Renewable Energy News and Research

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Green AI Slashes Emissions but Sacrifices Accuracy in Climate Trade-Off

Training large AI models like GPT-3 generates massive CO₂ emissions—comparable to dozens of transatlantic flights—due to extreme energy demands. Researchers urge a shift to Green AI, which cuts emissions by up to 50% through smarter tech and renewable energy.

23 Mar 2025

Can AI Get Smarter And More Reliable? New Study Shows The Path Forward

A new paper in Engineering explores how artificial intelligence can advance beyond large language models (LLMs) by focusing on knowledge empowerment, model collaboration, and model co-evolution. These strategies aim to tackle LLM limitations like hallucinations, inefficiency, and poor interpretability.

12 Mar 2025

Machine Learning Transforms Big Data Into Actionable Insights

Researchers from KIIT and Chandragupt Institute of Management explore how machine learning transforms big data challenges into opportunities, enabling industries to harness vast data resources effectively.

4 Mar 2025

Smart Cyber Defense: AI Tech Helps Power Grids Fight Off Hackers

Researchers at the University of Missouri have developed CIBR-Fort, an AI-driven cybersecurity system that predicts and mitigates cyberattacks on power grids with 91.88% accuracy, ensuring real-time protection for critical infrastructure.

26 Feb 2025

AI-Powered Weather Model AIFS Improves Forecast Accuracy and Reduces Energy Use

The European Centre for Medium-Range Weather Forecasts (ECMWF) has launched the Artificial Intelligence Forecasting System (AIFS), a cutting-edge AI-driven model that improves weather prediction accuracy by up to 20% while reducing energy consumption by 1,000 times compared to traditional methods.

25 Feb 2025

Next-Gen 6G Trials Showcase AI, Sustainability, and Industry Innovation

A groundbreaking initiative is set to redefine how 6G technology supports sustainability and industry transformation. Through large-scale trials across Europe, the 6G-VERSUS project aims to showcase the commercial and environmental potential of next-generation networks.

5 Feb 2025

Explainable AI Boosts Wind Power Forecasting for Smarter Energy Grids

Researchers at EPFL's WiRE Lab have integrated explainable AI (XAI) into wind power forecasting models, improving transparency and reliability in predicting wind energy generation. Their study shows that XAI can identify key input variables, reducing uncertainty and making wind power more competitive in the energy market.

29 Jan 2025

AI-Powered Neural Networks Drive Renewable Energy and Emission Predictions

Artificial neural networks (ANNs) revolutionize renewable energy and greenhouse gas prediction, offering precise, efficient, and scalable solutions for sustainable energy transitions.

21 Nov 2024

AI Extends EV Battery Life

Researchers developed a domain knowledge-guided machine learning framework that accurately estimates the state of health of lithium-ion batteries, achieving high precision even with limited data, to advance electric vehicle technologies.

18 Nov 2024

AI Transforms Climate Research, China Leads Global Innovation

Researchers used a vast, multilingual dataset to systematically review how artificial intelligence is applied in global climate research, identifying China as the leading contributor and uncovering opportunities for AI to further impact climate science.

3 Oct 2024

55 Green AI Initiatives

Research paper reviews 55 green AI initiatives aimed at reducing energy consumption and carbon emissions while identifying the challenges of adopting sustainable AI technologies across industries. The study emphasizes collaboration, model efficiency, and ethical practices to advance green AI development.

27 Sep 2024

Green AI: Exploring Sustainable Strategies for Energy-Efficient Systems and Eco-Friendly Innovations

Researchers explore green AI as a key approach to minimizing AI's environmental impact through energy-efficient algorithms and hardware, driving sustainability without sacrificing performance.

27 Sep 2024

Machine Learning Optimizes Polymer Analysis

Researchers integrated a convolutional neural network with broadband dielectric spectroscopy to predict the electrical equivalent circuit (EEC) topology of polymer membranes. This method reduces user bias, enhancing the accuracy and efficiency of polymer analysis in renewable energy applications.

30 Aug 2024

Hybrid Deep Learning Optimizes Renewable Power Flow

This study introduces HDRL-QIGA, a hybrid deep learning model combining reinforcement learning and quantum-inspired algorithms to optimize power flow in renewable energy systems. The model outperforms traditional methods, reducing fuel costs and power losses while ensuring voltage stability.

28 Aug 2024

Deep Learning Boosts Renewable Energy Forecasting

Deep learning models, particularly LSTM and CNN-GRU, were employed to forecast solar and wind energy production with high accuracy. The study demonstrated DL's superiority over traditional methods, offering reliable predictions for optimizing renewable energy systems.

21 Aug 2024

Improving Renewable Power Systems with Reinforcement Learning

Researchers developed a hierarchical deep reinforcement learning (HDRL) approach to manage uncertainty in power systems with large-scale renewable sources. Combining global reinforcement learning with local heuristic algorithms, HDRL improves decision-making speed and efficiency in economic dispatch under uncertain conditions.

7 Aug 2024

ML Models Predict Wind-Solar Power Output

The study compared various machine-learning models for predicting wind-solar tower power output. While linear regression was inadequate, polynomial regression and deep neural networks (DNN) showed improved accuracy. The DNN model outperformed others, demonstrating high prediction accuracy and efficiency for renewable energy forecasting.

6 Aug 2024

ANN Enhances Solar Panel Tilt Prediction

Researchers used feature selection-based artificial neural networks (ANN) to predict the optimal tilt angle (OTA) for photovoltaic (PV) systems, improving accuracy from 38.59% to 90.72%. The study, which focused on 37 sites across India, demonstrated that the Elman neural network (ELM) achieved the highest accuracy, significantly enhancing PV system efficiency for solar energy capture.

29 Jul 2024

AI Enhances Power Grid Efficiency and Reliability

Researchers reviewed AI advancements in electric power systems, highlighting its transformative potential due to modern microprocessors and data storage. The study categorizes AI applications into four areas and presents detailed case studies in wind power forecasting, smart grid security, and fault detection.

17 Jun 2024

Advancing Energy Modeling with AI Synergy

A review in Energy Strategy Reviews examines the integration of meta-heuristic (MH) algorithms and deep learning (DL) for energy modeling, showcasing advancements from 2018 to 2023. The proposed framework enhances predictive accuracy and optimization efficiency by leveraging MH's optimization strengths and DL's pattern recognition capabilities.

7 Jun 2024