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  • Open Access

    ARTICLE

    Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

    Qiang Yu*, Xiankai Chen, Xiaoyue Li, Chaoqun Zhou, Zhichao Li

    Energy Engineering, Vol.119, No.1, pp. 359-369, 2022, DOI:10.32604/EE.2022.015397 - 22 November 2021

    Abstract Smart grid puts forward higher requirements for power quality. Power quality evaluation can provide a decision-making basis for quality improvement. Based on power quality monitoring data, a grey target method is proposed for power quality evaluation. The grey target is composed of power quality evaluation standard and power quality monitoring data to be evaluated. Combining with the characteristics of each power quality evaluation index, the target center of the whole grey target system is found. Then, the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to More >

  • Open Access

    ARTICLE

    Fine-Grained Bandwidth Estimation for Smart Grid Communication Network

    Jingtang Luo1, Jingru Liao2, Chenlin Zhang3, Ziqi Wang4, Yuhang Zhang2, Jie Xu2,*, Zhengwen Huang5

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1225-1239, 2022, DOI:10.32604/iasc.2022.022812 - 17 November 2021

    Abstract Accurate estimation of communication bandwidth is critical for the sensing and controlling applications of smart grid. Different from public network, the bandwidth requirements of smart grid communication network must be accurately estimated in prior to the deployment of applications or even the building of communication network. However, existing methods for smart grid usually model communication nodes in coarse-grained ways, so their estimations become inaccurate in scenarios where the same type of nodes have very different bandwidth requirements. To solve this issue, we propose a fine-grained estimation method based on multivariate nonlinear fitting. Firstly, we use More >

  • Open Access

    ARTICLE

    A New Task Scheduling Scheme Based on Genetic Algorithm for Edge Computing

    Zhang Nan1, Li Wenjing1,*, Liu Zhu1, Li Zhi1, Liu Yumin1, Nurun Nahar2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 843-854, 2022, DOI:10.32604/cmc.2022.017504 - 03 November 2021

    Abstract With the continuous evolution of smart grid and global energy interconnection technology, amount of intelligent terminals have been connected to power grid, which can be used for providing resource services as edge nodes. Traditional cloud computing can be used to provide storage services and task computing services in the power grid, but it faces challenges such as resource bottlenecks, time delays, and limited network bandwidth resources. Edge computing is an effective supplement for cloud computing, because it can provide users with local computing services with lower latency. However, because the resources in a single edge… More >

  • Open Access

    ARTICLE

    Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network

    Abdullah Musaed Alkhiari1, Shailendra Mishra2,*, Mohammed AlShehri1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2149-2169, 2022, DOI:10.32604/cmc.2022.019562 - 27 September 2021

    Abstract Smart Grid is a power grid that improves flexibility, reliability, and efficiency through smart meters. Due to extensive data exchange over the Internet, the smart grid faces many security challenges that have led to data loss, data compromise, and high power consumption. Moreover, the lack of hardware protection and physical attacks reduce the overall performance of the smart grid network. We proposed the BLIDSE model (Blockchain-based secure quantum key distribution and Intrusion Detection System in Edge Enables Smart Grid Network) to address these issues. The proposed model includes five phases: The first phase is blockchain-based… More >

  • Open Access

    ARTICLE

    Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

    Lijo Jacob Varghese1, K. Dhayalini2, Suma Sira Jacob3, Ihsan Ali4,*, Abdelzahir Abdelmaboud5, Taiseer Abdalla Elfadil Eisa6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1053-1067, 2022, DOI:10.32604/cmc.2022.019435 - 07 September 2021

    Abstract Peer-to-Peer (P2P) electricity trading is a significant research area that offers maximum fulfilment for both prosumer and consumer. It also decreases the quantity of line loss incurred in Smart Grid (SG). But, uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and consumer. In recent times, numerous Machine Learning (ML)-enabled load predictive techniques have been developed, while most of the existing studies did not consider its implicit features, optimal parameter selection, and prediction stability. In order to overcome fulfill this research gap, the current research paper… More >

  • Open Access

    ARTICLE

    Earth Fault Management for Smart Grids Interconnecting Sustainable Wind Generation

    Nagy I. Elkalashy*, Sattam Al Otaibi, Salah K. Elsayed, Yasser Ahmed, Essam Hendawi, Ayman Hoballah

    Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 477-491, 2021, DOI:10.32604/iasc.2021.016558 - 01 April 2021

    Abstract In this study, the active traveling-wave fault location function is incorporated into the management of earth faults for smart unearthed and compensated distribution networks associated with distributed renewable generation. Unearthed and compensated networks are implemented mainly to attain service continuity, specifically during earth faults. This advantage is valued for service continuity of grid-interconnected renewable resources. However, overcurrent-based fault indicators are not efficient in indicating the fault path in these distribution networks. Accordingly, in this study, the active traveling-wave fault location is complemented using distributed Rogowski coil-based fault passage indicators. Active traveling waves are injected by… More >

  • Open Access

    ARTICLE

    Power System Resiliency and Wide Area Control Employing Deep Learning Algorithm

    Pandia Rajan Jeyaraj1, Aravind Chellachi Kathiresan1, Siva Prakash Asokan1, Edward Rajan Samuel Nadar1, Hegazy Rezk2,3,*, Thanikanti Sudhakar Babu4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 553-567, 2021, DOI:10.32604/cmc.2021.015128 - 22 March 2021

    Abstract The power transfer capability of the smart transmission grid-connected networks needs to be reduced by inter-area oscillations. Due to the fact that inter-area modes of oscillations detain and make instability of power transmission networks. This fact is more noticeable in smart grid-connected systems. The smart grid infrastructure has more renewable energy resources installed for its operation. To overcome this problem, a deep learning wide-area controller is proposed for real-time parameter control and smart power grid resilience on oscillations inter-area modes. The proposed Deep Wide Area Controller (DWAC) uses the Deep Belief Network (DBN). The network… 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 - 23 December 2020

    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… More >

  • 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 - 07 January 2021

    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) 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… More >

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