The Enershare Concept articulates around the deployment of a trusted, secure, and sovereign level playing field for energy data sharing and exchange and a stack of cross-stakeholder data-driven services among energy and non-energy stakeholders. The initiative builds on 11 user scenarios that integrate intra-energy and cross-sector interactions. Furthermore, it includes validation through seven large-scale pilot projects. In this series of blog posts, we invite you to discover more about these pilot projects.
AI for Smarter Green Investments
How can AI drive better energy efficiency and investment decisions? A collaboration between the Latvian Environmental Investment Fund (LEIF) and the National Technical University of Athens (NTUA) within the Enershare Horizon Europe project is answering this question.
LEIF funds energy projects that help municipalities and businesses transition to cleaner energy sources. To enhance its impact, LEIF partnered with NTUA to develop AI4EF, an AI-powered tool providing data-driven insights for energy efficiency and green financing. AI4EF supports homeowners, policymakers, and businesses in making informed, cost-effective energy investment decisions.
Meet AI4EF: Your AI-Powered Guide to Green Investments
AI4EF assists stakeholders—including public sector representatives, energy consultants, and building owners—in analyzing and predicting energy consumption, retrofit costs, and environmental impacts. With a modular framework, the tool supports various energy efficiency goals, such as investment planning and photovoltaic installation insights, while also allowing customization for tailored ML models. By leveraging real-world, high-quality data from the Enershare Data Space, AI4EF ensures accurate recommendations and secure, standardized data sharing, enabling smarter decision-making and driving sustainable energy investments.
1. AI4EF Homepage
What Can AI4EF Do?
Think of AI4EF as a personal assistant for energy decisions. AI4EF leverages artificial intelligence (AI) and big data analytics to offer tailored solutions for diverse energy efficiency goals, from residential buildings to large industrial complexes. Here is how it is making an impact:
1. Smarter Building Retrofitting 🏡🔧
Thinking of upgrading your building for better energy efficiency? Through the Building retrofitting service, AI4EF conducts detailed assessments for building retrofitting by analyzing factors such as total area, floors, energy usage, and heating systems, along with regional costs, to provide a comprehensive retrofit assessment. It offers insights into:
- Energy savings ⚡💰
- CO2 reduction 🌍
- Improved energy class 🔋
- Financial payback 💵
Bonus: The tool also lets you download a handy Excel sheet to help you calculate the potential energy savings and environmental benefits from heating system upgrades.
This tool empowers homeowners and decision-makers to make data-driven renovation choices, optimizing energy efficiency while minimizing costs and environmental impact. By providing a list of specific energy efficiency measures, such as insulation upgrades and renewable heat installations, users can plan actionable steps towards achieving better energy classes after renovations.
2. Building Retrofitting Interface
2. Optimized Solar Investments ☀️⚡
Thinking about installing solar panels? The Photovoltaic (PV) Installation tool evaluates the economic and environmental benefits of solar panel systems using machine learning, factoring in inputs such as average monthly electricity consumption, electricity price, installation costs, and estimated solar energy generation. It provides estimates regarding:
- Energy production 🌞
- CO2 reductions 🌍
- Financial savings 💵
- Self-consumption rates 🔄
- Payback periods ⏳
With AI4EF, users gain confidence in their solar energy investments, ensuring maximum return and sustainability while contributing to a cleaner planet. This tool calculates primary energy consumption after installation and provides essential financial insights to help users decide if a photovoltaic system is the right fit for their home or business.
3. PV Installation Interface
3. Tailored AI Training Ground 🤖🔄
Want to Build Your Own Models? AI4EF features a Dagster-based ML environment within AI4EF that streamlines model development for energy efficiency predictions. Unlike fixed models trained on predefined data, the AI4EF Training Playground allows users to train their own models using their own data whenever they want to use AI4EF. This powerful tool solves the limitation of rigid, one-size-fits-all models by offering full customization and adaptability. This intelligent training hub provides:
- Optuna for hyperparameter optimization 🧠⚙️
- PyTorch Lightning for seamless model management ⚡
- Automated data ingestion, training & evaluation 🔄📈
By refining ML workflows, it improves prediction accuracy and supports sustainable energy planning, helping users make more precise and tailored investment decisions. This tool is ideal for data scientists seeking to develop and integrate custom machine-learning models into the AI4EF system for more personalized forecasting.
4. Data Marketplace 💼📊
AI4EF also integrates with the EnerShare Data Marketplace, offering users a platform to exchange valuable energy data. With this tool, users can easily access datasets from the EnerShare Data Space, enabling collaborative decision-making and fostering a shared knowledge ecosystem. This adds an important layer to AI4EF, as it allows for data-driven projects to be enhanced with accessible resources, facilitating smarter investment and development opportunities in the energy sector.
Data-Driven Sustainability with Enershare
At the heart of AI4EF’s accuracy lies the Enershare Data Space, ensuring secure, standardized, and high-quality datasets for analysis. This data-sharing ecosystem enhances AI4EF’s decision-making power, leading to better energy efficiency strategies and smarter green financing decisions.
4. Enershare data space integration
Ready to Dive Deeper into AI4EF?
- 📌 Watch the AI4EF Demo Video: AI4EF Demo
- 📌 Discover AI4EF on the Enershare AppStore here
- 📌 Contact us for more details – Alexandros Tzortzis @ EPU NTUA
