Real-time calculation method and system for energy storage capacity of thermal power generating unit

Abstract

The invention discloses a thermal power generating unit energy storage capacity real-time calculation method and system, and the method comprises the steps: S1, collecting n-layer temperature data of a steam pocket wall, and calculating the heat storage increment and the total heat storage amount of each layer; s2, establishing a dynamic capacity flow model of the main steam, the reheat steam and the water supply system, calculating the energy change of the main steam, and updating the heat absorption capacity of the reheat steam; s3, periodically acquiring an infrared thermal image of the heating surface, designing a dust scale layer inversion method based on the infrared thermal image and a genetic algorithm, executing dust scale distribution optimization calculation, and updating equivalent thermal resistance in a heat transfer equation; and S4, an energy storage release strategy under pressure-temperature gradient constraint is constructed, the pipe wall temperature rise rate is monitored in real time, and the desuperheating water flow is automatically increased. The problems that according to an existing thermal power unit energy storage capacity real-time calculation method, energy of a steam-water system is unbalanced, and a dynamic correlation equation of desuperheating water injection and reheat steam heat absorption is not established are solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of thermal power unit energy storage calculation, in particular to a thermal power unit energy storage capacity real-time calculation method and system. BACKGROUND

[0002] The thermal power unit energy storage capacity calculation needs to consider both the boiler metal heat storage and the energy dynamics of the steam-water system.

[0003] The existing thermal power unit energy storage capacity real-time calculation method has defects: the steam-water system energy is unbalanced, and the dynamic correlation equation of desuperheating water injection and reheat steam heat absorption is not established. SUMMARY

[0004] In view of the problems of the existing thermal power unit energy storage capacity real-time calculation method, i.e. the steam-water system energy is unbalanced, and the dynamic correlation equation of desuperheating water injection and reheat steam heat absorption is not established, the application provides a thermal power unit energy storage capacity real-time calculation method and system.

[0005] To achieve the above technical purposes, the technical scheme adopted by the application is as follows:

[0006] A thermal power unit energy storage capacity real-time calculation method, comprising the steps of:

[0007] S1, collecting the temperature data of the n layers of the steam drum wall, calculating the heat storage increment of each layer and the total heat storage;

[0008] S2, establishing a dynamic capacity flow model of the main steam, reheat steam and feedwater system, calculating the energy change of the main steam, and updating the heat absorption of the reheat steam;

[0009] S3, periodically obtaining the infrared thermal image of the heating surface, designing a soot layer inversion method based on the infrared thermal image and genetic algorithm, performing soot distribution optimization calculation, and updating the equivalent thermal resistance in the heat transfer equation;

[0010] S4, constructing an energy storage release strategy under the constraint of pressure-temperature gradient, real-time monitoring the pipe wall temperature rise rate, and automatically increasing the desuperheating water flow.

[0011] Further, the detailed steps of step S1 include:

[0012] Collecting the temperature data of the 10 layers of the steam drum wall;

[0013] Constructing a metal component heat storage real-time calculation formula based on the heat transfer differential equation:

[0014] Steam drum wall layered modeling:

[0015] The steam drum wall is divided into n layers (n≥10), and the temperature gradient of each layer is calculated:

[0016]

[0017] where a is the thermal diffusivity of the material, dynamically corrected with temperature (based on measured data of CrMoV steel), x is the unit normal vector, q ext is the heat loss of the drum, Cp is the specific heat capacity, p is the material density.

[0018] Total heat storage calculation:

[0019]

[0020] Q metal is the total heat storage of the metal, V i is the metal volume, T amb is the ambient temperature.

[0021] Further, a dynamic capacity flow model of the main steam, reheat steam and feedwater system is established:

[0022] Main steam energy equation:

[0023]

[0024] is the main steam flow, h main is the main steam enthalpy, h fw is the feedwater enthalpy, is the heat loss of the pipe wall;

[0025] Reheat steam heat absorption correlation:

[0026] The desuperheating water quantity is established as a transfer function of the reheat steam enthalpy rise:

[0027]

[0028] Δh reheat is the reheat steam enthalpy rise, K is the energy conversion coefficient, and t is the energy transfer lag time.

[0029] Further, the detailed steps of step S2 include:

[0030] Reading the main steam flow Feedwater enthalpy h fw ;

[0031] Calculating the main steam energy change AE main , and deducting the heat loss of the pipe wall (based on infrared inversion of ash fouling thermal resistance);

[0032] Updating the reheat steam heat absorption quantity Q spray by the desuperheating water quantity .

