Optimal Placement of Intermittent Renewable Energy Resources and Energy Storage System in Smart Power Distribution Networks

This paper presents an efficient strategy to optimally allocate renewable energy sources (RES), primarily wind and solar photovoltaic (PV), and energy storage system (ESS) in electrical distribution networks with a goal of minimizing costs and active power losses. The proposed planning strategy is used to determine the number of possible and optimal locations for the hybrid RES–ESS system. This paper further presents a control scheme to optimally dispatch the output of ESS, which increases the effective utilization of RES by reducing their day-ahead forecast errors in order to minimize the deviation between forecasted and actual values. In our proposed strategy, the location that produces the least overall power losses complying with the system constraints is considered as the optimal one. In order to evaluate the effectiveness of the proposed method, this paper considers a case study of a 16-bus test system that comprises of several loads, wind farm, PV, and ESS. The test results demonstrate that by determining the optimal bus location for the RES–ESS system, overall power losses as well as peak load can be significantly reduced.     

Design and development of a simple and highly sensitive anthocyanin-based sensing device for colorimetric urea determination

We introduce a rapid anthocyanin-based paper sensor with very high sensitivity and optical visibility for colorimetric detection of urea. The working principle is based on a colour change from purple to blue upon sensor exposure to ammonia generated from urea hydrolysis in the presence of urease as a catalyst. To improve sensor sensitivity and optical visibility, anthocyanin storage, urease solvent, urea hydrolysis time, and temperature were investigated. The results indicated that the anthocyanin extracted from red cabbage and stored in dark and low-temperature conditions, urease extracted into water₅₅ + glycerol₄₅ (Aq₅₅ + G₄₅), and urea hydrolysis time of 40 min and temperature of 45°C offer the best detection condition. The fabricated sensor showed exceptional sensitivity of 0.018 pixel/mg urea-N/L with a very low limit of detection (2.01 mg urea-N/L) and a limit of quantification (6.71 mg urea-N/L). Moreover, the sensor reaction zone is optically visible for urea concentration as low as 5 mg urea-N/L, making it a promising tool for urea screening in diverse applications. The unique analytical features and accuracy of the sensor compared to the spectrophotometry method also suggest that it can be used as a replacement for environmentally unfriendly spectrophotometry methods for on-site urea determination.     

Google Scholar University Ranking Algorithm to Evaluate the Quality of Institutional Research

Education quality has undoubtedly become an important local and international benchmark for education, and an institute’s ranking is assessed based on the quality of education, research projects, theses, and dissertations, which has always been controversial. Hence, this research paper is influenced by the institutes ranking all over the world. The data of institutes are obtained through Google Scholar (GS), as input to investigate the United Kingdom’s Research Excellence Framework (UK-REF) process. For this purpose, the current research used a Bespoke Program to evaluate the institutes’ ranking based on their source. The bespoke program requires changes to improve the results by addressing these methodological issues: Firstly, Redundant profiles, which increased their citation and rank to produce false results. Secondly, the exclusion of theses and dissertation documents to retrieve the actual publications to count for citations. Thirdly, the elimination of falsely owned articles from scholars’ profiles. To accomplish this task, the experimental design referred to collecting data from 120 UK-REF institutes and GS for the present year to enhance its correlation analysis in this new evaluation. The data extracted from GS is processed into structured data, and afterward, it is utilized to generate statistical computations of citations’ analysis that contribute to the ranking based on their citations. The research promoted the predictive approach of correlational research. Furthermore, experimental evaluation reported encouraging results in comparison to the previous modification made by the proposed taxonomy. This paper discussed the limitations of the current evaluation and suggested the potential paths to improve the research impact algorithm.     

A typology of secure multicast communication over 5 G/6 G networks

International Journal of Information Security - The growth of media services, multimedia conferencing, interactive distance learning, and distributed interactive simulations is becoming more...     

Improved voltage tracking of autonomous microgrid technology using a combined resonant controller with lead-lag compensator adopting negative imaginary theorem

Growing application of distributed generation units at remote places has led to the evolution of microgrid (MG) technology. When an MG system functions independently, i.e., in autonomous mode, unpredictable loads and uncertainties emerge throughout the system. To obtain stable and flexible operation of an autonomous MG, a rigid control mechanism is needed. In this paper, a robust high-performance controller is introduced to improve the performance of voltage tracking of an MG system and to eliminate stability problems. A combination of a resonant controller and a lead-lag compensator in a positive position feedback path is designed, one which obeys the negative imaginary (NI) theorem, for both single-phase and three-phase autonomous MG systems. The controller has excellent tracking performance. This is investigated through considering various uncertainties with different load dynamics. The feasibility and effectiveness of the controller are also determined with a comparative analysis with some well-known controllers, such as linear quadratic regulator, model predictive and NI approached resonant controllers. This confirms the superiority of the designed controller.     

Photoactive and Intrinsically Fuel Sensing Metal–Organic Framework Motors for Tailoring Collective Behaviors of Active-Passive Colloids

Microorganisms display nonequilibrium predator–prey behaviors, such as chasing–escaping and schooling via chemotactic interactions. Even though artificial systems have revealed such biomimetic behaviors, switching between them by control over chemotactic interactions is rare. Here, a spindle-like iron-based metal–organic framework (MOF) colloidal motor which self-propels in glucose and H₂O₂, triggered by UV light is reported. These motors display intrinsic UV light-triggered fuel-dependent chemotactic interactions, which are used to tailor the collective dynamics of active-passive colloidal mixtures. In particular, the mixtures of active MOF motors with passive colloids exhibit distinctive “chasing–escaping” or “schooling” behaviors, depending on glucose or hydrogen peroxide being used as the fuel. The transition in the collective behaviors is attributed to an alteration in the sign of ionic diffusiophoretic interactions, resulting from a change in the ionic clouds produced. This study offers a new strategy on tuning the communication between active and passive colloids, which holds substantial potentials for fundamental research in active matter and practical applications in cargo delivery, chemical sensing, and particle segregation.     

Multistage-batch bipolar membrane electrodialysis for base production from high-salinity wastewater

Bipolar membrane electrodialysis (BMED) is considered a state-of-the-art technology for the conversion of salts into acids and bases. However, the low concentration of base generated from a traditional BMED process may limit the viability of this technology for a large-scale application. Herein, we report an especially designed multistage-batch (two/three-stage-batch) BMED process to increase the base concentration by adjusting different volume ratios in the acid (V_acid), base (V_base), and salt compartments (V_salt). The findings indicated that performance of the two-stage-batch with a volume ratio of V_acid:V_base:V_salt = 1:1:5 was superior in comparison to the three-stage-batch with a volume ratio of V_acid:V_base:V_salt = 1:1:2. Besides, the base concentration could be further increased by exchanging the acid produced in the acid compartment with fresh water in the second stage-batch process. With the two-stage-batch BMED, the maximum concentration of the base can be obtained up to 3.40 mol∙L^–1, which was higher than the most reported base production by BMED. The low energy consumption and high current efficiency further authenticate that the designed process is reliable, cost-effective, and more productive to convert saline water into valuable industrial commodities.     

SE-MD: a single-encoder multiple-decoder deep network for point cloud reconstruction from 2D images

Pattern Analysis and Applications - 3D model reconstruction from single 2D RGB images is a challenging and actively researched computer vision task. Several techniques based on conventional network...