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Updated: Feb 5, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
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Cost-effective and sustainable operation of microgrids using Improved Whale Optimization Algorithm.

Sohayla M El-Zaher1, Aya M Ahmed1, Eman M Ahmed1

  • 1Electrical Engineering Department, Faculty of Engineering, Mansoura University, El- Mansoura, 35516, Egypt.

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|February 3, 2026
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Summary
This summary is machine-generated.

This study introduces an Improved Whale Optimization Algorithm (IWOA) for energy management systems (EMS) in microgrids (MGs). The IWOA significantly reduces operational costs by 39.66% while ensuring reliable power supply.

Keywords:
Energy management systemImproved Whale OptimizationMicrogridsRenewable energy resources

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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Optimization Algorithms

Background:

  • The global shift to sustainable energy necessitates resilient microgrids (MGs) and efficient renewable energy integration.
  • Managing energy supply and demand in MGs is challenging due to variable renewable generation and fluctuating grid prices.
  • Existing energy management systems (EMS) may struggle with cost-effectiveness and adaptability in grid-connected and islanded modes.

Purpose of the Study:

  • To develop a cost-effective and sustainable Energy Management System (EMS) for microgrids (MGs).
  • To enhance the resilience and economic performance of MGs operating in both grid-connected and islanded modes.
  • To address the challenges posed by renewable energy variability and grid price fluctuations.

Main Methods:

  • Development of an Improved Whale Optimization Algorithm (IWOA) with a nonlinear swimming parameter and Lévy flight mechanism.
  • Integration of a dynamic energy trading strategy for optimizing real-time grid interactions.
  • Simulation and validation on a benchmark low-voltage microgrid (MG) system.

Main Results:

  • The proposed IWOA-based EMS achieved a 39.66% reduction in operational costs compared to standard algorithms.
  • The IWOA demonstrated a competitive runtime of 4.2 minutes, indicating efficiency.
  • The dynamic energy trading strategy effectively optimized real-time energy transactions.

Conclusions:

  • The developed EMS framework, utilizing IWOA, provides a robust solution for microgrid energy management.
  • The approach enhances both the economic viability and environmental sustainability of modern power systems.
  • The study validates the effectiveness of advanced optimization techniques for microgrid operations.