Fuzzy intelligent system for the operation of fossil power plants

Abstract

In artificial intelligence applications in large-scale industry, such as fossil fuel power plants, the knowledge about the process comes from an expert's experience, and is generally expressed in a vague and fuzzy way, using ill-defined linguistic terms. This paper presents a fuzzy intelligent system to assist an operator of fossil power plants. The approach is characterized as a fuzzy diagnostic and fuzzy control system. The fuzzy diagnostic system is based on a novel representation for dealing with uncertainty and time, called as fuzzy temporal network (FTN). An FTN is a formal and systematic structure, used to model temporal linguistic sentences about the occurrence of an event. The fuzzy controller was designed for the regulation of the steam temperature of a steam generator. The fuzzy rules were obtained by observing the dynamic characteristics of the steam temperature response. The results show that the fuzzy controller has a better performance than advanced model-based controller, either an dynamic matrix control (DMC) or a conventional PID controller. The main benefits are the reduction of the overshoot and the tighter regulation of the superheater and reheater steam temperatures. The intelligent system has shown that fuzzy logic techniques can play an important role in power-plant operation and control tasks. The scheme not only makes the problem formulation more flexible but, if applied correctly, can improve the computational efficiency. This makes it practical for many applications in complex fields where the real-time tasks are important.