CN117436153B - Entity characteristic parameterization implementation method applied to power plant heat supply - Google Patents
Entity characteristic parameterization implementation method applied to power plant heat supply Download PDFInfo
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Abstract
The invention provides a physical characteristic parameterization realization method applied to heat supply of a power plant, which belongs to the technical field of heat energy, and comprises the following steps: collecting physical quantity data and operation parameter data of a power plant through a sensor and monitoring equipment; preprocessing physical quantity data and operation parameter data; according to the preprocessed data and by combining the operation characteristics of the power plant, a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant is established; parameterizing the physical characteristics of the power plant by adopting the physical model, and establishing a parameterized model; step 5: and simulating the heat supply process of the power plant through a parameterized model, obtaining heat transmission and heat loss conditions of the power plant under different operating conditions, and optimizing the heat supply process of the power plant. The method solves the problems that in the background technology, large-scale parametric modeling and simulation are required to be carried out on the whole system, the calculation complexity and the time delay are high, and the heating capacity of the power plant is reduced.
Description
Technical Field
The invention relates to the technical field of heat energy, in particular to a physical characteristic parameterization realization method applied to heat supply of a power plant.
Background
Along with the continuous increase of the energy demand of the modern society, the power plant is used as a main supplier of energy, the stable and efficient operation of the power plant has important significance for guaranteeing the social stability and economic sustainable development, the traditional thermal power plant often has the problems of low operation efficiency, high energy consumption and environmental pollution, and a heat transmission optimization method based on a physical model and artificial intelligence is provided for the problems, however, the method often needs to carry out large-scale parametric modeling and simulation on the whole system, has higher calculation complexity and time delay, and reduces the heating capacity of the power plant.
Therefore, the invention provides a physical characteristic parameterization implementation method applied to heat supply of a power plant.
Disclosure of Invention
The invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, which is characterized in that physical quantity data and operation parameter data of a power plant are collected through a sensor and monitoring equipment, the physical quantity data and the operation parameter data are preprocessed, a physical model between the physical quantity data and the operation parameter data in the power plant heat supply process is established according to the preprocessed data and by combining the operation characteristics of the power plant, the physical characteristic parameterization of the power plant is implemented by adopting the physical model, a parameterization model is established, the power plant heat supply process is simulated through the parameterization model, the heat transmission and heat loss conditions of the power plant under different operation conditions are obtained, and the power plant heat supply process is optimized, so that the problems that the whole system needs to be modeled and simulated in a large scale in a parameterization manner in the background technology are solved, the calculation complexity and the time delay are higher, and the heat supply capacity of the power plant is reduced.
The invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, which comprises the following steps:
step 1: collecting physical quantity data and operation parameter data of a power plant through a sensor and monitoring equipment;
step 2: preprocessing the physical quantity data and the operation parameter data;
step 3: according to the preprocessed data and by combining the operation characteristics of the power plant, a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant is established;
step 4: parameterizing the physical characteristics of the power plant by adopting the physical model, and establishing a parameterized model;
step 5: and simulating the heat supply process of the power plant through a parameterized model, obtaining heat transmission and heat loss conditions of the power plant under different operating conditions, and optimizing the heat supply process of the power plant.
Preferably, collecting physical quantity data and operating parameter data of the power plant by the sensor and the monitoring device includes:
acquiring attributes of a plurality of key areas of a power plant and each key area;
determining the sensor type of each key area based on the attribute of the key area;
acquiring the monitoring range and the monitoring precision of the sensors of the types corresponding to each key area, and determining the number of the sensors in the key area according to the monitoring range and the monitoring precision of the sensors of the types corresponding to each key area;
setting a corresponding number of sensors in each key area based on the set number of the sensors in the key area to acquire physical quantity data of the power plant;
and meanwhile, the monitoring equipment is used for collecting the operation parameter data of the power plant.
Preferably, preprocessing the physical quantity data and the operation parameter data includes:
drawing a change curve according to the physical quantity data, determining whether an abnormal peak value or an abnormal valley value exists in the change curve, and if so, determining that the abnormal data exists in the physical quantity data;
filtering and de-duplication preprocessing are carried out on the physical quantity data;
meanwhile, carrying out integrity check on the operation parameter data to obtain a check result;
and selectively interpolating the operation parameter data according to the checking result.
Preferably, before combining the operation characteristics of the power plant according to the preprocessed data, the method further comprises: the operation characteristics of the power plant are determined, specifically:
determining an index to be monitored according to the heat supply requirement of the power plant, and acquiring the running state of the power plant based on the index;
acquiring real-time state parameters of the power plant based on the running state;
determining the performance index of the power plant according to the real-time state parameters;
and determining the operation characteristics of the power plant based on the performance index.
