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  • Open Access

    ARTICLE

    Research on Grid-Connected Control Strategy of Distributed Generator Based on Improved Linear Active Disturbance Rejection Control

    Xin Mao*, Hongsheng Su, Jingxiu Li

    Energy Engineering, Vol.121, No.12, pp. 3929-3951, 2024, DOI:10.32604/ee.2024.057106 - 22 November 2024

    Abstract The virtual synchronous generator (VSG) technology has been proposed to address the problem of system frequency and active power oscillation caused by grid-connected new energy power sources. However, the traditional voltage-current double-closed-loop control used in VSG has the disadvantages of poor disturbance immunity and insufficient dynamic response. In light of the issues above, a virtual synchronous generator voltage outer-loop control strategy based on improved linear autonomous disturbance rejection control (ILADRC) is put forth for consideration. Firstly, an improved first-order linear self-immunity control structure is established for the characteristics of the voltage outer loop; then, the… More >

  • Open Access

    ARTICLE

    A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

    Wenlu Ji*, Teng Tu, Nan Ma

    Energy Engineering, Vol.121, No.5, pp. 1223-1243, 2024, DOI:10.32604/ee.2024.046112 - 30 April 2024

    Abstract To improve the resilience of a distribution system against extreme weather, a fuel-based distributed generator (DG) allocation model is proposed in this study. In this model, the DGs are placed at the planning stage. When an extreme event occurs, the controllable generators form temporary microgrids (MGs) to restore the load maximally. Simultaneously, a demand response program (DRP) mitigates the imbalance between the power supply and demand during extreme events. To cope with the fault uncertainty, a robust optimization (RO) method is applied to reduce the long-term investment and short-term operation costs. The optimization is formulated More >

  • Open Access

    ARTICLE

    Optimal Location and Sizing of Multi-Resource Distributed Generator Based on Multi-Objective Artificial Bee Colony Algorithm

    Qiangfei Cao1, Huilai Wang2, Zijia Hui1, Lingyun Chen2,*

    Energy Engineering, Vol.121, No.2, pp. 499-521, 2024, DOI:10.32604/ee.2023.042702 - 25 January 2024

    Abstract Distribution generation (DG) technology based on a variety of renewable energy technologies has developed rapidly. A large number of multi-type DG are connected to the distribution network (DN), resulting in a decline in the stability of DN operation. It is urgent to find a method that can effectively connect multi-energy DG to DN. photovoltaic (PV), wind power generation (WPG), fuel cell (FC), and micro gas turbine (MGT) are considered in this paper. A multi-objective optimization model was established based on the life cycle cost (LCC) of DG, voltage quality, voltage fluctuation, system network loss, power… More >

  • Open Access

    ARTICLE

    Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource

    Guobin He*, Rui Su, Jinxin Yang, Yuanping Huang, Huanlin Chen, Donghui Zhang, Cangtao Yang, Wenwen Li

    Energy Engineering, Vol.120, No.9, pp. 2133-2154, 2023, DOI:10.32604/ee.2023.029007 - 03 August 2023

    Abstract In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization, multi-resource penetration in active distribution networks has been advancing fiercely. In particular, distributed generation (DG) based on renewable energy is critical for active distribution network operation enhancement. To comprehensively analyze the accessing impact of DG in distribution networks from various parts, this paper establishes an optimal DG location and sizing planning model based on active power losses, voltage profile, pollution emissions, and the economics of DG costs as well as meteorological conditions. Subsequently, multi-objective particle swarm optimization (MOPSO) is… More >

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