Data Centre Energy Efficiency With DeepCtrls
Energy Optimization Solutions | Energy Management System & Data Centre Cooling Singapore
AI-Powered Energy Optimization Platform for Smart Buildings & Industrial Facilities
Singapore operates one of the highest concentrations of data centres in Asia, consuming approximately 7% of the nation’s total electricity. The Infocomm Media Development Authority (IMDA) has responded with strict Power Usage Effectiveness (PUE) requirements and a framework for sustainable data centre operations that makes energy management no longer a cost centre consideration but a regulatory compliance requirement.
LHS delivers DeepCtrl’s AI-powered energy optimization platform to data centres, manufacturing facilities, and commercial buildings in Singapore and Southeast Asia — reducing energy consumption by 10–40% without equipment overhaul, using the power of PhyAI intelligent optimization technology.
Why Choose DeepCtrl’s Energy Management System Platform?
Real-time energy analytics powered by advanced physics-based AI (PhyAI™)
Predictive control modeling with <3% Root Mean Square Error
Plug-and-play deployment (installation in just 1–2 days)
Zero disruption to your existing infrastructure
Supports compliance for ESG and carbon reduction goals
DeepCtrl — Our Energy Optimization Platform
DeepSys-HVAC: Real-Time HVAC Optimization
DeepSys-HVAC uses PhyAI — a physics-informed artificial intelligence model — to optimise HVAC system performance in real time. Rather than applying fixed setpoints, the system continuously models the thermal behaviour of the building or data hall and adjusts chiller setpoints, air handling unit parameters, and cooling tower operations to minimize energy consumption while maintaining the required temperature and humidity conditions.
The Foxconn implementation demonstrated the scale of what is possible: DeepSys-HVAC deployed across 36 sites achieved significant energy reductions through smart adjustments to HVAC water flows and terminal equipment logic — with zero equipment replacement required.
DeepSys-CDA: Compressed Dry Air Optimization
Compressed dry air (CDA) systems are significant energy consumers in manufacturing facilities, consuming up to 30% of total facility electricity in some industrial environments. DeepSys-CDA applies the same AI optimization approach to CDA generation and distribution — dynamically adjusting compressor staging and pressure setpoints to match actual demand while eliminating the energy waste of fixed-pressure operation.
Data Centre Cooling Optimization
Data centre cooling is the largest energy consumer in most Singapore data centers — typically accounting for 30–40% of total facility power. DeepCtrl’s data center cooling optimization module addresses this directly, applying AI to chillers, cooling towers, CRAC units, and airflow management to achieve PUE improvements that fixed-rule BMS systems cannot match.
For Singapore data centers operating under IMDA’s Green Data Centre (GDC) roadmap, which targets a sector-wide average PUE of 1.3 or below, DeepCtrl provides a software-only path to PUE improvement that does not require the capital investment of hardware upgrades.
Energy Management System Integration
DeepCtrl integrates with existing Building Management Systems (BMS), SCADA platforms, and energy metering infrastructure — providing a unified energy management layer that enhances the optimisation capability of existing systems without requiring replacement. The platform generates detailed energy consumption reports and analytics that support both internal performance management and regulatory reporting requirements.
Where It Works
Optimize energy efficiency across:
- HVAC systems in factories, data centre cooling system, and hospitals
- CDA (Compressed Dry Air) systems in semiconductor fabs
- PV-coupled energy grids with load balancing and storage
- Chiller plants, CRAC units, and air handling units
- Energy-intensive equipment with high maintenance loads
How the Platform Works
(EV Charger Park Example)
Step 1
DeepBox edge computing device captures real-time facility data
Step 2
DeepLogic builds a physics-informed digital twin
Step 3
DeepSight enables drag-and-drop system configuration
Step 4
“One-Switch Validation” confirms savings in <10 minutes
Step 5
Full deployment is rolled out via DeepOS and DeepReport
Singapore Data Centre Regulations & Energy Compliance
IMDA’s data centre policy framework includes requirements for minimum energy efficiency standards, regular energy audits, and disclosure of PUE performance. Facility operators who fail to meet these standards face regulatory risk and potential restrictions on expansion capacity.
DeepCtrl’s detailed energy reporting and PUE tracking capabilities provide the documentation required for IMDA compliance reporting — making the platform not just an energy saving tool but a regulatory compliance asset for Singapore data centre operators.
Real Case Study
Public Case Study: Foxconn (36 Manufacturing Sites)
Foxconn implemented DeepCtrl’s DeepSys-HVAC and DeepSys-CDA across 36 sites for real-time system-level optimization. This included smart adjustments to CDA pressure, HVAC water flows, and terminal equipment logic.
Results:
• 💡 50+ million kWh saved annually
• ⏱ 70% efficiency gain in facility energy management
• ⚙️ Zero change to plant layout or production systems
Source:
DeepCtrl Project Showcase (PDF)
Other Proven Deployments
CATL
17 sites, Chiller & dehumidifier optimization
BOE
16 bases, >8% HVAC savings
Canadian Solar
25% total energy reduction
China Unicom
36 data centers, 17%+ reduction
Metro stations & hospitals
20–40% average HVAC savings
Core Features of DeepSys™ & DeepOS™
-
DeepBox
Edge AI controller for data capture and actuation -
DeepLogic
System-level modeling engine for real-time prediction -
DeepSight
Low-code interface for control logic configuration -
DeepReport
Automated reporting for ESG, carbon & energy KPIs -
DeepOS
Unified operational dashboard with alerting & lifecycle analytics
Frequently Asked Questions
1. What is an Energy Management System (EMS) and how does it reduce energy costs?
An Energy Management System (EMS) is a platform that monitors, analyses, and optimizes energy consumption across a facility or portfolio of facilities. Unlike basic BMS controls that apply fixed schedules and setpoints, an advanced EMS uses real-time data and AI models to continuously optimise energy use — identifying and eliminating waste that fixed-rule systems miss. DeepCtrl’s EMS delivers 10–40% energy savings across HVAC, CDA, and cooling systems.
2. How does DeepCtrl optimise data centre cooling without equipment replacement?
DeepCtrl installs software and sensors on existing cooling infrastructure without modifying the hardware. The PhyAI model learns the thermal characteristics of the data centre and begins optimizing chiller setpoints, cooling tower operations, and airflow management in real time. The physical cooling equipment remains unchanged — DeepCtrl makes it work smarter, not harder.
3. What is PUE and how does DeepCtrl help Singapore data centres meet IMDA requirements?
PUE (Power Usage Effectiveness) measures how efficiently a data centre uses energy — a PUE of 1.0 is perfect efficiency (all power goes to IT equipment), while higher values indicate energy wasted in cooling and power distribution. IMDA’s Singapore data centre guidelines target a sector PUE of 1.3 or below. DeepCtrl’s cooling optimization directly reduces cooling energy consumption, improving PUE without hardware capital investment.