Development of functionalities for improved storage modelling in OSeMOSYS. (15th March 2020)

• Record Type: Journal Article
• Authors: Palombelli, Andrea; Gardumi, Francesco; Rocco, MatteoVincenzo; Howells, Mark; Colombo, Emanuela
• Is Part Of: Energy. Volume 195(2020)
• Publication Date: 2020-03-15
• Subjects: Energy system modelling -- Energy storage systems -- OSeMOSYS -- Sustainable development -- Renewable energy; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.117025
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Integrated systems modelling has provided insights on pathways for the sustainable use of energy, land and water resources. Among the existing modelling tools, some have been widely used to engage policy makers, due to their open source and basic structure. Yet, in the attempt of simplifying the representation of integrated systems, essential features significantly influencing the dynamics between systems may have been left aside. This study proposes an improved formulation of the Open Source Energy Modelling System (OSeMOSYS), for a better representation of energy and resource storage processes. In particular, the focus of this work is the storage losses introduction for both dams for hydropower generation and batteries for electricity storage. The modifications were applied to a case study representing key features of both a developed and developing country. The results highlight that, with low additional computational effort, a much more accurate representation of the storage technologies can be achieved. Despite the introduction of losses, renewable energy technologies tend to have a high penetration in the future energy mix thanks to storage applications that remedy their unpredictability and seasonality. Highlights: An improved storage formulation in the OSeMOSYS modelling framework is proposed. Storage losses for water dams and batteries have been implemented in OSeMOSYS. The improved formulation has been tested and verified through the Atlantis case study. An accurate storage representation can be performed with few computational effort.