most citedPyPSA: Python for Power System Analysis

544 citations · 1.5k across the 5 of their papers we have counts for

collaborators

5 papers

physics.soc-ph2018★ 132 cited

The role of hydro power, storage and transmission in the decarbonization of the Chinese power system

Hailiang Liu, Tom Brown, Gorm Bruun Andresen +2

Deep decarbonization of the electricity sector can be provided by a high penetration of renewable sources such as wind, solar PV and hydro power. Flexibility from hydro and storage…

physics.soc-ph2018★ 392 cited

PyPSA-Eur: An Open Optimisation Model of the European Transmission System

Jonas Hörsch, Fabian Hofmann, David Schlachtberger +1

PyPSA-Eur, the first open model dataset of the European power system at the transmission network level to cover the full ENTSO-E area, is presented. It contains 6001 lines (alterna…

physics.soc-ph2018★ 155 cited

Cost optimal scenarios of a future highly renewable European electricity system: Exploring the influence of weather data, cost parameters and policy constraints

David P. Schlachtberger, Tom Brown, Mirko Schäfer +2

Cost optimal scenarios derived from models of a highly renewable electricity system depend on the specific input data, cost assumptions and system constraints. Here this influence…

physics.soc-ph2017★ 544 cited

PyPSA: Python for Power System Analysis

Tom Brown, Jonas Hörsch, David Schlachtberger

Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern electrical power systems over multiple periods. PyPSA includes models for c…

physics.soc-ph2017★ 323 cited

The Benefits of Cooperation in a Highly Renewable European Electricity Network

David P. Schlachtberger, Tom Brown, Stefan Schramm +1

To reach ambitious European CO emission reduction targets, most scenarios of future European electricity systems rely on large shares of wind and solar photovoltaic power gener…