A multi-signal optimization energy-saving electrostatic precipitator control method

Abstract

The present invention discloses a multi-signal optimization energy-saving electrostatic precipitator control method, which relates to the field of energy-saving and environmental protection technology. The present invention includes an electrostatic precipitator control system, and the electrostatic precipitator control system includes an optimization algorithm system based on the electrostatic precipitator control system, and the optimization algorithm system includes a signal acquisition device, a data storage module, and a logic analysis module. The present invention obtains the electrostatic precipitator dust removal efficiency of known airflow parameters and dust radius under different limit line plate spacings by combining and analyzing the unit load, the dust concentration at the powder outlet, and the coal quality parameters, and brings in the voltage and current when the signal peak occurs, and obtains the energy consumption change of the system before and after, which is the optimization strategy of the energy-saving model, and minimizes the power consumption of the system operation.

Description

Technical Field

[0001] The invention relates to the technical field of energy conservation and environmental protection, and in particular to a multi-signal optimization energy-saving electrostatic precipitator control method. Background Art

[0002] The electrostatic precipitator is an essential supporting equipment for thermal power plants. Its function is to remove particulate smoke from the flue gas discharged by coal-fired or oil-fired boilers, thereby greatly reducing the amount of smoke discharged into the atmosphere. It is an important environmental protection equipment to improve environmental pollution and air quality. Its working principle is that when the flue gas passes through the flue in front of the main structure of the electrostatic precipitator, the smoke is positively charged, and then the flue gas enters the electrostatic precipitator channel with multiple layers of cathode plates. Due to the mutual adsorption between the positively charged smoke and the cathode plate, the particulate smoke in the flue gas is adsorbed on the cathode, and the cathode plate is hit regularly, so that the smoke with a certain thickness falls into the ash hopper below the electrostatic precipitator structure under the dual effects of self-weight and vibration, so as to achieve the purpose of removing smoke in the flue gas.

[0003] As the country's environmental protection control policies become increasingly stringent, ultra-low emissions have become a new benchmark for coal-fired power generation units. In order to reduce dust emissions from power plants, factories must use a variety of dust removal equipment including electrostatic precipitators. In order to meet the ultra-low emission standards, the fully loaded electrostatic precipitator has high power consumption and high energy consumption, which will have a certain degree of impact on the production efficiency of the power plant over time, causing unnecessary energy waste. Therefore, it is necessary to transform and optimize multiple dust removal equipment including electrostatic precipitators, and try to reduce the high energy consumption operation state of the electrostatic precipitator caused by various unreasonable factors without reducing the dust removal efficiency and requirements. Therefore, the present invention specifically proposes a multi-signal optimization energy-saving electrostatic precipitator control method to solve the problems raised in the above background technology. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a multi-signal optimization energy-saving electrostatic precipitator control method.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A multi-signal optimization energy-saving electrostatic precipitator control method, comprising an electrostatic precipitator control system, wherein the electrostatic precipitator control system comprises an optimization algorithm system based on the electrostatic precipitator control system, wherein the optimization algorithm system comprises a signal acquisition device, a data storage module and a logic analysis module;

[0007] Signal acquisition device: different signal collectors correspond to different signal generating devices, and the actual operating status data of different signal generating devices are collected;

[0008] Data storage module: stores the information collected by the signal acquisition device into the module, takes out the operation history data of the generating device in the recent period, and uses the operating parameters of the collected generating device as the training model and reference factors of the energy-saving optimization algorithm;

[0009] Logical analysis module: Through the optimized energy-saving algorithm model established by the logical analysis module, the different parameters obtained under different analysis factors are used as the reference law of system energy consumption changes to analyze the operating parameters of the generating device under the optimal energy-saving operating state.

[0010] Preferably, the signal generating device includes a power supply unit attached to the electrostatic precipitator control system, an electrostatic precipitator, an ash hopper and an ash silo pump, and collects information through the corresponding unit load signal collector, dust concentration signal collector, ash hopper level signal collector, silo pump conveying collector and the sensor components installed on the corresponding generating device.

