A Dynamic Self-Healing System for Harmonic and Unbalanced Smart Microgrids Considering Renewable Energy Intermittency

Authors

  • Ontoseno Penangsang Electrical Engineering Department, Faculty of Intelligent Electrical and Informatics Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia https://orcid.org/0000-0002-3058-1972
  • Rony Seto Wibowo Electrical Engineering Department, Faculty of Intelligent Electrical and Informatics Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia https://orcid.org/0000-0002-6774-988X
  • Fysna Candra Pratama Electrical Engineering Department, Faculty of Intelligent Electrical and Informatics Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia https://orcid.org/0009-0009-1867-3143
  • Muhammad Rifad Faturrahman Electrical Engineering Department, Faculty of Intelligent Electrical and Informatics Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia https://orcid.org/0009-0007-7469-979X
  • Tanazzaha Nur Izzati Electrical Engineering Department, Faculty of Intelligent Electrical and Informatics Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia https://orcid.org/0009-0004-2932-5869
Volume: 15 | Issue: 5 | Pages: 28232-28241 | October 2025 | https://doi.org/10.48084/etasr.12080

Received: 12 May 2025 | Revised: 21 June 2025, 11 July 2025, 20 July 2025, and 17 August 2025 | Accepted: 20 August 2025 | Online: 6 October 2025


Corresponding author: Fysna Candra Pratama

Abstract

This paper presents a dynamic, self-healing system for smart microgrids that addresses the harmonic distortion, voltage imbalance, and Renewable Energy Source (RES) intermittency using an Improved Whale Optimization Algorithm (IWOA). The IWOA simultaneously optimizes four equally weighted objectives — active power losses, voltage deviation, Total Harmonic Distortion (THD), and Phase Voltage Unbalance Rate (PVUR) — thereby overcoming the limitations of the conventional methods. An enhanced IWOA movement mechanism prevents the premature convergence in complex, unbalanced harmonic scenarios. When validated on a modified IEEE 33-bus system under diverse fault, load, and generation conditions, with realistic RES and harmonic modeling, the IWOA was found to significantly improve THD and PVUR compared to the conventional approaches. Furthermore, the IWOA outperforms the standard Whale Optimization Algorithm (WOA) by converging faster and providing a superior final solution, thus demonstrating its effectiveness in enhancing the microgrid resilience and power quality.

Keywords:

IWOA, smart microgrids, dynamic self-healing, network reconfiguration, power quality, fault recovery

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How to Cite

[1]
O. Penangsang, R. S. Wibowo, F. C. Pratama, M. R. Faturrahman, and T. N. Izzati, “A Dynamic Self-Healing System for Harmonic and Unbalanced Smart Microgrids Considering Renewable Energy Intermittency”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 5, pp. 28232–28241, Oct. 2025.

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Copyright (c) 2025 Ontoseno Penangsang, Rony Seto Wibowo, Fysna Candra Pratama, Muhammad Rifad Faturrahman, Tanazzaha Nur Izzati

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