(724f) Dynamic Simulation and Optimization of Power Plants Operating at Transient Electricity Demand and Carbon Footprint Constraints

Modern
power plant designs are required to provide better operational flexibility and
improved performance, and adapt to the rapidly evolving energy infrastructure.^1–3 Dynamic simulation and
optimization can be useful tools in analyzing the dynamic performance of power
plants in response to seasonal and daily fluctuations in power demand and in
the assessment of the value proposition and feasibility of new programs focused
on renewable energy. Moreover, dynamic optimization offers the potential of
reducing operating cost, improving exergy efficiency, meeting environmental
requirements and reducing CO₂ emissions.

Figure 1: Simplified diagram of
the steam side system of the 605 MW subcritical-pressure coal-fired power plant
with control system.

In
this work, a high-fidelity dynamic model was developed, for a 605 MW coal-fired,
subcritical power plant with regenerative reheat cycle, as shown in Figure 1. Conventional
regulatory controllers were incorporated in the plant model. The model was
validated against static, full-load data from a fossil-fueled power plant
reported in the literature.⁴ This validated plant model was
used as a test-bed for dynamic simulations, in which the power plant operation
was studied under transient power demand. The performance in closed-loop
operation in response to step changes in coal load was assessed, showing that
the plant model is stable and reliable for sudden changes, and the control
system is able to maintain the controlled variables at their set points. Advanced
power plant-level control architectures, including controllers for coal load,
feed water load, and preheated air load, were used to adjust the power plant
operations, in response to time-varying power demand. A supervisory control architecture
was designed for the  purpose of optimizing the net efficiency of the power
plant operating under steady state and dynamically, in response to realistic
load changes, employed using power demand from the New England ISO data. The
value proposition of static and dynamic optimization of the plant operating at
variable load was assessed. An improvement in time-averaged efficiency of up to
1.95% points was shown feasible with corresponding savings in coal consumption
of 184.7 tons/day and carbon footprint decrease of 0.0352 kg/kWh. In summary, this
presentation will show the complete work flow of data collection, model
development and validation, control tuning, dynamic optimization formulation
and solution, and supervisory control architecture for a coal-fired subcritical
power plant, focusing on the potential efficiency, energy and carbon footprint
benefits of model-based approaches.

References

1.         Chen, C., Han, L.
& Bollas, G. M. Dynamic Simulation of Fixed-Bed Chemical-Looping Combustion
Reactors Integrated in Combined Cycle Power Plants. Energy Technol. 4,
1209–1220 (2016).

2.         Chen, C., Zhou, Z.
& Bollas, G. M. Dynamic Modeling, Simulation and Optimization of a
Subcritical Steam Power Plant. Part I: Plant Model and Regulatory Control. Energy
Convers. Manag. (unpublished) (2017).

3.         Chen, C., Zhou, Z.
& Bollas, G. M. Dynamic Modeling, Simulation and Optimization of a
Subcritical Steam Power Plant. Part II: Dynamic Optimization under Time-Varying
Power Load. Energy Convers. Manag. (unpublished) (2017).

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

Acknowledgements

This material is based upon work
supported by the National Science Foundation under Grant No. 1054718. CC
gratefully acknowledges support by the GE Graduate Fellowship for Innovation
and helpful advice and guidance from Alstom Power.