Preferably, establishing a physical model between physical quantity data and operation parameter data in the heating process of the power plant according to the preprocessed data and by combining with the operation characteristics of the power plant, includes:
determining a boiler type and a fuel type based on operating characteristics of the power plant;
determining boiler parameters based on the boiler type and the fuel type;
acquiring the relation between the preprocessed data and the boiler parameters by a regression analysis method;
determining a power transmission state description parameter of the power plant according to the relation between the preprocessed data and the boiler parameters;
and establishing a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant based on the power transmission state description parameters.
Preferably, the physical model is used for parameterizing physical characteristics of the power plant, and the parameterized model is built, including:
acquiring the operation condition and historical data analysis of a power plant, and determining key entity characteristic parameters;
acquiring and classifying the parameter attribute of the entity characteristic parameter;
and carrying out parameterization processing on the physical characteristics of the power plant by adopting the physical model based on the classification result, and establishing a parameterized model.
Preferably, through parameterized model, simulate the heat supply process of the power plant, obtain the heat transmission and the heat loss condition of the power plant under different operation conditions, and optimize the heat supply process of the power plant, including:
simulating a power plant heating process through a parameterized model;
determining a plurality of parameters of each link in the power plant under different conditions based on water supply quantity, water supply temperature and water supply pressure based on simulation results;
determining heat transfer relation of each link in the power plant based on the plurality of parameters;
determining a heat transfer condition based on the heat transfer relationship, and acquiring heat transfer and heat loss conditions;
and optimizing the heat supply process of the power plant based on the heat transmission and heat loss conditions.
Preferably, optimizing the power plant heating process based on the heat transfer and heat loss conditions includes:
acquiring historical combustion data of a power plant boiler;
analyzing the historical combustion data by adopting a fuzzy clustering data analysis method to determine the fuel consumption characteristics of the boiler under different loads and running conditions;
constructing a characteristic model of the boiler according to the fuel consumption characteristics of the boiler under different loads and running conditions;
performing a first optimization according to a characteristic model of the boiler, wherein the first optimization is optimization of the boiler fuel and the boiler construction;
determining the distribution condition of heat supply pipeline nodes of the power plant according to the deployment of each link of the power plant;
calculating the working medium transmission time delay of the branch pipeline of each node of the heat supply pipeline according to the distribution condition of the nodes of the heat supply pipeline of the power plant;
merging branch pipes with transmission time delay above a preset threshold and at the same node into one pipe;
obtaining pipeline parameters of the combined pipelines;
constructing a heat supply pipeline network model of the power plant according to the pipeline parameters;
simulating pipeline heat supply flow characteristics of the power plant according to a heat supply pipeline network simulation of the power plant;
and solving the pipeline heat supply flow characteristics of the power plant by using a statistical regression method to obtain characteristic coefficients, and performing second optimization on the heat supply pipeline, wherein the second optimization is optimization on the flow and the structure of the heat supply pipeline.
Compared with the prior art, the beneficial effects of the application are as follows:
physical quantity data and operation parameters of the power plant are obtained and preprocessed, a physical model is built according to the processed data and the operation characteristics of the power plant, the physical characteristics of the power plant are parameterized through the physical model, a parameterized model is built and simulated, and a heating process is optimized through a simulation result, so that the need of carrying out large-scale parameterized modeling and simulation on the whole system is avoided, the modeling process and analysis process are improved, and the high efficiency and energy conservation of the heating operation of the power plant are realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for implementing physical feature parameterization applied to power plant heating in an embodiment of the invention;
FIG. 2 is a flow chart of data collection in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1:
the invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, as shown in fig. 1, the method comprises the following steps:
step 1: collecting physical quantity data and operation parameter data of a power plant through a sensor and monitoring equipment;
step 2: preprocessing the physical quantity data and the operation parameter data;
step 3: according to the preprocessed data and by combining the operation characteristics of the power plant, a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant is established;
step 4: parameterizing the physical characteristics of the power plant by adopting the physical model, and establishing a parameterized model;
step 5: and simulating the heat supply process of the power plant through a parameterized model, obtaining heat transmission and heat loss conditions of the power plant under different operating conditions, and optimizing the heat supply process of the power plant.
In this embodiment, the sensor is a device that is capable of sensing the internal and external environment and converting it into a usable signal, such as: light sensor, temperature sensor, humidity sensor, pressure sensor, acceleration sensor, gyroscope sensor.
