Hybrid Energy Systems Optimization Using Firefly Algorithm: Integration of Various Resources for Enhanced Stability and Flexibility

Document Type : Research paper

Authors

1 Department of Electrical Engineering, Institut Teknologi Padang, Indonesia

2 Al-Hadi University College /Baghdad,10011, Iraq

3 Al-Manara College For Medical Sciences/ (Maysan)/Iraq

4 Department of Engineering/Al-Esraa University/Baghdad, Iraq

5 College of Computer/ National University of Science and Technology, Dhi Qar, Iraq

6 College of Petroleum Engineering, Al-Ayen University, Thi-Qar , Iraq

7 Department of Medical Laboratories Technology/ AL-Nisour University College/ Baghdad/ Iraq

8 The Department of Audit, Tashkent State University of Economics, Tashkent, Uzbekistan

9 Department of Electrical Engineering, Universitas Darma Agung, Medan, Indonesia

10 Associate Professor, Kazakh National Agrarian Research University, Department of Energy Saving and Automation , Almaty , Republic of Kazakhstan

Abstract

The concept of hybrid energy systems has emerged as a distinct alternative in the past few decades, with the aim of enhancing the resilience and adaptability of energy systems to fluctuations and diverse energy sources. One of the principal objectives of hybrid energy systems is to mitigate the environmental repercussions associated with the generation and utilization of energy. Using more than one energy source at the same time, like solar panels, wind turbines, and combined heat and power (CHP) systems, has many benefits, such as higher efficiency, less reliance on fossil fuels, and lower greenhouse gas emissions. This study presents an optimal approach for the design of hybrid energy systems utilizing the Firefly algorithm within the given paradigm. Incorporated into the structure are vital components like wind turbines, solar panels, combined heat and power (CHP) systems, battery storage, and converters. Furthermore, it considers the various uncertainties pertaining to production capacity, demand, and costs. The firefly optimization technique is being employed to effectively identify the most optimal solutions within a context characterized by several uncertainties. The optimization results of this framework are demonstrated to be superior in effectiveness and efficiency when compared to those obtained from other optimization algorithms. This finding provides confirmation of the algorithm's effectiveness and efficiency in enhancing the performance and stability of hybrid energy systems.

Keywords

Main Subjects

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Journal of Operation and Automation in Power Engineering
Volume 11, Special Issue
Sustainable Power Systems, Energy Management, and Global Warming
March 2023

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History

  • Receive Date: 11 December 2023
  • Revise Date: 02 May 2024
  • Accept Date: 02 May 2024
  • First Publish Date: 05 May 2024

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