Influência da variação da produtividade das usinas hidroelétricas no cálculo da energia firme

In the present work, the problem associated to the firm energy evaluation is treated as a non linear optimization model, which allows the representation of the productivity variation of the hydro plants. The proposed model takes into account the individualized representation of the plants and the historical series of flows since the month of January of 1931. The proposed optimization problem will be solved using the Primal-Dual Interior Point Method. A case study will be presented including the Brazilian Interconnected National System. The results obtained show that the proposed methodology is promising, since it presents an energy market value more realistic when compared with existing methodologies.No presente trabalho, o problema associado ao cálculo da energia firme é tratado como um modelo não linear de otimização, o que permite a representação da variação da produtividade das usinas. No modelo proposto é considerada a representação individualizada das usinas bem como a série histórica de vazões desde o mês de janeiro de 1931. O problema de otimização proposto é resolvido através do método primal-dual de pontos interiores. Adicionalmente, é apresentado um estudo de caso abrangendo o Sistema Interligado Nacional Brasileiro. Os resultados obtidos mostram que a metodologia proposta é promissora, tendo em vista que apresenta um valor de mercado de energia mais realista quando comparado com outras metodologias

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Optimization Approach for Planning Soft Open Points in a MV-Distribution System to Maximize the Hosting Capacity

Distributed energy resources (DERs) based on renewable power, such as photovoltaic (PV), have been increasing worldwide. To support this growth, some technologies have been developed to increase the hosting capacity (HC) of distribution networks (DNs), such as the Soft Open Point (SOP), which can replace normally open switches in DNs with the advantage of allowing power and voltage control. The benefits of SOPs in terms of increasing distributed generation (DG) hosting capacity can be enhanced by network reconfiguration (NR). In this work, an optimization-based approach is proposed for placing SOP in DN with simultaneous NR; that is, the proposed algorithm consists of a promising alternative to previous works in the literature that deal with SOP placement and NR in an iteratively way or in a two-step procedure, considering that better results can be obtained by simultaneously handling both options, as shown in the introduced case studies. The optimization problem is modeled as nonlinear mixed-integer programming, and solved by a Multi-objective Artificial Immune System (MOAIS). The proposed algorithm is applied to a well-known medium-voltage (MV) test system that is widely used for the problem at hand, and the results show the effectiveness of the proposed approach to maximize the HC by optimizing the SOP installation site in the tested system. An important outcome is that the association of SOP planning and NR in a simultaneous manner tends to provide better quality solutions, where HC can overcome 400% for multiple SOPs. Another outcome is that the proposed MOAIS is able to provide good concurrent solutions to support the decision-making of the DN planner

Community Energy Markets with Battery Energy Storage Systems: A General Modeling with Applications

Traditional models of power systems are undergoing a restructuring process, stimulated by the growing deployment of renewable energy sources, making them more decentralized and progressively increasing the focus on the consumer. New arrangements are being explored, allowing consumers to play a more active role in energy systems, highlighting the concept of consumer-centric markets. This work presents an optimization model that considers the insertion of the battery energy storage system (BESS) in the concept of community energy markets. This model aims to increase the community income and includes the degradation of BESS, also evaluating different arrangements of BESS in the community markets. In the investigated scenarios, discussions about the feasibility of inserting BESS through the analysis of social welfare (SW) and fairness indicators were carried out. With the results, it was possible to observe that there are structures that are more advantageous from the perspective of the communities and others from the perspective of the members of the communities, bringing some insights into the different impacts of a BESS in an energy community

Wind Generation Impact in Transmission Expansion Planning

This research proposes a post-stage investment analysis in the transmission expansion network planning problem considering the intermittence of renewable energy sources, especially wind power sources. The main goal of this study is to analyze the voltage profiles in all the system buses and the level of electrical losses in the lines using AC flow for impact evaluation of renewable energy insertion. This research also performs an additional analysis considering wind energy insertion during the planning stage. This analysis is to demonstrate the effect in the stage of investment in transmission lines. The variability of these sources is represented through scenarios obtained by the K-means classification algorithm that allows the preservation of the correlation among generating stations. The methodology performance is tested using the IEEE 24-bus system, which is modified to include a significant share of wind energy

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p