Research and Analysis of Step Intelligent Model Predictive Control of Generator Excitation System Based on the Field of Building Installation

Abstract

The traditional hydroelectric unit control system mostly adopts proportional integral derivative (PID) control strategy, which has simple control algorithm structure and is easy to understand and realize by the operation and maintenance personnel of the power station. However, its control objective is single, and the dynamic process and internal state information of the system water machine electricity coupling are less considered, especially the lack of the ability to constrain the system state variables In order to meet the increasingly complex operating environment in the regulation system of hydropower units high-quality control needs. Therefore, a step intelligent model predictive control method for synchronous generator excitation system based on tree algorithm is proposed. The step control and intelligent optimization algorithm are introduced into the rolling optimization of model predictive control, which effectively reduces the dimension of nonlinear programming solution in the rolling optimization and improves the feasibility of the control algorithm. In order to ensure the closed-loop stability of the control system, the concept of "quasi infinite time domain optimization" is introduced into the design process of the model predictive control of the excitation system of synchronous generator. The terminal penalty term and the terminal inequality domain are added in the rolling optimization link, and the "virtual" local linear feedback controller outside the prediction domain is designed. Compared with the traditional excitation control method in single machine and multi machine systems, it is proved that the predictive control method has stronger ability of generator terminal voltage maintenance and electromechanical oscillation damping than the conventional excitation control method.