In this embodiment, monitoring devices refer to devices for collecting and analyzing plant operational data, including, but not limited to: data acquisition equipment, data processing system, display device, automation equipment.
In this embodiment, the plant physical quantity data refers to physical quantity data for describing the operation state and performance of the plant, such as: voltage, current, frequency, temperature, humidity.
In this embodiment, the operating parameter data refers to parameters generated during operation of a machine in the power plant, such as: the generated electric energy and the rotating speed of the machine.
In this embodiment, preprocessing refers to cleaning, converting, and integrating raw data, detecting and correcting outliers, missing values, and erroneous values in the data, and converting the data into a form suitable for analysis.
In this embodiment, the operating characteristics of the power plant refer to the power generation capacity and the load capacity of the power plant.
In this embodiment, the physical model describes the flow of heat in the equipment and piping during the power plant heating process.
In this embodiment, the entity signature parameterization is a machine learning algorithm that processes datasets with multiple categories of entity signatures.
In this embodiment, the parameterized model is a machine learning algorithm that uses parameters to describe and optimize the model.
In this embodiment, the optimizing may include:
the combustion efficiency of the boiler is improved: the parameters of the combustion process, such as the air quantity, the temperature, the flow rate and the like of the air preheater, are adjusted so as to improve the combustion efficiency of the boiler and reduce the fuel consumption and the pollutant emission.
Optimizing water supply treatment: advanced water treatment technology, such as reverse osmosis, ion exchange, etc. is adopted to reduce impurity and salt in water, raise water quality of boiler, reduce corrosion and scale and raise heat efficiency of boiler.
Adjusting the heat load of the boiler: according to the actual load condition of the boiler, the operation working condition of the boiler is reasonably adjusted, such as the combustion speed of the boiler, the output of the boiler and the like, so as to achieve the optimal heat efficiency and energy utilization rate.
The beneficial effects of the technical scheme are as follows: physical quantity data and operation parameters of the power plant are obtained and preprocessed, a physical model is built according to the processed data and the operation characteristics of the power plant, the physical characteristics of the power plant are parameterized through the physical model, a parameterized model is built and simulated, and a heating process is optimized through a simulation result, so that the need of carrying out large-scale parameterized modeling and simulation on the whole system is avoided, the modeling process and analysis process are improved, and the high efficiency and energy conservation of the heating operation of the power plant are realized.
Example 2:
the invention provides a physical characteristic parameterization implementation method applied to heat supply of a power plant, which is shown in fig. 2, and collects physical quantity data and operation parameter data of the power plant through a sensor and monitoring equipment, and comprises the following steps:
s01: acquiring attributes of a plurality of key areas of a power plant and each key area;
s02: determining the sensor type of each key area based on the attribute of the key area;
s03: acquiring the monitoring range and the monitoring precision of the sensors of the types corresponding to each key area, and determining the number of the sensors in the key area according to the monitoring range and the monitoring precision of the sensors of the types corresponding to each key area;
s04: setting a corresponding number of sensors in each key area based on the set number of the sensors in the key area to acquire physical quantity data of the power plant;
s05: and meanwhile, the monitoring equipment is used for collecting the operation parameter data of the power plant.
In this embodiment, the plurality of critical areas of the power plant include: generator room, boiler room, heating power pipeline room, electric control room, fuel storage room and oxidizer room.
In this embodiment, the attributes of the key regions are, for example: a heat source part, a fuel part, a cooling part and an oxidant part.
In this embodiment, the sensor types include: thermocouple sensor, photoelectric sensor, pressure sensor, humidity sensor.
In this embodiment, the monitoring range of the sensor means, for example:
thermocouple sensor: for monitoring high and low temperature environments, typically ranging from-200 ℃ to +1200 ℃.
Photoelectric sensor: for monitoring the intensity of light, the monitoring range is usually between 0 light and 40000 light.
A pressure sensor: for monitoring various pressures, such as air pressure, water pressure, etc., the monitoring range is usually 0 to 100.
Humidity sensor: for monitoring air humidity, the monitoring range is typically between 0% and 100%.
In this embodiment, the monitoring accuracy of the sensor refers to a range of physical or chemical quantities that the sensor can measure, for example, a monitoring range of a certain temperature sensor is 0 ℃ to 50 ℃, which means that the sensor can measure a temperature range between 0 ℃ and 50 ℃, different sensors have different monitoring accuracy in different monitoring ranges, in general, the monitoring accuracy of the sensor may be lower for monitoring in a large range, and the monitoring accuracy of the sensor may be higher for monitoring in a small range.
