2019 AIChE Annual Meeting
(737d) Optimal Design and Operation of Power Plants with Reduced Emissions Via Intermittent Renewable Energy Integration
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.
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