from the data storage module; the second sample set comprises a sample regulation scheme, and sample control parameters and sample regulation periods corresponding to the sample regulation scheme; inputting the sample regulation and control scheme into the control model, and obtaining a reference control parameter and a reference regulation and control period output by the control model; and adjusting the model parameters of the control model according to the sample control parameters, the sample regulation and control period, the reference control parameters and the reference regulation and control period until a trained control model is obtained.
In a second aspect, an embodiment of the present invention provides a method for controlling power generation efficiency of a power plant in real time, including:
Collecting operation data generated in the operation process of the power plant; screening target operation data from the operation data based on a preset rule; the operation data comprise operation parameters of each device and operation state data of each device in the operation process of the power plant;
predicting the power generation efficiency of the power plant in a preset time period according to the target operation data; if the power generation efficiency is determined to be lower than a threshold value, determining a regulation scheme for regulating equipment in the power plant according to the target operation data;
and determining control parameters which need to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameters.
Optionally, the determining a regulation scheme for regulating equipment in the power plant according to the target operation data includes:
determining a regulation scheme for regulating equipment in the power plant according to the target operation data and a predefined basic algorithm; or,
and inputting the target operation data into a trained data analysis model, and acquiring a regulation scheme which is output by the trained data analysis model and used for regulating equipment in the power plant.
Optionally, the determining, according to the regulation scheme, a control parameter that needs to regulate and control equipment in the power plant, and regulating and controlling the power plant according to the determined control parameter includes:
determining control parameters and a control period for controlling equipment in the power plant according to the control scheme and a predefined control algorithm;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
Optionally, the determining, according to the regulation scheme, a control parameter that needs to regulate and control equipment in the power plant, and regulating and controlling the power plant according to the determined control parameter includes:
inputting the regulation scheme into a trained control model, and acquiring control parameters and regulation periods which are output by the trained control model and are required to regulate equipment in the power plant;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
Optionally, training the data analysis model in the algorithm calculation analysis module according to the first sample set to obtain the trained data analysis model; and/or training the control model in the control module according to a second sample set to obtain the trained control model.
Optionally, the method further comprises:
acquiring a regulation scheme input by a user for regulating equipment in the power plant; or the control parameters and the regulation period which are input by a user and need to regulate and control the equipment in the power plant.
Optionally, the method further comprises:
the method comprises the steps of storing collected historical operation data generated in the operation process of the power plant, and storing a regulation scheme input by a user or storing control parameters and regulation periods input by the user.
Optionally, the model is trained by:
acquiring the first sample set; the first sample set comprises sample operation data and a sample regulation and control scheme corresponding to the sample operation data; inputting the sample operation data into the data analysis model to acquire a reference regulation and control scheme output by the data analysis model; adjusting model parameters of the data analysis model according to the sample regulation and control scheme and the reference regulation and control scheme until a trained data analysis model is obtained; and/or, obtaining the second sample set; the second sample set comprises a sample regulation scheme, and sample control parameters and sample regulation periods corresponding to the sample regulation scheme; inputting the sample regulation and control scheme into the control model, and obtaining a reference control parameter and a reference regulation and control period output by the control model; and adjusting the model parameters of the control model according to the sample control parameters, the sample regulation and control period, the reference control parameters and the reference regulation and control period until a trained control model is obtained.
According to the embodiment of the invention, the data acquisition module is used for acquiring the operation data generated in the operation process of the power plant in real time, and the screened target operation data is sent to the algorithm calculation analysis module; the algorithm calculation analysis module predicts the power generation efficiency of the power plant within a preset time period according to the target operation data, judges the operation state of the power plant, determines a regulation and control mode according to the target operation data when the power generation efficiency is determined to be lower than a threshold value, regulates and controls the power plant according to the determined regulation and control scheme, realizes real-time control of the power plant, and enables the power plant to maintain the optimal power generation efficiency operation state, so that the working efficiency of the power plant is improved, energy is saved, and the generated energy is improved. In addition, the embodiment of the invention adopts the real-time control system for the power generation efficiency of the power plant, so that the power plant is not required to be controlled manually, and the intelligent control level of the power plant is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it will be apparent that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a real-time control system for generating efficiency of a power plant according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a PID model according to an embodiment of the invention;
FIG. 3 is a schematic diagram of another real-time control system for generating efficiency of a power plant according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a flow chart of a method for controlling power generation efficiency of a power plant in real time according to an embodiment of the present invention.
Detailed Description
In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.
Some terms appearing hereinafter are explained:
1. in embodiments of the present invention, the term "and/or": the association relationship describing the association object may represent that there are three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
2. System control optimization algorithm: according to the control relation among the systems such as boilers, steam turbines, fuel systems, water systems, auxiliary equipment and the like in the operation process, the regulation and control scheme is analyzed, the algorithm is refined, the operation data of the power plant are regulated through algorithm control of each system, and the power generation efficiency is improved.
