基于智能算法的火电机组变负荷控制策略优化

Optimization of Variable Load Control Strategy for Thermal Power Units Based on Intelligent Algorithms

现有火电机组的AGC(automatic generation control,自动发电控制)系统存在控制精度低、响应速度慢等问题,为满足电力保供要求,引入人工智能算法对火电机组变负荷控制逻辑进行升级优化。对行业内已开展应用的神经网络、模糊控制、智能优化算法、专家系统、模型预测控制等各类智能算法进行特性总结与适用性分析,在此基础上提出利用线性自回归模型修正锅炉、汽轮机主控逻辑的方案,并在某350 MW超临界燃煤机组上进行10%额定出力的变负荷仿真实验,结果表明,智能算法优化后的控制逻辑有利于机组缩短响应时间,减少超调量,提高AGC系统的调节品质。

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.