NRGISE – Battery Integration and Optimization for Energy Production

Co-developed for: Fraunhofer ISE (2023-2025)

Tools used: Python · FastAPI · Flask · Dash · Streamlit · Flask-SQLAlchemy · pandas · NumPy · Docker · Kubernetes · GitLab CI/CD · Linux · Git

NRGISE.ONE is a commercial SaaS product suite developed at Fraunhofer ISE — Europe’s largest solar energy research institute — that enables energy planners and operators to design and control battery storage systems in an economically optimised way. The platform combines AI-based optimisation algorithms with detailed battery models to help customers maximise return on investment across use cases like peak shaving, PV self-consumption optimisation, and energy arbitrage.
As a full-stack Python developer on the Applied Storage Systems team, I contributed to the development and maintenance of the web application frontend and backend, simulation and data processing pipelines, and the deployment and testing infrastructure for the platform over almost two years.
What I worked on:

• Frontend development using Dash and Streamlit for interactive simulation result visualisation and configuration interfaces
• Backend API development with FastAPI and Flask; database layer with Flask-SQLAlchemy for tiered subscription and user management
• Data processing pipelines using pandas and NumPy to evaluate battery system performance metrics and cost/savings projections across configurable scenarios
• CI/CD pipeline setup and maintenance with GitLab Actions, integrating pytest and unittest test suites for automated testing and deployment
• Linux server administration, Docker containerisation, and Kubernetes-based workload management
• Parallelisation of simulation workloads to improve computational performance

Images courtesy of Fraunhofer.