云南水火电机组功率振荡的控制研究

发布时间：2018-04-20 13:21

本文选题：机组功率 + 变工况　；参考：《华北电力大学》2014年硕士论文

【摘要】：原动机侧的功率扰动会引发整个电网的振荡，因此保证发电机组的稳定出力是影响电力系统安全稳定运行的重要课题。水火电机组是我国发电机组中的绝对主力，其功率控制必须满足较高的精度要求。水火电机组的运行过程是一个工况多变的过程，火电机组的主蒸汽压力、水电机组的工作水头及导叶开度都会随工况的变化而变化，导致机组功率控制回路的被控对象发生变化。经典PID控制难以保证对时变、非线性的功率控制系统获得较好的控制品质。机组有功功率会发生超调甚至振荡，影响电网的正常运行。模糊自整定PID控制可以根据系统的偏差及偏差变化率及时调整控制器的输出，以适应机组工况变化，对时变系统可以获得较好的控制品质。但模糊自整定PID的量化因子和比例因子的选取较为复杂，往往需要通过繁琐的重复试凑。本文采用粒子群算法对模糊自整定PID的量化因子和比例因子进行寻优，离线确定参数，避免了大量的人为重复实验，节省了时间与精力。仿真结果表明，，通过粒子群算法寻优得到的参数可使模糊自整定PID保证较好的控制品质。在水火电机组运行工况发生变化的情况下仍能对机组功率保证较好的控制精度，保证机组出力稳定。因模糊自整定PID算法较复杂，现场应用存在一定困难，本文提出在功率控制回路中经典PID控制器输出端引入自适应因子的方案，和反函数法校正水轮机导叶开度非线性的方案。通过实际观察，这两种方案较适用于现场工程应用，可使PID控制器的输出量根据被控对象的变化进行相应调整，对机组功率控制保证较好的控制品质。
[Abstract]:The power disturbance on the prime mover side will cause the oscillation of the whole power network, so it is an important problem to ensure the stable output force of the generator set to affect the safe and stable operation of the power system. Hydro-thermal motor unit is the absolute main force of generating units in China, and its power control must meet the higher precision requirements. The operation process of the hydro-thermal motor group is a variable working condition. The main steam pressure of the thermal power unit, the working head of the hydroelectric unit and the opening degree of the guide vane will all change with the change of the working condition. The change of the controlled object in the power control loop of the unit. Classical PID control can not guarantee better control quality for time-varying and nonlinear power control systems. Overshoot or even oscillation will occur in the unit active power, which will affect the normal operation of the power grid. Fuzzy self-tuning PID control can adjust the output of the controller according to the deviation of the system and the rate of variation of the deviation in time, so as to adapt to the change of unit working conditions and obtain better control quality for time-varying system. However, the selection of quantization factor and scale factor of fuzzy self-tuning PID is complex, and it often needs to be tried again and again. In this paper, particle swarm optimization (PSO) is used to optimize the quantization factor and scale factor of fuzzy self-tuning PID, to determine the parameters offline, to avoid a large number of artificial repeated experiments, and to save time and energy. The simulation results show that the parameters obtained by particle swarm optimization can make fuzzy self-tuning PID guarantee better control quality. Under the condition that the operating condition of the hydraulic motor group changes, the power of the unit can still be controlled with good precision and the output of the unit can be guaranteed to be stable. Due to the complexity of fuzzy self-tuning PID algorithm and some difficulties in field application, this paper presents a scheme of introducing adaptive factor into the output of classical PID controller in power control loop, and an inverse function method to correct the nonlinearity of guide vane of hydraulic turbine. Through practical observation, the two schemes are more suitable for field engineering application, the output of PID controller can be adjusted according to the change of the controlled object, and better control quality can be guaranteed for the power control of the unit.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TV734;TM621

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