Renewable Energy Transition in South America: Predictive Analysis of Generation Capacity by 2050
원문 초록
In this research, renewable energy expansion in South America up to 2050 is predicted based on machine learning models that are trained on past energy data. The research employs gradient boosting regression and Prophet time series forecasting to make predictions of future generation capacities for solar, wind, hydroelectric, geothermal, biomass, and other renewable sources in South American nations. Model output analysis indicates staggering future expansion in the generation of renewable energy, with solar and wind energy registering the highest expansion rates. Geospatial visualization methods were applied to illustrate regional disparities in the utilization of renewable energy. The results forecast South America to record nearly 3-fold growth in the generation of renewable energy by the year 2050, with Brazil and Chile spearheading regional development. Such projections help design energy policy, investment strategy, and climate change mitigation throughout the region, in helping the developing economies to transition to sustainable energy.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models
Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection
A foundation model with multi-variate parallel attention to generate neuronal activity
Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks
PeakWeather: MeteoSwiss Weather Station Measurements for Spatiotemporal Deep Learning
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
토론
이 논문과 연결된 포럼 글이 아직 없습니다.