The current EU energy and climate policy targets a significant reduction of carbon dioxide emissions in the forthcoming years. Carbon pricing, embedded in the EU emissions trading system, aims at achieving emission reductions in a more evenly spread way and at the lowest overall cost for society, compared with other environmental policy tools, such as coal or electricity taxes, or incentives such as subsidies on renewables. Still, the implementation of the decarbonization policy depends on several technical parameters such as the type, size and connectivity of the energy system as well as economic restrictions that occur. Within this paper, an optimization tool will be presented, focusing on cleaner energy production and on the control and reduction of environmental impact regarding energy storage solutions. Various types of batteries are examined and evaluated towards this direction. Emphasis is given to setting new criteria for the decision-making process, considering the size of battery storage and the selection of the battery type based on the environmental impact assessment parameter. The objective function of the system is formulated so as to evaluate, monitor and finally minimize environmental emissions, focusing mainly on carbon emissions. Optimization is carried out based on mixed integer nonlinear programming (MINLP). Two of the main battery types compared are lead−acid and lithium-ion; both of them result in results worth mentioning regarding the replacement impact (seven times during system lifetime for lead−acid) and the total environmental impact comparison (lithium-ion may reach a 60% reduction compared to lead−acid). Case studies are presented based on representative scenarios solved, which underline the importance of choosing the appropriate scope for each case and demonstrate the potential of the tool developed, as well as the possibilities for its further improvement.