Vol. 3 No. 2 (2025)

Published: 2025-03-14

Article

  • Open Access

    Article ID: 305

    Inverting tristate step-up converter

    by Felix A. Himmelstoss
    Clean Energy Science and Technology, Vol.3, No.2, 2025;
    22 Views
    DOI: https://doi.org/10.18686/cest305

    The here-treated step-up converter with two interference possibilities has several interesting features. First the output voltage is inverse to the input voltage, second the voltage transformation ratio is linearized, third the dynamic behavior is that of a phase-minimum system, and fourth the stress of the electronic switches is reduced. The function of the converter is explained, the steady state presented, the large and small signal models are derived, and the Bode plots concerning the output voltage around the operating point are given. The start-up is investigated. LTSpice is used to check the considerations.

  • Open Access

    Article ID: 335

    Hybrid Artificial Bee Colony and incremental conductance—Algorithm for enhanced MPPT in photovoltaic systems

    by Ahmed G. Abo-Khalil, Abdel-Rahman Al-Qawasmi, AlAmir Hassan
    Clean Energy Science and Technology, Vol.3, No.2, 2025;
    28 Views
    DOI: https://doi.org/10.18686/cest335

    The growing global demand for electricity necessitates efficient renewable energy solutions, with photovoltaic (PV) systems emerging as a prominent candidate. This study presents a novel hybrid Maximum Power Point Tracking (MPPT) algorithm that integrates the Artificial Bee Colony (ABC) optimization method with the Incremental Conductance (IC) technique, ensuring 100% accurate identification of the Global Maximum Power Point (GMPP) under partial shading conditions. Unlike standalone MPPT methods, the proposed approach leverages the exploratory capabilities of ABC for global search while utilizing IC for fast and precise tracking, achieving a convergence time of 0.37 s and minimal power oscillations of 2.7%. Experimental validation demonstrates the algorithm’s superior performance, attaining 100% efficiency, significantly outperforming standalone IC (74%) and ABC (99.5%) methods. The hybrid ABC-IC algorithm consistently tracks the GMPP, delivering 60 W under optimal irradiation (1000 W/m2) and surpassing conventional techniques such as P&O, FA, and PSO in terms of convergence speed, robustness, and adaptability to dynamic shading conditions. This innovative integration of bio-inspired and deterministic MPPT strategies offers a highly efficient and reliable solution for maximizing PV energy harvesting in real-world environments.