Distributed Generation (DG) unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to the load centers, interchanging electric power with the network. Moreover, DGs influence distribution system parameters such as reliability, loss reduction and efficiency while they are highly dependent on their situation in the distribution network. This paper focuses on optimal placement and estimation of DG capacity for installation and takes more number of significant parameters into account compare to the previous studies which consider just a few parameters for their optimization algorithms. Using a proposed optimal Genetic Algorithm, a destination function that includes the cost parameters (such as loss reduction, fuel price, etc.) has been optimized. This method is also capable of changing the weights of each cost parameter in the destination function of the Genetic Algorithm and the matrix of coefficients in the DIGSILENT environment. It has been applied and simulated on a sample IEEE 13-bus network. The obtained results show that any change in the weight of each parameter in the destination function of the Genetic Algorithm and in the matrix of coefficients leads to a meaningful change in the location and capacity of the prospective DG in the distribution network
Hydraulic fracturing is a widely employed well stimulation technique in which a synthesized fracking fluid is pumped into the well bore at high pressures to propagate fractures in rock formation matrix for hydrocarbon production. Proppant being one of the essential component of fracturing fluid is used to keep the hydraulically induced fractures open and conductive by acting as a mechanically strong support particle. Hydraulic fracturing operations are gradually shifting into deeper and low permeability (tight) formation at elevated temperature and pressure conditions at which conventionally used silica sand is becoming unviable as proppant due to its crushing. For resin-coated sand (RCS), temperatures greater than 60°C under high pressures, the glass transition temperature (Tg) threshold limit of polyurethane-based resin coating is reached at which this applied coating tends to soften that results reduction in the mechanical strength of the coated sand pack. Glass beads are also considered as good contestant for proppant that were selected in this study due to their high roundness and sphericity. They were drip coated with urethane resin incorporated with three different concentrations of 0.1 wt%, 0.5 wt% and 1 wt% carbon nanotubes (CNTs) and reduced graphene oxide (rGO) nanofillers, respectively. Crush test analysis by means of Universal Testing Machine (UTM) revealed significant improvement in the mechanical strength of coated glass bead proppants. 0.5 wt% loading of CNTs into urethane resin proved to be the best optimum concentration at which the mechanical strength of the coated glass bead improved by 84% along with 40% reduction in fines generation due to its containment within the applied coating. Crush test results also further revealed that nanofillers concentration loadings greater than the optimum threshold limit into urethane resin promoted their mutual agglomeration that resulted in profound reduction in mechanical strength of coated glass beads therefore resulting in more crushing and higher generation of undesired and detrimental fine particles.
An approach has been proposed for automatic adaptive subtitle coloring using fuzzy logic-based algorithm. This system changes the color of the video subtitle/caption to “pleasant” color according to color harmony and the visual perception of the image background colors. In the fuzzy analyzer unit, using RGB histograms of background image, the R, G, and B values for the color of the subtitle/caption are computed using fixed fuzzy IF-THEN rules fully driven from the color harmony theories to satisfy complementary color and subtitle-background color harmony conditions. A real-time hardware structure has been proposed for implementation of the front-end processing unit as well as the fuzzy analyzer unit.
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