3. Basic working condition and performance index algorithm: the method is characterized in that a basic calculation formula and a calculation formula of specific conversion parameters such as pressure, flow, heat, electric quantity and the like are written according to the performances and operation modes of different equipment in the power generation industry.
4. Differential consumption analysis algorithm: different equipment has different indexes of energy consumption, and the efficiency of each power generation module equipment is improved and the energy consumption of the equipment is reduced by compiling a basic algorithm.
5. Development algorithm: and analyzing the working condition of the power plant in real time, calculating the operation in real time, and compiling a power generation control real-time algorithm by taking the change of the real-time and non-occurrence time to the power generation efficiency into consideration.
6. PID algorithm: it is meant that in process control, a PID controller (also called PID regulator) that controls the ratio (P), integral (I) and derivative (D) of the deviation is one of the most widely used automatic controllers. The method has the advantages of simple principle, easy realization, wide application range, mutually independent control parameters, simple parameter selection and the like; it can also be theoretically demonstrated that the PID controller is an optimal control for the control objects of "first-order hysteresis + pure hysteresis" and "second-order hysteresis + pure hysteresis", which are typical of process control. The PID regulation rule is an effective method for correcting the dynamic quality of a continuous system, and the parameter setting mode is simple and convenient, and the structure is flexible to change.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, when the control system of the thermal power plant detects that the running state of the power plant equipment has a problem and needs to be adjusted, the control system is controlled and adjusted by a rear platform worker. The existing control system has low speed when being adjusted, and needs the post-platform staff to have abundant experience for control adjustment, and a great deal of manpower resources and training cost are consumed.
Based on the above problems, as shown in fig. 1, the embodiment of the invention provides a real-time control system for generating efficiency of a power plant, which comprises a data acquisition module 101, an algorithm calculation and analysis module 102, a control module 103 and a power plant 107;
the data acquisition module 101 is used for acquiring operation data generated in the operation process of the power plant 107; screening target operation data from the operation data based on a preset rule;
the operation data includes operation parameters of each device and operation state data of each device in the operation process of the power plant 107;
the algorithm calculation and analysis module 102 is used for predicting the power generation efficiency of the power plant 107 in a preset duration according to the target operation data; if the power generation efficiency is determined to be lower than the threshold value, determining a regulation scheme for regulating equipment in the power plant 107 according to the target operation data;
the control module 103 is configured to determine, according to a regulation scheme, a control parameter that needs to regulate equipment in the power plant 107, and regulate the power plant 107 according to the determined control parameter.
According to the embodiment of the invention, the data acquisition module is used for acquiring the operation data generated in the operation process of the power plant in real time, and the screened target operation data is sent to the algorithm calculation analysis module; the algorithm calculation analysis module predicts the power generation efficiency of the power plant within a preset time period according to the target operation data, judges the operation state of the power plant, determines a regulation and control mode according to the target operation data when the power generation efficiency is determined to be lower than a threshold value, regulates and controls the power plant according to the determined regulation and control scheme, realizes real-time control of the power plant, and enables the power plant to maintain the optimal power generation efficiency operation state, so that the working efficiency of the power plant is improved, energy is saved, and the generated energy is improved. In addition, the embodiment of the invention adopts the real-time control system for the power generation efficiency of the power plant, so that the power plant is not required to be controlled manually, and the intelligent control level of the power plant is improved.
In the system shown in fig. 1, the system further comprises a super computing module 104, a data storage module 105 and a user input module 106;
the super computing module 104 is configured to train the data analysis model in the algorithm computing and analyzing module according to the first sample set, so as to obtain a trained data analysis model; and/or training the control model in the control module according to the second sample set to obtain a trained control model.
The data storage module 105 is used for storing the historical operation data generated in the operation process of the power plant and collected by the data collection module, and storing the regulation and control scheme input by the user through the user input module or storing the control parameters and the regulation and control period input by the user through the user input module.
The user input module 106 is used for acquiring a regulation scheme input by a user for regulating equipment in the power plant; or the control parameters and the regulation period which are input by the user and need to regulate and control the equipment in the power plant.
In some embodiments, the embodiments of the present invention collect, in real time, operation data generated during operation of a power plant through a data collection module; the operation data comprise operation parameters of each device and operation state data of each device in the operation process of the power plant.
It should be noted that the operation parameters generated during the operation of the power plant include, but are not limited to: heat, pressure, flow, power generation, and fuel quantity.
In some embodiments, after acquiring operation data generated during operation of the plurality of power plants, the data acquisition module may screen data for determining power generation efficiency of the power plants from the operation data as target operation data according to a preset rule.
In specific implementation, the data acquisition module performs layering processing on the acquired operation data, and screens target operation data from the operation data according to a preset rule (for example, a factor to be referred to according to current efficiency control) according to a correlation between the operation parameters and the operation state data.
The power generation basic operation equipment algorithm is compiled according to the interrelationship among various operation data generated in the operation process of the power plant and the influence of parameters of different levels on the power plant equipment. The power generation basic operation equipment algorithm can calculate the operation data acquired by the data acquisition module in real time to acquire the target operation data which is the same as relevant deep cell nuclei, and the target operation data is not only remained on the surface.
