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  • Open Access

    ARTICLE

    Anomaly Detection and Classification in Streaming PMU Data in Smart Grids

    A. L. Amutha1, R. Annie Uthra1,*, J. Preetha Roselyn2, R. Golda Brunet3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3387-3401, 2023, DOI:10.32604/csse.2023.029904 - 03 April 2023

    Abstract The invention of Phasor Measurement Units (PMUs) produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible. PMUs are used in transmitting data to Phasor Data Concentrators (PDC) placed in control centers for monitoring purpose. A primary concern of system operators in control centers is maintaining safe and efficient operation of the power grid. This can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal data. The normal data indicates the normal behavior of the grid whereas the… More >

  • Open Access

    ARTICLE

    Optimal Management of Energy Storage Systems for Peak Shaving in a Smart Grid

    Firas M. Makahleh1, Ayman Amer2, Ahmad A. Manasrah1, Hani Attar2, Ahmed A. A. Solyman3, Mehrdad Ahmadi Kamarposhti4,*, Phatiphat Thounthong5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3317-3337, 2023, DOI:10.32604/cmc.2023.035690 - 31 March 2023

    Abstract In this paper, the installation of energy storage systems (EES) and their role in grid peak load shaving in two echelons, their distribution and generation are investigated. First, the optimal placement and capacity of the energy storage is taken into consideration, then, the charge-discharge strategy for this equipment is determined. Here, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to calculate the minimum and maximum load in the network with the presence of energy storage systems. The energy storage systems were utilized in a distribution system with the aid of a peak load More >

  • Open Access

    ARTICLE

    Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems

    Firas Abedi1, Hayder M. A. Ghanimi2, Mohammed A. M. Sadeeq3, Ahmed Alkhayyat4,*, Zahraa H. Kareem5, Sarmad Nozad Mahmood6, Ali Hashim Abbas7, Ali S. Abosinnee8, Waleed Khaild Al-Azzawi9, Mustafa Musa Jaber10,11, Mohammed Dauwed12

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3359-3374, 2023, DOI:10.32604/cmc.2023.034221 - 31 March 2023

    Abstract Recent economic growth and development have considerably raised energy consumption over the globe. Electric load prediction approaches become essential for effective planning, decision-making, and contract evaluation of the power systems. In order to achieve effective forecasting outcomes with minimum computation time, this study develops an improved whale optimization with deep learning enabled load prediction (IWO-DLELP) scheme for energy storage systems (ESS) in smart grid platform. The major intention of the IWO-DLELP technique is to effectually forecast the electric load in SG environment for designing proficient ESS. The proposed IWO-DLELP model initially undergoes pre-processing in two More >

  • Open Access

    ARTICLE

    Ensemble Voting-Based Anomaly Detection for a Smart Grid Communication Infrastructure

    Hend Alshede1,2,*, Laila Nassef1, Nahed Alowidi1, Etimad Fadel1

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3257-3278, 2023, DOI:10.32604/iasc.2023.035874 - 15 March 2023

    Abstract Advanced Metering Infrastructure (AMI) is the metering network of the smart grid that enables bidirectional communications between each consumer’s premises and the provider’s control center. The massive amount of data collected supports the real-time decision-making required for diverse applications. The communication infrastructure relies on different network types, including the Internet. This makes the infrastructure vulnerable to various attacks, which could compromise security or have devastating effects. However, traditional machine learning solutions cannot adapt to the increasing complexity and diversity of attacks. The objective of this paper is to develop an Anomaly Detection System (ADS) based… More >

  • Open Access

    ARTICLE

    Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

    Muhammad Irfan1, Ch. Anwar Ul Hassan2, Faisal Althobiani3, Nasir Ayub4,*, Raja Jalees Ul Hussen Khan5, Emad Ismat Ghandourah6, Majid A. Almas7, Saleh Mohammed Ghonaim3, V. R. Shamji3, Saifur Rahman1

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1723-1740, 2023, DOI:10.32604/csse.2023.035141 - 09 February 2023

