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Nowadays, the popularity of grid integrated systems primarily supplied by renewable energy sources based hybrid Microgrids have increased. This is due to their ability to reduce global warming and meet the increasing electrical load demand worldwide. In order to guarantee an uninterrupted power supply to loads when operating in the operation of off-grid, the system incorporates a storage device, thereby establishing an effective energy management system. A new energy management system has been developed to enhance the stability of the proposed system. The system has the ability to stabilize voltage at the load bus, compensate for reactive power, and mitigate the harmonics as well as the effect of unbalanced load. In order to attain quick reactions amidst swift alterations, the suggested control technique has integrated LSTM controllers. Practical outcomes have been achieved by leveraging Hardware-in-the-Loop using OPAL-RT modules. Numerous case studies have been carried out to further confirm the efficacy of the suggested approach.

Simulation of SIMO based DC-DC Converter for multi level Solar PV Inverter is presented in this paper. In order to reduce the number of distinct DC supplies for an H-bridge inverter SIMO DCDC converter is applied which in turn allows the usage of single PV system for a multi level H-bridge inverter. Simulation model of three level and five level inverters is built and results are presented to validate the proposed ideas.

The present study aims to quantify the flow field, flow velocity, and heat transfer features over a horizontal flat plate under the influence of an applied magnetic field, with a particular emphasis on low Prandtl number fluids. Nonlinear partial differential expressions can be incorporated into the ordinary differential framework with the use of appropriate transformations. This research utilizes the variational iteration method (VIM) to approximate solutions for the system of nonlinear differential equations that define the problem. The objective is to demonstrate superior flexibility and broader application of the VIM in addressing heat transfer issues, compared to alternative approaches. The results obtained from the VIM are compared with numerical solutions, revealing a significant level of accuracy in the approximation. The numerical findings strongly suggest that the VIM is effective in providing precise numerical solutions for nonlinear differential equations. The analysis includes an examination of the flow field, velocity, and temperature distribution across various parameters. The study found that improving temperature patterns, velocity distribution, and flow dynamics were all positively impacted by increasing the Prandtl numbers. As a result, this leads to the thickness of the boundary layer to decrease and improves heat transfer at the moving surface. Thus, the convection process becomes more efficient. When the strength of the magnetic field is increased, the velocity of the fluid decreases. This observation aligns with expectations since the magnetic field hampers the natural flow of convection. Notably, the convection process can be precisely controlled by carefully applying magnetic force. [ABSTRACT FROM AUTHOR]

In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents [...]

In conventional diesel combustion (CDC), a centrally located multi-hole injector supplies fuel radially outwards. This study introduces and explores the concept of peripheral fuel injection (PeFI) to supply fuel from multiple locations on top of the combustion chamber using several single-hole injectors. The PeFI concept is designed to eliminate flame-wall and jet-wall interactions, and, ideally, to produce independent flames without any interference. PeFI is also intended to increase air entrainment in the near field and thus, reduce equivalence ratio at the lift-off length and subsequent soot formation. PeFI reduces wall heat transfer compared to CDC although this feature is not considered in the present study. The two methods of fuel injection are compared in a non-reacting optical chamber via high-speed imaging of the jets. N-heptane fuel at 1500 bar supply pressures is injected into a test chamber filled with nitrogen at engine relevant ambient densities of 23.0 and 18.5 kg/m3. Four configurations are trialed including a six-hole central injector and six, single-hole PeFI injectors with holes oriented at a layout angle, defined as the angle between the center of the fuel jet and chamber radius, of 0°, 15°, and 30°. Flow visualizations show jet-to-jet interactions at small layout angles for PeFI, but little to no jet-to-jet (or jet-wall) interference as the layout angle increases to 30°. Image analysis reveals that PeFI provides faster rate of injection, longer jet penetration length, greater width near the jet tip, and larger jet volume compared to those for the central injector. Overall, results demonstrate the potential of PeFI to simultaneously improve fuel efficiency and reduce emissions in diesel engines. [ABSTRACT FROM AUTHOR]

Analyses of artificial intelligence (AI) adoption focus on its adoption at the individual task level. What has received significantly less attention is how AI adoption is shaped by the fact that organizations are composed of many interacting tasks. AI adoption may, therefore, require system‐wide change, which is both a constraint and an opportunity. We provide the first formal analysis where multiple tasks may be part of an interdependent system. We find that reliance on AI, a prediction tool, increases decision variation, which, in turn, raises challenges if decisions across the organization interact. Reducing inter‐dependencies between decisions softens that impact and can facilitate AI adoption. However, it does this at the expense of synergies. By contrast, when there are mechanisms for inter‐decision coordination, AI adoption is enhanced when there are more inter‐dependencies. Consequently, we show that there are important cases where AI adoption will be enhanced when it can be adopted beyond tasks but as part of a designed organizational system. [ABSTRACT FROM AUTHOR]