After the data acquisition module acquires the target operation data, the data acquisition module sends the target operation data to the algorithm calculation analysis module, so that the algorithm calculation analysis module determines a regulation scheme for regulating equipment in the lost power plant according to the target operation data.
In specific implementation, the algorithm calculation and analysis module in the embodiment of the invention determines the power generation efficiency of each device in the power plant in a preset time period according to the target operation data, and determines a regulation scheme for regulating and controlling the devices in the power plant according to the determined target operation data when the power generation efficiency of the power plant is determined to be lower than a threshold value.
For example, the algorithm analysis and calculation module determines that the power generation efficiency of each device in the power plant is 80%, 88%,90%,97% in a preset time period, and the power generation efficiency threshold value of each device in the power plant is 85%, wherein the power generation efficiency 80% is less than the threshold value 85%, and determines that the power generation efficiency of the device corresponding to the power generation efficiency 80% is too low in the operation process, and the device needs to be regulated and controlled so that the power generation efficiency of the device in the next operation process can be higher than the threshold value; the algorithm analysis and calculation module determines a regulation and control scheme corresponding to the equipment according to the target operation data corresponding to the equipment, so that the control module regulates and controls the equipment according to the determined regulation and control scheme.
The algorithm analysis and calculation module in the embodiment of the invention can determine the regulation scheme according to the following mode.
The first mode is that the algorithm analysis and calculation module determines a regulation and control scheme according to a basic algorithm.
In implementation, the algorithm analysis and calculation module in the embodiment of the invention determines a regulation scheme for regulating and controlling equipment in the power plant according to the target operation data and a predefined basic algorithm.
The basic algorithm includes a basic working condition, a performance index algorithm and a differential consumption algorithm.
An optional implementation manner is that an algorithm calculation analysis module in the embodiment of the invention determines the power generation efficiency of the power plant in the operation time based on the acquired target operation data and according to a basic working condition and performance index algorithm.
In implementation, after the power generation efficiency of the power plant within the preset time period is obtained, whether the power generation efficiency of the power plant is lower than a threshold value is determined; if the power generation efficiency of the power plant is higher than or equal to the threshold value, determining that the power generation efficiency of the power plant meets the standard; and if the power generation efficiency of the power plant is determined to be lower than the threshold value, determining a regulation scheme for regulating equipment in the power plant according to the target operation data.
In some alternative embodiments, embodiments of the present invention may determine the modulation scheme in the following manner.
In the implementation, the algorithm calculation analysis module can determine the energy consumption index of each device in the power plant based on the target operation data, and determine a regulation scheme for regulating the devices in the power plant according to the determined energy consumption index.
In specific implementation, the algorithm calculation analysis module determines equipment with problems in energy consumption indexes according to the determined relation between the energy consumption indexes of all the equipment and the preset energy consumption indexes, and further determines a regulation scheme for regulating the equipment according to the determined energy consumption indexes.
In some alternative embodiments, the algorithm calculation analysis module determines a power plant device having a problem in the energy consumption index after determining that the power generation efficiency of the power plant is below a threshold, and determines a type of the problem; the algorithm calculation analysis module determines a regulation scheme according to the determined problem type and the power plant equipment corresponding to the problem based on the corresponding relation between the problem type, the equipment and the preset regulation scheme.
It should be noted that the preset regulation schemes include, but are not limited to: expert opinion, historical experience, and practitioner experience. Different devices correspond to different regulatory schemes and different problems also correspond to different regulatory schemes. Problems with energy consumption indicators include, but are not limited to: the energy consumption is high, and the operation is faulty; the operation fault is that the operation of the equipment is caused to be faulty under the condition that the energy consumption of the equipment reaches a certain index.
In specific implementation, after the algorithm calculation analysis module determines the energy consumption index of each device of the power plant based on the basic algorithm, the algorithm calculation analysis module determines a corresponding regulation scheme from preset regulation schemes according to the problems existing in the energy consumption index.
For example, the preset regulation schemes comprise a regulation scheme 1 and a regulation scheme 2; when the algorithm calculation sub-module determines that the energy consumption index of the power plant has a problem, the equipment combustion equipment with the problem of the energy consumption index in the power plant is determined, the problem of the energy consumption index of the combustion equipment is determined to be that the energy consumption is higher, and the regulation scheme is determined to be regulation scheme 1 according to the corresponding relation between the preset regulation scheme and the equipment and the problem.
And the algorithm analysis and calculation module determines a regulation and control scheme according to the trained data analysis model.
The algorithm analysis and calculation module inputs the target operation data into the trained data analysis model, and obtains a regulation scheme for regulating equipment in the power plant, which is output by the trained data analysis model.
In specific implementation, after the algorithm calculation analysis module inputs the obtained target operation data into the trained data analysis model, the trained data analysis model is used for analyzing the target operation data, the power generation efficiency of the power plant in a preset duration is predicted, and whether the power generation efficiency of the power plant is lower than a threshold value is judged.
