Fossil-fueled power plants typically operate below their design capacities for a large fraction of their service life. In the United States, increased fuel and capital costs attributable to this off-design operation are considerable. This article describes the reasons for off-design operation and its importance in designing and selecting new power plants. Recent studies of coal gasification combined-cycle power plants show how computer simulations of off-design performance can aid in the design process, and they suggest that such simulations can be useful in reducing the cost of building and operating new power plants.

A strength of parabolic trough concentrating solar power (CSP) plants is the ability to provide reliable power by incorporating either thermal energy storage or backup heat from fossil fuels. Yet these benefits have not been fully realized because thermal energy storage remains expensive at trough operating temperatures and gas usage in CSP plants is less efficient than in dedicated combined cycle plants. For example, while a modern combined cycle plant can achieve an overall efficiency in excess of 55%; auxiliary heaters in a parabolic trough plant convert gas to electricity at below 40%. Thus, one can argue the more effective use of natural gas is in a combined cycle plant, not as backup to a CSP plant. Integrated solar combined cycle (ISCC) systems avoid this pitfall by injecting solar steam into the fossil power cycle; however, these designs are limited to about 10% total solar enhancement. Without reliable, cost-effective energy storage or backup power, renewable sources will struggle to achieve a high penetration in the electric grid. This paper describes a novel gas turbine / parabolic trough hybrid design that combines solar contribution of 57% and higher with gas heat rates that rival that for combined cycle natural gas plants. The design integrates proven solar and fossil technologies, thereby offering high reliability and low financial risk while promoting deployment of solar thermal power.

Data reconciliation is widely used in the chemical process industry to suppress the influence of random errors in process data and help detect gross errors. Data reconciliation is currently seeing increased use in the power industry. Here, we use data from a recently constructed cogeneration system to show the data reconciliation process and the difficulties associated with gross error detection and suspect measurement identification. Problems in gross error detection and suspect measurement identification are often traced to weak variable redundancy, which can be characterized by variable adjustability and threshold value. Proper suspect measurement identification is accomplished using a variable measurement test coupled with the variable adjustability. Cogeneration and power systems provide a unique opportunity to include performance equations in the problem formulation. Gross error detection and suspect measurement identification can be significantly enhanced by increasing variable redundancy through the use of performance equations. Cogeneration system models are nonlinear, but a detailed analysis of gross error detection and suspect measurement identification is based on model linearization. A Monte Carlo study was used to verify results from the linearized models.

The GATE (GAs Turbine Evaluation) code has been developed to evaluate the design and off-design performance of existing and advanced gas-turbine-based systems for power plant applications. By combining an intuitive, graphical user interface with detailed analytical models for the thermodynamic, heat-transfer and fluid-mechanical processes within gas-turbine-based power plants, GATE can be used by novices as well as experts for complex design and simulation studies. It can model a variety of gas turbine configurations and cooling technologies, and users can also interactively design and analyze an associated steam bottoming cycle. The basic formulations used in GATE are presented here, along with sample cases demonstrating the power and flexibility of the code.

To meet increasing demand for education and experience with commercial-scale, coal-fired, integrated gasification combined cycle (IGCC) plants with CO2 capture, the Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) is leading a project to deploy a generic, full-scope, real-time IGCC dynamic plant simulator for use in establishing a world-class research and training center, and to promote and demonstrate IGCC technology to power industry personnel. The simulator, being built by Invensys Process Systems (IOM), will be installed at two separate sites, at NETL and West Virginia University (WVU), and will combine a process/gasification simulator with a power/combined-cycle simulator together in a single dynamic simulation framework for use in engineering research studies and training applications. The simulator, scheduled to be launched in mid-year 2010, will have the following capabilities: • High-fidelity, dynamic model of process-side (gasification and gas cleaning with CO2 capture) and power-block-side (combined cycle) for a generic IGCC plant fueled by coal and/or petroleum coke. • A fully integrated virtual reality Immersive Training System which allows for training of field personnel using a full scale three dimensional IGCC plant environment that is tied to the simulation and emulated DCS. • Highly flexible configuration that allows concurrent training on separate gasification and combined cycle simulators, or up to two IGCC simulators. • Ability to enhance and modify the plant model to facilitate studies of changes in plant configuration, equipment, and control strategies to support future R&D efforts. • Training capabilities including startup, shutdown, load following and shedding, response to fuel and ambient condition variations, control strategy analysis (turbine vs. gasifier lead, etc.), representative malfunctions/trips, alarms, scenarios, trending, snapshots, data historian, etc.