Advancing Efficient Fossil Energy Based Power Generation II
The objective of this session is to present new computational approaches and results to more effectively evaluate the cost and performance of innovative new ideas for fossil-based power generation in the context of reducing CO2 emissions and water consumption. Major topics include: optimization and comparison of low-carbon, low-water, fossil-based power generation; power systems optimization under uncertainty; reduction of CO2 emissions and water use from fossil energy power plants; promising process and technology development pathways; process intensification as a means to increase efficiency and drive down costs. Questions to be addressed may include: o How can new or existing fossil based power be generated more cost effectively? How can equipment improvements drive down installed cost? How can systematic process intensification improve cost and/or performance? o How does a focus on reducing water consumption change the design paradigm? o Accounting for market and/or regulatory uncertainty, is EOR or CO2 sale likely to succeed? If not, what carbon tax level would incentivize significant CO2 reduction? o What are the major cost and performance bottlenecks of low carbon power technologies? How is the cost of electricity impacted after implementing carbon capture and other process enhancements? o What promising developmental pathways have been identified? What is the relative potential of these technologies? Are these developmental pathways cost- or performance-limited? How do key uncertainties affect development choices? Which optimization frameworks for power systems modeling under uncertainty have proven most effective? Stochastic optimization approaches? Robust optimization approaches?
Paper abstracts are public but to access Extended Abstracts, you must first purchase the conference proceedings.
Do you already own this?
Log In for instructions on accessing this content.
|AIChE Graduate Student Members||Free|
|AIChE Undergraduate Student Members||Free|