Limitations,challenges, and solution approaches in grid-connected renewable energy systems

In the modern world, only conventional energy resources cannot fulfil the growing energy demand. Electricity is a fundamental building block of a technological revolution. Today, most of the electricity demand is met by the burning of fossil fuels but at the cost of adverse environmental impact. In order to bridge the gap between electricity demand and supply, nonconventional and eco-friendly means of energy generation are considered. Renewable energy systems (RESs) offer an adequate solution to mitigate the challenges originated due to greenhouse gasses (GHG). However, they have an unpredictable power generation with specific site requirements. Grid integration of RESs may lead to new challenges related to power quality, reliability, power system stability, harmonics, subsynchronous oscillations (SSOs), power quality, and reactive power compensation. The integration with energy storage systems (ESSs) can reduce these complexities that arise due to the intermittent nature of RESs. In this paper, a comprehensive review of renewable energy sources has been presented. Application of ESSs in RESs and their development phase has been discussed. Role of ESSs in increasing lifetime, efficiency, and energy density of power system having RESs has been reviewed. Moreover, different techniques to solve the critical issues like low efficiency, harmonics, and inertia reduction in photovoltaic (PV) systems have been presented. Unlike most of the available review papers, this article also investigates the impact of FACTS technology in RESs-based power system using multitype flexible AC transmission system (FACTS) controllers. Three simulation models have been developed in MATLAB/Simulink. The results show that FACTS devices help to maintain the stability of RESs integrated power system. This review paper is believed to be of potential benefit for researchers from both the industry and academia to develop better understanding of challenges and solution techniques for REs-based power systems and future research dimensions in this area.     

Flow‐based electromagnetic‐type energy harvester using microplanar coil for IoT sensors application

Battery is the sole power source for Internet of thing (IoT) sensors. Due to limited shelf life, the batteries are required to be replaced intermittently. This periodic replacement of batteries is inflated in terms of both logistics and time. This article illustrates conceptual design, development, and characterization of a flow‐based electromagnetic‐type energy harvester (F‐EH) using microplanar coil for IoT sensors application. The F‐EH converts hydro energy into useful electrical energy utilizing electromagnetic transduction mechanism. The microfabrication and macrofabrication techniques adopted to manufacture harvester's components are presented. The F‐EH has been successfully characterized by laboratory scale experimental flow test loop commissioned for this work. Experimentation with associated uncertainty analysis prevails that at a matching impedance, the F‐EH can generate a 686 μW of maximum power at an operating flow rate of 12 L/min with an uncertainty of 8.1%.     

Characterisation of phenolic components present in raw and roasted wattle (Acacia victoriae Bentham) seeds

The effect of roasting on the phenolic components of Australian wattle (Acacia victoriae Bentham) seed was investigated. Wattle seeds were roasted at 200 °C for 5–30 min and ground to flour, which were then extracted with 70% acetone. The total phenolic and flavonoid contents of the extracts were determined, and the phenolic components were analysed by reverse phase-high performance liquid chromatography (RP-HPLC) coupled with an on-line post-column reaction system to determine the active antioxidant peaks. The major peaks were then purified by preparative HPLC and identified by gas chromatography–mass spectrometry (GC–MS) analysis. Roasting of wattle seeds resulted in significant increases in its soluble phenolic content. The concentration of total phenolics and flavonoids in the seeds roasted for 30 min was more than nine and four times higher, respectively, than that in the raw seeds. The major phenolic acids present in wattle seeds were found to be succinic and gallic acids, the concentration of which increased by up to 10-fold as a result of roasting.     

Increasing the toughness of nylon 12 by the incorporation of functionalized graphene

The effect of functionalized graphene (FG) on the mechanical properties, especially toughness, of nylon12 was investigated. The results revealed that the incorporation of a very small amount (about 0.6 wt%) of the FG caused a significant improvement in ultimate tensile strength, elongation, impact strength and toughness. With 0.6 wt% FG ultimate tensile strength and elongation at break of the nylon 12 are improved by ∼35% and ∼200%, respectively. The K_Ic of the nylon 12 is ∼1.28 MPa m^0.5 and the incorporation of 0.6 wt% FG causes a significant increase of 72% (∼2.2 MPa m^0.5). 0.6 wt% FG also causes a significant improvement of 175% in impact failure energy of the nylon 12. The incorporation of FG resulted in an increase in amount of γ-phase of nylon12 which could be the direct reason for the increase of toughness.     

