Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (64)
  • 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 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 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 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… More >

Displaying 61-70 on page 7 of 64. Per Page