global power system data: PLEXOS-World and GlobalEnergyGIS

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Tom Brown

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Feb 22, 2021, 2:22:05 PM (4 days ago) Feb 22
to openmod list, maarten.b...@ucc.ie, Niclas Mattsson
Dear openmodders,

A few publications last year presented global power system models that
you may find interesting, with time series data for all/most countries,
and in one case also with power plant data.

The age of global open models is upon us! Lots of advantages for getting
global experience curves and fossil/synthetic fuel trading right.

Might be fun to feed into a live optimiser like:

https://model.energy/

(Shameless plug, sorry.)

Best wishes,

Tom


# PLEXOS-World

Brinkerink M, Gallachóir BÓ, Deane P (2021). Building and Calibrating a
Country-Level Detailed Global Electricity Model Based on Public Data.
Energy Strategy Reviews 33: 100592. doi: 10.1016/j.esr.2020.100592 doi:
10.1016/j.esr.2020.100592

CC-BY data in useable formats, not just scrofulous PLEXOS:

https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/CBYXBY

"This dataset includes the model data of a calibrated version of
PLEXOS-World based on the 2015 calendar year. It furthermore includes
supplementary material to the journal article titled 'Building and
Calibrating a Country-Level Detailed Global Electricity Model Based on
Public Data' that describes the model development and calibration
process. The detailed global electricity model is capable of simulating
the dispatch of over 30,000 existing power plants spread out over 164
countries and 258 regions, all using public data. The data includes the
full model in PLEXOS format and in raw data format including all its
input data to be able to recreate the model in a range of other
modelling tools. Next to the power plant portfolio, the openly available
input data consists of among others hourly demand profiles for all
globally modeled countries, plant specific capacity factor profiles for
renewables and a full global set of existing cross-border transmission
capacities between countries and regions. Use of the data/model is upon
citation of the journal paper and dataset following the underneath CC
license without further restrictions."


# GlobalEnergyGIS

An autopilot for energy models – automatic generation of
renewable supply curves, hourly capacity factors and hourly
synthetic electricity demand for arbitrary world regions
Niclas Mattsson, Vilhelm Verendel, Fredrik Hedenus and Lina Reichenberg
(2020)

https://arxiv.org/abs/2003.01233

https://github.com/niclasmattsson/GlobalEnergyGIS

"Energy system models are increasingly being used to explore scenarios
with large shares of variable renewables. This requires input data of
high spatial and temporal resolution and places a considerable
preprocessing burden on the modeling team. Here we present a new code
set with an open source license for automatic generation of input data
for large-scale energy system models for arbitrary regions of the world,
including sub-national regions, along with an associated generic
capacity expansion model of the electricity system. We use ECMWF ERA5
global reanalysis data along with other public geospatial datasets to
generate detailed supply curves and hourly capacity factors for solar
photovoltaic power, concentrated solar power, onshore and offshore wind
power, and existing and future hydropower. Further, we use a machine
learning approach to generate synthetic hourly electricity demand series
that describe current demand, which we extend to future years using
regional SSP scenarios. Finally, our code set automatically generates
costs and losses for HVDC interconnections between neighboring regions.
The usefulness of our approach is demonstrated by several different case
studies based on input data generated by our code. We show that our
model runs of a future European electricity system with high share of
renewables are in line with results from more detailed models, despite
our use of global datasets and synthetic demand."



--
Karlsruhe Institute of Technology (KIT)
Institute for Automation and Applied Informatics (IAI)

Tom Brown (he/him)
Research Group Leader, Energy System Modelling

Phone: +49 721 608 25737
Fax: +49 721 608 22602
Group website: https://www.iai.kit.edu/english/ESM.php
Personal website: https://nworbmot.org/

Visitor Address:
Office 309
Campus North Building 445
Hermann-von-Helmholtz-Platz 1
76344 Eggenstein-Leopoldshafen
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