An advanced analytics platform
The Energy.ML platform provides monitoring, predictive analytics, self-serve analy-sis, and reporting functionality for operators, asset managers, and O&M service providers.
- The monitor module provides an overview of performance KPIs at a fleet, project, and turbine level
- The analyze module provides powerful self-serve analytics capabilities and allows users to gain insights into the behavior and health of their as-sets.
- Fully deployed on AWS infrastructure
- The predict module provides details on the health of turbine compo-nents and behaviors for mechanical (bearings, hydraulic cylinders, gear-boxes, pumps, etc.) and electrical (generators, transformers, power con-vertors, etc.) components
- Energy.ML platform is feature rich with modules like Alarms, Reports, Maintainence, Energy Calculator etc.
- User customisable beautiful dashboards
Online Video, QA
Effort and Duration:
3 months, 12 man-months
• Python/Django • Reactjs • DB -> Relational, NonRelational • SearchEngines • Data Processing Pipelines • Deployment Pipelines • Process Scheduling
Challenge here was to build a system which will continuously consume & process huge volumes of real time and historical data.
The processing of data should be quick enough to provide real time monitor-ing of resulting analysis and predications.
A micro-service based architecture, where many system with single responsibility principles are working together to provide monitoring, analysis & prediction.
Ensemble Energy is able to assist wind operators to reduce the cost of renewable energy and increase its adoption around the world by employing data science and advanced analytics with physics-based methods to accurately and quickly identify underperforming assets, predict failures, and in many cases, prevent failure from occurring.
We have had the pleasure of working
with some fantastic organisations
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