The beneficial effects of the technical scheme are as follows: through the multiple key areas of the power plant and the attributes of the key areas, the monitoring range and the monitoring precision of the sensors of the key areas are determined, so that the number of the sensors which should be arranged in each key area is determined, the data acquired by the sensors can be more accurate, and the physical quantity data of each area are more comprehensive.
Example 3:
the invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, which is used for preprocessing physical quantity data and operation parameter data and comprises the following steps:
drawing a change curve according to the physical quantity data, determining whether an abnormal peak value or an abnormal valley value exists in the change curve, and if so, determining that the abnormal data exists in the physical quantity data;
filtering and de-duplication preprocessing are carried out on the physical quantity data;
meanwhile, carrying out integrity check on the operation parameter data to obtain a check result;
and selectively interpolating the operation parameter data according to the checking result.
In this embodiment, the drawing of the change curve means that each physical quantity data corresponds to one curve.
In this embodiment, the abnormal peak value or the abnormal valley value refers to a phenomenon in which parameters such as current or voltage of an object appear to exceed a normal range in some cases.
In this embodiment, the data filtering refers to screening or processing data by a specific rule or algorithm so as to extract data meeting a specific condition.
In this embodiment, data deduplication refers to the removal of duplicate values in the data.
In this embodiment, the selective interpolation process refers to selecting a suitable interpolation method to perform interpolation according to the change trend and property of the known data in the interpolation process, for example: polynomial interpolation, quadratic interpolation.
In this embodiment, the process of selectively interpolating the operation parameter data according to the inspection result further includes:
the operation parameter data are subjected to standardized processing and sequentially input into a filling curve, and a first curve is constructed and obtained;
determining the number of missing points in the first curve, and simultaneously, obtaining the number of continuous missing segments of the first curve;
determining the number of single interpolation according to the number of missing points and the number of continuous missing segments;
；
wherein N4 is the number of single interpolation; m2 represents the number of continuous missing segments; m1 represents the number of missing points in the first curve;representing the number of missing points in the j1 th continuous missing segment; />Representing a rounding symbol;
and determining the interpolation number, and selecting a corresponding interpolation mode to perform interpolation processing according to the number-method mapping table.
In this embodiment, the purpose of the normalization processing is to normalize the parameters, so that the subsequent curve drawing is convenient, and drawing anomalies caused by different parameter dimensions are avoided.
In this embodiment, the filling curve is preset, for example, the position point 1 is the parameter 1 after the normalization process, the position point 2 is the parameter 2 after the normalization process, and so on, to obtain the first curve.
In this embodiment, for example, there are no parameters for placement at all of the consecutive location points 2, 3, 4, and the consecutive missing segments are considered.
In this embodiment, the inspection result is the case where the determined curve has missing points.
In this embodiment, the single interpolation number refers to the number of all missing points that need to be numerically complemented.
In this embodiment, the number-method mapping table includes different interpolation numbers and interpolation methods matched with the interpolation numbers, so as to implement preprocessing of data.
The beneficial effects of the technical scheme are as follows: by drawing a change curve on the physical quantity data, determining whether abnormal data exists in the data, filtering and de-duplication preprocessing the data, the accuracy of the data can be improved, meanwhile, the integrity checking is carried out on the operation parameter data, the data loss and the error can be effectively prevented, further, the interpolation precision and the stability can be improved through the selective interpolation processing of the operation parameter data, and the interpolation result is more approximate to the actual situation.
Example 4:
the invention provides a physical characteristic parameterization implementation method applied to heat supply of a power plant, which comprises the following steps of: the operation characteristics of the power plant are determined, specifically:
determining an index to be monitored according to the heat supply requirement of the power plant, and acquiring the running state of the power plant based on the index;
acquiring real-time state parameters of the power plant based on the running state;
determining the performance index of the power plant according to the real-time state parameters;
and determining the operation characteristics of the power plant based on the performance index.
In this embodiment, the heating requirement of the power plant refers to that the heating capacity of the boiler is adapted to the load requirement by adjusting the supply amount of the fuel and air mixture to the boiler according to the actual load condition in the normal operation state of the power plant, for example: providing a proper fuel and air mixture for the boiler, keeping the temperature of the feed water of the boiler in a proper range, and controlling the flue gas emission of the boiler.
In this embodiment, the index includes: temperature, pressure, flow, electrical energy.
In this embodiment, the thermal state, the electrical state, the mechanical state, the hydraulic state, the thermal state.
