•Solar system for a heterogeneous cellular networks (HCNs) is proposed.•Optimum size and technical criteria of the solar-powered HCNs is investigated.•Performance and reliability of the solar system ...under fault conditions.•Economic feasibility of the solar system compare with a traditional power sources.
The present study aims to address the sustainability of power resources and environmental conditions for heterogeneous cellular networks. To this end, this study examined an autonomous solar power system to supply heterogeneous cellular networks with their required energy sources. Optimal criteria, system architecture, energy production, and cost analysis are discussed based on the characteristics of solar radiation exposure in South Korea. However, the analysis can be generalized to other cases with a slight difference in daily peak solar hours per case. Additionally, this study compares the feasibility of using an autonomous solar power system to feed heterogeneous cellular networks versus a conventional energy source—i.e., the public electric grid. This study shows that the deployment of the solar power system can satisfactorily meet the energy needs of the base stations (BSs) in heterogeneous cellular networks cost effectively, efficiently, sustainably, and reliably and can improve planning by providing cleaner energy.
Whilst a net zero energy (NZE) home produces the same amount of energy as it consumes it still exchanges significant amount of energy with the grid due to mismatch between the generation and load ...patterns. Consequently, the homeowner has to pay an annual electric bill because the cost of imported energy is usually higher than that of exported energy. Installing a local battery energy storage system (BESS) can reduce the electric bill by exchanging less energy with the grid. This paper proposes a method of determining the optimal size of a BESS for a typical NZE home with rooftop solar photovoltaic (PV) system to minimize the annual net payment for electricity and battery cost. The optimal battery size is determined through solving an optimization problem which is formulated using hourly load and PV generation data for a South Australian home, battery annual payment rate, retail price (RP), and feed-in tariff (FIT). The effects of interest rate, RP and FIT on the annual net payment are investigated. The results obtained are thoroughly analysed and clearly indicate that, with current installation cost of BESS and South Australian RP and FIT, the use of a local BESS is economically beneficial for the homeowner.
•Proposed a method to optimize battery size for PV-connected net zero energy home.•It minimizes home owner's annual net payment for electricity usage and battery cost.•The method has been applied to a typical South Australian (SA) NZE home.•It shows that optimally sized battery storage is economically beneficial.•The method is applicable for NZE homes in any part of the world.
This paper exhibits a novel application of the coyote optimization algorithm (COA) in order to extract the nine unknown parameters of the three-diode photovoltaic (PV) model of PV modules. The main ...target of this study is to obtain a very highly precise PV model, which can be efficiently applied to represent the PV system in the simulation of dynamic power systems. The optimization problem is formulated to take into consideration the root mean squared current error between the calculated model current and the experimental current of the PV module. The COA is applied to minimize this fitness function. In this study, the COA-PV model is validated by the numerical results which are performed at different environmental conditions such as temperature and irradiation variation conditions. Moreover, its effectiveness is executed by making a comparison between its numerical and experimental results for some commercial PV modules in the market like the KC200GT and MSX-60 modules. With the adoption of the COA, a highly precise three-diode PV model can be established. This represents a novel contribution to the field of PV systems and its modeling.
•This paper presents a novel application of the COA to extract PV model parameters.•Three-diode PV (TDPV) model is used in this paper.•Parameters of COA-TDPV model are compared with other optimization based models.•COA-TDPV model is verified by comparing its results with the experimental results.•Two commercial PV modules are used in the paper (KC200GT and MSX-60).
The electromagnetic interference (EMI) shielding mechanisms of multi-walled carbon nanotube (MWCNT)/polymer composites were analyzed experimentally and theoretically. For the experimental analysis, ...EMI shielding effectiveness (SE) of MWCNT/polypropylene (PP) composite plates made in three different thicknesses and at four different concentrations were studied. A model based on the shielding of electromagnetic plane wave was used to theoretically study the EMI shielding mechanisms. The experimental results showed that absorption is the major shielding mechanism and reflection is the secondary shielding mechanism. The modeling results demonstrated that multiple-reflection within MWCNT internal surfaces and between MWCNT external surfaces decrease the overall EMI SE. The EMI SE of MWCNT/PP composites increased with increase in MWCNT content and shielding plate thickness.
The internet of things (IoT) has a significant economic and environmental impact owing to the billions or trillions of interconnected devices that use various types of sensors to communicate through ...the internet. It is well recognized that each sensor requires a small amount of energy to function; but, with billions of sensors, energy consumption can be significant. Therefore, it is crucial to focus on developing energy-efficient IoT technology and sustainable solutions. The contribution of this article is to support the implementation of eco-friendly IoT solutions by presenting a thorough examination of energy-efficient practices and strategies for IoT to assist in the advancement of sustainable and energy-efficient IoT technologies in the future. Four framework principles for achieving this are discussed, including (i) energy-efficient machine-to-machine (M2M) communications, (ii) energy-efficient and eco-sustainable wireless sensor networks (WSN), (iii) energy-efficient radio-frequency identification (RFID), and (iv) energy-efficient microcontroller units and integrated circuits (IC). This review aims to contribute to the next-generation implementation of eco-sustainable and energy-efficient IoT technologies.
