Local Energy Communities: AI for Democratic Energy

The SIMPLE project explores how AI can make energy management more democratic and efficient. By integrating renewable generation, battery storage, electric vehicles, and other IoT systems, RISE researchers are, together with industry partners, building an intelligent system that allows local energy communities to operate semi-independently from the main grid.

The System Architecture

The system consists of three AI modules: prediction, error correction, and optimization.

• Prediction: Forecast models predict renewable energy production based on weather data
• Error Correction: Adaptive algorithms detect and correct disruptions such as snow-covered solar panels or malfunctioning sensors
• Optimization: Algorithms simulate thousands of potential energy-use scenarios, balancing priorities like cost, comfort, and environmental impact

Community-Driven Priorities

This architecture allows each community to set its own priorities, whether reducing costs, minimizing grid dependency, or maximizing renewable use. Demonstrator sites include farmsteads and off-grid systems in northern Sweden, where the developing system is being tested under real-world conditions.

Impact

The approach explores how AI can support a fair and sustainable energy transition, empowering communities to take control of their own resources. It demonstrates how flexible, data-driven energy management can work across scales.