Study On Energy-saving Optimization Of The Large Scale Coal-fired Boiler

The coal-fired power plants make the greatest contribution to power generation.In recent years,coal-fired power plants develop toward higher parameters,larger capacity,the power generation efficiency has been significantly developed,and the average level of net coal consumption for active coal-fired power plants in China has reached the world advanced level.Under the premise of ensuring the sustainable development of economy,it is an important and adurous task to strengthen the optimization of boiler operation and deepen the auxiliary energy saving potential,in order to save energy and protect the environment to the greastes extent.The outlet temperature of the mill,primary air pressure and boiler operating parameters were investigated by mechanism analysis and test methods to realize the more efficient and environmentally friendly operation of coal-fired boiler.The main contents are as follows.(1)study on optimization of the outlet temperature of the millIn order to adapt to the complex and changeable coal,ensure the safe operation of the pulverizing system,during the parameter setting in the DCS,the upper limit of the mill outlet temperature is often set in a low level,which reduces the boiler efficiency and provides ample scope for energy saving.The explosion index and CO generated temperature are used to evaluate the safety of improving the outlet temperature of the mill.Under the premise of ensuing the safe operation of the pulverizing system,the oulet temperature of the mill is impoved to improve the economy of power plants.The explosion index of different types of coal burned by a 660 MW ultra-supercritical unit is calculated and the relationship between the explosion index and volatile,ash and moisture in coal is analyzed.The outlet temperature of the mill is improved by improving the inlet temperature of the mill,the CO generated temperature in the air atmosphere is considered to be the permitted highest inlet temperature of the mill.The CO generated temperature for different types of coal in the air atmosphere is obtained by TG-FTIR and the relationship between the CO generated temperature andvolatile,ash and moisture in coal is analyzed.Based on the two parameters of explosion index and CO generated temperature,the test of improving the outlet temperature of the mill is conducted on the 660 MW ultra-supercritical unit.Under the load of 500 MW,the outlet temperature of mill A and E is increased from 75? to 85?,the outlet temperature of mill F is increased from 75? to 95 ?,and the outlet temperature of mill C and D is increased from 60 ? to 65 ?,the exhaust gas temperature decreases by 3.71 ?,the boiler efficiency increases by 0.15%,the power consumption rate decreases by 0.018%,the net coal consumption decreases by 0.59 g/kW·h.The results show that it is a feasible energy-saving way to improve the outlet temperature of the mill while ensuring the safe operation of the pulverizing system.(2)study on optimization of the primary air pressureIn the conventional operation of primary air system from the coal fired boiler,the mill inlet cold and hot air damper openings are too small,resulting in a high primary pressure,leading to an increase in power consumption of the primary air fan,and power consumption rate.Therefore the power consumption of the primary air fan could be reduced by increasing the mill inlet cold and hot air damper opening.A primary air pressure adaptive control system(PAPACS)is proposed.The PAPACS automatically calculates a primary air pressure offset value in real time.Combining with the existing primary air pressure setting,it reduces the primary air pressure,and correspondingly decreases the power consumption of the primary air fan,while ensuring the safety of pulverizing system.The PAPACS includes two models,the adaptive control model and the mill outlet over temperature control model,respectively.Under the normol operating conditions,the adaptive control model works.Mechanistic modeling is implemented for the adaptive control model.The potential for reducing the power consumption is determined by the mill inlet hot air damper opening in real time,and amended by the mill inlet cold air damper opening,and the primary pressure is thereby calculated.The PAPACS is applied to a 1000 MW ultra-supercritical power plant,with a 500 MW load,the power consumption of the primary fan is reduced as much as 465 kW under all test conditions,resulting in a power consumption reduction of 15%and a power consumption rate of 0.093%.Considering the importance of boiler operation safety,the mill outlet over temperature control model is designed for the occasional conditions of mill over temperature.The model is governed by a conventional proportional derivative controller,which employs the deviation of the mill outlet temperature as its input.With the PAPACS in operation,when the mill is over temperature,the mill outlet temperature is first controlled within the set value,to ensure the pulverizing system safety,then the primary air pressure is decreased.(3)study on boiler combustion optimizationNOx and carbon content in fly ash,which directly affect the boiler economy and environmental protection,are the target parameters of boiler combustion optimization.Moreover,NOx and carbon content in fly ash are contradictory,if NOx and carbon content in fly ash are optimized respectively,it can not simultaneously take both the boiler economy and environmental protection into account.Therefore,the boiler combustion optimization based on the artificial intelligence are used to implement the coordinated control of NOx and carbon content in fly ash under the influence of multiple factors.The factors influencing the NOx and carbon content in fly ash are analyzed in details,and the input parameters of the models are determined accordingly.The least square support vector machine(LSSVM)is used to establish the model of NOx and carbon content in fly ash,based on the historical operation data.The performance of LSSVM model is compared with the error back propagation neural network(BPNN)and the adaptive neuro-fuzzy inference system(ANFIS)model.The results show that LSSVM has a higher prediction precision and a better generalization.The preprocessing process is added before the basic solution step of the niche genetic algorithm(NGA).Based on the NOx and carbon content in fly ash models,the niche genetic algorithm with pretreatment is used to optimize the damper openings of secondary air,over fire air and SOFA and furnace outlet oxygen content,so that both of the NOx and carbon content in fly ash are simultaneously obtained in low levels.The comparison between the performance of the niche genetic algorithm and conventional genetic algorithm(CGA).The results reveal that the optimization results of NGA with pretreatment has better reliability.