[0011] Preferably, the load signal acquisition device of the unit is used to acquire information about the load of the power supply unit and the corresponding high and low voltage characteristics, the dust concentration at the powder outlet of the electrostatic precipitator and the corresponding high and low voltage volt-ampere characteristics are acquired by the dust concentration signal acquisition device, the ash hopper level signal acquisition device is used to acquire information about the high and low level change time of the ash hopper and the corresponding high and low voltage volt-ampere characteristics, and the silo pump delivery signal acquisition device is used to acquire information about the silo pump ash delivery time and the corresponding high and low voltage volt-ampere characteristics, wherein the signal acquisition device includes a coal quality monitoring component, and the coal quality monitoring component directly transmits the acquired coal powder quality information to the data storage module;

[0012] The ash content of the coal used often exceeds the design value, the amount of fly ash in the flue gas of boiler combustion increases, the fly ash resistivity increases, the smoke particles are not easy to be charged, and back corona phenomenon will occur. At the same time, a large amount of fly ash is adsorbed on the plates and wires, which may wrap the wires and plates, causing corona closure. If you want to maintain the original environmental emission level or meet the environmental emission standards, it will inevitably lead to an increase in the energy consumption of electrostatic precipitator.

[0013] Preferably, the unit load information, dust concentration information at the powder outlet, ash delivery time information of the silo pump, high and low material level change time information of the ash hopper, and coal quality information collected by the information collection device are preprocessed by the data storage module, and the change rules between the information of several generating devices and the high and low voltage volt-ampere characteristics are preliminarily analyzed, and the collected data are retained, sorted and summarized;

[0014] After preliminary processing by the data storage module, it can be known that the greater the load of the power supply unit, the greater the system power supply voltage and current will be, and vice versa. The higher the dust concentration at the powder outlet of the electrostatic precipitator, the greater the system power supply voltage and current will be, and vice versa. The longer the ash hopper high and low level change time, the smaller the system power supply current and voltage will be, and vice versa. The greater the load, the longer the silo pump ash delivery time, the greater the system power supply voltage and current will be, and vice versa.

[0015] Preferably, the optimization algorithm system based on the electrostatic precipitator control system adopts a multi-signal operating parameter optimization method, and is obtained by mixing energy-saving and optimization data. The optimization plus energy-saving algorithm is used to achieve the lowest energy consumption operating parameters that meet the emission standards under the interference of multiple factors.

[0016] Preferably, the logic analysis module is based on the energy-saving algorithm module, and uses the unit load, dust concentration at the powder outlet, silo pump ash delivery time, and ash hopper high and low level change time as the training data and reference factors of the energy-saving algorithm model, and regularly retrieves the latest collected data to always achieve the latest and most complete system operation parameters:

[0017] According to the dust collection theory, the theoretical dust removal efficiency of the electrostatic precipitator is:

[0018] From the particle movement equation in the electrostatic precipitator, we can get:

[0019] Where F1 is a constant, η is the dust collection efficiency, ω is the dust driving speed, L is the plate length, υ is the average gas flow rate, b is the line plate spacing, K y is the turbulent diffusion coefficient in the Y direction;

[0020] The driving speed Where ε is the dust dielectric constant, a is the dust radius, F P is the electric field strength, F t The load μ of the power supply unit is the ash delivery time coefficient;

[0021] By combining and analyzing the unit load, dust concentration at the powder outlet, silo pump ash delivery time, and ash hopper high and low level change time, the electrostatic precipitator dust removal efficiency at different limit line plate spacings with known airflow parameters and dust radius is obtained, and the optimal dust removal efficiency is sought by comparison to obtain the optimal operating parameters.

[0022] Preferably, the logic analysis module is based on the optimization algorithm module, takes the unit load, dust concentration at the powder outlet, and coal quality parameters as the training data and reference factors of the energy-saving algorithm model, and regularly retrieves the latest collected data to always achieve the latest and most complete system operation parameters;

[0023] According to the principle of maximum fitness, the energy consumption of the system changes as follows:

[0024] Where power is the corona power, pfit is the power value;

[0025] Where power = UI / 10000, U is voltage, I is current;

[0026] According to this optimization algorithm, the n-th power of the electrostatic precipitator is:

[0027] Among them U i is the primary voltage, U 2i is the secondary voltage, I i is the primary current, I 2i is the secondary current;

[0028] By combining the analysis of unit load, dust concentration at the powder outlet, and coal quality parameters, and bringing in the voltage and current when the signal peak occurs, the energy consumption changes of the system before and after are obtained, and the optimization strategy of the energy-saving model is used to minimize the power consumption of the system operation.

