Multi-objective optimization of energy system with battery storage—A case study of Turkey

Transition to clean energy sources is currently a paramount concern, necessitating the development of a robust long-term energy strategy and effective resource planning. This planning must encompass not only the economic and technical attributes of renewable energy resources but also their societal and environmental impacts, as these aspects significantly influence the feasibility of sustainable energy plans. To address these challenges, this study explores the application of multi-objective optimization methods, known for their ability to simultaneously consider multiple objectives. In this research, we propose a multi-objective linear programming model to allocate electricity generation among a range of 13 power plant alternatives for the planning horizon spanning 2022 to 2030. The selection of these alternatives incorporates two-source hybrid systems and battery storage systems due to their contributions to system stability and flexibility. The findings of this study indicate that wind and solar resources hold the largest share of electricity generation at 34% followed closely by hydro contributing to 30% of the generation. Notably, storage systems, particularly battery energy storage systems, are ranked lower due to their lower scores in socio-political and sustainability indices, as well as higher unit generation costs. It is worth noting that battery energy storage systems represent a relatively novel technology in Turkey, with potential for improving system reliability in the future, even though the majority of generation currently stems from existing and hybrid facilities. •Economic, technological, social and environmental aspects of an energy-planning dilemma were considered simultaneously.•Wide range of alternatives were discussed for the first time in Turkey, including battery-integrated and hybrid technology.•Cost function was extended further comprising of GO incentives.•Sustainability index (SI) and Socio-political index (SPI) utilized in the objective function concurrently.