Getting Started with Smart Cool Tech

Smart Cool Tech is delivered as a turnkey solution. Our team handles all installation, configuration, and model training.
You only need to provide:

Required Information

1. Building Information

The following building information must be provided during system setup:

Information	Description	Example
Building Name	Official name of the facility	Elements Tower
Location	City and country	Hong Kong
GPS Coordinates	Latitude and longitude	22.3055° N, 114.1613° E
Building Type	Commercial, residential, mixed-use	Commercial
Total Floor Area	Gross floor area	50,000 m²
Operating Hours	Normal operating schedule	08:00 - 22:00

---

2. Chiller Specifications

Minimum Requirement

At least 4 chillers are required for optimal sequencing.

For each chiller, the following specifications must be provided:

Parameter	Description	Unit	Example
Chiller ID	Unique identifier	-	CH-01
Manufacturer	Equipment manufacturer	-	Trane
Model Number	Manufacturer's model	-	CVHG1100
Chiller Type	Water-cooled, air-cooled, seawater-cooled	-	Water-cooled
Rated Cooling Capacity	Nominal cooling capacity	kW	3,500
Rated Power Consumption	Nominal electrical power input	kW	580
Design COP	Coefficient of Performance at design	-	6.03
Minimum PLR	Minimum Part Load Ratio	%	30
Maximum PLR	Maximum Part Load Ratio	%	100
Minimum On Time	Minimum continuous running time	minutes	30
Minimum Off Time	Minimum time before restart	minutes	30

---

3. Real-Time Data Access

The system requires API access to 10 data points per chiller:

#	Data Point	Description	Unit
1	chiller_status	On/Off operating status	Boolean (0/1)
2	cooling_load	Current cooling load output	kW
3	power_consumption	Current electrical power input	kW
4	chws_temp	Chilled water supply temperature	°C
5	chwr_temp	Chilled water return temperature	°C
6	cdws_temp	Condenser water supply temperature	°C
7	cdwr_temp	Condenser water return temperature	°C
8	chw_flow	Chilled water flow rate	L/s
9	cdw_flow	Condenser water flow rate	L/s
10	part_load_ratio	Part load ratio	%

Notes

• If cooling_load is not directly measured, it can be calculated from flow rate and temperature difference
• If part_load_ratio is not available, it can be derived from cooling load and rated capacity

---

4. Historical Data

Critical Requirement

Minimum 1 year of historical data required for model training.

Requirement	Specification
Minimum Duration	At least 1 year
Data Completeness	> 90% availability
Data Format	CSV, Excel, or API
Timestamp Format	ISO 8601 (e.g., 2024-01-15T08:30:00+08:00)

Why 1 year?

• Captures seasonal variations
• Includes various weather conditions
• Enables accurate ML model training
• Provides baseline for energy savings comparison

---

5. API Access Requirements

For real-time data collection:

Requirement	Description
API Type	REST API, BACnet/IP, Modbus TCP, or OPC-UA
Authentication	API key, OAuth, or certificate-based
Access Level	Read access to all specified data points
Network	Secure connection (HTTPS, VPN, or dedicated line)
Availability	24/7 access with > 99% uptime

---

Next Steps

Once you provide the required information:

1. Week 1: Our team surveys your system and creates Brick model
2. Week 1: Historical data collection and preprocessing
3. Week 2: Model training (BNN for COP, XGBoost for load forecasting)
4. Week 2: System integration and testing
5. Week 3: Dashboard deployment and operator training
6. Week 3: Go-live with monitoring

Deployment Timeline

From initial assessment to full operation: < 1 week

---

Support

For questions or to get started:

📧 Email: [email protected]
⏰ Response Time: 1-2 business days