[0029] Preferably, according to the load of the power supply unit at different time periods, combined with the coal quality parameters and the blending conditions, the signal acquisition device includes monitoring the control mode of the electrostatic precipitator control system, wherein the system control mode includes the control mode, the spark rate control mode and the vibration mode;

[0030] By optimizing the vibration time of the electrostatic precipitator, the vibration cycle and interval are made more reasonable, the problem of vibration overlap is solved, the back corona of the electrostatic precipitator electric field and the secondary flying of dust are reduced, and the environmental protection and energy-saving operation of the electrostatic precipitator is guaranteed; by optimizing the secondary voltage and secondary current of the electrostatic precipitator in different load periods of the unit, the best operating control parameters are found out through experiments, so that the electrostatic precipitator can be in the best state of environmental protection and energy-saving operation.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. The present invention combines and analyzes the unit load, dust concentration at the powder outlet, silo pump ash delivery time, and ash hopper high and low level change time to obtain the dust removal efficiency of the electrostatic precipitator at different limit line plate spacings with known airflow parameters and dust radius, and compares and seeks the optimal dust removal efficiency to obtain the optimal operating parameters;

[0033] 2. The present invention combines and analyzes the unit load, dust concentration at the powder outlet, and coal quality parameters, and brings in the voltage and current when the signal peak occurs to obtain the energy consumption changes of the system before and after, and optimizes the energy-saving model to minimize the power consumption of the system operation;

[0034] 3. The present invention optimizes the vibration time of the electrostatic precipitator to make the vibration cycle and interval more reasonable, solves the problem of vibration overlap, reduces the back corona of the electric field of the electrostatic precipitator and the secondary flying of dust, and ensures the environmental protection and energy-saving operation of the electrostatic precipitator; by optimizing the secondary voltage and secondary current of the electrostatic precipitator in different load periods of the unit, the best operating control parameters are found out through experiments, so that the electrostatic precipitator can be in the best state of environmental protection and energy-saving operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1A schematic diagram of a control algorithm flow of a multi-signal optimization energy-saving electrostatic precipitator control method proposed by the present invention;

[0036] Figure 2 It is a flowchart of the analysis process in the algorithm module of a multi-signal optimization energy-saving electrostatic precipitator control method proposed by the present invention;

[0037] Figure 3 This is a schematic diagram of the structure of a multi-signal generating device in a multi-signal optimization energy-saving electrostatic precipitator control method proposed by the present invention;

[0038] Figure 4 This is a schematic diagram of the structural relationship between a multi-signal generating device and a data storage device in a multi-signal optimization energy-saving electrostatic precipitator control method proposed by the present invention. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0040] Reference Figure 1-4 , a multi-signal optimization energy-saving electrostatic precipitator control method, comprising an electrostatic precipitator control system, wherein the electrostatic precipitator control system comprises an optimization algorithm system based on the electrostatic precipitator control system, wherein the optimization algorithm system comprises a signal acquisition device, a data storage module and a logic analysis module;

[0041] Signal acquisition device: different signal collectors correspond to different signal generating devices, and the actual operating status data of different signal generating devices are collected;

[0042] Data storage module: stores the information collected by the signal acquisition device into the module, takes out the operation history data of the generating device in the recent period, and uses the operating parameters of the collected generating device as the training model and reference factors of the energy-saving optimization algorithm;

[0043] Logical analysis module: Through the optimized energy-saving algorithm model established by the logical analysis module, the different parameters obtained under different analysis factors are used as the reference law of system energy consumption changes to analyze the operating parameters of the generating device under the optimal energy-saving operating state.

