Plant Performance Monitoring and Diagnostics: Remote, Real-Time and Automation

Abstract

Combined cycle gas turbine plants are built and operated with higher availability, reliability, and performance than simple cycle in order to help provide the customer with capabilities to generate operating revenues and reduce fuel costs while enhancing dispatch competitiveness. The availability of a power plant can be improved by increasing the reliability of individual assets through maintenance enhancement and performance degradation recovery through remote efficiency monitoring to provide timely corrective recommendations. This paper presents a comprehensive system and methodology to pursue this purpose by using instrumented data to automate performance modeling for real-time monitoring and anomaly detection of combined cycle gas turbine power plants. Through thermodynamic performance modeling of main assets in a power plant such as gas turbines, steam turbines, heat recovery steam generators, condensers and other auxiliaries, the system provides an intelligent platform and methodology to drive customer-specific, asset-driven performance improvements, mitigate outage risks, rationalize operational patterns, and enhance maintenance schedules and service offerings at total plant level via taking appropriate proactive actions. In addition, the paper presents the components in the automated remote monitoring system, including data instrumentation, performance modeling methodology, operational anomaly detection, and component-based degradation assessment. As demonstrated in two examples, this remote performance monitoring of a combined cycle power plant aims to improve equipment efficiency by converting data into knowledge and solutions in order to drive values for customers including shortening outage downtime, lowering operating fuel cost and increasing customer power sales and life cycle value of the power plant.