If the determined operating efficiency of the power plant is higher than or equal to the power plant efficiency threshold, determining that the operating state of the power plant is good; or if the determined operating efficiency of the power plant is lower than the power plant efficiency threshold, determining that the operating state of the power plant has a problem.
After determining that the operation state of the power plant has a problem, the algorithm calculation analysis module determines a regulation and control scheme according to the target operation data based on the trained data analysis model.
In some embodiments, the algorithm computation analysis module analyzes the relevant parameters based on the trained data analysis model, analyzes the target operational data after determining that a problem exists in the operational state of the power plant, determines a device that has a problem, and determines a regulation scheme corresponding to the power plant device.
In other embodiments, the regulatory scheme in the embodiments of the present invention may also be a preset regulatory scheme, including but not limited to: expert opinion, historical experience, and practitioner experience.
In specific implementation, after determining that the operation state of the power plant has problems, the algorithm calculation analysis module determines power plant equipment with problems in the operation state and determines the type of the problems; the algorithm calculation analysis module determines a regulation scheme according to the determined problem type and the power plant equipment corresponding to the problem based on the corresponding relation between the problem type, the equipment and the preset regulation scheme.
It should be noted that different devices correspond to different control schemes, and different problems also correspond to different control schemes. Problems with operating conditions include, but are not limited to: the operation efficiency is low, the operation efficiency is lower, and the operation is faulty.
In specific implementation, after the algorithm calculation analysis module determines the operation state of the power plant based on the trained data analysis model, the algorithm calculation analysis module determines a corresponding regulation scheme from preset regulation schemes according to the problems occurring in the operation state of the power plant.
For example, the preset regulation schemes comprise a regulation scheme 1 and a regulation scheme 2; when the algorithm calculation sub-module determines that the operation state of the power plant has problems, determining that the operation state of the power plant has problems, namely the equipment combustion equipment has low operation efficiency, and determining that the regulation scheme is regulation scheme 1 according to the corresponding relation between the preset regulation scheme and the equipment and the problems.
It should be noted that, when the algorithm calculation analysis module in the embodiment of the present invention determines the regulation and control scheme according to the target operation data, the regulation and control scheme may be determined according to the basic algorithm or may be determined according to the trained data analysis model. In addition, in the early application stage of the real-time control system of the power plant power generation efficiency, the regulation and control scheme determined by the data analysis model in the algorithm calculation analysis module is inaccurate, and the data analysis model needs to be trained by the super calculation module to obtain a trained data analysis model.
In a specific implementation, the super computing module in the embodiment of the present invention may train the data analysis model according to the following manner:
in the implementation, the super computing module trains the data analysis model in the algorithm computing and analyzing module according to the first sample set to obtain a trained data analysis model.
An alternative embodiment is for the supercomputing module to obtain the first sample set from the data storage module.
It should be noted that the first sample set includes sample operation data and a sample regulation scheme corresponding to the sample operation data.
In the implementation, the super computing module inputs the obtained sample operation data into a data analysis model to obtain a reference regulation and control scheme output by the data analysis model; and adjusting model parameters of the data analysis model according to the sample regulation and control scheme and the reference regulation and control scheme until a trained data analysis model is obtained.
In specific implementation, the super computing module determines a loss value according to a reference regulation scheme and a sample regulation scheme which are obtained through the data analysis model, and adjusts model parameters of the data analysis model according to the loss value until the loss value is in a desired range, so as to obtain the trained data analysis model.
In some embodiments, the algorithm calculation analysis module determines a regulation scheme for regulating equipment in the power plant according to the target operation data when determining that the power generation efficiency of the power plant is lower than a threshold value; and sending the determined regulation to the control module.
After determining the regulation and control scheme, the algorithm calculation and analysis module sends the determined regulation and control scheme to the control module, so that the control module regulates and controls the power plant according to the regulation and control scheme, and the operation efficiency of the power plant is improved.
In other embodiments, the user input module sends the obtained user input regulation scheme for regulating the equipment in the power plant to the control module, so that the control module regulates the power plant equipment according to the received regulation scheme.
In the implementation, after receiving the regulation scheme, the control module determines control parameters which need to regulate equipment in the power plant according to the regulation scheme, and regulates the power plant according to the determined control parameters.
In a specific implementation, the control module in the embodiment of the present invention may regulate the power plant according to the following manner.
Mode 1, the control module regulates and controls the power plant according to a predefined control algorithm.
In the implementation, a control module determines control parameters and a control period for controlling equipment in a power plant according to a control scheme and a predefined control algorithm; and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
The control algorithm comprises the operation data, the data generation period and the control relation among the power plant devices, which are acquired from the data storage module, and is compiled.
In the specific implementation, the control module analyzes the received regulation scheme according to the determined control algorithm, and determines a set value and an actual value corresponding to the control parameter in the regulation scheme and a regulation period; the control module adjusts the actual value of the control parameter of the equipment corresponding to the control parameter in the power plant equipment into a set value according to the determined regulation and control period, and controls the equipment in the power plant to operate according to the adjusted control parameter.
