English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

An autopilot for energy models -- automatic generation of renewable  supply curves, hourly capacity factors and hourly synthetic electricity  demand for arbitrary world regions