(717g) Optimal Integration of CO2 Capture and Renewable Energy with Fossil Power Plants

While coal-based electricity generation plays an important role in the global energy mix, it contributes to one-third of all power-related CO₂ emissions. Promising technologies to reduce emissions from power generation include: (i) installation of CO₂ capture and storage (CCS) systems in power plants and (ii) integration of renewable energy with the electricity grid. However, these technologies currently have several limitations. CCS is highly energy-intensive and could reduce the net power output of a power plant by 25-40%¹. While renewable energy from solar and wind is inherently emission-free, capital-intensive grid level modifications are required to handle the intermittency and variability^2,3. Most of the previous studies on emission reduction considered these two technologies as independent of each other, resulting in high costs of CO₂ capture and renewable integration^4,5. We hypothesize that the CO₂ emissions from coal power plants can be effectively reduced by co-investing in a CO₂ capture system and a co-located renewable energy farm, thereby exploring the synergies between the two technologies. The clean renewable energy can be used for meeting the high energy requirement of CO₂ capture. On the other hand, CO₂ capture helps in handling the intermittency of renewables by acting in the form of a ‘storage’ system. Excess renewable energy can be used for flexible CO₂ capture⁶ during low electricity demand periods, thereby reducing curtailment. Furthermore, CO₂ capture operation can be turned down to provide energy to the grid for peak demand periods.

We investigate the potential of an integrated system that consists of a coal-based power plant, a flexible CO₂ capture unit and a renewable power generation unit. Specifically, we investigate under which conditions the benefits to a coal power plant from a CCS retrofit or a co-located renewable energy farm installation outweigh the upfront capital cost of these systems. We formulate a two-stage optimization framework to determine both the long-term investment and the short-term operational decisions for clean energy. The framework is based on a mixed integer nonlinear programming (MINLP) model with the objective of maximizing the net present value (NPV) of the integrated system. Seasonal and daily variabilities in electricity price and weather data are represented through deterministic scenarios. Incentive to reduce CO₂ emissions is provided by imposing a regulatory policy such as carbon tax. To solve the large-scale optimization problem in tractable time, we apply a scenario reduction technique and re-assign the scenario frequencies to obtain the time-aggregated representative scenarios. This subset of scenarios is used to obtain the designs as the first-stage decisions. The second stage involves solving for the operational variables subject to the original scenario set. This two-stage optimization framework strikes a balance between the computational tractability and the solution quality as we decouple the complicating design decisions from the hourly operating decisions. We demonstrate the framework through a case study based on the Petra Nova CO₂ capture facility, which is one of the few power plants worldwide with an operational CCS unit. Although a co-located natural gas-fired power plant is used to meet the high energy requirement of CO₂ capture at this facility⁷, it further adds to the CO₂ emissions. Our results suggest that for a carbon tax above $40 per ton, it is beneficial to invest in a co-located solar energy farm that would partially meet the energy demands of the CO₂ capture unit while providing an additional supply of renewable energy to the grid, thereby reducing the overall consumption of coal. This reduces the total CO₂ emission intensity of the integrated system by almost 50% as compared to the case without renewables. Moreover, the optimal solar farm size is influenced by the imposed carbon tax, with higher carbon tax resulting in a larger size of the solar energy farm. We further extend this analysis to a nationwide scale by identifying coal power plants where a CCS retrofit and/or a co-located renewable energy farm installation would be viable to reduce CO₂ emissions.

References:

1. Rubin ES, Davison JE, Herzog HJ. The cost of CO₂ capture and storage. Int J Greenh Gas Control. 2015;40:378-400.
2. Beaudin M, Zareipour H, Schellenberglabe A, Rosehart W. Energy storage for mitigating the variability of renewable electricity sources: An updated review. Energy Sustain Dev. 2010;14(4):302-314.
3. Perez-Arriaga IJ, Batlle C. Impacts of intermittent renewables on electricity generation system operation. Econ Energy Environ Policy. 2012;1(2):3-18.
4. Kang CA, Brandt AR, Durlofsky LJ. Optimal operation of an integrated energy system including fossil fuel power generation, CO₂ capture and wind. Energy. 2011;36(12):6806-6820.
5. Bandyopadhyay R, Patiño-Echeverri D. An alternate wind power integration mechanism: Coal plants with flexible amine-based CCS. Renew Energy. 2016;85:704-713.
6. Zantye MS, Arora A, Hasan MMF. Operational power plant scheduling with flexible carbon capture: A multistage stochastic optimization approach. Comput Chem Eng. 2019;130:106544.
7. U.S. Energy Information Administration-Petra Nova is one of two carbon capture and sequestration power plants in the world. https://www.eia.gov/todayinenergy/detail.php?id=33552.