CN111708333A - Intelligent prediction coordination control system of power plant - Google Patents
Intelligent prediction coordination control system of power plant Download PDFInfo
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- CN111708333A CN111708333A CN202010483347.1A CN202010483347A CN111708333A CN 111708333 A CN111708333 A CN 111708333A CN 202010483347 A CN202010483347 A CN 202010483347A CN 111708333 A CN111708333 A CN 111708333A
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention discloses an intelligent prediction coordination control system for a power plant, which comprises the following steps: the predictive control technology is characterized in that an optimized control system still adopts a feedforward and feedback control mode on the whole control structure, but is different from a conventional DCS control strategy in that the most advanced predictive control technology for solving the problem of large-lag object control in the world is applied to a feedback control part, the original PID control is replaced, the future change trend of the regulated quantity can be predicted in advance by adopting the predictive control technology, and then the control is carried out according to the future change quantity of the regulated quantity. After the invention is applied, the lowest load of the unit can be further reduced to 30% Pe from the lowest 50% rated load at present, a primary frequency modulation intelligent measurement and control homologous device is adopted to carry out homologous optimization on primary frequency modulation signals, and on the basis, the nonlinear problem of the load response characteristic of the unit under the working conditions of different pressures, valve positions, loads and the like is solved through nonlinear correction of the load response characteristic.
Description
Technical Field
The invention relates to the technical field of power plants, in particular to an intelligent prediction and coordination control system for a power plant.
Background
The coal-fired power generating unit mainly comprises a combustion system (taking a boiler as a core), a steam-water system (mainly comprising various pumps, a feed water heater, a condenser, a pipeline, a water-cooled wall and the like), an electric system (mainly comprising a turbine generator, a main transformer and the like), a control system and the like. The former two generate high-temperature high-pressure steam; the electrical system realizes the conversion from heat energy, mechanical energy to electric energy; the control system ensures that each system is operated safely, reasonably and economically. Coal-fired power generation also has the defects and shortcomings as a traditional power generation mode, for example, acidic gases such as SO2, NOX and the like discharged by direct combustion of coal are continuously increased, SO that the acid rain amount in China is increased, and dust pollution causes adverse effects on the life of people and the growth of plants. Therefore, the power generation process by coal burning is continuously improved, the power generation efficiency is improved by various technologies, and the environmental pollution is reduced, for example, smoke dust is treated by desulfurization and dust removal or natural gas is burnt, and a gas turbine is cooled by air.
The lowest load of the existing 2 x 300MW coal-fired power generator set is 50% of rated load, and an intelligent prediction coordination control system for the 300MW unit deep peak regulation is provided based on a whole set of intelligent control strategies for the whole undisturbed switching of the normal load section and the deep peak regulation load section of the unit based on the operation experience of operators.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides an intelligent prediction and coordination control system for a power plant.
The invention provides an intelligent prediction coordination control system for a power plant, which comprises the following steps:
s1: the optimal control system still adopts a feedforward and feedback control mode on the whole control structure, but is different from the conventional DCS control strategy in that the current most advanced prediction control technology for solving the problem of large-lag object control in the world is applied to a feedback control part, the original PID control is replaced, the future change trend of the regulated quantity can be predicted in advance by adopting the technology, then the control is carried out according to the future change quantity of the regulated quantity, the process is effectively adjusted in advance, and the closed-loop stability and the disturbance resistance of the AGC control system of the unit are greatly improved;
s2: the operation characteristic parameters of the unit are corrected in real time under all working conditions, the control parameters of a control loop of a conventional DCS cannot be changed once the setting is finished, and the change of the working conditions of the unit in the future cannot be considered, the optimization control system adopts a competitive neural network learning algorithm to correct various characteristic parameters closely related to the control system in the operation of the unit in real time, and corrects various control parameters in a feedforward loop and a feedback loop of an AGC control system in real time according to the characteristic parameters, so that the whole system is always in an online learning state, and the control performance is continuously close to an optimal target;
