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Editorial Complex Optimization and Simulation in Power Systems

With the extensive growth in technology, healthcare sector has benefitted a lot recently. Looking into the academic research and validation in the area of medical image processing and visualization, many platforms and the open-source resources are available. Insight toolkit (ITK) and visualization toolkit (VTK) are extensively used for medical image processing and 3D visualization respectively. Resources used to develop an application using ITK-VTK and same resources be used to deliver it to the users such as, clinicians, doctors etc. This can be achieved by using respective hardware and the infrastructure. In the proposed article, the infrastructure and resource used to build and deploy the application and remote access given to the users are elucidated.

Second-generation bioethanol can be produced from various lignocellulosic biomasses such as wood, agricultural or forest residues. Lignocellulosic biomass is inexpensive, renewable and abundant source for bioethanol production. The conversion of lignocellulosic biomass to bioethanol could be a promising technology though the process has several challenges and limitations such as biomass transport and handling, and efficient pretreatment methods for total delignification of lignocellulosics. Proper pretreatment methods can increase concentrations of fermentable sugars after enzymatic saccharification, thereby improving the efficiency of the whole process. Conversion of glucose as well as xylose to bioethanol needs some new fermentation technologies to make the whole process inexpensive. The main goal of pretreatment is to increase the digestibility of maximum available sugars. Each pretreatment process has a specific effect on the cellulose, hemicellulose and lignin fraction; thus, different pretreatment methods and conditions should be chosen according to the process configuration selected for the subsequent hydrolysis and fermentation steps. The cost of ethanol production from lignocellulosic biomass in current technologies is relatively high. Additionally, low yield still remains as one of the main challenges. This paper reviews the various technologies for maximum conversion of cellulose and hemicelluloses fraction to ethanol, and it point outs several key properties that should be targeted for low cost and maximum yield.

The study explores the enhancement of wind-solar hybrid microgrids via the use of Swarm Intelligence Algorithms (SIAs). It assesses the efficacy of these algorithms in efficiently managing renewable energy sources, load demands, and battery storage inside the microgrid system. An examination of actual data highlights the influence of environmental elements on the production of electricity, as seen by the diverse wind speeds resulting in power outputs that range from 15 kW at 4 m/s to 30 kW at 7 m/s. This underscores the clear and direct relationship between wind speed and the amount of power created. Likewise, solar irradiance levels demonstrate oscillations ranging from 500 W/m² to 800 W/m², therefore yielding power outputs that include a range of 15 kW to 24 kW, so illuminating the profound impact of solar irradiance on energy capture. The dynamic energy consumption patterns are exposed by the varying load demands, whereby the demand levels oscillate between 20 kW and 28 kW. This highlights the crucial significance of demand variability in determining energy needs. In addition, the data on battery storage reveals a range of charge levels, ranging from 25 kWh to 40 kWh, which underscores its pivotal function in the equilibrium of energy supply and consumption. When evaluating SIAs, it becomes evident that Particle Swarm Optimization (PSO) surpasses both Ant Colony Optimization (ACO) and Genetic Algorithms (GA) in obtaining an impressive 80% renewable energy penetration rate. PSO effectively reduces operating costs by 15%, demonstrating its exceptional proficiency in optimizing microgrid operations. This study provides valuable insights into the intricate interplay among environmental conditions, load demands, battery storage, and algorithmic optimization in wind-solar hybrid microgrids.

<abstract> <p>The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.</p> </abstract>

Laboratory corrosion and scaling testing of metallic materials exposed in high temperature and pressure environments generally involves complex, multi-instrument measurement setups. Here, we present a setup including an autoclave that is instrumented for in-situ electrochemical testing and that contains a ZrO2-based solid-state pH electrode and devices for temperature control and solution stirring. We show results highlighting the importance of adequate pre-calibration of the pH measurement, due to the hysteresis depending on temperature sweep. Additionally, we illustrate how interfacing the autoclave and the electrochemical cell to measuring and controlling instruments, using different data communication interfaces, can create ground loops. These ground loop interferences can introduce significant errors in the measurement, such as a potential shift of >100 mV. In complex, multi-instrument setups, a complete understanding of ground loops may often be difficult. Thus, we recommend systematic checks to identify the ground loops and we propose measures to avoid them. Measurement, 155 ISSN:0263-2241 ISSN:1873-412X

UV/visible light is a promising radiation source for biomass pretreatment, but very little knowledge is available on the effect of UV on the thermal behavior of lignocellulose in comparison with more classical, physical pretreatment methods. In this paper, we investigate the effects of ball-milling and UV irradiation on two species of softwood and two species of hardwood, using X-ray diffractometry (XRD), evolved gas analysis-mass spectrometry (EGA-MS), and pyrolysis-gas chromatography coupled to mass spectrometry (Py-GC/MS). The XRD data showed that the crystalline fraction of cellulose was destroyed by milling, but not by irradiation. The EGA-MS data and isoconversional kinetic analysis showed that both milling and irradiation can reduce the thermal stability of wood up to a limit value. The Py-GC/MS data showed that irradiation caused the most significant changes in the pyrolytic behavior of the wood species, increasing the ratio of holocellulose to lignin pyrolysis products and the reactivity of cellulose toward the derivatizing agent. Softwoods were more affected by irradiation than hardwoods. This paper shows that UV irradiation can decrease the recalcitrance of biomass toward pyrolysis, but its efficiency is highly dependent on the type of lignocellulosic substrate.

Research on corona discharge, shared by physics, chemistry and electrical engineering, has not arrested yet. As a dissipative process, the development of corona increases the resistive losses of transmission lines and enhances the line capacitance locally. Introducing additional losses and propagation delay, along the line, non-linearity and non-uniformity of the line parameters; therefore, corona should not be neglected. The present work is meant to provide the reader with comprehensive information on the corona macroscopic phenomenology and development, referring to the most relevant contributions in the literature on this subject. The models proposed in the literature for the simulation of the corona development are reviewed in detail, and sensitivity curves are provided to highlight their dependence on the input parameters.