PyPSA-Eur: An open optimisation model of the European transmission system

Abstract

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 (alternating current lines at and above 220 kV voltage level and all high voltage direct current lines), 3657 substations, a new open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power. The model is suitable both for operational studies and generation and transmission expansion planning studies. The continental scope and highly resolved spatial scale enables a proper description of the long-range smoothing effects for renewable power generation and their varying resource availability. The restriction to freely available and open data encourages the open exchange of model data developments and eases the comparison of model results. A further novelty of the dataset is the publication of the full, automated software pipeline to assemble the load-flow-ready model from the original datasets, which enables easy replacement and improvement of the individual parts. This paper focuses on the description of the network topology, the compilation of a European power plant database and a top-down load timeseries regionalisation. It summarises the derivation of renewable wind and solar availability time-series from re-analysis weather datasets and the estimation of renewable capacity potentials restricted by land-use. Finally, validations of the dataset are presented, including a new methodology to compare geo-referenced network datasets to one another. challenges for the efficient design and regulation of electricity markets; the need to decarbonise heating and transport is driving electrification of these sectors; and finally energy markets are being integrated across the continent [1].To study this transformation, accurate modelling of the transmission grid is required. The need to take account of international electricity trading and the possibility of smoothing variable renewable feed-in over large distances (wind generation has a typical correlation length of around 600 km [2]) mean that models should have a continental scope. At the same time, high spatial detail is required, since national grid bottlenecks are already hindering the uptake of renewable energy today [3], and given persistent public acceptance problems facing new transmission projects [4], severe grid bottlenecks will remain a feature of the energy system for decades to come.Currently there is no openly-available model of the full European transmission network with which researchers can investigate and compare different approaches to the energy transformation. The transmission grid dataset provided by the European Network of Transmission System Operators for Electricity (ENTSO-E) for the 2016 Ten Year Network Development Plan (TYNDP) [5] is rendered unusable by restrictive licensing, the exclusion of Finland, Norway and Sweden, and a lack of geographic...

Collective effects of link failures in linear flow networks

“…Based on the intuition developed in the last section, we will introduce a quantifier in the following section that may be used to identify in which situations collective effects need to be taken into account and in which situations they may be neglected, thus being able to rely on results obtained for single link failures. We will test this predictor on different test grids, mainly on the ones shown in figure 4; the Scandinavian power grid extracted from the software package PyPSA-eur [44] (panel a) and the IEEE test case 118 [45] (panel b).…”

“…Two different network topologies are used to demonstrate the performance of the predictor for collective effects. (a) Topology of the Scandinavian power grid extracted from an aggregated version of the PyPSA-eur model[44] after the removal of dead ends. The resulting topology has 260 nodes and 361 edges.…”

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

“…We study scenarios of a future Chinese electricity system using the one-node-per-province network presented in our previous paper [10], but here we replace the heuristics with a linear technoeconomic optimization [19,20] of total annualized cost: min G n,s ,F ,g n,s,t , f ,t ∑ n,s c n,s G n,s + ∑ n,s,t o n,s g n,s,t + ∑ c F .…”

Heuristics for Transmission Expansion Planning in Low-Carbon Energy System Models

“…The case-study model is obtained using PyPSA-Eur, an open model dataset of the European power system comprising the ENTSO-E transmission network. Full details on the underlying dataset and assumptions can be found in [19]; complementary considerations are outlined below. We allow simultaneous capacity expansion of transmission lines, HVDC links, and various types of generators: photovoltaic, onshore wind, and offshore wind generators with AC and DC grid connections, as well as open-and combined-cycle gas turbines.…”

“…To avoid issues with social acceptance, a limit on the total additional volume of transmission capacities of 25% measured in MWkm is imposed. Moreover, to approximate N − 1 security and withhold capacity for reactive power flows, line capacities may not be loaded by more than 70% of their nominal power rating [19].…”