    Abstract The smart grid has enabled users to control their home energy more effectively and efficiently. A home energy management system (HEM) is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy. Here, we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm (GWA) and Harmony Search Algorithms (HSA). Moreover, a fusion initiated on HSA and GWA operators is used to optimize energy intake. Furthermore, many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge. Hybridization has… More >

  • Open Access

    ARTICLE

    A Levenberg–Marquardt Based Neural Network for Short-Term Load Forecasting

    Saqib Ali1,2, Shazia Riaz2,3, Safoora2, Xiangyong Liu1, Guojun Wang1,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1783-1800, 2023, DOI:10.32604/cmc.2023.035736 - 06 February 2023

    Abstract Short-term load forecasting (STLF) is part and parcel of the efficient working of power grid stations. Accurate forecasts help to detect the fault and enhance grid reliability for organizing sufficient energy transactions. STLF ranges from an hour ahead prediction to a day ahead prediction. Various electric load forecasting methods have been used in literature for electricity generation planning to meet future load demand. A perfect balance regarding generation and utilization is still lacking to avoid extra generation and misusage of electric load. Therefore, this paper utilizes Levenberg–Marquardt (LM) based Artificial Neural Network (ANN) technique to… More >

  • Open Access

    ARTICLE

    Edge-Cloud Computing for Scheduling the Energy Consumption in Smart Grid

    Abdulaziz Alorf*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 273-286, 2023, DOI:10.32604/csse.2023.035437 - 20 January 2023

    Abstract Nowadays, smart electricity grids are managed through advanced tools and techniques. The advent of Artificial Intelligence (AI) and network technology helps to control the energy demand. These advanced technologies can resolve common issues such as blackouts, optimal energy generation costs, and peak-hours congestion. In this paper, the residential energy demand has been investigated and optimized to enhance the Quality of Service (QoS) to consumers. The energy consumption is distributed throughout the day to fulfill the demand in peak hours. Therefore, an Edge-Cloud computing-based model is proposed to schedule the energy demand with reward-based energy consumption. More >

  • Open Access

    ARTICLE

    Federated Blockchain Model for Cyber Intrusion Analysis in Smart Grid Networks

    N. Sundareswaran*, S. Sasirekha

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2129-2143, 2023, DOI:10.32604/iasc.2023.034381 - 05 January 2023

    Abstract Smart internet of things (IoT) devices are used to manage domestic and industrial energy needs using sustainable and renewable energy sources. Due to cyber infiltration and a lack of transparency, the traditional transaction process is inefficient, unsafe and expensive. Smart grid systems are now efficient, safe and transparent owing to the development of blockchain (BC) technology and its smart contract (SC) solution. In this study, federated learning extreme gradient boosting (FL-XGB) framework has been developed along with BC to learn the intrusion inside the smart energy system. FL is best suited for a decentralized BC-enabled… More >

  • Open Access

    ARTICLE

    Smart Grid Communication Under Elliptic Curve Cryptography

    B. Prabakaran1,*, T. R. Sumithira2, V. Nagaraj3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2333-2347, 2023, DOI:10.32604/iasc.2023.029725 - 05 January 2023

    Abstract Smart Grids (SGs) are introduced as a solution for standard power distribution. The significant capabilities of smart grids help to monitor consumer behaviors and power systems. However, the delay-sensitive network faces numerous challenges in which security and privacy gain more attention. Threats to transmitted messages, control over smart grid information and user privacy are the major concerns in smart grid security. Providing secure communication between the service provider and the user is the only possible solution for these security issues. So, this research work presents an efficient mutual authentication and key agreement protocol for smart More >

  • Open Access

    ARTICLE

    Machine Learning-based Electric Load Forecasting for Peak Demand Control in Smart Grid

    Manish Kumar1,2,*, Nitai Pal1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4785-4799, 2023, DOI:10.32604/cmc.2022.032971 - 28 December 2022

    Abstract Increasing energy demands due to factors such as population, globalization, and industrialization has led to increased challenges for existing energy infrastructure. Efficient ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these challenges with reliable, cheap, and easily available sources of energy. Grid integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants emissions. But the integration of distributed energy sources and increase in electric demand enhance instability in the grid. Short-term electrical load forecasting reduces the grid… More >

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