NetZero v1.0.0 – Initial Production Release
Overview
Version 1.0 represents the first complete release of NetZero, a carbon-aware energy management platform developed to optimise building energy consumption using thermodynamic modelling and real-time electricity grid carbon intensity forecasts. This release delivers the complete Minimum Viable Product (MVP) together with several advanced features planned for the Minimum Lovable Product (MLP).
Features
Core Functionality
- User authentication and account management
- Building profile creation and management
- Thermodynamic digital twin generation
- Flexible asset registration and management
- Regional postcode mapping
- Carbon intensity forecast ingestion
- Machine learning-based heating and cooling load prediction
- Carbon preference configuration
- Carbon-aware operational schedule generation
- Interactive operational dashboard
- Automated load modulation
- Retrofit simulation
- Portfolio dashboard
- ESG reporting
- Sustainability report generation
- Predictive notification infrastructure
Technology Stack
Frontend
- Next.js
- TypeScript
- Tailwind CSS
- shadcn/ui
- Recharts
Backend
- Django REST Framework
- Python
Machine Learning
- PyTorch
Database
- PostgreSQL (NeonDB)
Deployment
- Vercel
- Render
Testing
This release has been validated through comprehensive testing, including:
- Unit Testing
- Integration Testing
- Regression Testing
- API Testing
- Machine Learning Model Evaluation
Testing confirmed the correctness of frontend components, backend services, database interactions, authentication workflows, scheduling logic, and forecasting functionality.
Documentation
This release includes:
- Software Requirements Specification
- Agile Requirements Framework
- Architectural Design Document
- UML Diagrams
- Sprint Reviews
- Testing Documentation
- Deployment Documentation
- Dissertation Report
Release Information
Version: v1.0.0
Status: Production Release
This release represents the completion of the NetZero software engineering project and establishes a scalable foundation for future enhancements, including advanced optimisation algorithms, expanded renewable energy integration, and enhanced predictive analytics.