News
Scientific paper
Smarter designs, lighter vehicles: exploring the future of automotive engineering
This new study investigates how topology optimization and additive manufacturing can create lighter and high-performance automotive components, achieving up to 30% weight reduction while maintaining structural integrity.
Load estimation for low observability networks
This study presents a new modular framework for estimating electricity demand in distribution networks with limited monitoring data. Validated on a real network in Crete, it enables accurate load and voltage estimation even where smart meters are not widely available.
Strengthening long-term wind energy projections in complex terrain
The paper presents an enhanced Measure–Correlate–Predict (MCP) approach to evaluate long-term wind potential and energy production in complex terrain in Greece.
A modular pathway to scalable Renewable Energy Valleys
New study introduces a modular framework to design and scale Renewable Energy Valleys, combining renewable generation, storage solutions, and sector-specific demand to support flexible and transferable energy systems.
Improving accuracy of wind power forecasting
Accurate wind power forecasting represents a challenge in integrating renewable energy into modern power. This paper presents a new meta-learning framework combining machine learning models and multi-source data to significantly improve the accuracy and reliability of short-term wind power forecasting.
Updating SARGON ontology for semantic data sharing in the energy domain
This paper presents SARGON2, an updated ontology that improves semantic data sharing in the energy sector. By integrating renewable energy, weather, and grid data, SARGON2 enhances interoperability and supports smarter energy systems.
Less is more: a new approach to forecasting electricity prices
A new study shows that short-window machine learning (7–90 days) improves electricity price forecasting in changing markets. LightGBM outperforms deep learning, offering higher accuracy and better detection of seasonal trends and price spikes.
From traditional windmills to modern energy systems: lessons from Lasithi Plateau
This study explores how the design of traditional Lasithi Plateau windmills can inspire resilient, small-scale wind energy systems for electricity production.
Transfer learning improves building energy forecasting with limited data
This publication shows how transfer learning and advanced AI models significantly improve short-term building load forecasting, even when historical data are scarce.
Hybrid AI model boosts accuracy of wind power forecasting
The study introduces a new model that blends physics with artificial intelligence to improve wind power forecasting for better grid reliability.
Renewable energy valleys can reshape the energy landscape of Crete
Researchers present an innovative framework aimed at transforming the Greek island of Crete into a self-sufficient, renewable energy-powered region.
Finding the best spots for EV chargers in Greek cities
A smart decision-making tool helps planners choose where to place electric vehicle charging stations based on cost, environment, and community needs.
Co-funded by the European Union under grant agreement no. 101136139. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.