The exponential increase in mobile data traffic is considered to be a critical driver towards the new era, or 5G, of mobile wireless networks. 5G will require a paradigm shift that includes very high ...carrier frequency spectra with massive bandwidths, extreme base station densities, and unprecedented numbers of antennas to support the enormous increase in the volume of traffic. This paper discusses several design choices, features, and technical challenges that illustrate potential research topics and challenges for the future generation of mobile networks. This article does not provide a final solution but highlights the most promising lines of research from the recent literature in common directions for the 5G project. The potential physical layer technologies that are considered for future wireless communications include spatial multiplexing using massive multi-user multiple-input multiple-output (MIMO) techniques with millimetre-waves (mm-waves) in small cell geometries. These technologies are discussed in detail along with the areas for future research.
Recently, unmanned aerial vehicles (UAVs), also known as drones, have come in a great diversity of several applications such as military, construction, image and video mapping, medical, search and ...rescue, parcel delivery, hidden area exploration, oil rigs and power line monitoring, precision farming, wireless communication and aerial surveillance. The drone industry has been getting significant attention as a model of manufacturing, service and delivery convergence, introducing synergy with the coexistence of different emerging domains. UAVs offer implicit peculiarities such as increased airborne time and payload capabilities, swift mobility, and access to remote and disaster areas. Despite these potential features, including extensive variety of usage, high maneuverability, and cost-efficiency, drones are still limited in terms of battery endurance, flight autonomy and constrained flight time to perform persistent missions. Other critical concerns are battery endurance and the weight of drones, which must be kept low. Intuitively it is not suggested to load them with heavy batteries. This study highlights the importance of drones, goals and functionality problems. In this review, a comprehensive study on UAVs, swarms, types, classification, charging, and standardization is presented. In particular, UAV applications, challenges, and security issues are explored in the light of recent research studies and development. Finally, this review identifies the research gap and presents future research directions regarding UAVs.
•PP/PE blends filled with GNP:CNT hybrid nanofiller were prepared by melt mixing.•The CNT and GNP showed thermodynamic affinity towards the PE phase.•The 1D CNT is more effective than the 2D GNP in ...building conductive networks.•The nanofiller geometry should be considered in designing hybrid nanocomposites.•Tensile strength was found to increase with the decrease in GNP:CNT volume fraction.
Polypropylene (PP)/polyethylene (PE) blends filled with 5 vol% graphene nanoplatelets: carbon nanotube (GNP:CNT) hybrid nanofiller were prepared by melt mixing. The blends’ microstructure and the influence of GNP:CNT volume ratio on the electrical, electromagnetic interference (EMI) shielding and tensile strength were investigated. The scanning electron microscopy analysis showed that the CNT and GNP are localized in the PE phase. The electrical conductivity and EMI shielding were found to increase with the increase in CNT volume fraction due to the 1D geometry of the CNT that is more effective than the 2D geometry of the GNP in building conductive networks. This finding indicates that not only the nanofiller conductivity but also the nanofiller geometry should be considered in designing hybrid nanocomposite materials. Moreover, the tensile strength was found to increase with the decrease in GNP:CNT volume ratio due to the good adhesion between the CNT particles and the PE phase compared to the almost no adhesion between the GNP particles and the PE phase.
Cell death with morphological and molecular features of apoptosis has been detected in osteoarthritic (OA) cartilage, which suggests a key role for chondrocyte death/survival in the pathogenesis of ...OA. Identification of biomarkers of chondrocyte apoptosis may facilitate the development of novel therapies that may eliminate the cause or, at least, slow down the degenerative processes in OA. The aim of this review was to explore the molecular markers and signals that induce chondrocyte apoptosis in OA. A literature search was conducted in PubMed, Scopus, Web of Science and Google Scholar using the keywords chondrocyte death, apoptosis, osteoarthritis, autophagy and biomarker. Several molecules considered to be markers of chondrocyte apoptosis will be discussed in this brief review. Molecular markers and signalling pathways associated with chondroycte apoptosis may turn out to be therapeutic targets in OA and approaches aimed at neutralizing apoptosis-inducing molecules may at least delay the progression of cartilage degeneration in OA.
In many real-world problems, the datasets are imbalanced when the samples of majority classes are much greater than the samples of minority classes. In general, machine learning and data mining ...classification algorithms perform poorly on imbalanced datasets. In recent years, various oversampling techniques have been developed in the literature to solve the class imbalance problem. Unfortunately, few of the oversampling techniques can be spread to tackle the relationship between the classes and use the correlation between attributes. Moreover, in most cases, the existing oversampling techniques do not handle multi-class imbalanced datasets. To this end, in this paper, a simple but effective outlier detection-based oversampling technique (ODBOT) is proposed to handle the multi-class imbalance problem. In the proposed ODBOT, the outlier samples are detected by clustering within the minority class(es), and then, the synthetic samples are generated by consideration of these outlier samples. The proposed ODBOT generates very efficient and consistent synthetic samples for the minority class(es) by analyzing well the dissimilarity relationships among attribute values of all classes. Moreover, ODBOT can reduce the risk of the overlapping problem among different class regions and can build a better classification model. The performance of the proposed ODBOT is evaluated with extensive experiments using commonly used 60 imbalanced datasets and five classification algorithms. The experimental results show that the proposed ODBOT oversampling technique consistently outperformed the other common and state-of-the-art techniques in terms of various evaluation criteria.
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