The interdivisional PSI Laboratory for Energy Systems Analysis conducts analytical research on diverse energy technologies and systems.
LEA is a cross-center laboratory bridging the Centers for Nuclear Engineering and Sciences (NES) and Energy and Environment (CEE). It unites specific analytical research on diverse energy technologies and systems, including nuclear, fossil and (modern) renewables. Taking an holistic and interdisciplinary approach, LEA develops models, analysis and tools to support decision makers and researchers to address complex and systemic challenges in the broad field of energy. LEA includes the groups Technology Assessment, Energy Economics, Risk and Human Reliability, and the Chair of Energy Systems Analysis at the Department of Mechanical and Process Engineering (D-MAVT) of ETH Zurich. The link between LEA and D-MAVT was established in 2022 by the appointment of the LEA Head, Prof. Dr. Russell McKenna.
The LEA areas of activities fall into three main areas:
Lab News & Scientific Highlights
Wind energy and scenic landscapes: balancing beauty and power through better planning
Researchers at the Paul Scherrer Institute PSI and ETH Zurich have drawn up the first Europe-wide map of landscape quality and highlighted where wind energy and landscape protection overlap.
The competitiveness of low-carbon fuels depends on location
Production location, financing, and innovation shape the competitiveness of low-carbon fuels.
Hydrogen and the energy puzzle
What is the role of low-carbon molecules on the road to climate neutrality?
Publications
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Arrieta LAC, Camacho PS, Perez JM, Bauer C, Parra D
A prospective life cycle assessment of different battery technologies for mobility, including a second stationary application
Journal of Energy Storage. 2026; 164: 121839 (13 pp.). https://doi.org/10.1016/j.est.2026.121839
DORA PSI -
Barani M, Löffler K, Crespo del Granado P, Moskalenko N, Panos E, Hoffart FM, et al.
European energy vision 2050 and beyond: designing scenarios for Europe's energy transition
Renewable and Sustainable Energy Reviews. 2026; 225: 116074 (32 pp.). https://doi.org/10.1016/j.rser.2025.116074
DORA PSI -
Chen R, Pelser T, Lohrmann A, Weinand JM, McKenna R
Data-driven landscape scenicness mapping for continental-scale onshore wind resource assessment
Energy and AI. 2026; 24: 100752 (14 pp.). https://doi.org/10.1016/j.egyai.2026.100752
DORA PSI