For example, when the regulation scheme is to increase the fire rate to 80%, the control module determines that the power plant equipment corresponding to the regulation parameter fire rate is combustion equipment, and determines that the equipment parameter of the combustion equipment corresponding to the fire rate is oxygen supply amount, temperature and the like according to the operation data of the combustion equipment. The control device can determine the actual value and the set value of the oxygen supply according to the control algorithm, and adjust the actual value according to the set value of the oxygen supply.
In some embodiments, the control module may further determine a setting value of a next stage of the control parameter according to the development algorithm, and adjust the control parameter according to the setting value of the next stage of the adjustment parameter, so that the control module adjusts the future data index in advance.
And 2, regulating and controlling the power plant by the control module according to the trained control model.
In the implementation, a control module inputs a regulation scheme into a trained control model, and acquires control parameters and a regulation period which are output by the trained control model and are required to regulate equipment in a power plant; and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
In some alternative embodiments, the control module inputs the regulation scheme into a trained control model, analyzes the regulation scheme based on the trained control model, determines control parameters in the regulation scheme that need to be regulated, and a regulation period, and outputs actual values and set values of the control parameters, and the regulation period.
It should be noted that, when determining the control parameter and the control period according to the control scheme, the control module in the embodiment of the present invention may select to determine the control parameter and the control period according to the control algorithm, or select to determine the control parameter and the control period according to the trained control model. In addition, in the early application stage of a real-time control system of the power generation efficiency of the power plant, the control parameters and the regulation and control period determined by the control model in the control module are inaccurate, and the control model needs to be trained through the super computing module to obtain a trained control model.
In implementation, before determining the control parameters and the regulation and control period according to the trained control model, the embodiment of the invention needs to train the control model through a super computing module to obtain the trained control model.
Specifically, the embodiment of the invention can train the control model in the following way.
In implementations, the supercomputing module obtains the second sample set from the data storage module.
It should be noted that the second sample set includes a sample adjustment scheme, and a sample control parameter and a sample adjustment period corresponding to the sample adjustment scheme.
The super computing module inputs the sample regulation and control scheme into the control model to obtain reference control parameters and reference regulation and control periods output by the control model; and adjusting the model parameters of the control model according to the sample control parameters, the sample regulation and control period, the reference control parameters and the reference regulation and control period until the trained control model is obtained.
In specific implementation, the super computing module determines a loss value according to a sample control parameter, a sample regulation period, a reference control parameter and a reference regulation period which are obtained through the control model, and adjusts the model parameter of the control model according to the loss value until the loss value is in a desired range, so as to obtain the trained control model.
It should be noted that, before training the data analysis model and the control model by the supercomputer module, the embodiment of the invention establishes an initial data analysis model and an initial control model based on the historical operation data of the power plant obtained from the data storage module and the theoretical knowledge of an expert.
After the historical operation data of the power plant are obtained, the embodiment of the invention also needs to conduct data preprocessing on the historical operation data to obtain preprocessed data, and a database is built in the data storage module according to the obtained preprocessed data.
The data preprocessing includes denoising, dimension reduction and arrangement of the acquired data to obtain preprocessed data.
The training process of the initial data analysis model and the initial control model is described in detail below:
specifically, before training an initial data analysis model and an initial control model to obtain the data analysis model and the control model, the embodiment of the invention can establish a reasonable and efficient database according to the following mode;
in a specific implementation, the embodiment of the invention can establish a plurality of databases, such as a real-time database and a static database, a main database and a standby database, etc., in a data storage module, namely a power generation efficiency data cloud server; and a redundant space is reserved between the databases; and the relation design among the tables of various libraries in the data storage module is correct and reasonable; the data storage module has a set of specifications of different database names, table names, field names and the like.
It should be noted that, when storing data, the database needs to be reasonably compressed; specifically, reasonable data types are required to be selected to store historical data, so that memory is not wasted, and data overflow is prevented, so that data loss, inaccuracy and the like are caused; the historical data is correspondingly compressed, so that space is saved; cleaning intermediate cache data at regular time; moreover, the database needs to set a set of storage mechanism, such as sequential storage, batch storage, etc.; optimizing a reading command of the database, and preventing the database from carrying out unnecessary searching operation, so that the database access is slow; finally, to prevent the database from being tampered with, a firewall for unsafe access needs to be established.
According to the embodiment of the invention, the historical data in the data storage module is read, and the historical data is applied to training and learning of the initial data analysis model and the initial control model, wherein the training and learning process of the data analysis model and the initial control model is divided into two stages:
and training an initial data analysis model and an initial control model by adopting a machine learning mode when the historical data in the database is less in stage one.
Specifically, when the historical data is small, training an initial data analysis model and an initial control model through three sides of a linear regression, a tree model and a classification method, and adjusting model parameters to obtain an optimized data analysis model and an optimized control model; the linear regression comprises a logistic regression algorithm and a linear discrimination algorithm, the tree model comprises a decision tree and a random forest, and the classification method comprises a support vector machine algorithm and k neighbor classification (k-nearest neighbor classification, KNN).
