AI Article Synopsis
- The share of solar power in Brazil's grid is growing, helping reduce greenhouse gas emissions and improve energy security.
- A study evaluates climate models' ability to predict surface solar irradiance in Brazil, indicating most regions may see a 2% to 8% increase, while the South may experience a 3% decrease.
- The findings suggest potential growth in photovoltaic energy production if supported by public policies, emphasizing the need for careful assessment of climate model uncertainty.
Article Abstract
The share of solar power in Brazil's electrical grid has rapidly increased, relieving GHG emissions and diversifying energy sources for greater energy security. Besides that, solar resource is susceptible to climate change, adding uncertainty to electrical grid resilience. This study uses satellite and reanalysis data to evaluate the performance of CMIP6 models in replicating and predicting surface solar irradiance (SSR) in Brazil. The results from the most reliable models indicate an increase in SSR by 2% to 8% in most regions, with a decrease of around 3% in the South. These findings highlight the potential for increased photovoltaic (PV) yield if backed by supportive public policies while underlining the importance of uncertainty assessment of climate models.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494216 | PMC |
| http://dx.doi.org/10.1038/s41598-024-73769-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing.
Sensors (Basel)
December 2024
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Unmanned aerial vehicles (UAVs) furnished with computational servers enable user equipment (UE) to offload complex computational tasks, thereby addressing the limitations of edge computing in remote or resource-constrained environments. The application of value decomposition algorithms for UAV trajectory planning has drawn considerable research attention. However, existing value decomposition algorithms commonly encounter obstacles in effectively associating local observations with the global state of UAV clusters, which hinders their task-solving capabilities and gives rise to reduced task completion rates and prolonged convergence times.
View Article and Find Full Text PDFComparative Analysis of Edge Detection Operators Using a Threshold Estimation Approach on Medical Noisy Images with Different Complexities.
Sensors (Basel)
December 2024
Directorate for Railways, Nemanjina 6, 11000 Belgrade, Serbia.
The manuscript conducts a comparative analysis to assess the impact of noise on medical images using a proposed threshold value estimation approach. It applies an innovative method for edge detection on images of varying complexity, considering different noise types and concentrations of noise. Five edges are evaluated on images with low, medium, and high detail levels.
View Article and Find Full Text PDFPayload State Prediction Based on Real-Time IoT Network Traffic Using Hierarchical Clustering with Iterative Optimization.
Sensors (Basel)
December 2024
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
IoT (Internet of Things) networks are vulnerable to network viruses and botnets, while facing serious network security issues. The prediction of payload states in IoT networks can detect network attacks and achieve early warning and rapid response to prevent potential threats. Due to the instability and packet loss of communications between victim network nodes, the constructed protocol state machines of existing state prediction schemes are inaccurate.
View Article and Find Full Text PDFDSC-SeNet: Unilateral Network with Feature Enhancement and Aggregation for Real-Time Segmentation of Carbon Trace in the Oil-Immersed Transformer.
Sensors (Basel)
December 2024
State Grid Tianjin Electric Power Research Institute, Tianjin 300180, China.
Large oil-immersed transformers have metal-enclosed shells, making it difficult to visually inspect the internal insulation condition. Visual inspection of internal defects is carried out using a self-developed micro-robot in this work. Carbon trace is the main visual characteristic of internal insulation defects.
View Article and Find Full Text PDFElectrolytic Ni-P and Ni-P-Cu Coatings on PCM-Loaded Expanded Graphite for Enhanced Battery Thermal Management with Mechanical Properties.
Materials (Basel)
January 2025
Department of Mechanical Engineering, Samsun University, 55420 Samsun, Turkey.
This study addresses the thermal management challenge in battery systems by enhancing phase change material composites with Ni-P and Ni-P-Cu coatings on phase change material/expanded graphite structures. Traditional phase change materials are limited by low thermal conductivity and mechanical stability, which restricts their effectiveness in high-demand applications. Unlike previous studies, this work integrates Ni-P and Ni-P-Cu coatings to significantly improve both the thermal conductivity and mechanical strength of phase change material/expanded graphite composites, filling a crucial gap in battery thermal management solutions.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!