Search results for: smart power

Authors: Julian David Rios Acuna

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This paper seeks to argue that the phenomenon of ‘paramilitarism’ in Colombia exhibits the role of violence as constitutive of the political process of state formation in the country. In order to do this, it takes as its point of departure a landmark moment in the long history of private armies known as the ‘paramilitary’ in Colombia. In 2001, paramilitary commanders, politicians, and members of the military and other branches of state power singed what is known as the ‘Pact of Ralito.’ In this pact, the paramilitary appropriated constitutional and legal language. The paper argues that this appropriation shows that the paramilitary and the state express the same claim to sovereign power and therefore have the same foundation. More precisely, paramilitary power shows itself to base its power on the same foundation as the legal order, namely, extreme forms of violence where death is generative of power. In this sense, the paper shows how, by sharing its foundation, Colombian paramilitarism exhibits that state power in Colombia can be characterized as necro-power as Achille Mbembe understands it. The paper argues that paramilitarism shows state power as necro-power by constituting itself as a symptom understood, following Zizek, as that which both shows and overthrows its own foundation. In this way, paramilitarism shows the foundation of the state, thereby reconfiguring this very state. This reconfiguration, explicitly based on necro-power, the paper concludes, transforms the state into a form more appropriate to the political demands of neo-liberalism. By exhibiting its foundation in necro-power through paramilitarism, the Colombian State turns from a liberal into a (neo)liberal democracy.

Keywords: necro-power, necropolitics, paramilitarism in Colombia, state formation, state power, sovereign power

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Karandeep Kaur

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This paper presents the design of power amplifier (PA) for mmWave communication systems. The designed amplifier uses GlobalFoundries 22 FDX technology and works at an operational frequency of 140 GHz in the D-Band. With a supply voltage of 0.8V for the super low threshold voltage transistors, the amplifier is biased in class AB and has a total current consumption of 50 mA. The measured saturated output power from the power amplifier is 5.6 dBm with an output-referred 1dB-compression point of 1.6dBm. The measured gain of PA is 19 dB with 3 dB-bandwidth ranging from 120 GHz to 140 GHz. The chip occupies an area of 795µm × 410µm.

Keywords: mmWave communication system, power amplifiers, 22FDX, D-Band, cross-coupled capacitive neutralization

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Authors: Sabir Messalti, Bilal Boudjellal, Azouz Said

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In this paper, power system Voltage improvement using wind turbine is presented. Two controllers are used: a PI controller and Artificial Neural Networks (ANN) controllers are studied to control of the power flow exchanged between the wind turbine and the power system in order to improve the bus voltage. The wind turbine is based on a doubly-fed induction generator (DFIG) controlled by field-oriented control. Indirect control is used to control of the reactive power flow exchanged between the DFIG and the power system. The proposed controllers are tested on power system for large voltage disturbances.

Keywords: artificial neural networks controller, DFIG, field-oriented control, PI controller, power system voltage improvement

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Authors: Julia Langen

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This article describes the challenges of a wireless charging system for a cab waiting lane in a public space and presents a concept for solving them. In this concept, multiple cabs can be charged simultaneously and during stopping and rolling. Particular technical challenges are a coil topology that meets the EMF requirements and an intelligent control concept that allows the individual coil segments to be switched on and off. The charging concept explained here is currently being implemented as a pilot project, so that initial results on the operation can be presented.

Keywords: charge lane, inductive charging solution, smart city, wireless power transfer

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Authors: Dib Djalel, Mordjaoui Mourad

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The current trend towards the exploitation of various renewable energy resources has become indispensable, so it is important to improve the efficiency and reliability of the GPV photovoltaic systems. Maximum Power Point Tracking (MPPT) plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions. This paper presents a new fuzzy logic control based MPPT algorithm for solar panel. The solar panel is modeled and analyzed in Matlab/Simulink. The Solar panel can produce maximum power at a particular operating point called Maximum Power Point(MPP). To produce maximum power and to get maximum efficiency, the entire photovoltaic panel must operate at this particular point. Maximum power point of PV panel keeps on changing with changing environmental conditions such as solar irradiance and cell temperature. Thus, to extract maximum available power from a PV module, MPPT algorithms are implemented and Perturb and Observe (P&O) MPPT and fuzzy logic control FLC, MPPT are developed and compared. Simulation results show the effectiveness of the fuzzy control technique to produce a more stable power.