And 2, training an initial data analysis model and an initial control model by adopting a deep learning mode after the historical data in the database are increased.
Based on historical data in a database, calculating by using nonlinear processing capacity of deep learning, and carrying out iterative calculation on a large number of times of data to obtain an optimized initial data analysis model and an optimized initial control model; and applying the obtained optimized initial data analysis model and the optimized initial control model to a virtual test machine, observing the overall energy change of the virtual power plant, and continuously learning and updating the initial data analysis model and the initial control model to obtain a data analysis model and a control model.
Specifically, with the increase of historical data, training an optimized initial data analysis model and an optimized control model by using a Recurrent Neural Network (RNN) according to the serialized data in the historical data, training an optimized data analysis model and an optimized control model by using a Convolutional Neural Network (CNN) according to the graphical data in the historical data, and adjusting model parameters to obtain the data analysis model and the control model.
In particular implementations, the data analysis model and the control model may be neural network models.
It should be noted that, in the embodiment of the present invention, a plurality of initial data analysis models and a plurality of initial control models may be trained simultaneously, and appropriate models may be selected and applied to the control system of the power plant according to expert opinion, thresholds of model parameters, and the like.
Specifically, the embodiment of the invention can screen out qualified data analysis models and control models according to the thresholds of model parameters of the data analysis models and the control models, screen out proper data analysis models from the qualified data analysis models according to the opinion of experts, screen out proper control models from the qualified control models, and finally select an optimal data analysis model from the proper data analysis models and an optimal control model from the proper control models so as to be applied to a control system of a power plant.
It should be noted that, in the embodiment of the present invention, whether the data analysis model and the control model are suitable for the current environment is also determined according to the power generation efficiency of the power plant.
In some embodiments, after the data analysis model is applied to the algorithm calculation analysis module and the control model is applied to the control module, the data analysis model and the control model are trained through the super calculation module, the data analysis model and the control model are continuously optimized, and the trained data analysis model and the trained control model are obtained, so that the trained data analysis model and the trained control model can be more suitable for the current environment.
In other embodiments, the embodiment of the invention can also send the control parameters and the regulation and control period which are input by the user and need to regulate and control the equipment in the power plant to the control module through the user input module, so that the control module regulates and controls the power plant according to the received control parameters and regulation and control period.
In some embodiments, after the control module determines the control parameters and the regulation period to be regulated, the control parameters of the power plant equipment are regulated.
The embodiment of the invention can adjust the control parameters according to the following mode.
In particular implementations, the control module may adjust the control parameters via a PID model.
In practice, the control device inputs the set value and the actual value of the control parameter into the PID model, and adjusts the control parameter through the PID model.
When the control module determines that the deviation between the actual value and the set value of the control parameter is large through the PID model, coarse adjustment is carried out on the control parameter in a fuzzy control mode; and when the deviation is within a certain range, adopting a PID control mode to fine-tune the control parameters.
As shown in fig. 2, an embodiment of the present invention provides a PID model for adjusting control parameters.
In implementation, the embodiment of the invention inputs the control parameters into the PID model, determines the difference value between the actual value and the set value of the control parameters based on the PID model, and performs coarse adjustment on the control parameters of the power plant equipment through the fuzzy controller after determining that the difference value is larger than the preset difference value.
In some embodiments, obtaining an adjusted actual value of the control parameter of the power plant device through a measurement transmitter in the PID model, and determining again whether a difference between the adjusted actual value and the set value is less than a first threshold; and after the difference value between the adjusted actual value and the set value is smaller than the preset difference value, finely adjusting the control parameters of the power plant equipment through the PID controller.
According to the embodiment of the invention, after the control parameters are adjusted, the target operation data of the power plant equipment is obtained through the data acquisition module, the target operation data is analyzed through the algorithm calculation analysis module, the control scheme is obtained, the control parameters are adjusted through the control module, the circulation is carried out until the optimal control scheme is obtained, and the control parameters are corrected according to the optimal control scheme.
According to the embodiment of the invention, the data acquisition module acquires the operation data generated during the operation of the power plant in real time, and obtains the target operation data according to the preset rule; analyzing the obtained target related data through an algorithm calculation analysis module, determining the generating efficiency of the power plant, and obtaining a regulation and control scheme based on the target operation data; after the regulation scheme is obtained, the control module is used for determining the control parameters and the regulation period in the regulation scheme, the power plant equipment corresponding to the control parameters is regulated, the operation mode of the power plant equipment is regulated in real time, and in addition, the future data index is regulated in advance through the control module by pre-judging and analyzing the development algorithm of the later stage in advance, so that the real-time control is achieved in a time-free control stage. According to the embodiment of the invention, the algorithm of the relation between the industry basic data and the control data is prepared by analyzing the design performance index and the control principle of the power plant equipment, so that the relative standard parameters or curves of the power plant operation are obtained, the accuracy of calculating the relative parameters is improved, the efficiency control of power generation is fundamentally changed, the consumption difference is reduced, the mode of controlling the algorithm and the time difference is compiled, the control system automatically adjusts the relative parameters of the power plant to change the operation state of the power plant in consideration of the influence of continuous change of variables, the adjustment can be quickly made, the power plant can maintain the operation state of the optimal power generation efficiency, the working efficiency of the power plant is improved, the energy is saved, and the power generation capacity is improved; the embodiment of the invention adopts the real-time control system for the power generation efficiency of the power plant, so that the intelligent control level of the power plant is improved.
