Dr Niall Mac Dowell, Dr Carolina Font Palma and Prof Eric Fraga – Process Engineering technical session at UKCCSRC Biannual Cambridge 2014

Written by Laura Herraiz and Maria Sanchez del rio Saez, PhD students at the University of Edinburgh whose attendance at the UKCCSRC Biannual Meeting in Cambridge, 2-3 April 2014 was supported by the UKCCSRC ECR Meeting Fund

The following presentations were part of the Process Engineering Technical Session. The other two presenters were Dr Meihong Wang and Dr Evgenia Mechleri (blog reports can be accessed by clicking on their names) 

Dynamic modeling and analysis of a coal fired power plant integrated with post-combustion CO₂ capture process – Dr Niall Mac Dowell, Imperial College London

At the beginning of the talk Dr Niall Mac Dowell compares the UK Energy’s market in 2050 with today’s and highlights the importance of flexible fossil fuel-based power generation. The need for a flexible low-carbon electricity system, in a future system with high penetration of renewables, aiming to meet an increasing electricity demand, encouraged Dr Mac Dowell to study the dynamic behavior of a coal fired power plant integrated with post-combustion CO₂ capture.

This work presents a new approach for the cost-optimal process design and operation of the fully integrated power capture plant. The dynamic analysis was carried out using gPROMS software package.

The based case model consisted of a supercritical pulverised coal power plant, due to the higher thermal efficiency compared with a convectional coal power plant.The power plant consists of a supercritical pulverised coal power plant with three staged steam turbines and desulphurization unit. Operating data from a real power plant were collected in order to study its dynamic operation.

The selected carbon capture technology involved the widely studied alkanolamine-based process. A validated rate-based model of the absorber/stripper was used to study the chemisorption of the acid gas in aqueous solvent solutions.

As the opportunity cost associated with the operation of the capture plant varies in the different time periods of operation, Dr Mac Dowell found out that the way to operate the integrated power-capture plant to exploit this multiple period behavior is maximizing the total process profit.

Three different scenarios to support process flexibility were evaluated: (1) Conventional load following: The power plant ramps up and down to meet the variable electricity demand, and the capture plant follows the change in load. The ratio of flue gas to solvent flow rate is keep constant as well as the lean solvent loading and thus the regeneration rate. (2) Solvent storage: The carbon capture plant is decoupled during peak periods of electricity demand and thus a fraction of the rich loading solvent is stored. This fraction will be regenerated at off-peak operation. This strategy allows the maximum electricity output penalty at peak demand and thus high electricity prices. This higher the peak of electricity demand is, the larger fraction of solvent should be stored. However, Dr Niall Mac Dowell pointed out that the maximum fraction of solvent that could be stored during peak hours is around 10%. At larger fractions, the amount of steam available for off-peak solvent regeneration would not be enough. (3) Variable regeneration: The carbon capture plant is decoupled during peak periods of electricity demand and the solvent regeneration rate is varied in concordance with the electricity prices. Solvent regeneration rate is decreased to reach a minimum at peak periods and then is increased to reach a maximum at off-peak periods, in a dynamic operation. At larger regeneration rates, the loading of the lean solvent is lower which results in larger the CO₂ capture rate in the absorber. This strategy therefore takes advantage of the peak price and presents a more flexible operation of the capture plant compared with the previous one.

The three scenarios were compared in terms of short run marginal cost of electricity. In view of the results Dr Niall Mac Dowell concluded that the last scenario, variable solvent regeneration, increases the overall profits of the process by roughly 10% and that process flexibility does not seem to increase the overall carbon intensity of the power plant. 

Oxyfuel Power Plant with Novel CO₂ Separation and Compression Technology – Dr Carolina Font Palma, University of Leeds

Oxyfuel Penalty Reduction Option Programme addresses the key penalty for oxyfuel combustion of coal in boiler plant through the Costain CO₂ separation and compression technology.

The OxyPROP project was supported by the Department of Energy and Climate Change (DECC) and carried out as collaboration between three organisations: Costain, the University of Leeds and the University of Edinburgh.

Each organization was in charge of a specific part of the project, Costain worked on the separation and purification technology, the University of Leeds on the flue gas chemistry and power plant modelling and the University of Edinburgh on the steam cycle optimization.

The specification of the base case of the project comes from the report, ‘Oxycombustion CO₂ Capture from Power plants’, published by IEAGHG in 2005. During the presentation Dr Carolina Font Palma highlighted the different modifications and improvements of the base case. The main improvements are as follows:

• CPU Scheme selection: due to an additional vapour separation stage and a maximization of the product pressure, the process reaches a higher CO₂ purity and reduces the compression power requirements.
• Flue Gas Compressor: The number of intercoolers between compression stages is optimised in order to minimise the power consumption in the CO₂ compression train.
• Steam Cycle: better heat integration as feedwater heaters recover heat from the CO₂ compressor intercoolers and air separation unit compressor intercoolers.

In consideration of the results of the project Dr Carolina Font Palma concluded that the better heat integration and the modified low temperature process within the CPU increase the efficiency of the process and the CO₂ purity.

Efficient computational modelling for integrated power plant design – Prof Eric Fraga, University College London

The analysis of the behaviour of a process which involves a large number of unit operations requires developing complex computational models. This is the case of a power plant integrated with carbon capture technologies. The models may consist of several objective functions (e.g. power output, CO₂ recovery, thermal efficiency, etc.) and multiple variables. These variables will be optimised within the model.

Computational simulations help in the identification of the best combination of design and operational variables which lead to maximum or minimum values of the objective functions. For instance, in a power plant with integrated CCS, the objective is to reduce the electricity output penalty, and thus maximise the power output and minimum reduction in the thermal efficiency.

Complex computational models usually require large computational effort, resources and computational time. This aspect might constitute a limitation on its application.

This talk presented recent work in the use of advance model reduction techniques and its particular application in power plants with CSS modelling. Particularly, a statistical interpolating approach used for approximating deterministic models was described in this presentation, referred to as Kriging approach.

In the case of study, the method was applied to pressure swing adsorption technology. Results were presented and compared with the use of high fidelity model. The use of surrogate modelling resulted in a significant reduction in the computational time and maximum values of the objective functions (e.g. recovery and purity) were found for a lower number of simulations.