In this embodiment, the real-time state parameters are for example thermal states, the parameters comprise steam parameters, feed water temperature, boiler superheat, turbine superheat, for example electrical states, the parameters comprise voltage, frequency, short-circuit current, phase angle, for example mechanical states, the parameters comprise rotational speed, differential speed, vibrations, for example hydraulic states, the parameters comprise oil pressure, oil flow, oil temperature, for example thermal control states, the parameters comprise temperature, pressure, humidity.
In this embodiment, performance means that the cooling and heating effect of the power plant can be known, for example, by analyzing temperature and pressure data; by analyzing the flow and power data, the power generation capacity and load condition of the power plant can be known.
In this embodiment, the operating characteristics of the power plant refer to the power generation capacity and the load capacity of the power plant.
The beneficial effects of the technical scheme are as follows: the operation state of the power plant is acquired through the indexes to be monitored, the performance indexes of the power plant are determined by acquiring the real-time state parameters of the power plant according to the operation state, the operation characteristics of the power plant are finally acquired, the characteristics of the power plant in the operation process can be known in time, the equipment of the power plant can be regulated differently according to different characteristics, and the heat supply capacity is improved.
Example 5:
the invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, which establishes a physical model between physical quantity data and operation parameter data in the power plant heat supply process according to preprocessed data and by combining operation characteristics of a power plant, and comprises the following steps:
determining a boiler type and a fuel type based on operating characteristics of the power plant;
determining boiler parameters based on the boiler type and the fuel type;
acquiring the relation between the preprocessed data and the boiler parameters by a regression analysis method;
determining a power transmission state description parameter of the power plant according to the relation between the preprocessed data and the boiler parameters;
and establishing a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant based on the power transmission state description parameters.
In this embodiment, the boiler types are classified into: utility boilers, industrial boilers, air-conditioning boilers.
In this embodiment, the fuel types include: coal, oil, natural gas, renewable energy.
In this embodiment, the boiler parameters include: heat transfer coefficient, specific heat, density, temperature.
In this embodiment, regression analysis is a commonly used statistical analysis method for analyzing the relationship between two or more independent variables and one dependent variable.
In this embodiment, the power transmission state description parameters refer to respective parameters for describing the operation state of the power system, including: voltage, current, power, temperature.
In this embodiment, the physical model between the physical quantity data and the operation parameter data refers to a data acquisition model for describing various physical quantities (such as voltage, current, power, etc.) in the operation of the electric power system, such as: when the power factor output by the generator is analyzed, a relation physical model between the power factor and the active output can be established; and when the current in the power transmission line is analyzed, a physical model of the relation between the current and the voltage can be established.
The beneficial effects of the technical scheme are as follows: the boiler parameters are determined through the boiler type and the fuel type, and the relation between the preprocessed data and the boiler parameters is obtained through a regression analysis method, so that the power transmission state description parameters of the power plant are determined, a physical model is built, the understanding of the physical process in the power system can be helped, the running state and the problem are analyzed, and the heat supply efficiency of the power plant is improved.
Example 6:
the invention provides a physical characteristic parameterization implementation method applied to heat supply of a power plant, which adopts the physical model to parameterize the physical characteristic of the power plant and establishes a parameterization model, and comprises the following steps:
acquiring the operation condition and historical data analysis of a power plant, and determining key entity characteristic parameters;
acquiring and classifying the parameter attribute of the entity characteristic parameter;
and carrying out parameterization processing on the physical characteristics of the power plant by adopting the physical model based on the classification result, and establishing a parameterized model.
In this embodiment, the operating conditions of the power plant may include: the power generation efficiency is lowered, the stabilizer is over-current, the voltage is over-high or over-low.
In this embodiment, the entity characteristic parameters include: capacity, load, temperature, humidity, wind speed of the power plant.
In this embodiment, parameter attributes refer to values used to describe or identify various attributes of a data object during data storage or processing, which may include text, numbers, boolean values, dates, times.
In this embodiment, the parameterized model is a machine learning algorithm that uses parameters to describe and optimize the model.
The beneficial effects of the technical scheme are as follows: through the analysis of the running condition and the historical data of the power plant, the key entity characteristic parameters are determined, the classification is carried out according to the parameter attributes, the entity characteristic parameters are parameterized according to the classification result, a parameterized model is built, the safe sharing of the parameters in the model can be ensured, the parameters in the model can be quickly adjusted or modified according to the real-time condition, and the real-time performance of the data is ensured.
