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Abstract
Future electricity generation systems may include the widespread use of renewables along with fossil fuels. In recent work we developed novel computational procedures for modeling and optimizing the operations of an integrated fossil-renewable power generation system with CO2 capture, subject to a daily average CO2 emission constraint. System components were modeled using energy and mass balances, and a formal optimization procedure was applied to determine the optimal hourly dispatch of system components to maximize operating profit in response to time-varying electricity prices and wind generation. In this study we extend this work by assessing other policy schemes and system designs. First, in lieu of an emission performance standard, CO2 taxes of $10/Mg CO2 to $70/Mg CO2 are applied. Second, we consider emission performance standards ranging from 0.326 Mg CO2/MWh to 1.001 Mg CO2/MWh for systems with oversized and heuristically-sized components. Optimized operating profit shows a nonlinear response to varying emission constraint levels. Taken together, our findings illustrate the effect of different policy schemes on optimized operating economics and CO2 emission levels, and quantify the potential benefits of flexibility in an integrated energy system.

Introduction
CO2 capture and storage (CCS) has received wide attention in recent years as a possible means to mitigate the impact of fossil fuel use on climate. Widespread implementation of CCS would allow for the continued use of fossil fuels for electricity generation while reducing CO2 emissions. One problem CCS faces is that it entails large energy costs, with the cost for coal plants estimated at 24-40% of primary energy consumption (Metz et al. 2005), with a theoretical minimum of about 11% (House et al. 2009). It is nonetheless possible that CCS may be implemented at large scale in the coming decades.

Over a similar time frame, the electric power generation mix is expected to have an increasing fraction of energy provided by renewable energy resources, such as wind, that are characterized by high variability. The possible concurrence of CCS and the high penetration of renewables raises the question of how these two technologies will interact, and whether benefits can be realized by considering them within a unified framework.

In recent work we developed a modeling and optimization approach to begin to address this important question. Our methodology entails a modular representation of energy system components and enables the determination of system settings that maximize operating profit subject to a CO2 emission constraint. We treat an example system (based on a configuration actually proposed for a site in Wyoming to sell electricity to California (North American Power Group 2011)) that consists of a coal power station with CO2 capture powered by an auxiliary natural gas combustion turbine, and wind generation. Optimization of operating parameters was achieved for examples involving California energy prices and Wyoming wind generation data (Kang et al. 2011). The configuration used in that work differed from those most often studied in previous investigations, in that heat and energy demands for CO2 capture were provided by an auxiliary system, and not parasitically from the main coal plant. The system was constrained to meet a maximum daily average CO2 emission performance standard
(EPS) of 0.499 Mg CO2/MWh, modeled after a California emissions regulation (California State Legislature 2006). Other researchers have also examined optimization of CCS power plants, though their work involved parasitic operation of the CO2 capture and was based on carbon prices rather than a specific EPS (Chalmers et al. 2009; Cohen et al. 2011). Formal optimization techniques have also been used by previous investigators for the design of CCS retrofits (Harkin et al. 2011), and for the design and operation of cogeneration power plants (Jüdes et al. 2009).