AI-Powered Microgrid Database for Quality Decision-Making and Accelerated Adoption

The adoption of microgrids is hindered by inadequate relevant data to identify reliable technical and cost/benefits data for microgrid project implementation, the inability to map cost effective pathways to quantify the value of reliability, affordability and resiliency for microgrid systems, and the lacking ability to evaluate and implement lessons-learned and best-practices from successfully deployed microgrids. Existing solutions provide partial support, narrowly focusing on either financial optimization, technical modeling, or operational control, but do not offer an integrated database that brings together comprehensive datasets, predictive analytics, and realtime insights. This project proposes the development of an AI-powered microgrid database that will curate critical data sources, leverage artificial intelligence and machine learning (AI/ML) for predictive modeling, and provide stakeholders with an intuitive and simple user experience for scenario analysis and decision-making. This innovative solution will bridge critical data gaps to overcome perception issues and accelerate the market adoption and commercialization of microgrids by integrating microgrid data with AI-powered analytics and advanced machine learning for more precise financial and technical planning as well as insights to ensure that traditional and emerging energy resources are utilized, advanced and accelerated effectively. During Phase 1 the project will employ a federated data approach commencing with publicly available data. Additionally, AI/ML models- including clustering, regression, and deep neural networks- will be trained and tested, alongside frontier modeling techniques and natural language processing to extract hidden insights from a variety of data sources, laying the foundation for the next phase. In Phase II, the database will incorporate greater privacy controls and measures to temper cybersecurity risks for business owners. Advanced AI integration will provide insights that are more personalized, relevant, and based on real time, approved business data and mature the application for commercialization.