[0033] Further, an ash fouling layer inversion method based on infrared thermal imaging and genetic algorithm is designed:

[0034] Infrared temperature field analysis:

[0035] The temperature distribution T(x, y) of the heated surface is detected by a thermal imager, and the thickness δ of the scale is then calculated. ash :

[0036]

[0037] K ash The heat transfer coefficient;

[0038] Dynamic updates of thermal resistance:

[0039] Calculations to optimize the distribution of ash and dirt are performed every 30 minutes, updating the equivalent thermal resistance R in the heat transfer equation. fouling .

[0040] Furthermore, the detailed steps of step S3 include:

[0041] Infrared thermal images of the heated surface are acquired every 30 minutes, and SRCNN super-resolution reconstruction is performed.

[0042] Solve the inverse heat transfer problem and output the scale thickness distribution diagram δ. ash (x,y);

[0043] Update the equivalent thermal resistance R in the soda energy equation fouling .

[0044] Furthermore, energy storage and release strategies under pressure-temperature gradient constraints:

[0045] Dynamic limiting logic:

[0046]

[0047] In order to release stored energy, Q total For total energy storage, Q base This is the energy storage benchmark value;

[0048] When the pipe wall temperature rise rate |dT / dt|>3℃ / s, the desuperheating water-assisted heat storage release is triggered.

[0049] A real-time calculation system for the energy storage capacity of a thermal power unit includes a data acquisition unit, a metal thermal storage calculation unit, a steam-water coupling calculation unit, an online correction unit for ash and scale thermal resistance, and an energy storage safety release control unit.

[0050] The data acquisition unit collects steam drum wall temperature data;

[0051] The metal heat storage calculation unit constructs a real-time calculation formula for the heat storage of metal components based on the heat transfer differential equation, and calculates the heat storage increment of each layer.

[0052] The steam-water coupling calculation unit establishes a dynamic capacity flow model of the main steam, reheat steam, and feedwater system, calculates the energy change of the main steam, and updates the heat absorption of the reheat steam.

[0053] The online correction unit for scale thermal resistance periodically acquires infrared thermal images of the heated surface, designs a scale layer inversion method based on infrared thermal images and genetic algorithms, performs scale distribution optimization calculations, and updates the equivalent thermal resistance in the heat transfer equation.

[0054] The energy storage safety release control unit constructs an energy storage release strategy under pressure-temperature gradient constraints, monitors the pipe wall temperature rise rate in real time, and automatically increases the desuperheating water flow rate.

[0055] Compared with the prior art, the present invention has the following advantages:

[0056] By using layered modeling of metal thermal storage, energy coupling calculation of steam-water system, and online identification of ash and scale thermal resistance, we have achieved a physical mechanism-level innovation in energy storage capacity, solving the core defects of traditional methods in dynamic correlation and real-time correction of thermal systems. Attached Figure Description

[0057] Figure 1 This is an overall flowchart of a method for real-time calculation of energy storage capacity of thermal power units in an embodiment of the present invention. Detailed Implementation

[0058] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and accompanying drawings. The content mentioned in the embodiments is not intended to limit the present invention.

[0059] like Figure 1 As shown in the figure, this embodiment provides a method for real-time calculation of the energy storage capacity of thermal power units, including the following steps:

[0060] S1. Collect temperature data of n layers of the steam drum wall and calculate the heat storage increment of each layer and the total heat storage.

[0061] S2. Establish a dynamic capacity flow model for the main steam, reheat steam, and feedwater systems, calculate the energy change of the main steam, and update the heat absorption of the reheat steam.

[0062] S3. Periodically acquire infrared thermal images of the heated surface, design a method for inverting the dirt layer based on infrared thermal images and genetic algorithms, perform optimization calculations on dirt distribution, and update the equivalent thermal resistance in the heat transfer equation.

[0063] S4. Construct an energy storage and release strategy under pressure-temperature gradient constraints, monitor the pipe wall temperature rise rate in real time, and automatically increase the desuperheating water flow rate.

[0064] The detailed steps of step S1 include:

[0065] Temperature data were collected from 10 layers of the steam drum wall.

[0066] Construct a real-time calculation formula for heat storage in metal components based on the heat transfer differential equation:

[0067] Layered modeling of the steam drum wall:

[0068] Divide the steam drum wall into n layers (n≥10), and calculate the temperature gradient of each layer:

[0069]

[0070] Where α is the thermal diffusivity of the material, dynamically corrected with temperature (based on measured data of CrMoV steel), x is the normal unit vector, and q ext Cp is the heat loss of the steam drum, Cp is the specific heat capacity, and ρ is the material density.