[0044] The multi-signal optimization energy-saving electrostatic precipitator control method can be roughly divided into the following steps:

[0045] Step 1: The signal acquisition device collects operating status parameters of the power supply unit, the electrostatic precipitator, the ash hopper and the ash conveying silo pump attached to the electrostatic precipitator control system through corresponding different signal collectors;

[0046] Step 2: Sending information of several generating devices including coal quality monitoring parameters to the data storage module in the algorithm system through the signal acquisition device;

[0047] Step 3: Conduct a preliminary analysis of the collected generating device information and coal quality through the data storage module, explore the regular changes between the analyzing device and the power supply voltage and current, and retain, organize and summarize the collected data;

[0048] Step 4: The optimization algorithm system based on the electrostatic precipitator control system adopts a multi-signal operating parameter optimization method, and is obtained by mixing the energy-saving and optimization data. The optimization plus energy-saving algorithm is used to achieve the lowest energy consumption operating parameters that meet the emission standards under the interference of multiple factors;

[0049] Step 5: According to the dust collection theory, the theoretical dust removal efficiency of the electrostatic precipitator is:

[0050] From the particle movement equation in the electrostatic precipitator, we can get:

[0051] Where F1 is a constant, η is the dust collection efficiency, ω is the dust driving speed, L is the plate length, υ is the average gas flow rate, b is the line plate spacing, K y is the turbulent diffusion coefficient in the Y direction;

[0052] The driving speed Where ε is the dust dielectric constant, a is the dust radius, F P is the electric field strength, F t The load μ of the power supply unit is the ash delivery time coefficient;

[0053] By analyzing the unit load, dust concentration at the powder outlet, silo pump ash delivery time, and hopper high and low level change time, the dust removal efficiency of the electrostatic precipitator with known airflow parameters and dust radius at different limit line plate spacings is obtained, and the optimal dust removal efficiency is compared to obtain the optimal operating parameters;

[0054] Step 6: Based on the principle of maximum fitness, the system energy consumption changes as follows:

[0055] Where power is the corona power, pfit is the power value;

[0056] Where power = UI / 10000, U is voltage, I is current;

[0057] According to this optimization algorithm, the n-th power of the electrostatic precipitator is:

[0058] Among them U i is the primary voltage, U 2i is the secondary voltage, Ii is the primary current, I 2i is the secondary current;

[0059] By analyzing the unit load, dust concentration at the powder outlet, and coal quality parameters, and bringing in the voltage and current when the signal peak occurs, the energy consumption changes of the system before and after are obtained, and the optimization strategy of the energy-saving model is used to minimize the power consumption of the system operation;

[0060] By optimizing the vibration time of the electrostatic precipitator, the vibration cycle and interval are made more reasonable, the problem of vibration overlap is solved, the back corona of the electrostatic precipitator electric field and the secondary flying of dust are reduced, and the environmental protection and energy-saving operation of the electrostatic precipitator is guaranteed; by optimizing the secondary voltage and secondary current of the electrostatic precipitator in different load periods of the unit, the best operating control parameters are found out through experiments, so that the electrostatic precipitator can be in the best state of environmental protection and energy-saving operation.

