Investigation of hybrid renewable energy system application in the industrial sector

Hybrid renewable energy systems integrate multiple power generation, storage, and consumption patterns into a unified system, offering substantial benefits over single-source solutions. This system reduces industry costs and emissions and provides access to diverse renewable sources. Traditionally, such systems combined renewable energy (wind and solar) with diesel generators to ensure reliable power. However, increased demand for sustainable energy has led to exploring system configurations incorporating wind, solar, and battery storage. This study introduces a novel optimization approach, applying the Tabu Search algorithm, in designing an optimally sized hybrid renewable energy system specifically for industrial applications – focusing on maximizing electricity bill savings, minimizing grid dependency, and reducing CO2 emissions. The optimization focuses specifically on the optimal management of the battery system rather than the sizing or control of the other components. The research applies real-life solar and wind generation profiles to develop a mathematical model identifying the optimal mix of energy sources for varying industrial demands. Findings demonstrate that the economic benefits of such renewable systems are maximized through precise system sizing and higher shares of direct power consumption. This study uniquely highlights the importance of multi-objective optimization in enhancing hybrid renewable energy systems design and operational efficiency, establishing a model for cost-effective, sustainable energy solutions in industrial settings.