Regular Article

Optimal planning of energy microgrid with multi-objective functions in independent mode

¹ Department of Electrical Engineering, University of Technology-Iraq, Baghdad 10066, Iraq
² Department of Energy, Universidad de la Costa, Barranquilla, Colombia
³ Department of Electrical and Electronics Engineering, School of Engineering and Technology, JAIN (Deemed to be University), Bangalore, Karnataka, India
⁴ Marwadi University Research Center, Department of Electrical Engineering, Faculty of Engineering & Technology, Marwadi University, Rajkot 360003, Gujarat, India
⁵ Department of Mechanical Engineering, Chandigarh College of Engineering, Chandigarh Group of Colleges, Jhanjeri, Mohali 140307, Punjab, India
⁶ NIMS School of Electrical and Electronics Engineering, NIMS University Rajasthan, Jaipur, Rajasthan, India
⁷ Head of the Department Physics and Chemistry, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, Uzbekistan
⁸ Scientific Researcher, University of Tashkent for Applied Sciences, Str. Gavhar 1, Tashkent 100149, Uzbekistan
⁹ Scientific Researcher, Western Caspian University, Baku, Azerbaijan
¹⁰ Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia
¹¹ Department of computers Techniques engineering, College of technical engineering, The Islamic University, Najaf, Iraq
¹² Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq
¹³ Department of Computers Techniques engineering, College of technical engineering, The Islamic University of Babylon, Babylon, Iraq
¹⁴ Manipur International University, Imphal, Manipur, India

^* Corresponding author: harikumarpallathadka@gmail.com

Received: 12 June 2024
Accepted: 16 August 2024

Abstract

Energy storage systems are crucial in managing the uncertainties associated with power generation from renewable sources like wind turbines (WTs) and photovoltaic (PV) systems. This article presents the most effective sizing of energy resources within a microgrid, which includes hydrogen storage, PV, battery systems, and WT in the independent mode of the main grid. The study aims to minimize installation costs, maximize the penetration of WT and PV systems in meeting demand, and reduce load shedding. To tackle the intricacies of the planning process, the research utilizes the modified sunflower optimization (MSFO) algorithm. Through comparative experiments, the study confirms the efficacy of this method, showcasing its capacity to deliver enhanced outcomes. The findings indicate that the proposed method efficiently optimizes resource allocation at an optimal pace.