Drum-boiler dynamics

Abstract

A nonlinear dynamic model for natural circulation drum-boilers is presented. The model describes the complicated dynamics of the drum, downcomer, and riser components. It is derived from first principles, and is characterized by a few physical parameters. A strong effort has been made to strike a balance between fidelity and simplicity. Results from validation of the model against unique plant data are presented. The model describes the behavior of the system over a wide operating range.

Introduction

There are dramatic changes in the power industry because of deregulation. One consequence of this is that the demands for rapid changes in power generation is increasing. This leads to more stringent requirements on the control systems for the processes. It is required to keep the processes operating well for large changes in the operating conditions. One way to achieve this is to incorporate more process knowledge into the systems. There has also been a significant development of methods for model-based control, see Garcia, Prett and Morari (1989), Qin and Badgwell (1997) and Mayne, Rawlings and Rao (1999). Lack of good nonlinear process models is a bottleneck for using model-based controllers. For many industrial processes there are good static models used for process design and steady-state operation. By using system identification techniques it is possible to obtain black box models of reasonable complexity that describe the system well in specific operating conditions. Neither static models nor black box models are suitable for model-based control. Static design models are quite complex and they do not capture dynamics. Black box models are only valid for specific operating conditions.

This paper presents a nonlinear model for steam generation systems which are a crucial part of most power plants. The goal is to develop moderately complex nonlinear models that capture the key dynamical properties over a wide operating range. The models are based on physical principles and have a small number of parameters; most of which are determined from construction data. Particular attention has been devoted to model drum level dynamics well. Drum level control is an important problem for nuclear as well as conventional plants, see Kwatny and Berg (1993) and Ambos, Duc and Falinower (1996). In Parry, Petetrot and Vivien (1995) it is stated that about 30% of the emergency shutdowns in French PWR plants are caused by poor level control of the steam water level. One reason is that the control problem is difficult because of the complicated shrink and swell dynamics. This creates a nonminimum phase behavior which changes significantly with the operating conditions.

Since boilers are so common there are many modeling efforts. There are complicated models in the form of large simulation codes which are based on finite element approximations to partial differential equations. Although such models are important for plant design, simulators, and commissioning, they are of little interest for control design because of their complexity. Among the early work on models suitable for control we can mention Profos 1955, Profos 1962, Chien, Ergin, Ling and Lee (1958), de Mello (1963), Nicholson (1964), Thompson (1964), Quazza 1968, Quazza 1970, Caseau and Godin (1969), Kwan and Andersson (1970), McDonald and Kwatny (1970), Speedy, Bell and Goodwin (1970), Dolezal and Varcop (1970), McDonald, Kwatny and Spare (1971), Eklund (1971), Åström and Eklund (1972), Åström (1972), Bell (1973), Borsi (1974), Lindahl (1976), Tyssø, Brembo and Lind (1976), Bell, Rees and Lee (1977) and Morton and Price (1977). Boiler modeling is still of substantial interest. Among more recent publications we can mention Maffezzoni 1988, Maffezzoni 1992, Maffezzoni 1996, Klefenz (1986), Jarkovsky, Fessl and Medulova (1988), Unbehauen and Kocaarslan (1990), Höld (1990), Na and No (1992), Kwatny and Berg (1993), Na (1995).

The work presented in this paper is part of an ongoing long-range research project that started with Eklund (1971) and Bell (1973). The work has been a mixture of physical modeling, system identification and model simplification. It has been guided by plant experiments in Sweden and Australia. The unique measurements reported in Eklund (1971) have been particularly useful. A sequence of experiments with much excitation were performed on a boiler over a wide range of operating conditions. Because of the excitation used, these measurements reveal much of the dynamics of interest for control. Results of system identification experiments indicated that the essential dynamics could in fact be captured by simple models, see Åström and Eklund (1972). However, it has not been easy to find first principles models of the appropriate complexity. Many different approaches have been used. We have searched for the physical phenomena that yield models of the appropriate complexity. Over the years the models have changed in complexity both increasing and decreasing; empirical coefficients have been replaced by physical parameters as our understanding of the system has increased. The papers Åström and Eklund 1972, Åström and Eklund 1975, Åström and Bell 1988, Åström and Bell 1993 and Bell and Åström (1996) describe how the models have evolved. The models have also been used for control design, see Miller, Bentsman, Drake, Fahkfahk, Jolly, Pellegrinetti and Tse (1990), Pellegrinetti, Bentsman and Polla (1991), and Cheng and Rees (1997). Models based on a similar structure have been used for simulation and control of deaerators, see Lu, Bell and Rees (1997), and nuclear reactors, see Yeung and Chan (1990), Höld (1990), Irving, Miossec and Tassart (1980), Parry et al. (1995), Menon and Parlos (1992), Thomas, Harrison and Hollywell (1985), Schneider and Boyd (1985) and Kothare, Mettler, Morari, Bendotti and Falinower (1999).