Example 7:
the invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, which simulates a power plant heat supply process through a parameterization model to obtain heat transmission and heat loss conditions of a power plant under different operation conditions and optimize the power plant heat supply process, and comprises the following steps:
simulating a power plant heating process through a parameterized model;
determining a plurality of parameters of each link in the power plant under different conditions based on water supply quantity, water supply temperature and water supply pressure based on simulation results;
determining heat transfer relation of each link in the power plant based on the plurality of parameters;
determining a heat transfer condition based on the heat transfer relationship, and acquiring heat transfer and heat loss conditions;
and optimizing the heat supply process of the power plant based on the heat transmission and heat loss conditions.
In this embodiment, the parameterized model is a machine learning algorithm that uses parameters to describe and optimize the model.
In this embodiment, simulation refers to simulating a power plant heating process using a computer system or software tool to verify or study power plant heating process functions, performance, behavior, or performance.
In this embodiment, different operating conditions are, for example, different temperatures, different pressures, and different operating speeds.
In this embodiment, the plurality of parameters are, for example, heat transfer rate, heating temperature.
In this embodiment, the heat transfer relationship refers to the rate and path of heat transfer from the high temperature portion to the low temperature portion during the heat transfer process.
In this embodiment, the heat transfer relationship refers to the temperature distribution of different positions inside the object, and whether the heat transfer condition is good or poor is determined according to the temperature distribution.
In this embodiment, after the power plant heating process is simulated, the simulation result is visually displayed, including:
determining a central pixel point of any frame of color image, and acquiring a pixel value of any pixel point except the central pixel point in the frame of color image;
calculating a pixel analysis value between any pixel point and a central pixel point according to the pixel value of any pixel point in the frame color image:
；
wherein,expressed as a pixel analysis value between the i-th pixel and the center pixel point, +.>Expressed as a tuning constant, exp expressed as an exponential function based on e, ++>Pixel value denoted as i-th pixel, ">Represented as pixel mean value of the processed gray image, for example>Expressed as empirical parameters; />A pixel value representing a center pixel point; />Represented as a pixel mean value of all points on a straight line connection based on the ith pixel point and the center pixel point on the processed gray-scale image; />Representing positive and negative adjustment coefficients;
determining the pixel value of which the pixel analysis value is greater than or equal to a preset threshold value as a pixel with clear visual display;
and integrating all the pixel points with clear visual display to generate a display image for display.
The beneficial effects of the technical scheme are as follows: by simulating the heat supply process, a plurality of heat supply parameters under different conditions are determined according to simulation results, the heat transfer relation and the heat transfer condition of the power plant are determined according to the heat supply parameters, and the heat transfer and heat loss conditions are obtained, so that the energy consumption can be effectively reduced, the energy waste is reduced, and the heat transfer efficiency is improved.
Example 8:
the invention provides a physical characteristic parameterization implementation method applied to power plant heat supply, which optimizes the power plant heat supply process based on the heat transmission and heat loss conditions, and comprises the following steps:
acquiring historical combustion data of a power plant boiler;
analyzing the historical combustion data by adopting a fuzzy clustering data analysis method to determine the fuel consumption characteristics of the boiler under different loads and running conditions;
constructing a characteristic model of the boiler according to the fuel consumption characteristics of the boiler under different loads and running conditions;
performing a first optimization according to a characteristic model of the boiler, wherein the first optimization is optimization of the boiler fuel and the boiler construction;
determining the distribution condition of heat supply pipeline nodes of the power plant according to the deployment of each link of the power plant;
calculating the working medium transmission time delay of the branch pipeline of each node of the heat supply pipeline according to the distribution condition of the nodes of the heat supply pipeline of the power plant;
merging branch pipes with transmission time delay above a preset threshold and at the same node into one pipe;
obtaining pipeline parameters of the combined pipelines;
constructing a heat supply pipeline network model of the power plant according to the pipeline parameters;
simulating pipeline heat supply flow characteristics of the power plant according to a heat supply pipeline network simulation of the power plant;
and solving the pipeline heat supply flow characteristics of the power plant by using a statistical regression method to obtain characteristic coefficients, and performing second optimization on the heat supply pipeline, wherein the second optimization is optimization on the flow and the structure of the heat supply pipeline.
In this embodiment, the historical combustion data includes: rated power of the boiler, thermal efficiency of the boiler, operating time of the boiler, fuel consumption of the boiler.
In this embodiment, fuzzy clustering is a classification method based on fuzzy set theory, and can process uncertainty and fuzzy data.
