How We Built a GraphRAG & Counterfactual Simulation Engine to Optimize a 2.4MWp Solar Fleet

1. 1Build a GraphRAG model to represent the solar fleet's performance
2. 2Run counterfactual simulations to predict the impact of different scenarios on energy output
3. 3Configure the simulation engine to account for various environmental factors
4. 4Test the optimization strategy using historical data
5. 5Apply the optimized strategy to the actual solar fleet operation
6. 6Compare the results with traditional optimization methods

Data scientists and machine learning engineers on a team can benefit from this article to improve their skills in optimizing renewable energy systems, while product managers can understand the potential applications of GraphRAG and counterfactual simulation engines

💡 GraphRAG and counterfactual simulation can be used to optimize the performance of a solar fleet, leading to increased energy output and reduced costs

🌞💡 Optimizing a 2.4MWp solar fleet with GraphRAG and counterfactual simulation! 📈