Client Challenges
- Lack of Data Science and ML Engineering expertise with the core team of the Client
- Lack of experience in deployment of ML solutions as integrated parts of the complex Web-based platforms to work under high real-time load
- Existing forecasting techniques / methods do not provide the level of accuracy the Client needed to operate on the sustainable power grid-driven margins
Services
- Implemented the forecasting model to predict the wind power generation for every power generation facility of the customer in Europe (multiple locations in Germany, Switzerland, and Poland)
- Invented and programmed the original forecasting algorithm based on advanced fractal geometry concepts
- Implemented ML models
- Implemented Web API Wrappers around the ML models to make it ready for the customer product integration
Client: A EU-based Wind Power generation company.
Segment: ML, AI, Data Science
Users base: Hundreds of users in different country offices of the Client
Technology stack: Python, SQL
Team structure: 1 Sr ML Engineer, 1 Middle Data Scientist, 1 Jr Data Scientist