项目名称: 兆瓦级风力发电机组控制系统主动容错控制研究
项目编号: No.61473002
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 自动化技术、计算机技术
项目作者: 史运涛
作者单位: 北方工业大学
项目金额: 86万元
中文摘要: 风电机组在恶劣的气候条件和交变风力载荷下全天候运行,发生事故的概率非常大,机组故障造成停机、飞车等事故不断增加,兆瓦级风机情况尤甚。本项目研究:(1)在离散随机混杂自动机(DHSA)模型框架下实现兆瓦级风电机组故障(机械故障、控制系统故障、电网故障)建模研究;(2)基于兆瓦级风电机组的随机混杂故障模型(DHSAF),构造有限时间稳定的随机混杂故障滤波器,利用序贯马尔科夫链蒙特卡罗优化(sequential MCMC)和随机动态规划方法求解随机混杂系统滤波器;设计风电机组的随机混杂故障诊断单元(FDI);(3)研究兆瓦级风电机组的随机混杂预测控制策略,实现风电机组的最优风能捕捉与机械载荷的折衷控制、电网故障下机组的保性能控制;(4)基于离散随机混杂自动机(DHSA)模型预测控制理论,利用随机混杂故障诊断信息,设计模型、性能指标、约束三要素重组的兆瓦级风电机组的主动容错控制系统。
中文关键词: 风电机组;故障诊断;容错控制;混杂系统;随机混合逻辑动态
英文摘要: Since wind turbines run in very bad weather conditions and alternating stochastic wind loads around the clock, the probability of accidents is very large. Every year, the stop and flying accidents caused by the wind turbine faults increase continuously.The situation of megawatt is even worse. This project mainly studies the following contents:(1)Discrete Hybrid Stochastic Automaton (DSHA) model tool is adopted to estibished the normal and failure model of megawatt wind turbines including mechanical failure, control system failure and grid failure;(2)Based on the DHSA fault model of megawatt wind turbines, construct finite time stable stochastic hybrid filter using sequential Markov chain Monte Carlo optimization and stochastic dynamic programming methods for solving the stochastic hybrid state estimation optimization problem in real time, and design the stochastic hybrid fault detection and isolation unit of megawatt wind turbine;(3)Within the DHSA model framework,design the stochastic hybrid MPC controller for megawatt wind turbines to achieve optimal wind energy capture efficiency - mechanical load control, and grid failure - guaranteed Cost Control performance indicators;(4) Based on the DHSA model predictive control of the megawatt wind turbines,with the help of the output information of fault diagnosis unit,design the active fault tolerant controller with reconfiguring the three elements of predictive model, performance indicators, and constraints.
英文关键词: Megawatt wind turbines;fault diagnosis;fault tolerant control;hybrid system;stochastic hybrid system