Indoor radon levels and lung cancer risk estimates in seven cities of the Bahawalpur Division, Pakistan

Indoor radon concentration levels were measured in seven major cities of the Bahawalpur Division, Pakistan. These included Fort Abbas, Minchin Abad, Hasilpur, Bahawalpur, Liaqatpur, Rahimyar Khan and Sadiq Abad. In order to select houses for this survey, the inhabitants were approached through their school-registered children. Due to several constraints, only those 100 houses were chosen in each city that were relatively the best representatives of the built-up area. The selected houses were then divided into live categories according to the house locations and building characteristics. CR-39 detectors, placed in polyethylene bags. were installed at head height in bedrooms and sitting rooms of all the selected houses and were exposed to radon and its daughter products for 90 days. Four such measurements were performed over a year in order to average out the seasonal variation in radon levels. After exposure, all the detectors were etched and counted under an optical microscope. The track densities of four measurements were averaged out and related to radon concentration levels. The radon levels were found to be 20, 20, 26, 28, 34, 42, 47 Bq m(-3) in the bedrooms and 24, 26, 27, 26, 37, 40, 43 Bq m(-3) in sitting rooms of Hasilpur, Rahimyar Khan, Minchin Abad, Fort Abbas, Sadiq Abad, Bahawalpur and Liaqatpur respectively. The observed variation in the radon level may be attributed to the geological variation in the area. Based on the observed data, excess lung cancer risk was assessed using the risk factors recommended by the USEPA, UNSCEAR and the ICRP. According to the EPA model, the lifetime excess lung cancer risk due to the lifetime exposure is found to vary from 12-102 per million per year in the houses surveyed. This variation is from 16-114 and 26-62 per million per year if UNSCEAR and ICRP limits are applied respectively.     

Biosynthesized Gold Nanoclusters and Iron Complexes as Scaffolds for Multimodal Cancer Bioimaging

Cancer treatment has a far greater chance of success if the neoplasm is diagnosed before the onset of metastasis to vital organs. Hence, cancer early diagnosis is extremely important and remains a major challenge in modern therapeutics. In this contribution, facile and new method for rapid multimodal tumor bioimaging is reported by using biosynthesized iron complexes and gold nanoclusters via simple introduction of AuCl₄ ^? and Fe²⁺ ions. The observations demonstrate that the biosynthesized Au nanoclusters may act as fluorescent and computed tomography probes for cancer bioimaging while the iron complexes behave as effective contrast agent for magnetic resonance imaging. The biosynthesized iron complexes and gold nanoclusters are found biocompatible in vitro (MTT (3‐(4, 5‐dimethylthiazol‐2‐yl)‐2, 5‐diphenyltetrazolium bromide) assay) and in vivo for all the vital organs of circulatory and excretory system. These observations raise the possibility that the biosynthesized probes may find applications in future clinical diagnosis for deep seated early neoplasms by multimodal imaging.     

A survey on resource allocation in high performance distributed computing systems

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.     

Evolving Recurrent Neural Network using Cartesian Genetic Programming to Predict The Trend in Foreign Currency Exchange Rates

Forecasting the foreign exchange rate is an uphill task. Numerous methods have been used over the years to develop an efficient and reliable network for forecasting the foreign exchange rate. This study utilizes recurrent neural networks (RNNs) for forecasting the foreign currency exchange rates. Cartesian genetic programming (CGP) is used for evolving the artificial neural network (ANN) to produce the prediction model. RNNs that are evolved through CGP have shown great promise in time series forecasting. The proposed approach utilizes the trends present in the historical data for its training purpose. Thirteen different currencies along with the trade-weighted index (TWI) and special drawing rights (SDR) is used for the performance analysis of recurrent Cartesian genetic programming-based artificial neural networks (RCGPANN) in comparison with various other prediction models proposed to date. The experimental results show that RCGPANN is not only capable of obtaining an accurate but also a computationally efficient prediction model for the foreign currency exchange rates. The results demonstrated a prediction accuracy of 98.872 percent (using 6 neurons only) for a single-day prediction in advance and, on average, 92% for predicting a 1000 days’ exchange rate in advance based on ten days of data history. The results prove RCGPANN to be the ultimate choice for any time series data prediction, and its capabilities can be explored in a range of other fields.