As shown in fig. 3, the real-time control system for generating efficiency of a power plant in the embodiment of the present invention further includes a display platform module 108;
the display platform module 108 is configured to display operation data, target operation data, power generation efficiency, operation status, and a regulation scheme, and intuitively understand the system operation condition by temporarily accumulating one or more power plant data.
After the optimal regulation scheme is obtained, the optimal regulation scheme is fed back to the display control platform module for display.
In some embodiments, a user may determine an operational status of the power plant based on the operational data of the power plant displayed in the display platform module and the target operational data, thereby determining whether to regulate the power plant; if the user determines that the operation state of the power plant has a problem according to the operation data displayed by the display platform module, the control scheme of the power plant equipment can be input through the user input module, so that the control module can control the power plant equipment according to the control scheme sent by the user input module.
In some embodiments, the user input module may also be used to provide services such as visual remote control for overall management of one, more and overseas power plants, periodic diagnosis by experts, continuous accumulation of big data, formation of a combination of experts and an intelligent expert database, and improvement of overall power generation efficiency of the power plant by control.
For example, an expert can acquire operation data of the power plant in the operation process by logging in a user input module, diagnose the power plant according to the acquired operation data, and realize the regulation and control of the power plant by inputting a regulation and control scheme when determining that the operation state of the power plant has problems.
In some embodiments, the data storage module stores operation data of a plurality of power plants and various data generated by the control system in the operation process, historical data is provided for part of old power plants and new power plants in the future through continuous data accumulation, a scheme for influencing the power generation efficiency of the new power plants to be designed can be improved in advance, and equipment devices with huge influence on the power generation efficiency of the old power plants can be further improved, so that the function of industry data cloud space is played.
In some alternative embodiments, the control module of the embodiment of the invention can determine that the operation state of the power plant is faulty according to the received operation state of the power plant, and then perform alarm processing.
Specifically, the staff can also correct the power plant through the running state of the power plant and the regulation scheme displayed in the display platform module; and obtaining and printing the log in the database through the data storage module.
As shown in fig. 4, an embodiment of the present invention provides a schematic diagram of a flow of a method for controlling power generation efficiency of a power plant in real time, including the following steps:
step S401, collecting operation data generated in the operation process of the power plant; screening target operation data from the operation data based on a preset rule;
the operation data comprise operation parameters of each device and operation state data of each device in the operation process of the power plant;
step S402, predicting the power generation efficiency of the power plant in a preset time period according to target operation data; if the power generation efficiency is determined to be lower than the threshold value, determining a regulation scheme for regulating equipment in the power plant according to the target operation data;
and step S403, determining control parameters which need to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameters.
Optionally, determining a regulation scheme for regulating equipment in the power plant according to the target operation data includes:
determining a regulation scheme for regulating equipment in a power plant according to target operation data and a predefined basic algorithm; or,
and inputting the target operation data into the trained data analysis model, and acquiring a regulation scheme for regulating equipment in the power plant, which is output by the trained data analysis model.
Optionally, determining a control parameter that needs to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameter includes:
determining control parameters and a control period for controlling equipment in a power plant according to a control scheme and a predefined control algorithm;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
Optionally, determining a control parameter that needs to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameter includes:
inputting a regulation and control scheme into a trained control model, and acquiring control parameters and a regulation and control period which are output by the trained control model and are required to regulate and control equipment in a power plant;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
Optionally, the method further comprises:
training the data analysis model according to the first sample set to obtain a trained data analysis model; and/or training the control model according to the second sample set to obtain a trained control model.
Optionally, the method further comprises:
acquiring a regulation scheme input by a user for regulating equipment in a power plant; or the control parameters and the regulation period which are input by the user and need to regulate and control the equipment in the power plant.
Optionally, the method further comprises: the method comprises the steps of storing collected historical operation data generated in the operation process of the power plant, and storing a regulation scheme input by a user or storing control parameters and regulation periods input by the user.