[0061] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A multi-signal optimization energy-saving electrostatic precipitator control method, including an electrostatic precipitator control system, characterized in that: The electrostatic precipitator control system includes an optimization algorithm system based on the electrostatic precipitator control system, and the optimization algorithm system includes a signal acquisition device, a data storage module and a logic analysis module; Signal acquisition device: different signal collectors correspond to different signal generating devices, and the actual operating status data of different signal generating devices are collected; Data storage module: stores the information collected by the signal acquisition device into the module, takes out the operation history data of the generating device in the recent period, and uses the operating parameters of the collected generating device as the training model and reference factors of the energy-saving optimization algorithm; Logical analysis module: Through the optimization energy-saving algorithm model established by the logical analysis module, different parameters obtained under different analysis factors are used as reference rules for changes in system energy consumption, and the operating parameters of the generating device under the optimal energy-saving operating state are analyzed; The logic analysis module is based on the energy-saving algorithm module. It uses the unit load, dust concentration at the powder outlet, ash delivery time of the silo pump, and the high and low material level change time of the ash hopper as the training data and reference factors of the energy-saving algorithm model, and regularly retrieves the latest collected data to always achieve the latest and most complete system operation parameters; According to the dust collection theory, the theoretical dust removal efficiency of the electrostatic precipitator is: From the particle movement equation in the electrostatic precipitator: Where F1 is a constant, η is the dust collection efficiency, ω is the dust driving speed, L is the plate length, υ is the average gas flow rate, b is the line plate spacing, Ky is the turbulent diffusion coefficient in the Y direction; The driving speed Where ε is the dust dielectric constant, a is the dust radius, FP is the electric field strength, Ft is the power supply unit load, and μ is the ash delivery time coefficient; By analyzing the unit load, dust concentration at the powder outlet, silo pump ash delivery time, and hopper high and low level change time, the dust removal efficiency of the electrostatic precipitator with known airflow parameters and dust radius at different limit line plate spacings is obtained, and the optimal dust removal efficiency is compared to obtain the optimal operating parameters; The logic analysis module is based on the optimization algorithm module, taking the unit load, dust concentration at the powder outlet, and coal quality parameters as the training data and reference factors of the energy-saving algorithm model, and regularly retrieves the latest collected data to always achieve the latest and most complete system operation parameters; According to the principle of maximum fitness, the energy consumption of the system changes as follows: Where power is the corona power, pfit is the power value; where power = UI / 10000, U is the voltage, and I is the current; According to this optimization algorithm, the n-th power of the electrostatic precipitator is: Where Ui is the primary voltage, U2i is the secondary voltage, Ii is the primary current, and I2i is the secondary current; By combining the analysis of unit load, dust concentration at the powder outlet, and coal quality parameters, and bringing in the voltage and current when the signal peak occurs, the energy consumption changes of the system before and after are obtained, and the optimization strategy of the energy-saving model is used to minimize the power consumption of the system operation.

2. A multi-signal optimization energy-saving electrostatic precipitator control method according to claim 1, characterized in that: The signal generating device includes a power supply unit attached to the electrostatic precipitator control system, an electrostatic precipitator, an ash hopper and an ash silo pump, and collects information through the corresponding unit load signal collector, dust concentration signal collector, ash hopper level signal collector, silo pump conveying collector and the sensor components installed on the corresponding generating device.

3. A multi-signal optimization energy-saving electrostatic precipitator control method according to claim 2, characterized in that: The information on the load of the power supply unit and the corresponding high and low voltage characteristics is obtained through the unit load signal acquisition device, the information on the dust concentration at the powder outlet of the electrostatic precipitator and the corresponding high and low voltage volt-ampere characteristics is obtained by the dust concentration signal collector, the information on the high and low level change time of the ash hopper and the corresponding high and low voltage volt-ampere characteristics is obtained by the ash hopper level signal collector, and the information on the silo pump ash delivery time and the corresponding high and low voltage volt-ampere characteristics is obtained by the silo pump delivery signal collector, wherein the signal acquisition device includes a coal quality monitoring component, and the coal quality monitoring component directly transmits the acquired coal powder and coal quality information to the data storage module.

4. A multi-signal optimization energy-saving electrostatic precipitator control method according to claim 1, characterized in that: The data storage module pre-processes the unit load information, dust concentration information at the powder outlet, silo pump ash delivery time information, ash hopper high and low level change time information, and coal quality information collected by the information collection device, and preliminarily analyzes the changing rules between several generating device information and high and low voltage volt-ampere characteristics, and retains, organizes and summarizes the collected data.

5. A multi-signal optimization energy-saving electrostatic precipitator control method according to claim 1, characterized in that: The optimization algorithm system based on the electrostatic precipitator control system adopts a multi-signal operating parameter optimization method, and is obtained by mixing energy-saving and optimization data. Through the optimization plus energy-saving algorithm, the lowest energy consumption operating parameters that meet the emission standards are achieved under the interference of multiple factors.

6. A multi-signal optimization energy-saving electrostatic precipitator control method according to claim 1, characterized in that: According to the load of the power supply unit at different times, combined with coal quality parameters and blending conditions, the signal acquisition device includes monitoring of the control mode of the electrostatic precipitator control system, where the system control mode includes control mode, spark rate control mode and vibration mode.

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