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  • Open Access


    Enhancing Renewable Energy Integration: A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

    Ali S. Alghamdi1,*, Mohamed A. Zohdy2, Saad Aldoihi3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1339-1370, 2024, DOI:10.32604/cmes.2024.048839

    Abstract In the contemporary era, the global expansion of electrical grids is propelled by various renewable energy sources (RESs). Efficient integration of stochastic RESs and optimal power flow (OPF) management are critical for network optimization. This study introduces an innovative solution, the Gaussian Bare-Bones Levy Cheetah Optimizer (GBBLCO), addressing OPF challenges in power generation systems with stochastic RESs. The primary objective is to minimize the total operating costs of RESs, considering four functions: overall operating costs, voltage deviation management, emissions reduction, voltage stability index (VSI) and power loss mitigation. Additionally, a carbon tax is included in… More >

  • Open Access


    Economic Analysis of Demand Response Incorporated Optimal Power Flow

    Ulagammai Meyyappan*, S. Joyal Isac

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 399-413, 2023, DOI:10.32604/iasc.2023.026627

    Abstract Demand Response (DR) is one of the most cost-effective and unfailing techniques used by utilities for consumer load shifting. This research paper presents different DR programs in deregulated environments. The description and the classification of DR along with their potential benefits and associated cost components are presented. In addition, most DR measurement indices and their evaluation are also highlighted. Initially, the economic load model incorporated thermal, wind, and energy storage by considering the elasticity market price from its calculated locational marginal pricing (LMP). The various DR programs like direct load control, critical peak pricing, real-time More >

  • Open Access


    Disturbance Evaluation in Power System Based on Machine Learning

    Emad M. Ahmed1,*, Mohamed A. Ahmed1, Ziad M. Ali2,3, Imran Khan4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 231-254, 2022, DOI:10.32604/cmc.2022.022005

    Abstract The operation complexity of the distribution system increases as a large number of distributed generators (DG) and electric vehicles were introduced, resulting in higher demands for fast online reactive power optimization. In a power system, the characteristic selection criteria for power quality disturbance classification are not universal. The classification effect and efficiency needs to be improved, as does the generalization potential. In order to categorize the quality in the power signal disturbance, this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality disturbances.… More >

  • Open Access


    An Optimal DF Based Method for Transient Stability Analysis

    Z. A. Zaki1, Emad M. Ahmed1,*, Ziad M. Ali2,3, Imran Khan4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3449-3471, 2022, DOI:10.32604/cmc.2022.020263

    Abstract The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased. The capacity of the synchronous generators to keep working without losing synchronization when the system is exposed to severe faults such as short circuits is referred to as the power system's transient stability. As the power system's safe and stable operation and mechanism of action become more complicated, higher demands for accurate and rapid power system transient stability analysis are made. Current methods for analyzing transient stability are less accurate because they do not account… More >

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