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Search Results (11)
  • Open Access

    ARTICLE

    A Cascading Fault Path Prediction Method for Integrated Energy Distribution Networks Based on the Improved OPA Model under Typhoon Disasters

    Yue He1, Yaxiong You1, Zhian He1, Haiying Lu1, Lei Chen2,*, Yuqi Jiang2, Hongkun Chen2

    Energy Engineering, Vol.121, No.10, pp. 2825-2849, 2024, DOI:10.32604/ee.2024.052371 - 11 September 2024

    Abstract In recent times, the impact of typhoon disasters on integrated energy active distribution networks (IEADNs) has received increasing attention, particularly, in terms of effective cascading fault path prediction and enhanced fault recovery performance. In this study, we propose a modified ORNL-PSerc-Alaska (OPA) model based on optimal power flow (OPF) calculation to forecast IEADN cascading fault paths. We first established the topology and operational model of the IEADNs, and the typical fault scenario was chosen according to the component fault probability and information entropy. The modified OPA model consisted of two layers: An upper-layer model to More >

  • Open Access

    ARTICLE

    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 - 20 May 2024

    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

    ARTICLE

    Model Predictive Control Strategy of Multi-Port Interline DC Power Flow Controller

    He Wang1, Xiangsheng Xu1, Guanye Shen2, Bian Jing1,*

    Energy Engineering, Vol.120, No.10, pp. 2251-2272, 2023, DOI:10.32604/ee.2023.028965 - 28 September 2023

    Abstract There are issues with flexible DC transmission system such as a lack of control freedom over power flow. In order to tackle these issues, a DC power flow controller (DCPFC) is incorporated into a multi-terminal, flexible DC power grid. In recent years, a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability. This work proposes a model predictive control (MPC) strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance. Initially, the… More >

  • Open Access

    ARTICLE

    Reactive Power Flow Convergence Adjustment Based on Deep Reinforcement Learning

    Wei Zhang1, Bin Ji2, Ping He1, Nanqin Wang1, Yuwei Wang1, Mengzhe Zhang2,*

    Energy Engineering, Vol.120, No.9, pp. 2177-2192, 2023, DOI:10.32604/ee.2023.026504 - 03 August 2023

    Abstract Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions. To address the unsolvable power flow problem caused by the reactive power imbalance, a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed. The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment. For the non-convergence power flow, the 500 kV nodes with reactive power compensation devices on the low-voltage side More >

  • Open Access

    ARTICLE

    Machine Learning for Hybrid Line Stability Ranking Index in Polynomial Load Modeling under Contingency Conditions

    P. Venkatesh1,*, N. Visali2

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1001-1012, 2023, DOI:10.32604/iasc.2023.036268 - 29 April 2023

    Abstract In the conventional technique, in the evaluation of the severity index, clustering and loading suffer from more iteration leading to more computational delay. Hence this research article identifies, a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects. The polynomial load modelling or ZIP (constant impedances (Z), Constant Current (I) and Constant active power (P)) is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security. The process of finding the severity of the line using a Hybrid Line Stability Ranking… More >

  • Open Access

    ARTICLE

    A Data Driven Security Correction Method for Power Systems with UPFC

    Qun Li, Ningyu Zhang*, Jianhua Zhou, Xinyao Zhu, Peng Li

    Energy Engineering, Vol.120, No.6, pp. 1485-1502, 2023, DOI:10.32604/ee.2023.022856 - 03 April 2023

    Abstract The access of unified power flow controllers (UPFC) has changed the structure and operation mode of power grids all across the world, and it has brought severe challenges to the traditional real-time calculation of security correction based on traditional models. Considering the limitation of computational efficiency regarding complex, physical models, a data-driven power system security correction method with UPFC is, in this paper, proposed. Based on the complex mapping relationship between the operation state data and the security correction strategy, a two-stage deep neural network (DNN) learning framework is proposed, which divides the offline training… More >

  • Open Access

    ARTICLE

    Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

    Noor Zanib1, Munira Batool1, Saleem Riaz2, Farkhanda Afzal3, Sufian Munawar4, Ibtisam Daqqa5, Najma Saleem5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1105-1136, 2023, DOI:10.32604/cmes.2022.021676 - 31 August 2022

    Abstract This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system (DGs) that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner (UPQC). In addition to supplying active power to the utility grid, the system of hybrid wind photovoltaic functions as a UPQC, compensating reactive power and suppressing the harmonic load currents. Additionally, the load is supplied with harmonic-free, balanced and regulated output voltages. Since PVWind-UPQC is established on a dual compensation scheme, the series inverter works like a… More >

  • Open Access

    ARTICLE

    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 - 06 June 2022

    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

    ARTICLE

    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 - 03 November 2021

    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

    ARTICLE

    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 - 27 September 2021

    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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