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the Dresser-Rand/Siemens facility in Olean, NY [1]. The experience gained in cycle and system development during this process has provided added confidence in the ability of sCO2 power cycles to form the basis for larger-scale CCGT plants. The performance and cost models used in the present work are largely based on the actual performance and costs developed in the EPS100 commercialization process. Figure 2: EPS100 sCO2 heat engine, process and power skids The present work is a study of the potential for sCO2 cycles to form the basis of combined cycle power plant bottoming cycles up to and including utility scale applications. This combined performance and economic assessment of sCO2 cycles at large scale indicates that given sufficient time and effort, sCO2 can deliver a lower cost, higher performance option for CCGT plants that does the current steam technology. CYCLE DESIGN AND OPTIMIZATION The management of the internal and external sources of enthalpy is a challenging aspect of sCO2 power cycle design. The overall goal for the CCGT bottoming cycle is to generate the most power possible, while respecting appropriate economic and technical constraints. The conceptual design process consists of two major activities – selecting the cycle architecture, and sizing the equipment. The term “cycle architecture” refers to the general arrangement of turbines, pumps, recuperators and external heat exchangers. Within a given cycle architecture, the sizing of the various heat exchangers has direct influence on both the system performance (power output) and capital cost. Selection of the cycle operating pressures and flow rates also affects performance, but has a relatively minor impact on system cost within reasonable ranges. The process of cycle optimization requires a model that is a valid representation of both the thermodynamic performance of the system and its capital cost. The model utilized in this study contains an integrated set of component and system-based thermodynamic and cost submodels. Upon selection of the cycle architecture, and assignment of appropriate boundary conditions (generally heat source temperature, flow rate and constituents, and heat rejection sink temperature), the model uses a non-linear optimization process to define the lowest cost solution that will achieve a given target net output power. By specifying a range of target output powers, a curve of system cost as a function of power output can be generated. This process can be repeated over 6PDF Image | SUPERCRITICAL CO2 CYCLES FOR GAS TURBINE COMBINED CYCLE
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