Regular Article

Optimal energy generation of hybrid energy systems considering economic and environmental multi-objective functions

¹ Department of Faculty of Business and Communications, INTI International University, Putra Nilai 71800, Malaysia
² Department of Computer Science, Dhofar University, PO Box 2509, 211 Salalah, Oman
³ Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq
⁴ Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq
⁵ Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq
⁶ Marwadi University Research Centre, Department of Electrical Engineering, Faculty of Engineering and Technology, Marwadi University, Rajkot 360003, Gujarat, India
⁷ Department of Physics & Electronics, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India
⁸ NIMS School of Electrical and Electronics Engineering, NIMS University Rajasthan, Jaipur, India
⁹ Chandigarh College of Engineering, Chandigarh Group of Colleges, Jhanjeri, Mohali 140307, Punjab, India
¹⁰ Faculty (Research) Symbiosis Institute of Business Management, Hyderabad Symbiosis International (Deemed University), Pune, India
¹¹ Head of the Department “Physics and Chemistry”, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, Uzbekistan
¹² Scientific Researcher, University of Tashkent for Applied Sciences, Str. Gavhar 1, Tashkent 100149, Uzbekistan
¹³ Western Caspian University, Scientific Researcher, Baku, Azerbaijan
¹⁴ Department of Electrical Engineering, Islamic Azad University, Branch of Central Tehran, Tehran, Iran

^* Corresponding author: mahmud.en.ac@gmail.com

Received: 10 July 2024
Accepted: 15 October 2024

Abstract

This research is dedicated to exploring and identifying the most effective design for an energy source tailored specifically to meet the electricity demands of a residential community. In an era where energy efficiency and sustainability are paramount, this study emphasizes the importance of technical and economic considerations in energy sourcing. It posits that any viable solution must not only be efficient in its energy production and consumption but also reliable in its delivery and financially feasible for the residents who will depend on it. To address this multifaceted challenge, the study proposes the innovative use of a rotation-invariant coordinate convolutional neural network in conjunction with binary battle royale optimization techniques. These advanced methodologies are selected for their potential to enhance the modelling and optimization processes involved in energy source design. The primary goal of employing these methods is to minimize two critical factors: the net present cost of the energy system and the overall energy cost incurred by the residents. By focusing on these objectives, the research aims to ensure that the proposed energy solutions are not only cost-effective but also sustainable over the long term. To rigorously test the proposed model and evaluate its performance, the research is conducted using the MATLAB platform. The study employs established methodologies and performance metrics to assess the outcomes of the model, ensuring that the findings are both credible and applicable to real-world scenarios. Through comprehensive testing and detailed analysis, this research aims to provide significant insights and actionable recommendations for the optimal design of energy sources in residential areas. By contributing to the ongoing discourse on sustainable energy solutions, the study seeks to inform policymakers, energy planners, and community stakeholders about effective strategies for meeting residential energy demands while promoting environmental sustainability. Ultimately, the findings of this research could play a crucial role in shaping the future of energy sourcing in residential communities, paving the way for more resilient and sustainable energy systems.