GA-BASED ENERGY MANAGEMENT OPTIMIZATION FOR GRID-CONNECTED PHOTOVOLTAIC SYSTEM WITHOUT BATTERY STORAGE
Ahmet Afşin Kulaksız
Pages: 20-27
Published: 29 May 2015
Views: 2,818
Downloads: 701
Abstract: This paper presents genetic algorithm (GA) based optimization of energy management for grid connected photovoltaic (PV) systems without battery storage. The major objective of this work is to minimize energy cost by maximizing objective function of GA considering both energy consumption and generation. In objective function calculation, PV module output power obtained by model of PV modules and previous power recordings from the PV system were employed. In the system, some electrical appliances and lights are in the energy consumption side and photovoltaic energy source connected to the grid is in the energy generation side. A simulation study was implemented to obtain energy cost savings using GA optimization in a commercial building. Due to the cost of the batteries, PV system is implemented without battery storage. Therefore, by adapting fluctuating PV energy generation with the time-flexible loads, an effort was aimed to develop a smart-grid strategy.
Keywords: energy management, pv system, genetic algorithms, optimization, load scheduling
Cite this article: Ahmet Afşin Kulaksız. GA-BASED ENERGY MANAGEMENT OPTIMIZATION FOR GRID-CONNECTED PHOTOVOLTAIC SYSTEM WITHOUT BATTERY STORAGE. Journal of International Scientific Publications: Materials, Methods & Technologies 9, 20-27 (2015). https://www.scientific-publications.net/en/article/1000749/
Back to the contents of the volume
© 2025 The Author(s). This is an open access article distributed under the terms of the
Creative Commons Attribution License https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This permission does not cover any third party copyrighted material which may appear in the work requested.
Disclaimer: The Publisher and/or the editor(s) are not responsible for the statements, opinions, and data contained in any published works. These are solely the views of the individual author(s) and contributor(s). The Publisher and/or the editor(s) disclaim any liability for injury to individuals or property arising from the ideas, methods, instructions, or products mentioned in the content.