[0071] Calculation of total heat storage:

[0072]

[0073] Q metal For total heat storage of metal, V i T is the volume of the metal. amb The ambient temperature.

[0074] Establish dynamic capacity flow models for the main steam, reheat steam, and feedwater systems:

[0075] Main steam energy equation:

[0076] Main steam flow rate, h main Main steam enthalpy, h fw For the enthalpy value of the feedwater, Heat loss due to pipe wall heat dissipation; reheat steam heat absorption correlation:

[0077] Establish cooling water volume Transfer function with respect to enthalpy rise of reheated steam:

[0078]

[0079] Δh reheat For reheated steam enthalpy rise, K is the energy conversion coefficient, and τ is the energy transfer lag time.

[0080] The detailed steps of step S2 include:

[0081] Read the main steam flow rate Water enthalpy h fw ;

[0082] Calculate the main steam energy change ΔE main And deduct heat dissipation from the pipe wall (Based on infrared inversion of the thermal resistance of scale); by reducing the water volume Update reheat steam heat absorption Q spray .

[0083] Design a method for inverting dirt layers based on infrared thermal imaging and genetic algorithms:

[0084] Infrared temperature field analysis:

[0085] The temperature distribution T(x, y) of the heated surface is detected by a thermal imager, and the thickness δ of the scale is then calculated. ash :

[0086]

[0087] K ash The heat transfer coefficient;

[0088] Dynamic updates of thermal resistance:

[0089] Calculations to optimize the distribution of ash and dirt are performed every 30 minutes, updating the equivalent thermal resistance R in the heat transfer equation. fouling .

[0090] The detailed steps of step S3 include:

[0091] Infrared thermal images of the heated surface are acquired every 30 minutes, and SRCNN super-resolution reconstruction is performed.

[0092] Solve the inverse heat transfer problem and output the scale thickness distribution diagram δ. ash (x,y);

[0093] Update the equivalent thermal resistance R in the soda energy equation fouling .

[0094] Energy storage and release strategies under pressure-temperature gradient constraints:

[0095] Dynamic limiting logic:

[0096] In order to release stored energy, Q total For total energy storage, Q base This is the energy storage benchmark value;

[0097] When the pipe wall temperature rise rate |dT / dt|>3℃ / s, the desuperheating water-assisted heat storage release is triggered.

[0098] A real-time calculation system for the energy storage capacity of a thermal power unit includes a data acquisition unit, a metal thermal storage calculation unit, a steam-water coupling calculation unit, an online correction unit for ash and scale thermal resistance, and an energy storage safety release control unit.

[0099] The data acquisition unit collects steam drum wall temperature data;

[0100] The metal heat storage calculation unit constructs a real-time calculation formula for the heat storage of metal components based on the heat transfer differential equation, and calculates the heat storage increment of each layer.

[0101] The steam-water coupling calculation unit establishes a dynamic capacity flow model of the main steam, reheat steam, and feedwater system, calculates the energy change of the main steam, and updates the heat absorption of the reheat steam.

[0102] The online correction unit for scale thermal resistance periodically acquires infrared thermal images of the heated surface, designs a scale layer inversion method based on infrared thermal images and genetic algorithms, performs scale distribution optimization calculations, and updates the equivalent thermal resistance in the heat transfer equation.

[0103] The energy storage safety release control unit constructs an energy storage release strategy under pressure-temperature gradient constraints, monitors the pipe wall temperature rise rate in real time, and automatically increases the desuperheating water flow rate.

[0104] Compared with the prior art, the present invention has the following advantages:

[0105] By using layered modeling of metal thermal storage, energy coupling calculation of steam-water system, and online identification of ash and scale thermal resistance, we have achieved a physical mechanism-level innovation in energy storage capacity, solving the core defects of traditional methods in dynamic correlation and real-time correction of thermal systems.

[0106] The above provides a detailed description of a method and system for real-time calculation of energy storage capacity of thermal power units. The specific embodiments described are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims.

Claims

1. A method for real-time calculation of the energy storage capacity of a thermal power unit, characterized in that, Including the following steps: S1. Collect temperature data of n layers of the steam drum wall and calculate the heat storage increment of each layer and the total heat storage. S2. Establish a dynamic capacity flow model for the main steam, reheat steam, and feedwater systems, calculate the energy change of the main steam, and update the heat absorption of the reheat steam. S3. Periodically acquire infrared thermal images of the heated surface, design a method for inverting the dirt layer based on infrared thermal images and genetic algorithms, perform optimization calculations on dirt distribution, and update the equivalent thermal resistance in the heat transfer equation. S4. Construct an energy storage and release strategy under pressure-temperature gradient constraints, monitor the pipe wall temperature rise rate in real time, and automatically increase the desuperheating water flow rate.

