(737d) Optimal Design and Operation of Power Plants with Reduced Emissions Via Intermittent Renewable Energy Integration

Authors: 
Zantye, M. S., Texas A&M University
Hasan, M. M. F., Artie McFerrin Department of Chemical Engineering, Texas A&M University
Fossil fuels have contributed to meeting more than 80% of the global energy demand in the past three decades, leading to rising CO­2­ emissions [1]. To reduce emissions from fossil-fuel based electricity generation, some promising technologies are: (i) installation of absorption-based carbon capture systems in fossil-fueled power plants, and (ii) increasing penetration of clean renewable energy in the grid [2]. For the seamless integration of renewable energy in power grids, its inherent challenges due to intermittent and variable availability need to be addressed. This requires additional capital investment in storage capacities and modifications in operations at grid-level e.g. increased flexibility, higher ramping rates of fossil-fueled plants. Such flexible operation can result in increased operational cost and reliability concerns. On the other hand, the high energy requirement of the solvent regeneration stage in carbon capture prevents its widespread deployment in power plants [3-4]. These challenges can be addressed together by leveraging the synergies between carbon capture and renewable integration technologies; the excess renewable power can be effectively utilized for solvent regeneration in carbon capture operation. This energy integration provides a sustainable route for power plants to reduce their carbon emissions without compromising on the ability to meet the fluctuating power demand. However, to the best of our knowledge, limited studies exist which consider the optimal operation decisions of such integrated systems under real-time market conditions [5-7].

To this end, we develop a framework for identifying optimal designs and operational schedules for reducing cost of power plant carbon capture utilizing renewable sources such as solar and wind generation. Flexible operation of the carbon capture system in response to dynamically varying electricity prices is considered to be facilitated through solvent storage. A mixed integer linear programming problem (MILP) is formulated to maximize the combined operating profit of the resulting hybrid power plant while meeting variable electricity demands and CO2 emission targets. An initial optimal design is obtained under assumption of no uncertainty in input model parameters such as electricity price profile and renewable energy production profile. However, in reality, renewable energy generation and electricity prices exhibit uncertainty owing to changing weather conditions and electricity market forces. To incorporate this uncertainty in the profiles, the aforementioned deterministic model is further extended to a stochastic model. The framework is demonstrated by applying to a case-study for the state of Texas.

References:

[1] “U.S. Energy Information Administration-Recent data.” https://www.eia.gov/environment/.

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[5] C. A. Kang, A. R. Brandt, and L. J. Durlofsky, “Optimal operation of an integrated energy system including fossil fuel power generation, CO2 capture and wind,” Energy, vol. 36, no. 12, pp. 6806–6820, 2011.

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[7] S. Cohen and G. T. Rochelle, “Utilizing solar thermal energy for solvent regeneration in post-combustion CO2 capture,” in ASME 4th International Conference on Energy Sustainability, Phoenix, 2010.