Skip to main content
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
caso-studio
corso
Filter by Categories
Advanced AI Methods
Aerospace
Biomedical
Cybersecurity
Distributed Learning
Efficient Edge AI
Hyperdimensional Computing
Quantum computing
Renewable energy

Renewable energy

Challenges and perspectives of smart grid systems in islands: a real case study

Integrating renewables with AI tools offers sustainable solutions, especially in isolated contexts.

Renewable Energy Challenges for Island Systems

Islands like Ponza face unique challenges in achieving energy sustainability, primarily due to their reliance on imported diesel fuel. This dependency leads to high costs and frequent instability. Transitioning to renewable energy sources (RESs), such as photovoltaic (PV) and wind power, offers a promising alternative. However, intermittent energy production, limited storage options, and environmental constraints complicate the integration of RESs. Advanced technologies, including machine learning and deep learning, are instrumental in predicting energy demand and optimizing grid management.

The Role of Storage and Grid Innovations

Battery Energy Storage Systems (BESSs) play a pivotal role in stabilizing power grids with high RES penetration. For Ponza, the planned BESS infrastructure will provide a spinning reserve, manage fluctuations in RES production, and ensure consistent electricity supply during peak tourist seasons. Modernizing the grid further involves integrating automation, enabling real-time adjustments to power flows, and facilitating the seamless incorporation of new RES installations.

Predictive Insights Through AI

Artificial intelligence and deep learning techniques are applied to forecast energy production and demand accurately. These predictions are essential for designing efficient energy storage solutions and ensuring optimal use of RESs. On Ponza, machine learning models estimate future energy demand, incorporating variables like tourist influx, seasonal trends, and new electricity-driven initiatives such as electric vehicle charging stations and water desalination units.

Pathways to Sustainability

Achieving the 2030 targets outlined for Ponza involves significant upgrades to energy infrastructure. These include deploying RES systems with a capacity of up to 2.16 MW, installing advanced BESSs, and modernizing grid operations. By addressing environmental and logistical constraints, this approach aligns energy production with demand, reduces diesel reliance, and fosters long-term sustainability. The integration of smart grid systems ensures adaptability and efficiency, setting a benchmark for other islands globally.

Authors

F. Succetti, A. Rosato, R. Araneo, G. Di Lorenzo, M. Panella
January 4, 2023

Recommended

Recommended

More articles to read
Quantum computing

From graphs to qubits: a critical review of quantum graph neural networks

Quantum Graph Neural Networks merge relational learning with quantum computing to explore new paths toward more efficient AI.
Renewable energy

A Review of the Enabling Methodologies for Knowledge Discovery from Smart Grids Data

A KDD-driven pipeline turns smart meter streams into multi-step load forecasts, benchmarking feature reduction and models.
Quantum computing

Risc-v isa extensions with hardware acceleration for hyperdimensional computing

RISC-V hardware acceleration makes hyperdimensional computing up to 2665× faster while preserving flexibility and programmability.
Biomedical

Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks

A deep learning model enhances early autism diagnosis by analyzing visual patterns with eye tracking.
Quantum computing

Quantum Generative Modeling via Straightforward State Preparation

A lightweight quantum generative model creates high-fidelity data samples with minimal parameters and efficient state preparation.
Quantum computing

Enhancing QAOA Ansatz via Multi-Parameterized Layer and Blockwise Optimization

A novel quantum-classical algorithm boosts QAOA performance with fewer layers, enabling real-world optimization on NISQ devices.
Renewable energy

A Deep Learning-based Approach for Battery Life Classification

A deep learning-based LSTM network accurately classifies battery health, optimizing energy storage and predictive maintenance.
Biomedical

An explainable fast deep neural network for emotion recognition

A fast, explainable deep neural network enhances emotion recognition by optimizing facial landmark analysis.
Quantum computing

Evolving Hybrid Quantum-Classical GRU Architectures for Multivariate Time Series

QGRU combines quantum circuits with recurrent learning to forecast complex time series with fewer parameters and faster computation.
Renewable energy

Multi-label classification with imbalanced classes by fuzzy deep neural networks

A fuzzy deep neural network accurately classifies household appliances in real time using symbolic data and multi-label AI.

Do you have a specific need?

Fill out the form and tell us about your project.
We'll propose the solution that best fits your context.

Do you have a specific need?

Fill out the form and tell us about your project. We'll propose the solution that best fits your context.
GRID+ Copyright © 2026. All Rights Reserved.
VAT No. 17387741006 | The capital has been paid up in full €10,000 | RM – 1715269
GRID+ Copyright © 2026. All Rights Reserved.
VAT No. 17387741006 | The capital has been paid up in full €10,000 | RM – 1715269
P. IVA 17387741006 · The capital has been paid up in full €10,000 | RM – 1715269