In this embodiment, different loads refer to different loads in the power system, and the influence on the power system is different under the same power load due to different kinds and properties of the loads, including: residential load, commercial load, industrial load, traffic load.
In this embodiment, the fuel consumption characteristics refer to the characteristics of the relationship between the consumption amount and the use amount of the fuel during its use, including:
nonlinear characteristics: the relation between the fuel consumption and the usage is not linear, i.e. there is a certain non-linear range, for example, when the fuel consumption increases, the consumption may increase by a much larger extent than the usage.
Decremental: when the fuel consumption is increased, the consumption is gradually reduced, and when the fuel consumption reaches a certain degree in the use process, the consumption is not increased significantly.
In this embodiment, the characteristic model of the boiler refers to a mathematical model describing various aspects of thermodynamic, kinetic, combustion, corrosion and wear characteristics of the boiler.
In this embodiment, each link deployment of the power plant includes: deployment of a cogeneration system, deployment of a power generation system, deployment of a power transmission system and deployment of a power distribution system.
In this embodiment, the distribution of the nodes of the heating pipeline of the power plant includes: the specific location, number and manner of pipe connection of the pipe nodes.
In this embodiment, first, detailed data of power plant heat supply pipeline nodes are collected, including information of pipeline diameter, pipeline length, pipeline material and the like, and distances between the nodes and heat medium flow rates, and based on the collected data, a three-dimensional model is built to describe the structure and flow field of the power plant heat supply pipeline, wherein the model can include pipelines, branch pipes and space flow fields, and the model is used for analyzing the transmission time delay of working media of the heat supply pipeline nodes.
In this embodiment, the working medium transmission time delay refers to the time required for the transmission of the heating medium in the heat supply pipeline due to the friction, resistance, thermal resistance and other factors of the pipeline.
In this embodiment, the preset threshold is 5 seconds.
In this embodiment, the pipeline parameters include: the cross-sectional area of the pipeline, the shape of the pipeline, the pipeline material and the flow velocity in the pipeline.
In this embodiment, the heating pipeline network model is a model for describing the connection relationship between the respective parts, devices, and elements of the heating pipeline system.
In this embodiment, the pipeline heating flow characteristic refers to the regular characteristic of the fluid in the pipeline when moving in the pipeline, including flow rate, pressure, flow distribution and pipeline vibration.
In this embodiment, the characteristic coefficient is a coefficient describing a relationship between parameters such as a flow rate, a pressure, and a flow rate of the fluid in the pipe, for example: the larger the flow velocity, the smaller the flow characteristic coefficient; the smaller the flow velocity, the larger the flow characteristic coefficient; the flow characteristic coefficient of the steel pipe is higher than that of the copper pipe; the flow velocity distribution in the pipeline is relatively uniform, so that the flow characteristic coefficient is relatively small; if the flow velocity distribution in the pipe is relatively uneven, the flow characteristic coefficient is relatively large.
The beneficial effects of the technical scheme are as follows: the method has the advantages that the historical combustion data is analyzed through the fuzzy clustering data analysis method, the fuel consumption characteristics of the boiler under different loads and operation conditions are determined, the characteristic model of the boiler is built, the analysis and prediction of the working state, performance indexes and fault conditions of the boiler can be facilitated, thereby providing scientific basis for the operation and management of the boiler, further, the distribution condition of the heat supply pipeline nodes of the power plant is determined according to the arrangement of each link of the power plant, the transmission time is delayed above a preset threshold and is in the same pipeline of the same node, the pipeline parameters are acquired, the heat supply pipeline network model of the power plant is built, the pipeline heat supply flow characteristics of the power plant are simulated, the pipeline can be optimized, and the heat supply capacity of the power plant is improved.
