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As population grows, demand for reliable and sustainable energy increases prompting the need for innovative solutions. The numerous strategies are needed to shift centralized power generation to distributed generation in the evolution of smart energy systems. The response and electricity market paradigms using multiple loads are missing in literature. In this paper, multiple loads are considered to propose optimal energy hub modeling comprised of the various sources and storage. The proposed system is modelled using demand response technique. The exact method-based optimization is used to simulate the proposed model in MATLAB. The results obtained show the effectiveness of the proposed model to reduce the operational cost and greenhouse gas (GHG) emissions. A case study is taken, where a poultry farm producing approximately 1.94 million tons of poultry waste annually, is used to evaluate the proposed model. For the industrial load, the optimized scheduling reduced the operational cost to $161.8 as compared to $1670 relying only on the utility grid. For the residential load, the optimized cost is reduced by -$3.3 from the pre-optimization cost of $2.7. This work highlights the economic and environmental benefits, particularly in developing countries where biomass-based energy generation is yet to be fully explored.

Here we investigate the irreversibility aspects in magnetohydrodynamics flow of viscous nanofluid by a variable thicked surface. Viscous dissipation, Joule heating and heat generation/absorption in energy expression is considered. Behavior of Brownian diffusion and thermophoresis are also discussed. The nanoliquid is considered electrical conducting under the behavior of magnetic field exerted transverse to the sheet. Using similarity variables the nonlinear PDEs are altered to ordinary one. The obtained system are computed through Newton built in shooting method. Significant behavior of various involving parameters on entropy generation rate, velocity, concentration, Bejan number and temperature are examined. Gradient of velocity and heat transfer rate are numerically computed through tabulated form. Velocity field is augmented versus power index (n). Temperature and velocity profiles have opposite characteristics for larger approximation of Hartmann number. Concentration profile has similar impact against Brownian diffusion variable and Lewis number. Entropy optimization is boost up via rising values of Brinkman and Hartmann numbers. Bejan number is declined for increasing value of Hartmann number.

The entropy production in 2-D heat transfer system has been analyzed systematically by using the finite volume method, to develop new criteria for the numerical simulation in case of multidimensional systems, with the aid of the CFD codes. The steady-state heat conduction problem has been investigated for entropy production, and the entropy production profile has been calculated based upon the current approach. From results for 2-D heat conduction, it can be found that the stability of entropy production profile exhibits a better agreement with the exact solution accordingly, and the current approach is effective for measuring the accuracy and stability of numerical simulations for heat transfer problems.

Acute ingestion of ethanol impairs memory, an effect which might be related to ethanol-induced inhibition of vasopressin release. This was studied using tests of memory and cognitive function in 26 normal subjects before and after ethanol ingestion. Equal numbers of subjects received randomly, by double-blind intranasal administration, placebo or 1-desamino-8-D-arginine vasopressin prior to ethanol ingestion. Administration of the vasopressin analog did not reverse the ethanol-induced deficits in memory and cognitive function.

The microalgae-microbial fuel cell (mMFC) enables us to perform secondary and tertiary treatment of domestic wastewater while simultaneously producing green electricity. In this work, the treatment of wastewater and producing electricity using a dual-chambered mMFC were demonstrated. Furthermore, the electricity produced by the mMFC was utilized to drive microbial electrolysis cell (MEC) for hydrogen synthesis. Primary domestic wastewater was treated in the anodic compartment of mMFC. Chemical oxygen demand (COD) removal of 67.2 and 54% was achieved in the anodic compartment of batch and continuous mode, respectively. Wetland-treated water was filled in the cathodic compartment, and Scenedesmus sp. was used as a catholyte. The overall voltage of 1.85 V was used to run a 1-L MEC. Industrial wastewater was treated with a COD removal of 73% in the MEC and biohydrogen was produced at a rate of 9.8 ± 0.2 mL L−1 d−1.

This study focused on investigating the bottoming power cycles operating with CO2-based binary mixture, taking into account exergetic, economic and exergo-environmental impact indices. The main intent is to assess the benefits of employing a CO2-based mixture working fluid in closed Brayton bottoming power cycles in comparison with pure CO2 working fluid. Firstly, selection criteria for the choice of suitable additive compound for CO2-based binary mixture is delineated and the composition of the binary mixture is decided based on required cycle minimum temperature. The decided CO2-C7H8 binary mixture with a 0.9 mole fraction of CO2 is analyzed in two cycle configurations: Simple regenerative cycle (SRC) and Partial heating cycle (PHC). Comparative analysis among two configurations with selected working fluid are carried out. Thermodynamic analyses at varying cycle pressure ratio shows that cycle with CO2-C7H8 mixture shows maximum power output and exergy efficiency at rather higher cycle pressure ratio compared to pure CO2 power cycles. PHC with CO2-C7H8 mixture shows 28.68% increment in exergy efficiency with the levelized cost of electricity (LCOE) 21.62% higher than pure CO2 PHC. Whereas, SRC with CO2-C7H8 mixture shows 25.17% increment in exergy efficiency with LCOE 57.14% higher than pure CO2 SRC. Besides showing lower economic value, cycles with a CO2-C7H8 mixture saves larger CO2 emissions and also shows greater exergo-environmental impact improvement and plant sustainability index.

AbstractThis article studies the unsteady MHD free flow of a Casson fluid past an oscillating vertical plate with constant wall temperature. The fluid is electrically conducting and passing through a porous medium. This phenomenon is modelled in the form of partial differential equations with initial and boundary conditions. Some suitable non-dimensional variables are introduced. The corresponding non-dimensional equations with conditions are solved using the Laplace transform technique. Exact solutions for velocity and energy are obtained. They are expressed in simple forms in terms of exponential and complementary error functions of Gauss. It is found that they satisfy governing equations and corresponding conditions, and are reduced to similar solutions for Newtonian fluids as a special case. Expressions for skin-friction and Nusselt number are also evaluated. Computations are carried out and the results are analysed for emerging flow parameters.

AbstractPower companies are responsible for producing and transferring the required amount of electricity from grid stations to individual households. Many countries suffer huge losses in billions of dollars due to non-technical loss (NTL) in power supply companies. To deal with NTL, many machine learning classifiers have been employed in recent time. However, few has been studied about the performance evaluation metrics that are used in NTL detection to evaluate how good or bad the classifier is in predicting the non-technical loss. This paper first uses three classifiers: random forest,K-nearest neighbors and linear support vector machine to predict the occurrence of NTL in a real dataset of an electric supply company containing approximately 80,000 monthly consumption records. Then, it computes 14 performance evaluation metrics across the three classifiers and identify the key scientific relationships between them. These relationships provide insights into deciding which classifier can be more useful under given scenarios for NTL detection. This work can be proved to be a baseline not only for the NTL detection in power industry but also for the selection of appropriate performance evaluation metrics for NTL detection.