Research And Application On The AGC Performance Optimization Of The Shangdu Power Plant

Modern thermal power plant,which is large inertia,nonlinear,and strong coupled,is a typical multi-input multi-output(MIMO)object.With the continuous expansion of grid capacity,the requirements of power-up’s quality power grid is increasing,the power grid requires the unit a high load response speed and strong peak load cycling ability.The advanced control theories may achieve better performance than conventional PID controllers used.With the good running of 2*660MW of Shangdu power plant,the actual load on the AGC load command response is slow,the main steam pressure fluctuate sharply.This paper proposes an optimization including generalized predictive control and dynamic feedforward to resolve the problem.In order to obtain the accurate model of the coordinated control system of the unit,this paper applies the subspace identification algorithm based on principal component analysis.Instrumental variables method is recommended to eliminate the influence of noise,which avoids the projection calculation.An improvement is proposed during the principal component analysis process.Based on the data of the #5 unit of the Shangdu power plant,this paper uses the real-time data to estimate matrixes of state space system.And then,it uses the GPC arithmetic and dynamic feedforward to optimize the control system,which resolved the contradictions between quick load change capability and the unit’s stability.At last,the optimization control strategy is applied to the # 5 unit of the power plant by AOC3000,a newly external optimization control system.The validity of the optimization strategy is proved by observing and comparing the historical curve.