s3: the AGC operation mode is particularly optimized, the conventional DCS control scheme does not distinguish whether the unit operates in a CCS mode or AGC, and the optimization control system comprises a particularly optimizing module under the AGC operation mode: on one hand, the change trend of the AGC command of the scheduling EMS system at the future moment is predicted in real time according to parameters such as the current AGC command of the unit, actual power, power grid frequency and the like by adopting an intelligent prediction algorithm; on the other hand, the change value of a boiler thermal power signal representing the working capacity of the boiler at the future moment is predicted in real time according to the parameters of the fuel quantity, the air quantity, the water supply flow and the like of the unit, and the variation of a boiler instruction is corrected according to the matching degree between the two parameters, so that the practical application shows that after an AGC mode special optimization module is added, the fluctuation amplitude of the fuel quantity, the air quantity, the water supply flow and the water reducing flow of the unit can be reduced by more than 60 percent on the basis of ensuring AGC load response, and the method is very favorable for prolonging the service life of boiler pipes and reducing pipe explosion;
s4: the method comprises the steps that a delay control technology is used for optimizing a reheated steam temperature control system, the optimized control system firstly integrates an adaptive SMITH control technology, a state variable control technology and a phase compensation technology into a whole, dynamic compensation is carried out on the large delay characteristic of a reheated steam temperature controlled object, delay and inertia of the reheated steam temperature generalized controlled object after compensation are effectively reduced, then a generalized prediction controller is used as a feedback regulator, and fuzzy control is used as intelligent feedforward of the control system;
s5: adopting a multi-target control technology, wherein the INFIT adopts a multi-target control design idea for a plurality of important control loops;
s6: the control technology optimizes the denitration control system, and an advanced solution of the SCR denitration control of the modern thermal power generating unit based on prediction control, neural network learning technology and adaptive control technology is successfully provided through accurate control on the aspects of the operating environment, the examination requirements, the controlled characteristic mathematical simulation model and the like of the SCR denitration control system.
Preferably, in S1, the predicted adjusted amount in advance includes parameters such as main steam pressure and steam temperature.
Preferably, in S2, the characteristic parameters include a fuel calorific value, a steam consumption rate, a unit slip pressure curve, an intermediate point temperature setting curve, and a pulverizing system inertia time.
Preferably, in S4, the automatic control of the reheat steam temperature is successfully achieved by effectively combining multiple large-lag control strategies, where the flue gas damper adjustment is mainly performed and the accident water spray adjustment is mainly performed, so that the water spray flow rate of the reheat steam temperature is effectively reduced, and an obvious economic benefit is obtained.
Preferably, in S5, the steam turbine main control: comprehensively adjusting load and main steam pressure; controlling the degree of superheat: comprehensively adjusting the main steam temperature, the reheated steam temperature, the amount of superheated and desuperheated water and the wall temperature of a water wall; controlling the temperature of the superheated steam: comprehensively regulating the main steam temperature and the superheater wall temperature; reheating baffle control: comprehensively adjusting the temperature of reheated steam, the wall temperature of a reheater and the temperature of denitration inlet smoke; the INFIT optimization system redefines the coverage range of automatic control according to the design idea of multi-objective control, greatly reduces the operation of operators, and ensures stable and efficient operation of the unit under all working conditions.
The beneficial effects of the invention are as follows:
1. the intelligent multi-model predictive control technology for deep peak regulation of the 2 x 300MW unit at the load section of 30% -50% Pe is provided, a related intelligent predictive coordination control system is designed and developed, practical application is completed, and after the intelligent predictive coordination control system is applied, the lowest load of the unit can be further explored to 30% Pe from the current lowest rated load of 50%, so that the actual requirement of deep peak regulation is further met.
2. A set of intelligent AGC coordination, steam temperature and denitration optimization control strategies based on the operation experience of operators and used for the unit in a 30-50% Pe low-load section are provided, and practical application is completed.
3. And automatic operation of an AGC coordination, steam temperature and denitration control system of 40-100% Pe full load section is realized.
4. The problem of nonlinearity of unit load response characteristics under working conditions of different pressures, valve positions, loads and the like is solved by installing the primary frequency modulation intelligent measurement and control homologous device.
