Modelling Study Of Supercritical Power Plant And Parameter Identification Using Genetic Algorithms

The paper aims to study the whole process mathematical model for a supercritical coal-fired power plant. The modeling procedure is based on thermodynamic and engineering principles and the previously published literatures. Model unknown parameters are identified using Genetic Algorithms (GAs) with 600MW supercritical power plant on-site measurement data. The identified parameters are verified with different sets of measured plant data. Although some assumptions are made in modeling process, the supercritical coal-fired power plant model reported in the paper can be used to simulate the main features of the real plant once-through boiler operation and the simulation results show the main variation trends of the process.