Leveraging a partnership with the esteemed Robert Gordon University, UK, Syntax Genie and Alta Vision has strived to pioneer groundbreaking solutions, exemplified by our collaboration to develop AR-Mini, an innovative project demonstrating the feasibility of AI-based mini-grids for providing affordable and reliable electricity access in rural Sri Lanka. This endeavor underscores our dedication to empowering communities, enhancing energy access, and promoting environmental sustainability.

Project Budget

• Total Eligible Cost: 192,511 GBP
• Funded By: Energy Catalyst Round 9 – Early Stage

Project Objectives

The objectives of the AR-Mini project:

• To develop intelligent mini-grids powered by renewable energy like solar PV and wind, and enhanced with AI technologies.
• To demonstrate how uncertainties in renewable energy generation and electricity demand can be efficiently managed by AI systems.
• To reduce reliance on fossil fuels like diesel generators and associated emissions through increased renewable energy utilization.
• To improve the reliability, quality, and affordability of electricity supply to rural households, small and medium-sized enterprises (SMEs), and social institutions.
• To create a commercially scalable solution for democratizing rural electricity access with clean energy mini-grids.

Technical Overview

The AR-Mini solution has the following technical architecture in its first stage:

• 20kW rooftop solar PV system
• 2kW small wind turbine
• 50kWh battery storage system
• 10kW diesel generator for backup
• AI system implemented through cloud-based software
• IoT sensors, including smart meters for real-time measurement and control

The hybrid mini-grid operates by using solar and wind power as the primary sources. The diesel generator and battery energy storage provide backup and bridging power when renewable generation is insufficient to meet demand.

The AI system plays a critical role in forecasting, optimization, and automation functions:

• Solar and wind power generation is forecasted using weather data.
• Electricity demand is predicted using past load profiles.
• These forecasts are then utilized to optimally schedule and dispatch all energy assets.
• The AI system is cloud-hosted and controls the mini-grid through IoT.

This project has three core functionalities enhanced by AI:

1. Distribution Control
2. Demand-Side Management
3. Operation & Maintenance

This approach is designed to achieve multiple objectives like lowering costs, reducing emissions, enhancing supply reliability, and tackling the energy 'trilemma' effectively.

Expected Key Outcomes

Expected Key Outcomes of the AR-Mini project:

• A targeted reduction of over 50% in diesel generator usage through the integration of renewable energy sources and batteries.
• Provision of a 24x7 high-quality and reliable power supply to the community through the orchestration of solar, wind, diesel generator, and battery storage.
• Anticipated increase in renewable energy utilization by 15-20% through the implementation of AI-enabled forecasting and predictive control.
• Development of a commercially viable solution with an attractive return on investment (ROI) aimed at democratizing rural electricity access using smart mini-grids.
• Successful demonstration, providing a template for AI-powered mini-grids to serve as building blocks for a sustainable energy future.