TL;DR
This paper presents a comprehensive, high-resolution database of distributed energy resources in Switzerland's distribution grids, supporting research on grid flexibility, resilience, and future energy planning.
Contribution
It introduces a detailed, scalable database with projections of flexibility capabilities for distributed energy resources up to 2050, filling data gaps for Swiss distribution grids.
Findings
Database covers over 2 million connection points.
Includes projections aligned with 2030, 2040, 2050 forecasts.
Supports diverse studies on grid management and policy.
Abstract
The decarbonization goals worldwide drive the energy transition of power distribution grids, which operate under increasingly volatile conditions and closer to their technical limits. In this context, localized operational data with high temporal and spatial resolution is essential for their effective planning and regulation. Nevertheless, information on grid-connected distributed energy resources, such as electric vehicles, photovoltaic systems, and heat pumps, is often fragmented, inconsistent, and unavailable. This work introduces a comprehensive database of distributed energy resources and non-controllable loads allocated in Switzerland's medium- and low-voltage distribution grid models, covering over 2 million points of connection. Remarkably, this data specifies the flexibility capabilities of the controllable devices, with a set of projections aligned with national forecasts for…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsSparse Evolutionary Training
