The project centers on an energy router as its core equipment, which integrates with a 10kV distribution network system to directly convert grid power into a 750V DC supply. This system embodies an integrated “Power-Grid-Load-Storage” model combining distributed PV, advanced energy storage, DC power distribution, and intelligent flexible control technologies, alongside multi-scenario charging solutions including ultra-fast charging, fast charging, and V2G. Enabled by an exclusive intellectual property-backed integrated energy management platform, it achieves dynamic interaction between the PV-Storage-DC-Flexible-Charging infrastructure and the building’s conventional electricity usage.

The platform empowers enterprises to identify carbon reduction opportunities throughout the power equipment product lifecycle, uncover the carbon reduction potential within the supply chain, advance green supply chain management, and assist power equipment manufacturers toward a green and low-carbon future. The platform calculates the carbon emissions throughout the full lifecycle, provides feedback on emissions at each stage, and traces product carbon footprint to reduce supply chain carbon output. The platform possesses models for various power equipment production processes, features rapid calculation and loading capabilities, and combines a comprehensive emission factor database with precise data matching to ensure data credibility. It helps enterprises discover potential carbon reduction spaces and create enhanced green value. The platform fulfills requirements for carbon footprint calculation, disclosure, and management.

The system functions as a multi-capability "intelligent brain", executing crucial roles in energy management through perception, analysis, and decision-making. The platform collects variables including voltage, current, power, power factor, operational status, temperature, and humidity from energy-consuming equipment or energy measurement devices. It then conducts in-depth mining and analysis of these data to identify peak and off-peak energy usage patterns. Ultimately, enabling energy consumers to establish suitable energy management systems, achieving goals such as authentically reflecting their energy usage information and energy-saving status, optimizing energy allocation, and predicting future energy consumption patterns.