Comprehensive Performance Evaluation Of The Control System In Power Generation Process

Electric power relates the national economy and people’s livelihood and is the source of social economy development. No matter traditional or new ways of generating energy power generation, the process of energy conversion to electrical energy goes through complex physical and chemical processes, and these processes often contain a large number of equipment and components.In modern power plants, the control system is throughout the entire production process, and commands various equipment and components running automatically, and cooperatively in accordance with established specifications and operating procedures. With the increasing energy crisis and environmental problems, the control system further shoulders more functions in addition to the safe and stable operation. In this case, the performance of the control system will directly affect not only the running quality of the units but also the quality of output power.This paper studies the control system performance evaluation in power generation process., the main contributions of this dissertation are given as following:Nonlinearity is an important factor that affecting the control performance and the evaluation results. A nonlinearity measure based on minimum variance lower bound ratio is presented in this paper to qualify the nonlinear degree of closed loop systems. This measure is deduced from Hammerstein structure, but it also can be applied to Wiener structure and Wiener-Hammerstein structure. Besides, this measure can be estimated from the routine operating data. The threshold to judging whether nonlinearity is strong or weak is given by the principle of statistic interval. The effectiveness and consistency of this measure are illustrated by four simulations. The nonlinearity measure of coal mill outlet temperature control is given as an application example.A minimum information entropy benchmark is proposed for assessing linear Guassian system and is extented to nonlinear non-Gaussian system. Then, a minimum information entropy based performance index is defined and the control performance assessment procedures are developed. Simulation tests and an industrial case study of coal mill outlet temperature control system are utilized to verify the effectiveness of the proposed procedures.A new MIMO control system method based on output filtering is presented. This method can transform MIMO control performance assessment into multiple SISO control performance assessment by output filtering. The importance of every loop is obtained. With this CPA framework, a performance diagnosis method is presented with respect to the bootstrap resampling. The turbine load/speed control system is selected to test the effectiveness of the proposed procedures...