SmartRenew
Elevator Pitch: SmartRenew leverages cutting-edge AI to transform local renewable energy grids into efficient, cost-saving communities. By optimizing power flows and predictive energy management, we offer up to 20% savings, paving the way for a sustainable and economically viable energy future.
Concept
AI-driven energy management for renewable energy communities
Objective
To reduce energy costs and promote the use of local renewable energy within Renewable Energy Communities (RECs) using an AI-powered Hierarchical Energy Management System (HEMS).
Solution
Implementing an online HEMS that uses a hybrid Fuzzy Inference System – Genetic Algorithm (FIS-GA) for optimizing energy flows and storage, with predictive capabilities powered by LSTM algorithms trained on historical data.
Revenue Model
Subscription-based for access to the HEMS software platform, with tiered pricing based on energy usage levels and additional consultancy services for customization and integration.
Target Market
RECs, microgrids operators, local energy distributors, EU countries adopting renewable energy incentives, and potentially expanding to other countries with similar technical legislation frameworks.
Expansion Plan
After establishing a robust customer base in the EU, SmartRenew plans to adapt the HEMS for other countries by parameterizing the system to suit international technical legislation frameworks, thereby expanding globally.
Potential Challenges
Complexities in adapting the platform to different regional legislative conditions, ensuring data privacy and security, possible resistance from traditional energy suppliers, and technical challenges associated with accurate predictions and optimizations.
Customer Problem
Difficulty in managing energy consumption efficiently, high energy costs, and the complexity of optimizing energy flows within an REC.
Regulatory and Ethical Issues
Compliance with EU regulations and energy market policies, data protection laws like GDPR, ethical considerations in algorithm transparency, and user data handling.
Disruptiveness
Enhancing cost savings through optimized local energy sharing and storage, thus disrupting traditional energy consumption models and promoting widespread adoption of renewable energy sources.
Check out our related research summary: here.
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