Optimizing Photovoltaic and Battery Energy Storage In Off-Grid System Using Genetic Algorithm – Near-Zero Energy Building

Putra, Ilham Febrian (2025) Optimizing Photovoltaic and Battery Energy Storage In Off-Grid System Using Genetic Algorithm – Near-Zero Energy Building. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

This report presents an in-depth study on the optimal sizing of Photovoltaic (PV) systems and Battery Energy Storage Systems (BESS) for off-grid applications using a Genetic Algorithm (GA). The objective is to minimize the total cost while ensuring reliability and sustainability of the power supply. Unlike traditional integer or binary representations, this study employs a real-valued approach to accurately represent the continuous nature of PV and BESS capacities.The optimization framework integrates real-world constraints and parameters, ensuring practical applicability. The GA utilizes roulette wheel selection to maintain diversity within the population and enhance convergence towards the optimal solution. The fitness function incorporates both the capital and operational costs of PV and BESS, as well as the penalty costs associated with unmet load demands.Simulation results demonstrate the effectiveness of the proposed method in determining the optimal sizes of PV and BESS that minimize costs while satisfying the energy requirements. The performance of the GA is evaluated through various metrics, including convergence rate, solution quality, and computational efficiency.The findings suggest that the real-valued GA with roulette wheel selection is a robust and efficient tool for the optimal sizing of PV and BESS in off-grid systems, offering significant potential for improving energy sustainability and cost-effectiveness in remote areas.Based on this, as a student of Industrial Mechanical Engineering at ITS, I chose the Center of IoT Innovation laboratory at the National Taiwan University of Science and Technology as the place to carry out my internship or industrial practice. This decision was made with the consideration that this lab has a well-managed operational quality, which can provide us with more knowledge relevant to our field.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	Battery Energy Storage
Subjects:	T Technology > T Technology (General) > T57.5 Data Processing T Technology > TJ Mechanical engineering and machinery T Technology > TJ Mechanical engineering and machinery > TJ165 Energy storage. T Technology > TJ Mechanical engineering and machinery > TJ810.5 Solar energy
Divisions:	Faculty of Vocational > Mechanical Industrial Engineering (D4)
Depositing User:	Ilham Febrian Putra
Date Deposited:	30 Jul 2025 07:17
Last Modified:	30 Jul 2025 07:17
URI:	http://repository.its.ac.id/id/eprint/122486

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