(266a) Dynamic Modeling of Steam Thermal Power Plants for Real-Time Optimization

The variable market demand, and
the increasing safety and environmental regulations imposed on power plants, force
operators to develop dynamic
simulation tools, to optimize system operation, scheduling and maintenance, and test control strategies , using test-beds of dynamic
models of power
plants.^1?3 In this work, we explore such simulation
environments and in particular the Modelica language and the Thermal Power library of the Dymola software for dynamic simulation,
real time optimization and control of a 600
MW subcritical power plant with reheat cycle⁴ (Fig. 1). The detailed
modeling steps, steady-state validation and transient analysis (ramping of load)
are discussed. Conventional control designs are also
successfully incorporated in the system model. It is shown that the Dymola
environment provides a robust test-bed for controller tuning and stability
analysis.

Figure
1: Reheat
regenerative cycle, 600-MW subcritical-pressure fossil power plant.

The Functional Mockup Interface (FMI) is utilized
to bridge the models developed in Dymola with the optimization functionality of
Matlab, for the
real-time optimization application.⁵ The target of real-time power plant optimization
is to seek for maximum profit/efficiency of the plant by pushing the (steady
state) system operating point towards optimum time-varying operating
trajectories, while satisfying safety and operability constraints during the
transient between steady states. Here, the work flow for dynamic optimization
using the FMI Toolbox is presented. The optimization
capabilities of the complementary tool chain, which includes Dymola, FMI and
Matlab, were successfully demonstrated in case studies of nominal efficiency
optimization of the whole plant with respect to admissible plant inputs.

References

1.        Lu,
S. Dynamic modelling and simulation of power plant systems. Proc. Inst.
Mech. Eng. Part A J. Power Energy 213, 7?22 (2005).

2.        Lawal, A., Wang, M.,
Stephenson, P. & Obi, O. Demonstrating full-scale post-combustion CO₂
capture for coal-fired power plants through dynamic modelling and simulation. Fuel
101, 115?128 (2012).

3.        Lawal, A., Wang, M.,
Stephenson, P. & Yeung, H. Dynamic modelling of CO₂ absorption
for post combustion capture in coal-fired power plants. Fuel 88,
2455?2462 (2009).

4.        Singer, J. G. Combustion
Fossil Power: A Reference Book on Fuel Burning and Steam Generation.
(Combustion Engineering, 1991).

5.        Åkesson, J., Årzén, K.-E.,
Gäfvert, M., Bergdahl, T. & Tummescheit, H. Modeling and optimization with
Optimica and JModelica.org?Languages and tools for solving large-scale dynamic
optimization problems. Comput. Chem. Eng. 34, 1737?1749 (2010).