Mixed convection on the flow past a heated length and past a porous cavity located in a horizontal wall bounding a saturated porous medium is numerically simulated. The cavity is heated from below. The steady-state regime is studied for several intensities of the buoyancy effects due to temperature variations. The influences of Péclet and Rayleigh numbers on the flow pattern and the temperature distributions are examined. Local and global Nusselt numbers are reported for the heated surface. The convective-diffusive fluxes at the volume boundaries are represented using the UNIFAES, Unified Finite Approach Exponential-type Scheme, with the Power-Law approximation to reduce the computing time. The conditions established by Rivas for the quadratic order of accuracy of the central differencing to be maintained in irregular grids are shown to be extensible to other quadratic schemes, including UNIFAES, so that accuracy estimates could be obtained
Biomass gasification and the sequential use of the produced gas in gas turbines (the so called Biomass Integrated Gasifier - Gas Turbine cycles) is one of the technologies that can minimize carbon dioxide emissions during electricity generation.
As the primer mover of such power plants, gas turbine performance is a key parameter on the economics of BIG-GT systems. At least within the first generation of this technology, gas turbines originally designed for burning conventional fuels (natural gas and light oils) will be adapted to syngas burning. At this stage some changes on combustion chamber will be required, and some modifications on operational control parameters must be done as well. Gas turbine de-rating (reduction of gas turbine firing temperature) is the simplest control alternative to avoid problems concerned with reduction of compressor surge margin and increased thermal loads. However, from the performance view point of the gas turbine (and also for the whole system), this seems to be the worst option.
In this paper the de-rating alternative is analyzed both from a thermodynamic and an economic point of view. A BIG-CC system based on a nearly atmospheric air-blown gasifier is considered. De-rating is analyzed vis-à-vis moderate increases of compressor pressure ratio. A simulation code (developed by the authors) able to perform analysis of thermal power systems (and particularly BIG-GT systems) is applied on this study. Cost functions are used to estimate the total installed unit capital cost, allowing a proper evaluation of electricity generating costs. The results indicate that electricity costs are sensitive to de-rating either due to the reduction on electricity generating efficiency and to the increase on the unit capital cost.
The need of advanced and high performance power cycles is becoming an ever increasing social demand, to reduce environmental impacts as well as to get a better use of natural resources in power generation.
The HAT cycle is one of these advanced cycles being considered for use in the next years. This cycle is gas-turbine based, comprises a recuperator and uses water to recover low temperature energy from compressor intercooler, aftercooler and from exhaust gases. However, this cycle requires high-quality water consumption. Consequently, some concerns about water use and costs are being discussed.
This work presents an exergetic analysis of the HAT cycle, for different total pressure-ratio on compressor train. The effect of pressure ratio over the water use is also shown. The turbine inlet temperature was kept fixed, to simulate the same technological level on blade cooling and metal alloys. All sub-systems are analyzed from irreversibility viewpoint.
An exergy-based thermoeconomic evaluation is made, regarding only fuel and water costs and their impacts on power cost. This methodology can highlight not only the final electric power cost (result that could be also achieved by conventional economic analysis), but also the internal costs of each stream and sub-system of the plant. The complete exergoeconomic analysis of the HAT cycle will depend on reliable economic data, as investment costs of each sub-system, operation and maintenance costs and the operational profile of the plant (base or peak load, yearly operation hours), as well as financial conditions.
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