2. The method for real-time calculation of energy storage capacity of thermal power units according to claim 1, characterized in that, The detailed steps of step S1 include: Temperature data were collected from 10 layers of the steam drum wall. Construct a real-time calculation formula for heat storage in metal components based on the heat transfer differential equation: Layered modeling of the steam drum wall: Divide the steam drum wall into n layers (n≥10), and calculate the temperature gradient of each layer: Where α is the thermal diffusivity of the material, dynamically corrected with temperature, x is the normal unit vector, and q ext Cp is the heat loss of the steam drum, Cp is the specific heat capacity, and ρ is the material density. Calculation of total heat storage: Q metal For total heat storage of metal, V i T is the volume of the metal. amb The ambient temperature.

3. The method for real-time calculation of energy storage capacity of thermal power units according to claim 2, characterized in that, Establish dynamic capacity flow models for the main steam, reheat steam, and feedwater systems: Main steam energy equation: Main steam flow rate, h main Main steam enthalpy, h fw For the enthalpy value of the feedwater, This is due to heat loss from the pipe wall; Reheat steam endothermic relationship: Establish cooling water volume Transfer function with respect to enthalpy rise of reheated steam: Δh reheat For reheated steam enthalpy rise, K is the energy conversion coefficient, and τ is the energy transfer lag time.

4. The method for real-time calculation of energy storage capacity of thermal power units according to claim 3, characterized in that, The detailed steps of step S2 include: Read the main steam flow rate Water enthalpy h fw ; Calculate the main steam energy change ΔE main And deduct heat dissipation from the pipe wall By reducing the amount of water heated Update reheat steam heat absorption Q spray .

5. The method for real-time calculation of energy storage capacity of thermal power units according to claim 4, characterized in that, Design a method for inverting dirt layers based on infrared thermal imaging and genetic algorithms: Infrared temperature field analysis: The temperature distribution T(x, y) of the heated surface is detected by a thermal imager, and the thickness δ of the scale is then calculated. ash : K ash The heat transfer coefficient; Dynamic updates of thermal resistance: Calculations to optimize the distribution of ash and dirt are performed every 30 minutes, updating the equivalent thermal resistance R in the heat transfer equation. fouling .

6. The method for real-time calculation of energy storage capacity of thermal power units according to claim 5, characterized in that, Step S3 includes the following steps: acquiring infrared thermal images of the heated surface every 3 minutes, performing SRCNN super-resolution reconstruction; solving the inverse heat transfer problem, and outputting a sludge thickness distribution map δ. ash (x,y); Update the equivalent thermal resistance R in the steam energy equation. fouling .

7. The method for real-time calculation of energy storage capacity of thermal power units according to claim 6, characterized in that, Energy storage and release strategies under pressure-temperature gradient constraints: Dynamic limiting logic: In order to release stored energy, Q total For total energy storage, Q base This is the energy storage benchmark value; When the pipe wall temperature rise rate |dT / dt|>3℃ / s, the desuperheating water-assisted heat storage release is triggered.

8. A real-time calculation system for the energy storage capacity of a thermal power unit, characterized in that, It includes a data acquisition unit, a metal thermal storage calculation unit, a steam-water coupling calculation unit, an online correction unit for ash and scale thermal resistance, and an energy storage safety release control unit; The data acquisition unit collects steam drum wall temperature data; The metal heat storage calculation unit constructs a real-time calculation formula for the heat storage of metal components based on the heat transfer differential equation, and calculates the heat storage increment of each layer. The steam-water coupling calculation unit establishes a dynamic capacity flow model of the main steam, reheat steam, and feedwater system, calculates the energy change of the main steam, and updates the heat absorption of the reheat steam. The online correction unit for scale thermal resistance periodically acquires infrared thermal images of the heated surface, designs a scale layer inversion method based on infrared thermal images and genetic algorithms, performs scale distribution optimization calculations, and updates the equivalent thermal resistance in the heat transfer equation. The energy storage safety release control unit constructs an energy storage release strategy under pressure-temperature gradient constraints, monitors the pipe wall temperature rise rate in real time, and automatically increases the desuperheating water flow rate.

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