Abstract: This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.
Abstract: This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.
Abstract: Thermally insulating ceramic coatings also known as
thermal barrier coatings (TBCs) have been essential technologies to
improve the performance and efficiency of advanced gas turbines in
service at extremely high temperatures. The damage mechanisms of
air-plasma sprayed YSZ thermal barrier coatings (TBC) with various
microstructures were studied by microscopic techniques after thermal
cycling. The typical degradation of plasma TBCs that occurs during
cyclic furnace testing of an YSZ and alumina coating on a Titanium
alloy are analyzed. During the present investigation the effects of
topcoat thickness, bond coat oxidation, thermal cycle lengths and test
temperature are investigated using thermal cycling. These results
were correlated with stresses measured by a spectroscopic technique
in order to understand specific damage mechanism. The failure
mechanism of former bond coats was found to involve fracture
initiation at the thermally grown oxide (TGO) interface and at the
TGO bond coat interface. The failure mechanism of the YZ was
found to involve combination of fracture along the interface between
TGO and bond coat.
Abstract: In designing of condensers, the prediction of pressure
drop is as important as the prediction of heat transfer coefficient.
Modeling of two phase flow, particularly liquid – vapor flow under
diabatic conditions inside a horizontal tube using CFD analysis is
difficult with the available two phase models in FLUENT due to
continuously changing flow patterns. In the present analysis, CFD
analysis of two phase flow of refrigerants inside a horizontal tube of
inner diameter, 0.0085 m and 1.2 m length is carried out using
homogeneous model under adiabatic conditions. The refrigerants
considered are R22, R134a and R407C. The analysis is performed at
different saturation temperatures and at different flow rates to
evaluate the local frictional pressure drop. Using Homogeneous
model, average properties are obtained for each of the refrigerants
that is considered as single phase pseudo fluid. The so obtained
pressure drop data is compared with the separated flow models
available in literature.