The cooling and heating cogeneration system of distributed new energy stations is composed of modules such as energy production, energy conversion, energy storage and transmission, and control management. It adopts new energy sources (such as solar energy, wind energy, geothermal energy, air energy, etc.) to realize cooling and heating cogeneration. By utilizing IoT technology and the powerful computing power and data processing capability of cloud servers, it achieves optimal cloud-edge-end control over the equipment of new energy stations, enabling on-site autonomous regulation and remote optimization on the cloud.
Applicable to commercial parks, hotels, industrial plants, hospitals, banks, agricultural greenhouses, residential communities and other areas requiring cooling and heating supply.
Functional Characteristics
• It can provide scheme design for distributed energy stations, and by utilizing BIM modeling, offer digital and visual management methods throughout the full life cycle of construction, operation and service.
• Adopting PLC controllers and edge computing controllers developed by Hetong Information, it provides a human-machine interface to realize on-site control.
• Through 4G networks, remote monitoring and on-site unattended operation are realized, which improves work efficiency and service quality.
• Accurate heat load prediction: Based on data regarding ambient temperature, indoor temperature, water supply temperature, heat output, weather forecast, and temperature equalization system, it accurately calculates the heat load demand and target water temperature demand.
• Precise water temperature control: The cloud-based cluster control strategy can control the water temperature error to be ≤1℃. Compared with the water temperature threshold control methods of existing technologies, it not only improves the quality of heating and cooling supply, but also prolongs the operating time of heat pumps under stable working conditions and enhances the energy efficiency of the unit.
• Realize cluster regulation: Enable interconnection and intercommunication among the equipment within the station to achieve cluster control.
• AI services, energy conservation and carbon reduction: supporting one park with multiple modes (single selection) and one mode with multiple strategies (multiple selections), realizing one model per station. It conducts machine learning on equipment feedback data, with different control strategies applied to different stations.
