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  • Open Access

    ARTICLE

    Equivalent Modeling with Passive Filter Parameter Clustering for Photovoltaic Power Stations Based on a Particle Swarm Optimization K-Means Algorithm

    Binjiang Hu1,*, Yihua Zhu2, Liang Tu1,2, Zun Ma3, Xian Meng3, Kewei Xu3

    Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069777 - 27 December 2025

    Abstract This paper proposes an equivalent modeling method for photovoltaic (PV) power stations via a particle swarm optimization (PSO) K-means clustering (KMC) algorithm with passive filter parameter clustering to address the complexities, simulation time cost and convergence problems of detailed PV power station models. First, the amplitude–frequency curves of different filter parameters are analyzed. Based on the results, a grouping parameter set for characterizing the external filter characteristics is established. These parameters are further defined as clustering parameters. A single PV inverter model is then established as a prerequisite foundation. The proposed equivalent method combines the… More >

  • Open Access

    ARTICLE

    Research on Equivalent Modeling Method of AC-DC Power Networks Integrating with Renewable Energy Generation

    Weigang Jin1, Lei Chen2,*, Yifei Li2, Shencong Zheng2, Yuqi Jiang2, Hongkun Chen2

    Energy Engineering, Vol.120, No.11, pp. 2469-2487, 2023, DOI:10.32604/ee.2023.043021 - 31 October 2023

    Abstract Along with the increasing integration of renewable energy generation in AC-DC power networks, investigating the dynamic behaviors of this complex system with a proper equivalent model is significant. This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator (DFIG) based wind farms to decrease the simulation scale and computational burden. For the AC-DC power networks, the equivalent modeling strategy in accordance with the physical structure simplification is stated. Regarding the DFIG-based wind farms, the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo More >

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