Enhanced Nature-Inspired Meta-Heuristic Algorithm for Microgrid Performance Improvement

Abstract

In this article, a new selection technique based on Enhanced Nature-Inspired Meta-Heuristic (ENIMH) optimization algorithm is presented to improve the Microgrid (MG) dynamic performance. Interconnected microgrids have the ability to provide a clean and sustainable energy during normal and emergency operating conditions. The concerned microgrid includes hybrid renewable energy sources (RES) and energy storages systems (ESS). MG achieves a reduced dependency on the electric grid and provides flexible and adaptive energy supply. This paper develops a new selection technique based on ENIMH optimization that distinguishes the degrees of resemblance between the best individual and other individuals of current population. This technique proposes a binary coding of individuals, and is compared to conventional techniques; it allows each individual to occupy a section of the modified roulette wheel selection for the calculated degree of resemblance. This enhanced optimization technique tunes the dynamic PID parameters of microgrid closed loop system. The designed strategy is dependably to locate the arrangement of enhanced parameters to minimize the system frequency fluctuations in the microgrid and to provide the improved dynamic performance by being sensitive to variations for closed loop response under various power and load conditions. The proposed technique has been demonstrated using Matlab/Simulink simulation on the underlined microgrid, where the achieved results confirm the effectiveness of proposed selection method for the reproduction of best individuals to show the improved performance. The proposed technique achieved satisfactory performance for PID-controllers, and provided a good closed loop performance, minimum overshoot and minimum fitness index, in comparison with other well-established methods. The results emphasize that ENIMH optimization algorithm has the exploration and exploitation capability of population best individuals to accomplish the best solutions.     

Effects of Combined Heat and Mass Transfer on Entropy Generation due to MHD Nanofluid Flow over a Rotating Frame

The current investigation aims to explore the combined effects of heat and mass transfer on free convection of Sodium alginate-Fe3O4 based Brinkmann type nanofluid flow over a vertical rotating frame. The Tiwari and Das nanofluid model is employed to examine the effects of dimensionless numbers, including Grashof, Eckert, and Schmidt numbers and governing parameters like solid volume fraction of nanoparticles, Hall current, magnetic field, viscous dissipation, and the chemical reaction on the physical quantities. The dimensionless nonlinear partial differential equations are solved using a finite difference method known as Runge-Kutta Fehlberg (RKF-45) method. The variation of dimensionless velocity, temperature, concentration, skin friction, heat, and mass transfer rate, as well as for entropy generation and Bejan number with governing parameters, are presented graphically and are provided in tabular form. The results reveal that the Nusselt number increases with an increase in the solid volume fraction of nanoparticles. Furthermore, the rate of entropy generation and Bejan number depends upon the magnetic field and the Eckert number.     

A Multifunctional Electronic Skin Empowered with Damage Mapping and Autonomic Acceleration of Self-Healing in Designated Locations

Integrating self-healing capabilities into soft electronic devices and sensors is important for increasing their reliability, longevity, and sustainability. Although some advances in self-healing soft electronics have been made, many challenges have been hindering their integration in digital electronics and their use in real-world conditions. Herein, an electronic skin (e-skin) with high sensing performance toward temperature, pressure, and pH levels—both at ambient and/or in underwater conditions is reported. The e-skin is empowered with a novel self-repair capability that consists of an intrinsic mechanism for efficient self-healing of small-scale damages as well as an extrinsic mechanism for damage mapping and on-demand self-healing of big-scale damages in designated locations. The overall design is based on a multilayered structure that integrates a neuron-like nanostructured network for self-monitoring and damage detection and an array of electrical heaters for selective self-repair. This system has significantly enhanced self-healing capabilities; for example, it can decrease the healing time of microscratches from 24 h to 30 s. The electronic platform lays down the foundation for the development of a new subcategory of self-healing devices in which electronic circuit design is used for self-monitoring, healing, and restoring proper device function.     

A performance study of uplink scheduling algorithms in point-to-multipoint WiMAX networks

The IEEE 802.16 standard defines the specifications for medium access control (MAC) and physical (PHY) layers of WiMAX networks. A critical part of the MAC layer specification is packet scheduling, which resolves contention for bandwidth and determines the transmission order of users. Evaluating the performance packet scheduling algorithms is of utmost importance towards realizing large-scale WiMAX deployment. In this paper, we conduct a comprehensive performance study of scheduling algorithms in point-to-multipoint mode of OFDM-based WiMAX networks. We first make a classification of WiMAX scheduling algorithms, then simulate a representative number of algorithms in each class taking into account that vital characteristics of the IEEE 802.16 MAC layer and OFDM physical layer. We evaluate the algorithms with respect to their abilities to support multiple classes of service, providing quality of service (QoS) guarantees, fairness amongst service classes and bandwidth utilization. To the best of our knowledge, no such comprehensive performance study has been reported in the literature. Simulation results indicate that none of the current algorithms is capable of effectively supporting all WiMAX classes of service. We demonstrate that an efficient, fair and robust scheduler for WiMAX is still an open research area. We conclude our study by making recommendations that can be used by WiMax protocol designers.     

