Modelon supports the development of CO2-removal processJens Pålsson
Modelica modeling & simulation for improved & greener fossil fuel power plant operation
Needed: flexible operation & lower emissions for fossil fuel power plants
In 2015 Modelon participated in a carbon capture and storage (CCS) research project together with Chalmers University in Sweden.
With evolving energy market requirements for flexible, load-following operation of fossil fuel power plants and also expected more stringent future emission limits for greenhouse gases, there is a strong motivation for simulation-based evaluation of new concepts in both steady state and dynamic operation. Modelon provided the modeling and simulation support for the project to study the dynamic effects of integrating a fossil fueled power plant with an amine based post combustion unit.
The work has been applied on a coal-fired power plant of 400 MW.
Fig. 1 Full plant model of the modeled 400 MW coal-fired power plant including controls
The overall modeling solution involved the following products:
- Dymola, as the dynamic simulation tool
- Thermal Power Library used for composing the models of the boiler, flue gas train and the Rankine (steam) cycle.
- A service model package called Gas-Liquid-Contactor for composing models of the monoethanolamine-based CO2 absorption system.
The dynamic power plant model developed in Modelica resembles a typical supercritical power plant process and will be included in the May 2016 release of the Thermal Power Library.
As shown in Fig. 1 and 2, the full plant model is conveniently available on a top level, with extended subsystem classes such as the Rankine cycle.
Fig. 2 Dynamic power plant model built in Dymola with components from Modelon’s Thermal Power Library, Modelica Standard Library and custom made components
Implemented loops regulate the combustion and the power output
As part of the work, several control loops were also implemented to regulate important process parameters. For example the power output by the fuel supply, and the air-to-fuel ratio in the combustion chamber by the flow of combustion air were controlled by closed loops.
CO2 absorption model
The rate based CO2 absorption model was further improved in an earlier collaboration between Chalmers and Modelon . This model connected to the extended power plant model at the flue gas side and on the steam cycle (reboiler) side.
Increased understanding of the overall plant dynamics, operation and performance
The results of this work was presented at an IEA Greenhouse Gas conference in Canada .
Modelon’s contributions to the project demonstrated:
- Good agreement between the simulation results and plant data for generator power output and live steam and reheat pressures (see Fig. 3)
- The boiler exhaust gas flow follows as expected dynamic ramp in fuel input and overall dynamic behavior similar between a process with and without a post combustion unit (see Fig. 4).
Fig. 3 Steady-state results in Dymola compared to plant data. Output power (left) and reheat & live steam pressures (right).
Fig. 4 Dynamic simulation results. Fuel input (left) and generator power (right).
Key results from the overall project include the following:
- Integration of the post combustion with the power plant showed only minor effects on the overall plant dynamics compared with a plant without post combustion capture and thus proves that the method for lowering the plant’s carbon dioxide emissions is technically viable.
- The steam extraction in the low pressure turbine needs to be carefully designed to maintain correct temperature in the absorption process over the load range.
- Modeling and simulation is a key enabler for significant improvements in plant design and operation.
- Garðarsdóttir, S.O., Dynamic modeling of a supercritical coal fired power plant integrated with post-combustion CO2 capture, 3rd Post Combustion Capture Conference, Canada, September 2015
- Garðarsdóttir, S.O., et al., Post-combustion CO2 capture applied to a state-of-the-art coal-fired power plant—The influence of dynamic process conditions, Intl. J. of Greenhouse Gas Control, Vol. 33, pp. 51-62, 2015.
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