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Related Experiment Video

Updated: Jun 16, 2025

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
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The optimization and operation of multi-energy-coupled microgrids by the improved fireworks algorithm-shuffled

Xubo Yue1, Jing Zhang2, Junhui Guo2

  • 1Taizhou Hongchuang Group, Taizhou, China.

Peerj. Computer Science
|August 15, 2024
PubMed
Summary

This study introduces an improved fireworks algorithm (IFWA) and shuffled frog-leaping algorithm (SFLA) to optimize multi-energy microgrids. The IFWA-SFLA approach enhances microgrid stability, energy flow management, and reduces voltage fluctuations.

Keywords:
Coupled microgridImproved fireworks algorithmMulti-objective optimizationShuffled frog leaping algorithmVoltage stability index

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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Optimization Algorithms

Background:

  • Multi-energy coupled microgrids face optimization and operational challenges impacting system stability and reliability.
  • Comprehensive energy systems require advanced solutions for efficient energy management.
  • Existing algorithms may not adequately address the complex interdependencies within these systems.

Purpose of the Study:

  • To propose and validate an improved fireworks algorithm (IFWA) integrated with the shuffled frog-leaping algorithm (SFLA) for microgrid optimization.
  • To develop a multi-objective optimization model addressing active power network losses and static voltage.
  • To enhance the stability and reliability of multi-energy coupled microgrids.

Main Methods:

  • An improved fireworks algorithm (IFWA) incorporating adaptive resource allocation and community genetic strategies was developed.
  • A multi-objective optimization model was formulated considering active power network losses and static voltage.
  • The shuffled frog-leaping algorithm (SFLA) was employed to solve the constrained multi-objective optimization problems.

Main Results:

  • The IFWA-SFLA approach demonstrated superior performance in optimizing microgrid stability.
  • Effective management of electrical energy flow within the microgrid was achieved.
  • Significant reduction in voltage fluctuations was observed through simulations.

Conclusions:

  • The proposed IFWA-SFLA method is effective for optimizing multi-energy coupled microgrids.
  • The approach enhances system reliability by improving stability and managing energy flow.
  • Further investigation into microgrid energy storage inverter control strategies based on IFWA is warranted.