GA, MR, FFNN, PNN and GMM based models for automatic text summarization

This work proposes an approach to address the problem of improving content selection in automatic text summarization by using some statistical tools. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First, we investigate the effect of each sentence feature on the summarization task. Then we use all features in combination to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. Moreover, we use all feature parameters to train feed forward neural network (FFNN), probabilistic neural network (PNN) and Gaussian mixture model (GMM) in order to construct a text summarizer for each model. Furthermore, we use trained models by one language to test summarization performance in the other language. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 Arabic political articles and 100 English religious articles. The results of the proposed approach are promising, especially the GMM approach.     

Organic Transistor Based on Cyclopentadithiophene‐Benzothiadiazole Donor–Acceptor Copolymer for the Detection and Discrimination between Multiple Structural Isomers

Distinguishing structural isomers is a critical and challenging task for biotechnology, chemical industry, and environmental monitoring. Approaches currently available are limited in terms of selectivity and simplicity. In this paper, a highly sensitive organic field‐effect transistor (OFET) using the cyclopentadithiophene‐benzothiadiazole (CDT‐BTZ) copolymers as a semiconductor is presented for easy and selective detection of different families of structural isomers, as well as between different isomers within each family. High accuracy discrimination is achieved over a range of concentrations using only a single sensing parameter derived from the OFET characteristic transfer curve. As a reference, other homopolymer‐ and donor–acceptor copolymer‐based OFET sensors are examined but do not have an equivalent sensing performance to that of the CDT‐BTZ‐based OFETs. Investigating the link between isomer absorption and swelling, supramolecular order and energy levels of the active layer reveals a unique effect of each isomer on the energy bands of the semiconducting polymer.     

Physicochemical studies on ZnO-Al2O3 system

Several mixed ZnO-Al₂O₃ systems were prepared by the impregnation method and calcined for 5 h at 300, 600 and 1000 ° C. The crystal structure, surface acidity, surface basicity, surface area, catalytic decomposition of H₂O₂ and the electrical conductivity of the samples prepared were studied. It was found that the decomposition of H₂O₂ is catalysed by the acidic sites formed on the catalyst surface at composition less than 50 mol% ZnO and by basic sites for oxides having composition higher than 50 mol% ZnO. ZnAl₂O₄-spinel was found to be formed at temperatures 600 ° C and it has a catalytic activity and electrical conductivity lower than each of the pure ZnO and the oxide mixtures. The results obtained were correlated together and discussed.     

New corrosion inhibitors based on fatty materials—II. Epoxidized fatty materials modified with aromatic amines

Eight compounds prepared by modification of epoxidized linseed oil and oleic acid with aniline, p-chloro-aniline, p-toluidine and p-anizidine, were tested as corrosion inhibitors. The test coupons were mild steel and the environment consisted of 0.05N HCl at 70°C or mixed vapours of gasoline and HCl. In HCl, the percentage inhibition ranged from 26.0 to 59.5% for linseed oil and from 88.0 to 94.5% for oleic acid derivatives. In the gas phase, the ranges were from 70.3 to 85.98 and from 62.5 to 74.0%, respectively. The values obtained for two commercial inhibitors tested under the same conditions were 34.5 and 91.7% in HCl and 57.0 and 64.0% in the mixed vapours. The results conformed with a simple Langmuir model and with predictions based on NMR measurements, basicity values (pK_a) and Hammett constants. A ranking of the compounds according to percentage inhibition agreed with the order of increasing electron density on the nitrogen atom in these compounds.     

Two Extended Programmable BCH Soft Decoders Using Least Reliable Bits Reprocessing

This paper proposes two Bose–Chaudhuri–Hocquenghem (BCH) soft decoders suitable for high-rate codes with medium to large word length. The proposed decoders extend the correcting capability by providing a programmable performance gain according to the choice of the extra compensated bits p, with a theoretical maximum likelihood decoding when 2t+p approaches the codeword size n, where t is the correcting capability of the code under algebraic decoding. Our proposed architectures for the proposed algorithms use pipelined arithmetic units, leading to a reduction in the critical paths. This allows for an increase in the operating frequency by up to m/2 times compared to algebraic decoders, where m is the Galois field size. Our proposed decoders operate only on the least reliable bits, which leads to a reduction in the decoder complexity by removing the Chien search procedure.     

Virtual base stations for wireless mobile ad hoc communications: an infrastructure for the infrastructure‐less

In this paper, we propose a new protocol for wireless mobile ad hoc networks, which establishes a dynamic wireless mobile infrastructure. The proposed protocol, namely, the virtual base stations (VBS) protocol, mimics and maintains the operation of the conventional fixed infrastructure in cellular networks. In the VBS protocol, a mobile node is elected from a set of nominees to act as a temporary base station within its zone. We provide proofs for the correctness of the VBS protocol, and show lower and upper bounds for its global convergence time. Likewise, we study the characteristics and performance of VBS by means of simulation. It is shown that VBS scales well to large networks of mobile stations, and that it outperforms other infrastructure‐formation protocols in terms of stability. The VBS protocol would facilitate the development of a comprehensive and promising framework for quality of service (QoS) management in wireless mobile ad hoc networks once the proper integration of the MAC protocol with the routing and call admission control mechanisms is established. The VBS architecture lays the groundwork for assigning bandwidth, and/or implementing priorities, and hence for QoS‐based routing by conveying the quality of a path prior to call setup. Copyright © 2001 John Wiley & Sons, Ltd.