Keywords: MPPT, photovoltaic panel, fuzzy logic control, modeling, solar power

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Serdal Akyüz, Halit Turan, Mehmet Öztürk

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The future security environment will have new battlefield and enemies. The boundaries of battlefield and the identity of enemies cannot be noticed easily. The politicians may not want to lose their soldiers in very risky operations. This approach will pave the way for smart machines like war robots and new drones. These machines will have the decision-making ability and act simultaneously. This ability can change the military targeting process. Military targeting process (MTP) benefits from a wide scope of lethal and non-lethal weapons to reach an intended end-state. This process is now managed by people but in the future smart machines can do it by themselves. At first sight, this development seems useful for humanity owing to decrease the casualties in war. Using robots -which can decide, detect, deliver and asses without human support- for homeland security and against terrorist has very crucial risks and threats. Besides, it can decrease the havoc but also increase the collateral damages. This paper examines the current use of smart war machines, military targeting process and presents a new approach to MTP from lethal autonomy concept's point of view.

Keywords: the autonomous weapon systems, the lethal autonomy, military targeting process (MTP)

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Authors: Wegene Demisie Jima

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Leather is a durable and flexible material used for various purposes including clothing, footwear, upholstery and gloves. However, the use of leather for smart product applications is a challenge since it is electrically insulating material. Here, we report a simple method to produce conducting glove leathers using an in-situ polymerization of pyrrole. The concentrations of pyrrole, ferric chloride and anthraquinone-2-sulfonic acid sodium salt monohydrate were optimized to produce maximum conductivity in the treated leathers. The coating of polypyrrole in the treated leathers was probed using FT-IR, X-ray diffraction and electron microscopic analysis. FTIR confirms that the formation of polypyrrole on the leather surface as well as presence of prominent N-C stretching band. X-ray diffraction analysis suggests para-crystallinity in the PPy-treated leathers.We further demonstrate that the treated leathers, with maximum conductivity of 7.4 S/cm, can be used for making conductive gloves for operating touch-screen devices apart from other smart product applications.

Keywords: electrical conductivity, in-situ polymerization, pyrrole, smart product

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Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad

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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.

Keywords: unified theory of acceptance and use of technology (UTAUT) model, UTAUT2 model, smart national identity card (SNIC), health information application, privacy calculus model (PCM)

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Abdullah M. Alodhaiani, Yasir A. Alturki, Mohamed A. Elkady

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Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF’s) or power transfer distribution factors (PTDF’s), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF’s), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method.

Keywords: distribution factors, power system, sensitivity factors, electricity market

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analysed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power

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Authors: G. Levacic, A. Zupan

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Application of new technological solutions and installation of new elements into the network requires special attention when investigating its interaction with the existing power system. Special attention needs to be devoted to the occurrence of harmonic resonance. Sources of increasing harmonic penetration could be wind power plants, Flexible Alternating Current Transmission System (FACTS) devices, underground and submarine cable installations etc. Calculation in frequency domain with various software, for example, the software for power systems transients EMTP-RV presents one of the most common ways to obtain the harmonic impedance of the system. Along calculations in frequency domain, such software allows performing of different type of calculations as well as steady-state domain. This paper describes a power system modeling with software EMTP-RV based on data from SCADA/EMS system. The power flow results on 220 kV and 400 kV voltage levels retrieved from EMTP-RV are verified by comparing with power flow results from power transmissions system planning software PSS/E. The determination of the harmonic impedance for the case of remote power plant connection with cable up to 2500 Hz is presented as an example of calculations in frequency domain.

Keywords: power system modeling, frequency domain, steady state, EMTP-RV, PSS/E

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Authors: Wei Hu, Wenguang Chen, Chong Dong

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In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.

Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management

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Authors: A. B. Arani, R. Shojaee

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Electrical power distribution system is one of the vital infrastructures of an oil refinery, which requires wide area of study and planning before construction. In this paper, power distribution reliability of Tehran Refinery’s KHDS/GHDS unit has been taken into consideration to investigate the importance of these kinds of studies and evaluate the designed system. In this regard, the authors chose and evaluated different configurations of electrical power distribution along with the existing configuration with the aim of finding the most suited configuration which satisfies the conditions of minimum cost of electrical system construction, minimum cost imposed by loss of load, and maximum power system reliability.

Keywords: power distribution system, oil refinery, reliability, investment cost, interruption cost

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Authors: Safwan Mawlood Hussien

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Internet of Things (IoT) is a promising technology has received considerable attention in different fields such as health, industry, defence, and agro, etc. Due to the limitation capacity of computing, storage, and communication, IoT objects are more vulnerable to attacks. Many solutions have been proposed to solve security issues, such as key management using symmetric-key ciphers. This study provides a scalable group distribution key management based on ECcryptography; with less transmitted messages The method has been validated through simulations in OMNeT++.

Keywords: elliptic curves, Diffie–Hellman, discrete logarithm problem, secure key exchange, WSN security, IoT security, smart-agro

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Authors: Dae-Hee Son, Soon-Ryul Nam

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The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.

Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)

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Authors: Yehya Abdellatif, Ahmed Alsalaymeh, Iyad Muslih, Ali Alshduifat

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Photovoltaic (PV) power generation systems, mainly small scale, are rapidly being deployed in Jordan. The impact of these systems on the grid has not been studied or analyzed. These systems can cause many technical problems such as reverse power flows and voltage rises in distribution feeders, and real and reactive power transients that affect the operation of the transmission system. To fully understand and address these problems, extensive research, simulation, and case studies are required. To this end, this paper studies the cloud shadow effect on the power generation of a ground mounted PV system installed at the test field of the Renewable Energy Center at the Applied Science University.

Keywords: photovoltaic, cloud effect, MPPT, power transients

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Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Hsieh-Hua Liu

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By introduction of Relay Nodes (RNs), LTE-Advanced can provide enhanced coverage and capacity at cell edges and hot-spot areas. The authors have been researching the issue of power saving in mobile communications technology such as WiMax and LTE for some years. Based on the idea of Load-Based Power Saving (LBPS), three efficient power saving schemes for the user equipment (UE) were proposed in the authors’ previous work. In this paper, three revised schemes of the previous work in order to integrate RN and UE in power saving are proposed. Simulation study shows the proposed schemes can achieve significantly better power saving efficiency than the standard based scheme at the cost of moderately increased delay.

Keywords: DRX, LTE-A, power saving, RN

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Razika Ihaddadene, Nabila Ihaddadene

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This paper aims to highlight the importance of the application of the IEC 61724 standard in the study of the performance analysis of photovoltaic power plants on a monthly and annual scale. Likewise, the comparison of two photovoltaic power plants with two different climates was carried out in order to determine the effect of climatic parameters on the analysis of photovoltaic performances. All data from the Ain Skhouna and Adrar photovoltaic power plants for 2018 and the data from the Saida1 field for one month in 2019 were used. The results of the performance analysis according to the indicated standard show that the Saida PV power plant performs better than the Adrar PV power plant, which is due to the effect of increasing the ambient temperature. Increasing ambient temperature increases losses decreases system efficiency and performance ratio. It presents a key element in the proper functioning of PV plants.

Keywords: pv power plants, IEC 61724 norm, grid connected pv, algeria

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Authors: S. Sudhharani

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Energy distribution networks are the main link between the energy industry and consumers and are subject to the most scrutiny and testing of any category. As a result, it is important to monitor energy levels during the distribution phase. Power distribution networks, on the other hand, remain subject to common problems, including voltage breakdown, power outages, harmonics, and capacitor switching, all of which disrupt sinusoidal waveforms and reduce the quality and power of the network. Using power appliances in the form of custom power appliances is one way to deal with energy quality issues. Dynamic Voltage Restorer (DVR), integrated with network and distribution networks, is one of these devices. At the same time, by injecting voltage into the system, it can adjust the voltage amplitude and phase in the network. In the form of injections and three-phase syncing, it is used to compensate for the difficulty of energy quality. This article examines the recent use of DVR for power compensation and provides data on the control of each DVR in distribution networks.

Keywords: dynamic voltage restorer (DVR), power quality, distribution networks, control systems(PWM)

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Authors: Guiheng Zhang, Wei Zhang, Jun Fu, Yudong Wang

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A 900 MHz three-stage SiGe power amplifier (PA) with high power gain is presented in this paper. Volterra Series is applied to analyze nonlinearity sources of SiGe HBT device model clearly. Meanwhile, the influence of operating current to IMD3 is discussed. Then a β-helper current mirror bias circuit is applied to improve linearity, since the β-helper current mirror bias circuit can offer stable base biasing voltage. Meanwhile, it can also work as predistortion circuit when biasing voltages of three bias circuits are fine-tuned, by this way, the power gain and operating current of PA are optimized for best linearity. The three power stages which fabricated by 0.18 μm SiGe technology are bonded to the printed circuit board (PCB) to obtain impedances by Load-Pull system, then matching networks are done for best linearity with discrete passive components on PCB. The final measured three-stage PA exhibits 21.1 dBm of output power at 1 dB compression point (OP1dB) with power added efficiency (PAE) of 20.6% and 33 dB power gain under 3.3 V power supply voltage.

Keywords: high gain power amplifier, linearization bias circuit, SiGe HBT model, Volterra series

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: Gagnesh Kumar, Prashant Gupta

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This paper investigates the performance of the bundle of single wall carbon nanotubes (SWCNT) for low-power and high-speed interconnects for future VLSI applications. The power dissipation, delay and power delay product (PDP) of SWCNT bundle interconnects are examined and compared with that of the Cu interconnects at 22 nm technology node for both intermediate and global interconnects. The results show that SWCNT bundle consume less power and also faster than Cu for intermediate and global interconnects. It is concluded that the metallic SWCNT has been regarded as a viable candidate for intermediate and global interconnects in future technologies.

Keywords: carbon nanotube, SWCNT, low power, delay, power delay product, global and intermediate interconnects

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Kari Huhtala, Iiro Jussila

Abstract:

The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: board, co-operative, supervisory board, selection, director

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