Theoretical, technical, and practical aspects of the identification and use of dynamic matrices in supervisory control for different types of fossil power plants are discussed. The control structures for once-through and drum boilers are reviewed, and modifications necessary for conversion to matrix base controls are discussed. The control of dynamic, nonlinear models that replicate the response to actual plants is demonstrated. A lecture series and support system of analytical tools for use on personal computers to transfer the technology from its roots in the process industries to fossil power plants are described. >

Dynamic matrix based control of fossil power plants

Adaptive Control for Steam Temperature of Thermal Power Plant

Optimal control strategy for minimization of exergy destruction in boiler superheater

Over the last decade, there has been considerable change in the electric power generation industry. Larger, faster plants have been constructed and old plants have been forced to operate in a much more dynamic environment, thanks to strong competition and market forces. Massive changes have also occurred in information technology, designed to improve power plant performance, by including large amounts of computing and digital circuits, together with very advanced man-machine interface tools, allowing efficient information retrieval and display at reasonable cost. By contrast, the control systems implemented in the distributed control computer systems remain largely conventional control, a mix of various types of PID control and feedforward, which is not at all what is thought of as advanced control. This paper looks at this issue, and describes some of the advanced controllers that might be very effective in the industry, including many that are being offered to the industry by the control vendor companie...

Some thoughts on the advanced control of electric power plants

In response to the multiple and tighter operation requirements already placed on power plants, and anticipating everyday variations on their quantity and relevance due to competition on deregulated energy markets, this dissertation contributes the Intelligent Coordinated Control System (ICCS) paradigm that establishes a reference framework for the design of overall control systems for fossil-fuel power units, and develops a minimum prototype (ICCS-MP) to show its feasibility. 
The ICCS consists of a multiagent system organization structured as an open set of functionally grouped agent clusters in a two-level hierarchy. The upper level performs the supervisory functions needed to produce self-governing system behavior, while the lower level performs the fast reactive functions necessary for real-time control and protection. 
The ICCS-MP greatly extends the concept of current coordinated control schemes and embraces a minimum set of ICCS functions for the power unit to participate in load-frequency control in deregulated power systems; provides the means to achieve optimal wide-range load-tracking in multiobjective operating scenarios. The ICCS-MP preserves the ICCS structure. Supervisory functions include optimization and command generation, learning and control tuning, and performance and state monitoring. Direct level control functions realize a nonlinear multivariable feedforward-feedback scheme. These functions are implemented in three modules: reference governor, feedforward control processor (FFCP), and feedback control processor (FBCP). 
The reference governor provides set-point trajectories for the control loops by solving a multiobjective optimization problem that accommodates the operating scenario at hand. The FFCP facilitates achievement of wide-range operation; it is implemented as a fuzzy system that emulates the inverse static behavior of the power unit, and it is designed using neural networks. The FBCP provides disturbance and uncertainty compensation along the set-point trajectories; it includes fuzzy-PID controllers in a multiloop configuration and a multivariable feedforward interaction compensator, both scheduled in two-dimensions. Controllers are tuned using a genetic algorithm based procedure, and the compensator is designed using the relative gain array method. 
Simulation results show that the proposed ICCS paradigm provides a suitable conceptual framework to manage the complexity and to integrate either algorithmic or heuristic techniques into a control system that provides high maneuverability and optimized unit operation.

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Overall intelligent hybrid control system for a fossil-fuel power unit

The design of an advanced digital control system that is used to regulate the steam temperature in the boiler of a thermal power plant is described. An autoregressive model is used to obtain the plant transfer characteristics. To compensate for system nonlinearities, the calculations for system identification and feedback gain are determined for two or three load levels. Experimental results have demonstrated the viability of the method and suggest that the advanced digital control system will replace conventional control in future applications. >

H. Nakamura

Papers

Optimal regulation for thermal power plants