Optimization of Variable Load Control Strategy for Thermal Power Units Based on Intelligent Algorithms
The existing AGC (automatic generation control) system of thermal power units has problems such as low control accuracy and slow response speed. In order to meet the requirements of power supply guarantee, artificial intelligence algorithms are introduced to upgrade and optimize the variable load control logic of thermal power units. This paper summarizes the characteristics and analyzes the applicability of various intelligent algorithms that have been applied in the industry, such as neural network, fuzzy control, intelligent optimization algorithm, expert system, model predictive control, etc. On this basis, a scheme to modify the main control logic of boiler and turbine by using linear autoregressive model is proposed. The simulation test of 10％rated output of a 350 MW supercritical coal-fired unit is carried out. The results show that the control logic optimized by the intelligent algorithm is beneficial to shorten the response time of the unit, reduce the overshoot and improve the regulation quality of the AGC system.
intelligent algorithmscontrol logicoptimization and upgradingvariable load
万方数据
维普
