Overview
OptiGrid is an AI-driven decision management framework designed for energy utilities, smart cities, and industrial operators managing distributed energy resources (DERs). It leverages advanced analytics, real-time IoT data, and machine learning models to optimize generation, consumption, and storage within microgrids.
OptiGrid automates energy forecasting, demand management, and grid balancing using continuous learning pipelines built on AWS services such as Amazon SageMaker for ML model training and deployment, AWS IoT Core and AWS IoT Analytics for sensor and SCADA data ingestion, and Amazon Kinesis Data Streams for real-time data processing. Historical and operational data is securely stored in Amazon S3 and AWS Glue Data Catalog, enabling seamless analytics with Amazon Athena and QuickSight dashboards for energy insights.
By aligning with modern decarbonization and sustainability goals, the platform enables efficient renewable energy utilization, cost reduction, and operational reliability. Its modular, cloud-native architecture built on AWS Lambda, Amazon ECS (Elastic Container Service), and Amazon API Gateway ensures easy deployment, scalability, and interoperability with existing grid and enterprise systems supporting smarter, greener, and more resilient energy networks.
Highlights
- AI-Powered Decision Engine with Real-Time Data Intelligence: A unified intelligence layer that uses machine learning to optimize distributed energy generation, consumption, and storage while seamlessly integrating real time IoT, SCADA, and weather data for continuously improved decision-making.
- Scalable Cloud Architecture: Built on AWS compute and storage services for robust, high-performance energy optimization. Dynamic Load Management: Predicts and balances power supply-demand variations to maintain grid stability and efficiency.
- Renewable Energy Optimization: Maximizes solar and wind generation utilization through predictive analytics and automation. Flexible Deployment: Modular and API-driven design that integrates easily into existing energy management systems.
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