Optionally, the model is trained by:
acquiring a first sample set; the first sample set comprises sample operation data and a sample regulation and control scheme corresponding to the sample operation data; inputting the sample operation data into a data analysis model to obtain a reference regulation and control scheme output by the data analysis model; adjusting model parameters of the data analysis model according to the sample regulation and control scheme and the reference regulation and control scheme until a trained data analysis model is obtained; and/or, obtaining a second sample set; the second sample set comprises a sample regulation scheme, sample control parameters corresponding to the sample regulation scheme and a sample regulation period; inputting the sample regulation and control scheme into a control model, and obtaining a reference control parameter and a reference regulation and control period which are output by the control model; and adjusting the model parameters of the control model according to the sample control parameters, the sample regulation and control period, the reference control parameters and the reference regulation and control period until the trained control model is obtained.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The real-time control system for the power generation efficiency of the power plant is characterized by comprising a data acquisition module, an algorithm calculation and analysis module and a control module;
the data acquisition module is used for acquiring operation data generated in the operation process of the power plant; screening target operation data from the operation data based on a preset rule; the operation data comprise operation parameters of each device and operation state data of each device in the operation process of the power plant;
the algorithm calculation analysis module is used for predicting the power generation efficiency of the power plant in a preset duration according to the target operation data; if the power generation efficiency is determined to be lower than a threshold value, determining a regulation scheme for regulating equipment in the power plant according to the target operation data;
and the control module is used for determining control parameters which need to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameters.
2. The system according to claim 1, wherein the algorithmic calculation analysis module is specifically configured to:
determining a regulation scheme for regulating equipment in the power plant according to the target operation data and a predefined basic algorithm; or,
And inputting the target operation data into a trained data analysis model, and acquiring a regulation scheme which is output by the trained data analysis model and used for regulating equipment in the power plant.
3. The system according to claim 2, wherein the control module is specifically configured to:
determining control parameters and a control period for controlling equipment in the power plant according to the control scheme and a predefined control algorithm;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
4. The system according to claim 2, wherein the control module is specifically configured to:
inputting the regulation scheme into a trained control model, and acquiring control parameters and regulation periods which are output by the trained control model and are required to regulate equipment in the power plant;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
5. The system of claim 4, further comprising a super computing module;
The super computing module is used for training the data analysis model in the algorithm computing and analyzing module according to a first sample set to obtain the trained data analysis model; and/or training the control model in the control module according to a second sample set to obtain the trained control model.
6. The system of claim 5, further comprising a data storage module and a user input module;
the user input module is used for acquiring a regulation scheme input by a user for regulating equipment in the power plant; or a control parameter and a regulation period which are input by a user and need to regulate equipment in the power plant;
the data storage module is used for storing the historical operation data generated in the operation process of the power plant, which is acquired by the data acquisition module, and storing a regulation and control scheme input by a user through the user input module or storing control parameters and a regulation and control period input by the user through the user input module;
the super computing module is specifically configured to: acquiring the first sample set from the data storage module; the first sample set comprises sample operation data and a sample regulation and control scheme corresponding to the sample operation data; inputting the sample operation data into the data analysis model to acquire a reference regulation and control scheme output by the data analysis model; adjusting model parameters of the data analysis model according to the sample regulation and control scheme and the reference regulation and control scheme until a trained data analysis model is obtained; and/or obtaining the second sample set from the data storage module; the second sample set comprises a sample regulation scheme, and sample control parameters and sample regulation periods corresponding to the sample regulation scheme; inputting the sample regulation and control scheme into the control model, and obtaining a reference control parameter and a reference regulation and control period output by the control model; and adjusting the model parameters of the control model according to the sample control parameters, the sample regulation and control period, the reference control parameters and the reference regulation and control period until a trained control model is obtained.
7. The real-time control method for the power generation efficiency of the power plant is characterized by comprising the following steps of:
collecting operation data generated in the operation process of the power plant; screening target operation data from the operation data based on a preset rule; the operation data comprise operation parameters of each device and operation state data of each device in the operation process of the power plant;
predicting the power generation efficiency of the power plant in a preset time period according to the target operation data; if the power generation efficiency is determined to be lower than a threshold value, determining a regulation scheme for regulating equipment in the power plant according to the target operation data;
and determining control parameters which need to regulate equipment in the power plant according to the regulation scheme, and regulating the power plant according to the determined control parameters.
8. The method of claim 7, wherein determining a regulatory scheme for regulating a plant in the power plant based on the target operating data comprises:
determining a regulation scheme for regulating equipment in the power plant according to the target operation data and a predefined basic algorithm; or,
and inputting the target operation data into a trained data analysis model, and acquiring a regulation scheme which is output by the trained data analysis model and used for regulating equipment in the power plant.
9. The method of claim 8, wherein determining control parameters for controlling equipment in the power plant according to the control scheme, and controlling the power plant according to the determined control parameters comprises:
determining control parameters and a control period for controlling equipment in the power plant according to the control scheme and a predefined control algorithm;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
10. The method of claim 8, wherein determining control parameters for controlling equipment in the power plant according to the control scheme, and controlling the power plant according to the determined control parameters comprises:
inputting the regulation scheme into a trained control model, and acquiring control parameters and regulation periods which are output by the trained control model and are required to regulate equipment in the power plant;
and regulating and controlling the power plant based on the determined regulation and control period and the control parameters, so that equipment in the power plant operates according to the regulated control parameters.
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