Building Automation System Architecture and Monitoring Solution
The BAS adopts a three-tier network architecture: the management tier (workstations and servers), the control tier (DDC controllers), and the field tier (sensors and actuators). The management tier performs data acquisition and report generation via Ethernet. The control tier uses BACnet or Modbus protocols. A five-star hotel BAS typically has 1500-3000 monitoring points. Key monitoring objects include the cooling and heating source system, HVAC system, water supply and drainage system, lighting system, and electrical system. The most core function is energy-saving optimization control of the HVAC system, achieving dynamic optimized setpoint of chilled water supply temperature through PID regulation.
Energy Management System and Data Analytics
EMS is an energy consumption management platform that works in coordination with BAS, consisting of smart metering instruments, data acquisition gateways, and analysis software. Electricity is metered by category: lighting, HVAC, power, kitchen, etc.; water is metered by category: domestic hot water, cooling tower makeup water, etc. GB 50189 requires that public buildings with a floor area exceeding 20000 m2 should be equipped with an energy management platform. Data analysis functions include energy consumption trend analysis, benchmark analysis, anomaly alarms, and quantification of energy-saving effects.
Guest Room Intelligent Control System and Energy Saving
The RCU system achieves intelligent control of the guest room environment through thermostat panels, door magnetic sensors, and key card switches. Core functions include key card power activation, temperature control, lighting control, and do-not-disturb indication. Through occupancy sensing and door magnetic linkage, it automatically adjusts the air conditioning temperature in unoccupied states (raised to 26°C in summer and lowered to 18°C in winter) and turns off unnecessary lighting. Taking 400 guest rooms as an example, the RCU investment is approximately 1.2-2 million yuan, saving approximately 350,000-500,000 yuan per year in electricity costs, with a payback period of approximately 3-5 years.
Intelligent O&M and Predictive Maintenance Platform
The intelligent O&M platform collects real-time status data such as vibration, temperature, current, and noise through wireless sensors, and uses machine learning algorithms to predict potential failures. Core functions include real-time equipment status monitoring, fault early warning (accuracy above 85%), automatic generation of maintenance work orders, and intelligent spare parts recommendations. The investment in an intelligent O&M platform is approximately 1.5-2 times that of a traditional BAS, but it can reduce unplanned downtime by more than 80% and extend equipment life by 15%-20%.