To reduce carbon emissions and promote sustainable development, VisEra implemented AI technology to upgrade its chiller systems for smart energy optimization, aiming to enhance efficiency and lower carbon output.
- AI platform was established to collect and process real-time operational data from the chiller system. It analyzed key metrics like outdoor temperature, system pressure, and chilled water output temperature.
- The platform built predictive models and identified critical control points affecting energy efficiency, such as compressor load, condenser temperature, and demand. These data-driven adjustments enabled dynamic optimization for precise energy savings.
- Distributed Control Systems(DCS) for remote automated control. Each chiller unit was equipped with independent control modules that, through the AI system, allowed both local and remote adjustments. This architecture improved system response speed and flexibility, enabling the equipment to adjust operations based on load demand and prevent energy waste.
- The AI system also features a data feedback function, continuously optimizing models through regression training to ensure the equipment operates at optimal efficiency in varying conditions. This self-learning mechanism further enhances system stability and reduces failures and maintenance costs.
This technology has resulted in a 4% energy savings and reduction in carbon emissions for the chiller system. This innovative approach not only lowers operational costs but also significantly improves the company's ESG performance.
