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  • Open Access

    ARTICLE

    Big Data of Home Energy Management in Cloud Computing

    Rizwan Munir1,*, Yifei Wei1, Rahim Ullah2, Iftikhar Hussain3, Kaleem Arshid4, Umair Tariq1

    Journal of Quantum Computing, Vol.2, No.4, pp. 193-202, 2020, DOI:10.32604/jqc.2020.016151

    Abstract A smart grid is the evolved form of the power grid with the integration of sensing, communication, computing, monitoring, and control technologies. These technologies make the power grid reliable, efficient, and economical. However, the smartness boosts the volume of data in the smart grid. To obligate full benefits, big data has attractive techniques to process and analyze smart grid data. This paper presents and simulates a framework to make sure the use of big data computing technique in the smart grid. The offered framework comprises of the following four layers: (i) Data source layer, (ii) Data transmission layer, (iii) Data… More >

  • Open Access

    ARTICLE

    Demand Responsive Market Decision-Makings and Electricity Pricing Scheme Design in Low-Carbon Energy System Environment

    Hongming Yang1,*, Qian Yu1, Xiao Huang1, Ben Niu2, Min Qi3

    Energy Engineering, Vol.118, No.2, pp. 285-301, 2021, DOI:10.32604/EE.2021.013734

    Abstract The two-way interaction between smart grid and customers will continuously play an important role in enhancing the overall efficiency of the green and low-carbon electric power industry and properly accommodating intermittent renewable energy resources. Thus far, the existing electricity pricing mechanisms hardly match the technical properties of smart grid; neither can they facilitate increasing end users participating in the electricity market. In this paper, several relevant models and novel methods are proposed for pricing scheme design as well as to achieve optimal decision-makings for market participants, in which the mechanisms behind are compatible with demand response operation of end users… More >

  • Open Access

    ARTICLE

    A Novel Knowledge-Based Battery Drain Reducer for Smart Meters

    Isma Farah Siddiqui1, Scott Uk-Jin Lee2,*, Asad Abbas3

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 107-119, 2020, DOI:10.31209/2019.100000132

    Abstract The issue of battery drainage in the gigantic smart meters network such as semantic-aware IoT-enabled smart meter has become a serious concern in the smart grid framework. The grid core migrates existing tabular datasets i.e., Relational data to semantic-aware tuples in its Resource Description Framework (RDF) format, for effective integration among multiple components to work aligned with IoT. For this purpose, WWW Consortium (W3C) recommends two specifications as mapping languages. However, both specifications use entire RDB schema to generate data transformation mapping patterns and results large quantity of unnecessary transformation. As a result, smart meters use huge computing resources, maximum… More >

  • Open Access

    ARTICLE

    An Efficient Supervised Energy Disaggregation Scheme for Power Service in Smart Grid

    Weilie Liu, Jialing He, Meng Li, Rui Jin, Jingjing Hu, Zijian Zhang

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 585-593, 2019, DOI:10.31209/2019.100000113

    Abstract Smart energy disaggregation is receiving increasing attention because it can be used to save energy and mine consumer's electricity privacy by decomposing aggregated meter readings. Many smart energy disaggregation schemes have been proposed; however, the accuracy and efficiency of these methods need to be improved. In this work, we consider a supervised energy disaggregation method which initially learns the power consumption of each appliance and then disaggregates meter readings using the previous learning result. In this study, we improved the fast search and find of density peaks clustering algorithm to cluster appliance power signals twice to learn appliance feature matrices.… More >

  • Open Access

    ARTICLE

    Cyber-security Risk Assessment Framework for Critical Infrastructures

    Zubair Baig1, Sherali Zeadally2

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 121-129, 2019, DOI:10.31209/2018.100000049

    Abstract A critical infrastructure provides essential services to a nation’s population. Interruptions in its smooth operations are highly undesirable because they will cause significant and devastating consequences on all stakeholders in the society. In order to provide sustained protection to a nation’s critical infrastructure, we must continually assess and evaluate the risks thereof. We propose a risk assessment framework that can evaluate the risks posed to the security of a critical infrastructure from threat agents, with a special emphasis on the smart grid communications infrastructure. The framework defines finegrained risk identification to help quantify and assess exploitable vulnerabilities within a critical… More >

  • Open Access

    ARTICLE

    A Cryptographic-Based Approach for Electricity Theft Detection in Smart Grid

    Khelifi Naim1, *, Benahmed Khelifa2, Bounaama Fateh3

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 97-117, 2020, DOI:10.32604/cmc.2020.09391

    Abstract In order to strengthen their security issues, electrical companies devote particular efforts to developing and enhancing their fraud detection techniques that cope with the information and communication technologies integration in smart grid fields. Having been treated earlier by several researchers, various detection schemes adapted from attack models that benefit from the smart grid topologies weaknesses, aiming primarily to the identification of suspicious incoming hazards. Wireless meshes have been extensively used in smart grid communication architectures due to their facility, lightness of conception and low cost installation; however, the communicated packets are still exposed to be intercepted maliciously in order either… More >

  • Open Access

    ARTICLE

    Electrical Data Matrix Decomposition in Smart Grid

    Qian Dang1, Huafeng Zhang1, Bo Zhao2, Yanwen He2, Shiming He3,*, Hye-Jin Kim4

    Journal on Internet of Things, Vol.1, No.1, pp. 1-7, 2019, DOI:10.32604/jiot.2019.05804

    Abstract As the development of smart grid and energy internet, this leads to a significant increase in the amount of data transmitted in real time. Due to the mismatch with communication networks that were not designed to carry high-speed and real time data, data losses and data quality degradation may happen constantly. For this problem, according to the strong spatial and temporal correlation of electricity data which is generated by human’s actions and feelings, we build a low-rank electricity data matrix where the row is time and the column is user. Inspired by matrix decomposition, we divide the low-rank electricity data… More >

  • Open Access

    ARTICLE

    A Hybrid Model for Anomalies Detection in AMI System Combining K-means Clustering and Deep Neural Network

    Assia Maamar1,*, Khelifa Benahmed2

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 15-39, 2019, DOI:10.32604/cmc.2019.06497

    Abstract Recently, the radical digital transformation has deeply affected the traditional electricity grid and transformed it into an intelligent network (smart grid). This mutation is based on the progressive development of advanced technologies: advanced metering infrastructure (AMI) and smart meter which play a crucial role in the development of smart grid. AMI technologies have a promising potential in terms of improvement in energy efficiency, better demand management, and reduction in electricity costs. However the possibility of hacking smart meters and electricity theft is still among the most significant challenges facing electricity companies. In this regard, we propose a hybrid approach to… More >

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