Modeling And Simulation Of Thermal Controlled Object In Power Plant Based On System Dynamics

The " deficient oil, lean gas, rich coal " energy structure in China determines that the coal-fired power generation becomes our country's long-term main power source. China's energy supply system is in the face of double pressures from both the current society's growing demand for energy and the energy-saving and emissionreduction. The static and dynamic study of thermal power plant process has a great significance for coordinating the relationship between energy and environment and achieving sustainable economic development. Modeling of thermal controlled objects based on system dynamics has benefit in better static and dynamic study and optimization which can achieve energy saving and emission reduction. Thesis topic has important practical value and wide range of engineering application prospect.From the prespective of matter and energy transfer, this paper presents the system dynamics models of three important controlled objects based on the operating of the thermal control objects, which are the drum, double in and double out ball mill, superheated steam temperature system. The causal loop diagrams are established by analyzing the causal relationship and feedback between variables within the system. The stock and flow diagrams are established according to quantify the variable relationship between the actual system. This paper presents variable step size fruit fly optimization algorithm to identify model parameters. Based on original fruit fly optimization algorithm, the step size is adjusted by iterative search error, meanwhile adding the relaxation factor to improve smell concentration judgment value. Variable step size fruit fly optimization algorithm overcomes the shortcomings of the original algorithm to improve the algorithm performance and gets better model parameters of thermal controlled objects that has actual characteristics. The system dynamics model built is simulated in Vensim PLE environment. The correctness of the system dynamics model is verified by comparison and analysis of the model simulation results with traditional model simulation curves.