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Research On The Method Of Improving The Flexibility Of Coal-Fired Units Based On Energy Storage System

Posted on:2022-01-24Degree:MasterType:Thesis
Country:ChinaCandidate:H Y LiFull Text:PDF
GTID:2492306326461554Subject:Control Science and Engineering
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In recent years,new energy sources such as wind energy and solar energy have developed rapidly.However,the volatility and interval of renewable energy sources due to the influence of intermittent characteristics,new energy power is facing the problem of difficult to absorb.Thermal power will play a leading role in China’s energy structure for a long time.Improving the flexibility of thermal power units is the best choice in China’s energy structure.Although the existing boilerturbine coordinated control system has a certain variable load capacity,the traditional boilerturbine coordinated control system cannot solve the problem that the new energy power is difficult to absorb due to the limitation of the large delay characteristic on the boiler side.In order to ensure that the power grid can operate safely and stably after large-scale grid connection of new energy power,this paper studies the flexibility improvement methods of the combined heat and power units equipped with a thermal storage tank.The main research content of this paper is as follows.Firstly,the lumped parameter method is adopted to establish the mechanism model of coalfired system,boiler steam-water system,heating network heater,inclined thermostat,steam turbine,feed water heater and deaerator based on the conservation of mass and energy.The mathematical model of the mechanism is verified by the field data of a 330 MW combined heat and power unit equipped with a inclined temperature layer heat storage tank in a certain power plant.The error between the simulation results and the field data is relatively small.Within the allowable range,the mechanism model established in this paper can be used to study the dynamic characteristics of the combined heat and power unit with thermal storage tanks.Secondly,a simulation experiment was carried out on the basis of the system mechanism model.The variation of the inclined temperature layer of the heat storage tank in the state of energy storage and energy release are tudied respectively.Step disturbance experiments are carried out for the input of coal supply,steam turbine control valve,heating extraction steam butterfly valve,and hot water outlet flow of thermal storage tank.The influence of key parameters such as unit load,main steam pressure and heating load under different input step disturbances is studied.According to the simulation results,the input,output and transfer function structure of the unit control model are determined,combined with the particle swarm algorithm,the unknown parameters in the transfer function are identified,and a “4 inputs and 4 outputs” structure of combined heat and power unit with heat storage tank is established.The control model of the production unit.It provides a foundation for the research on the method of improving the flexibility of the unit.Finally,in order to improve the flexibility of the unit,a new coordinated control system suitable for combined heat and power unit equipped with thermal storage tanks was designed.Taking a 330 MW combined heat and power unit as an example,simulation experiments under load command step disturbance and slope disturbance are carried out.Experimental results show that the control effect of the new coordinated control system is better than that of the traditional coordinated control system.In order to reduce the fluctuation of the heating load caused by the unit in the process of variable load,a thermal compensation system was added to the new coordinated control system,and a simulation experiment was carried out.The simulation experiment results show that the thermal compensation system can effectively reduce the heating load fluctuation caused by the unit in the process of variable load.
Keywords/Search Tags:mechanism model, combined heat and power unit, heat storage tank, flexibility, particle swarm algorithm
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