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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1460940
This article is part of the Research Topic Urban Multi-energy System Networks with High Proportion of Renewable Energy View all 4 articles

Multi-Objective Parameter Design and Economic Analysis of VSG-Controlled Hybrid Energy Systems in Islanded Grids

Provisionally accepted
Yi-Syuan Wu Yi-Syuan Wu Jian-Tang Liao Jian-Tang Liao *Hong-Tzer Yang Hong-Tzer Yang *
  • National Cheng Kung University, Tainan, Taiwan

The final, formatted version of the article will be published soon.

    Photovoltaic (PV) systems offer cost-effective power solutions for outlying islands but often compromise system stability due to reduced inertia. This study introduces a Virtual Synchronous Generator (VSG) control strategy, integrated with Energy Storage Systems (ESS) and PV, to enhance system inertia. By optimizing coordination between these energy sources, the proposed method mitigates oscillations and improves grid stability. However, PV-VSG systems are generally not favored by energy providers due to the requirement for pre-curtailment of power output. To address this, the paper proposes a parameter design method for VSG control of ESS and PV, utilizing multi-objective genetic algorithm (MOGA) optimization to simultaneously increase the frequency nadir and minimize the settling time after disturbances. Additionally, an adaptive curtailment decision and parameter design method based on artificial neural networks is introduced to enhance the feasibility of PV-VSG systems by reducing PV pre-curtailment and prioritizing PV power release and ESS charging during frequency oscillations. Real data from the Penghu Archipelago in Taiwan are used to build a dynamic model in DIgSILENT, enabling interaction with MOGA. The Value at Risk (VaR) method with dual stochastic variables is employed to assess the allowable PV installed capacity. The results show that when VaR is set at 1%, the proposed PV-VSG method can increase PV penetration by 57.5% compared to scenarios without VSG. Furthermore, compared to traditional PV-VSG methods, the proposed approach achieves a 16.8% increase in PV penetration and reduces annual PV curtailment by 25 MWh. This study also evaluates the economic impact of planners choosing different risk levels, offering valuable insights for grid development in remote or island regions.

    Keywords: Artificial Neural Network1, energy storage system2, Frequency Nadir3, Hybrid Energy System4, Multi-objective optimization5, Power System Dynamic Simulation6, Risk Management7, Virtual Synchronous Generator8

    Received: 07 Jul 2024; Accepted: 05 Sep 2024.

    Copyright: © 2024 Wu, Liao and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jian-Tang Liao, National Cheng Kung University, Tainan, Taiwan
    Hong-Tzer Yang, National Cheng Kung University, Tainan, Taiwan

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.