Drawings
Fig. 1 is a table of the main technical and economic index completion condition of the intelligent prediction and coordination control system of the power plant according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1, an intelligent prediction and coordination control system for a power plant includes the following steps:
s1: the optimal control system still adopts a feedforward and feedback control mode on the whole control structure, but is different from the conventional DCS control strategy in that the current most advanced prediction control technology for solving the problem of large-lag object control in the world is applied to a feedback control part, the original PID control is replaced, the future change trend of the regulated quantity can be predicted in advance by adopting the technology, then the control is carried out according to the future change quantity of the regulated quantity, the process is effectively adjusted in advance, and the closed-loop stability and the disturbance resistance of the AGC control system of the unit are greatly improved;
s2: the operation characteristic parameters of the unit are corrected in real time under all working conditions, the control parameters of a control loop of a conventional DCS cannot be changed once the setting is finished, and the change of the working conditions of the unit in the future cannot be considered, the optimization control system adopts a competitive neural network learning algorithm to correct various characteristic parameters closely related to the control system in the operation of the unit in real time, and corrects various control parameters in a feedforward loop and a feedback loop of an AGC control system in real time according to the characteristic parameters, so that the whole system is always in an online learning state, and the control performance is continuously close to an optimal target;
s3: the AGC operation mode is particularly optimized, the conventional DCS control scheme does not distinguish whether the unit operates in a CCS mode or AGC, and the optimization control system comprises a particularly optimizing module under the AGC operation mode: on one hand, the change trend of the AGC command of the scheduling EMS system at the future moment is predicted in real time according to parameters such as the current AGC command of the unit, actual power, power grid frequency and the like by adopting an intelligent prediction algorithm; on the other hand, the change value of a boiler thermal power signal representing the working capacity of the boiler at the future moment is predicted in real time according to the parameters of the fuel quantity, the air quantity, the water supply flow and the like of the unit, and the variation of a boiler instruction is corrected according to the matching degree between the two parameters, so that the practical application shows that after an AGC mode special optimization module is added, the fluctuation amplitude of the fuel quantity, the air quantity, the water supply flow and the water reducing flow of the unit can be reduced by more than 60 percent on the basis of ensuring AGC load response, and the method is very favorable for prolonging the service life of boiler pipes and reducing pipe explosion;
s4: the method comprises the steps that a delay control technology is used for optimizing a reheated steam temperature control system, the optimized control system firstly integrates an adaptive SMITH control technology, a state variable control technology and a phase compensation technology into a whole, dynamic compensation is carried out on the large delay characteristic of a reheated steam temperature controlled object, delay and inertia of the reheated steam temperature generalized controlled object after compensation are effectively reduced, then a generalized prediction controller is used as a feedback regulator, and fuzzy control is used as intelligent feedforward of the control system;
s5: adopting a multi-target control technology, wherein the INFIT adopts a multi-target control design idea for a plurality of important control loops;
s6: the control technology optimizes the denitration control system, and an advanced solution of the SCR denitration control of the modern thermal power generating unit based on prediction control, neural network learning technology and adaptive control technology is successfully provided through accurate control on the aspects of the operating environment, the examination requirements, the controlled characteristic mathematical simulation model and the like of the SCR denitration control system.
In the invention, in S1, the adjusted quantity is predicted in advance to include parameters such as main steam pressure and steam temperature, in S2, characteristic parameters include fuel heat value, steam consumption rate, unit sliding pressure curve, middle point temperature setting curve and powder making system inertia time, in S4, through effective combination of a plurality of large-lag control strategies, automatic control of reheat steam temperature with flue gas baffle plate regulation as a main part and accident water spray regulation as an auxiliary part is successfully realized, water spray flow of reheat steam temperature is effectively reduced, obvious economic benefit is obtained, in S5, steam turbine main control: comprehensively adjusting load and main steam pressure; controlling the degree of superheat: comprehensively adjusting the main steam temperature, the reheated steam temperature, the amount of superheated and desuperheated water and the wall temperature of a water wall; controlling the temperature of the superheated steam: comprehensively regulating the main steam temperature and the superheater wall temperature; reheating baffle control: comprehensively adjusting the temperature of reheated steam, the wall temperature of a reheater and the temperature of denitration inlet smoke; the INFIT optimization system redefines the coverage range of automatic control by the design idea of multi-objective control, greatly reduces the operation of operators, ensures the stable and efficient operation of the unit in all working conditions, can further ensure the lowest load of the unit to reach 30% Pe from the lowest 50% rated load in the prior art after application, further meets the actual requirement of deep peak shaving, simultaneously adopts a primary frequency modulation intelligent measurement and control homologous device to carry out homologous optimization of primary frequency modulation signals, solves the nonlinear problem of unit load response characteristics under the working conditions of different pressures, valve positions, loads and the like through nonlinear correction of load response characteristics on the basis, optimizes a primary frequency modulation control strategy according to the evaluation index of primary frequency modulation of a power grid in the area, finally realizes the aim of comprehensively optimizing the primary frequency modulation performance under the condition of existing main and auxiliary equipment, and simultaneously ensures the safe and stable operation of the unit, the important performance index reaches the technical requirement.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (5)
