Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System

Improvements in modeling energy systems of populous emerging economies are highly decisive for a successful global energy transition. The models used – increasingly published open source – still suffer from the lack of appropriate open data. As an illustrative example, we take the Brazilian energy system, which has great potential for renewable energy resources but still relies heavily on fossil fuels. We provide a comprehensive open dataset for scenario analyses, which can be directly used with the popular open energy system model PyPSA and other modeling frameworks. It includes three categories: 1) time series data of variable renewable potentials, electricity load profiles, inflows for the hydropower plants, and cross-border electricity exchanges, 2) geo-referenced data for 27 defined regions, and 3) tabular data, which contains power plant data with installed and planned generation capacities, aggregated grid network topology, biomass thermal plant potential, as well as scenarios of energy demand. This data fosters global or country-specific energy system studies based on open data relevant to decarbonizing Brazil’s energy system

Versorgungsicherheit in Deutschland und Mitteleuropa während Extremwetter-Ereignissen (VERMEER) - Der Beitrag des transnationalen Stromhandels bei hohen Anteilen erneuerbarer Energien

The VERMEER project evaluates the consequences of extreme weather events for the securi-ty of supply of electricity in Germany, considering the flexibility potential of cross-border electricity trading with regard to weather-dependent transmission grid transfer capacities. For this purpose, several specialized models for defining extreme weather situations, calcu-lating renewable energy generation timeseries, simulating cross-border trading and grid transfer capacities have been further developed and coupled. "Dunkelflauten" or dark dol-drums, periods of low combined wind and solar power generation, are projected to increase in the coming century by approximately 11% to 19% according to two climate projection calculations. An in-depth analysis of historical weather patterns (applied to wind and solar generation fleet of the target year of this study - 2035) reveals this for a system as defined in the TYNDP Distributed Energy scenario. During the winter of 1996/1997, the residual load, an indicator of potential under-supply situations like cold dark doldrums, reached notably high levels over a three-month period - but also for shorter periods such as days or weeks. Analyses of the German and neighboring electricity markets show that within the assump-tions based on this scenario extreme weather events such as the examined cold dark dol-drums lead to shortages in the German market zone that cannot be compensated by conven-tional generation or cross-border trading. Trading flows to neighboring market zones are significantly altered during such events compared to a base case scenario. The simultaneous occurrence of extreme weather across Europe limits the effectiveness of increased trans-mission capacities in ensuring security of supply, necessitating additional reserve capacities. Regarding power grids, the analyzed extreme situation reduces the occurrence of grid bot-tlenecks, as they strongly correlate with wind power generation and constitute a weak wind event. However, with increased transmission capacity, the overall amount for redispatch rises; renewable energy curtailment is less affected than conventional power plants. In addi-tion to the market-oriented assessment of security of supply, network simulations indicate that a slight amount of load shedding is necessary in all scenarios to ensure a bottleneck-free operation. The necessary load shedding does not exhibit a significant increase between the base scenario and the extreme situation, nor can it be substantially reduced by increas-ing transmission capacities. In summary, and contrary to expectations, the expansion of the electricity network does not offer significant additional relief during extreme weather events

Thousands of small, novel genes predicted in global phage genomes.

Small genes (<150 nucleotides) have been systematically overlooked in phage genomes. We employ a large-scale comparative genomics approach to predict >40,000 small-gene families in ∼2.3 million phage genome contigs. We find that small genes in phage genomes are approximately 3-fold more prevalent than in host prokaryotic genomes. Our approach enriches for small genes that are translated in microbiomes, suggesting the small genes identified are coding. More than 9,000 families encode potentially secreted or transmembrane proteins, more than 5,000 families encode predicted anti-CRISPR proteins, and more than 500 families encode predicted antimicrobial proteins. By combining homology and genomic-neighborhood analyses, we reveal substantial novelty and diversity within phage biology, including small phage genes found in multiple host phyla, small genes encoding proteins that play essential roles in host infection, and small genes that share genomic neighborhoods and whose encoded proteins may share related functions