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 (6)
1. The utility model provides a physical characteristic parameterization realization method applied to power plant heat supply, which is characterized in that the method comprises the following steps:
step 1: collecting physical quantity data and operation parameter data of a power plant through a sensor and monitoring equipment;
step 2: preprocessing the physical quantity data and the operation parameter data;
step 3: according to the preprocessed data and by combining the operation characteristics of the power plant, a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant is established;
step 4: parameterizing the physical characteristics of the power plant by adopting the physical model, and establishing a parameterized model;
step 5: simulating a power plant heat supply process through a parameterized model, obtaining heat transmission and heat loss conditions of the power plant under different running conditions, and optimizing the power plant heat supply process;
wherein, step 5 includes:
simulating a power plant heating process through a parameterized model;
determining a plurality of parameters of each link in the power plant under different conditions based on water supply quantity, water supply temperature and water supply pressure based on simulation results;
determining heat transfer relation of each link in the power plant based on the plurality of parameters;
determining a heat transfer condition based on the heat transfer relationship, and acquiring heat transfer and heat loss conditions;
optimizing a power plant heating process based on the heat transfer and heat loss conditions;
wherein optimizing the power plant heating process based on the heat transfer and heat loss conditions comprises:
acquiring historical combustion data of a power plant boiler;
analyzing the historical combustion data by adopting a fuzzy clustering data analysis method to determine the fuel consumption characteristics of the boiler under different loads and running conditions;
constructing a characteristic model of the boiler according to the fuel consumption characteristics of the boiler under different loads and running conditions;
performing a first optimization according to a characteristic model of the boiler, wherein the first optimization is optimization of the boiler fuel and the boiler construction;
determining the distribution condition of heat supply pipeline nodes of the power plant according to the deployment of each link of the power plant;
calculating the working medium transmission time delay of the branch pipeline of each node of the heat supply pipeline according to the distribution condition of the nodes of the heat supply pipeline of the power plant;
merging branch pipes with transmission time delay above a preset threshold and at the same node into one pipe;
obtaining pipeline parameters of the combined pipelines;
constructing a heat supply pipeline network model of the power plant according to the pipeline parameters;
simulating pipeline heat supply flow characteristics of the power plant according to a heat supply pipeline network simulation of the power plant;
and solving the pipeline heat supply flow characteristics of the power plant by using a statistical regression method to obtain characteristic coefficients, and performing second optimization on the heat supply pipeline, wherein the second optimization is optimization on the flow and the structure of the heat supply pipeline.
2. The method for implementing physical characteristic parameterization applied to heat supply of power plant according to claim 1, wherein collecting physical quantity data and operation parameter data of the power plant through sensors and monitoring devices comprises:
acquiring attributes of a plurality of key areas of a power plant and each key area;
determining the sensor type of each key area based on the attribute of the key area;
acquiring the monitoring range and the monitoring precision of the sensors of the types corresponding to each key area, and determining the number of the sensors in the key area according to the monitoring range and the monitoring precision of the sensors of the types corresponding to each key area;
setting a corresponding number of sensors in each key area based on the set number of the sensors in the key area to acquire physical quantity data of the power plant;
and meanwhile, the monitoring equipment is used for collecting the operation parameter data of the power plant.
3. The method for implementing physical characteristic parameterization applied to heat supply of a power plant according to claim 1, wherein preprocessing the physical quantity data and the operation parameter data comprises:
drawing a change curve according to the physical quantity data, determining whether an abnormal peak value or an abnormal valley value exists in the change curve, and if so, determining that the abnormal data exists in the physical quantity data;
filtering and de-duplication preprocessing are carried out on the physical quantity data;
meanwhile, carrying out integrity check on the operation parameter data to obtain a check result;
and selectively interpolating the operation parameter data according to the checking result.
4. The method for implementing physical characteristic parameterization applied to heat supply of a power plant according to claim 1, further comprising, before combining the operation characteristics of the power plant according to the preprocessed data: the operation characteristics of the power plant are determined, specifically:
determining an index to be monitored according to the heat supply requirement of the power plant, and acquiring the running state of the power plant based on the index;
acquiring real-time state parameters of the power plant based on the running state;
determining the performance index of the power plant according to the real-time state parameters;
and determining the operation characteristics of the power plant based on the performance index.
5. The method for realizing physical characteristic parameterization applied to heat supply of a power plant according to claim 1, wherein establishing a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant according to the preprocessed data and by combining operation characteristics of the power plant comprises the following steps:
determining a boiler type and a fuel type based on operating characteristics of the power plant;
determining boiler parameters based on the boiler type and the fuel type;
acquiring the relation between the preprocessed data and the boiler parameters by a regression analysis method;
determining a power transmission state description parameter of the power plant according to the relation between the preprocessed data and the boiler parameters;
and establishing a physical model between physical quantity data and operation parameter data in the heat supply process of the power plant based on the power transmission state description parameters.
6. The method for realizing the parameterization of the physical characteristics applied to the heat supply of the power plant according to claim 1, wherein the step of adopting the physical model to parameterize the physical characteristics of the power plant to establish a parameterized model comprises the following steps:
acquiring the operation condition and historical data analysis of a power plant, and determining key entity characteristic parameters;
acquiring and classifying the parameter attribute of the entity characteristic parameter;
and carrying out parameterization processing on the physical characteristics of the power plant by adopting the physical model based on the classification result, and establishing a parameterized model.
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