1. The intelligent prediction and coordination control system for the power plant is characterized by comprising the following steps:
s1: the optimal control system still adopts a feedforward and feedback control mode on the whole control structure, but is different from the conventional DCS control strategy in that the current most advanced prediction control technology for solving the problem of large-lag object control in the world is applied to a feedback control part, the original PID control is replaced, the future change trend of the regulated quantity can be predicted in advance by adopting the technology, then the control is carried out according to the future change quantity of the regulated quantity, the process is effectively adjusted in advance, and the closed-loop stability and the disturbance resistance of the AGC control system of the unit are greatly improved;
s2: the operation characteristic parameters of the unit are corrected in real time under all working conditions, the control parameters of a control loop of a conventional DCS cannot be changed once the setting is finished, and the change of the working conditions of the unit in the future cannot be considered, the optimization control system adopts a competitive neural network learning algorithm to correct various characteristic parameters closely related to the control system in the operation of the unit in real time, and corrects various control parameters in a feedforward loop and a feedback loop of an AGC control system in real time according to the characteristic parameters, so that the whole system is always in an online learning state, and the control performance is continuously close to an optimal target;
s3: the AGC operation mode is particularly optimized, the conventional DCS control scheme does not distinguish whether the unit operates in a CCS mode or AGC, and the optimization control system comprises a particularly optimizing module under the AGC operation mode: on one hand, the change trend of the AGC command of the scheduling EMS system at the future moment is predicted in real time according to parameters such as the current AGC command of the unit, actual power, power grid frequency and the like by adopting an intelligent prediction algorithm; on the other hand, the change value of a boiler thermal power signal representing the working capacity of the boiler at the future moment is predicted in real time according to the parameters of the fuel quantity, the air quantity, the water supply flow and the like of the unit, and the variation of a boiler instruction is corrected according to the matching degree between the two parameters, so that the practical application shows that after an AGC mode special optimization module is added, the fluctuation amplitude of the fuel quantity, the air quantity, the water supply flow and the water reducing flow of the unit can be reduced by more than 60 percent on the basis of ensuring AGC load response, and the method is very favorable for prolonging the service life of boiler pipes and reducing pipe explosion;
s4: the method comprises the steps that a delay control technology is used for optimizing a reheated steam temperature control system, the optimized control system firstly integrates an adaptive SMITH control technology, a state variable control technology and a phase compensation technology into a whole, dynamic compensation is carried out on the large delay characteristic of a reheated steam temperature controlled object, delay and inertia of the reheated steam temperature generalized controlled object after compensation are effectively reduced, then a generalized prediction controller is used as a feedback regulator, and fuzzy control is used as intelligent feedforward of the control system;
s5: adopting a multi-target control technology, wherein the INFIT adopts a multi-target control design idea for a plurality of important control loops;
s6: the control technology optimizes the denitration control system, and an advanced solution of the SCR denitration control of the modern thermal power generating unit based on prediction control, neural network learning technology and adaptive control technology is successfully provided through accurate control on the aspects of the operating environment, the examination requirements, the controlled characteristic mathematical simulation model and the like of the SCR denitration control system.
2. A power plant intelligent prediction coordination control system according to claim 1, characterized in that in S1, the predicted adjusted amount in advance comprises parameters such as main steam pressure and steam temperature.
3. The power plant intelligent prediction coordination control system according to claim 1, wherein in S2, the characteristic parameters include a fuel calorific value, a steam consumption rate, a unit slip pressure curve, a middle point temperature setting curve, and a pulverizing system inertia time.
4. The power plant intelligent prediction coordination control system according to claim 1, wherein in S4, the automatic control of the reheat steam temperature mainly based on flue gas damper adjustment and assisted by accident water spray adjustment is successfully realized through effective combination of multiple large-lag control strategies, the water spray flow of the reheat steam temperature is effectively reduced, and obvious economic benefits are obtained.
5. A power plant intelligent prediction coordination control system according to claim 1, wherein in S5, the steam turbine master controller: comprehensively adjusting load and main steam pressure; controlling the degree of superheat: comprehensively adjusting the main steam temperature, the reheated steam temperature, the amount of superheated and desuperheated water and the wall temperature of a water wall; controlling the temperature of the superheated steam: comprehensively regulating the main steam temperature and the superheater wall temperature; reheating baffle control: comprehensively adjusting the temperature of reheated steam, the wall temperature of a reheater and the temperature of denitration inlet smoke; the INFIT optimization system redefines the coverage range of automatic control according to the design idea of multi-objective control, greatly reduces the operation of operators, and ensures stable and efficient operation of the unit under all working conditions.
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| CN115822790A (en) * | 2022-12-28 | 2023-03-21 | 华能威海发电有限责任公司 | Frequency modulation control strategy and control execution system based on frequency modulation control strategy |
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Application publication date: 20200925 |