In a groundbreaking study, researchers at Kazan State Power Engineering University have harnessed the power of machine learning to tackle one of the most pressing challenges in renewable energy: accurately predicting electricity generation from solar
Kazan Researchers Leverage Machine Learning to Revolutionize Solar Forecasting Read More »
In a significant advancement for the solar energy sector, researchers from the Belarusian State University of Informatics and Radioelectronics have developed a groundbreaking methodology for identifying defective solar panels using telemetry data. Th
Belarusian Researchers Unveil Method to Detect Defective Solar Panels Read More »
As the world increasingly turns to renewable energy sources, the efficiency and reliability of solar power plants have become paramount. A recent study led by S. V. Valevich from the Belarusian State University of Informatics and Radioelectronics has
Belarusian Research Introduces Smart Anomaly Detection for Solar Plants Read More »
As the proliferation of unmanned aerial vehicles (UAVs) continues to reshape various sectors, ensuring the security of critical infrastructure has become a paramount concern. Recent research led by Dao Van Luc from L
AI-Powered Algorithm Enhances Drone Detection for Wind Power Safety Read More »
The energy landscape is rapidly evolving, particularly with the integration of super large-scale offshore wind clusters into onshore power grids. A recent study led by Jingwen Ling from the Electrical Engineering College at Shanghai University of Ele
Groundbreaking Model Optimizes Offshore Wind Integration for Power Grids Read More »
As offshore wind farms (OWFs) continue to proliferate in urban power systems, the challenge of maintaining system inertia and frequency stability becomes increasingly critical. A recent study led by Xiao Qi from the Energy and Electricity Research Ce
Innovative Control Method Enhances Frequency Stability in Offshore Wind Farms Read More »
In a significant advancement for the wind energy sector, researchers have unveiled a cutting-edge control strategy designed to optimize the mechanical loads on wind turbines. This innovative approach, spearheaded by Deyi Fu from the National Key Labo
New Control Strategy Revolutionizes Wind Turbine Performance and Longevity Read More »
The wind energy sector is on the brink of a technological breakthrough that could significantly enhance the reliability of power generation from wind farms. A recent study led by Shun Yang from the School of Computer Science and Engineering at Centra
Groundbreaking Model Enhances Wind Power Forecasting for Greater Reliability Read More »
In a significant advancement for the energy sector, researchers have introduced a novel two-stage stochastic energy and reserve market clearing model that takes into account the strategic offerings of renewable energy sources. This research, led by Z
New Two-Stage Model Enhances Market Stability for Renewable Energy Sources Read More »
In a significant stride towards harnessing solar energy in Northern Cameroon, researchers have employed advanced LSTM (Long Short-Term Memory) neural networks to predict solar irradiation and temperature, key factors in optimizing photovoltaic energy
AI-Driven Solar Forecasting in Cameroon Optimizes Energy for Electric Vehicles Read More »
