Association for Public Policy Analysis & Management

Electricity storage technologies (ESTs) can play an important role in supporting the transition towards a low-carbon electricity sector by enabling higher shares of intermittent renewable energy sources.^1,2 To support strategic planning by policy makers and industrial players alike, studies have projected the future cost of various ESTs using experience curves.^3–6 While using experience curves is well established for renewable energy technologies,⁷utilization for ESTs is more complex. There are two reasons, which have so far not been considered in literature: First, a key driver of cost reductions is deployment⁸, which is in turn determined by a technology’s competitiveness. If a specific EST is chosen to be deployed at scale, this technology can realize cost improvements, while others fall further behind. Second, ESTs are multi-purpose technologies, which are used in multiple applications, within and outside the electricity sector.⁹ Consequently, the future and uncertain growth of ESTs outside the electricity sector (e.g., Lithium-ion batteries for electric vehicles) will likely affect the future competitiveness of ESTs in the electricity sector.

In this contribution, we present a system-dynamic modelling approach to address this gap. We use component-based experience curves to project the cost development of ESTs based on their deployment, allowing us to reflect their multi-purpose character. Deployment is probabilistically derived by calculating each technology’s market share based on its cost-competitiveness relative to others in every period. Preliminary results highlight the importance of continuously monitoring developments across sectors and investigating spillover-effects when assessing multi-purpose technologies.