Automation's Role in Decarbonizing India’s Industrial Cooling Systems

In an interaction with Thiruamuthan, Correspondent, Industry outlook, Abhishek Sarmah, Head IAQ Business Group at Delta Electronics India, discusses how advanced automation through PLC-integrated VFDs, sensor-feedback loops, edge controls, and AI-driven orchestration is transforming industrial cooling by cutting energy use, reducing Scope 2 emissions, enabling ESG compliance, and overcoming legacy system integration challenges. Abhishek, a seasoned business leader with over 15 years in the ESDM industry, excels in strategic management, sales, and sustainability. Recognized for driving innovation and market growth, he has delivered impactful results across telecom, renewable energy, automotive, and HVAC sectors.

How are PLC-integrated VFDs reducing load variance and emission spikes in real time?

India’s industrial cooling systems, particularly in process-heavy sectors like manufacturing and pharma, are known for high and often fluctuating power demands—making them significant contributors to Scope 2 emissions. PLC-integrated Variable Frequency Drives (VFDs) address this by enabling precise, real-time control over motors and compressors. These systems dynamically adjust motor speed based on cooling demand, reducing unnecessary power draw during low-load conditions.

Our industrial automation solutions combine smart PLCs with VFDs, delivering fine-grained control, eliminating start-stop cycles, and thus flattening load curves. This not only lowers grid stress but also improves energy efficiency, offering up to 30–40 percent energy savings and measurable Scope 2 emission reductions across industrial facilities.

How are automated sensor-feedback loops optimizing chiller efficiency and reducing energy per ton?

Chillers are often the largest energy consumers in industrial cooling. When operating at fixed loads or without real-time feedback, their kilowatt-hour (kWh) per ton performance deteriorates. The integration of automated sensor-feedback loops using pressure, temperature, and flow sensors enables dynamic load management.

Our advanced control platforms allow these sensors to continuously monitor environmental and operational variables. The data is then fed into the chiller’s logic controller, which adjusts setpoints—like water flow rate or compressor speed—in real time. This results in improved Coefficient of Performance (COP) and optimized part-load operation, ultimately reducing energy consumption by 20–25% per ton of refrigeration delivered.

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What are the key protocol-level challenges in retrofitting automation with legacy BMS?

Legacy Building Management Systems (BMS) often operate on outdated or proprietary communication protocols, which limits interoperability. When attempting to deploy digital twins or edge automation systems, protocol mismatches (e.g., BACnet vs. Modbus or LonWorks) can prevent seamless data exchange, creating data silos and control lag.

Delta’s open-protocol architecture and use of protocol converters and middleware gateways enable smooth integration with existing BMS infrastructure. However, common challenges include lack of metadata standardization, time sync issues, and limited backward compatibility. Industry-wide, the move toward standardized, open BMS protocols like BACnet/IP and MQTT is essential to make retrofits scalable and future-ready.

How are automation systems tracking refrigerant leakage and runtime for ESG reporting?

As ESG mandates tighten, companies must track not just energy use but also refrigerant leakage and equipment inefficiencies that contribute to indirect emissions. Delta’s automation systems integrate smart flow meters, leak sensors, and runtime diagnostics with edge-based data loggers, enabling real-time monitoring of refrigerant levels, compressor health, and cooling runtime.

Data is aggregated into dashboards with automated carbon reporting features, allowing facilities to quantify emission reductions due to fewer leak events or reduced excess runtime. These insights support accurate ESG disclosures aligned with frameworks like GRI and CDP. Moreover, predictive alerts help preempt failures, ensuring continuous compliance and operational integrity.

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How are edge-automated cooling systems helping reduce peak demand and emissions in sectors like textiles and data centers?

Textile units and data centers both operate under high and fluctuating thermal loads, making cooling a critical energy challenge. Delta’s edge-automated cooling systems apply predictive control logic at the source, using machine learning algorithms to anticipate peak load conditions and preemptively adjust cooling parameters.

This local intelligence reduces reliance on centralized BMS and avoids abrupt demand spikes. Features like demand-response readiness, compressor sequencing, and adaptive fan control enable facilities to optimize performance during peak grid hours—resulting in lower demand charges, enhanced equipment life, and overall emissions reduction. In data centers, such automation also contributes to lowering Power Usage Effectiveness (PUE).

How viable is AI-powered cooling orchestration for autonomous industrial environments?

As India advances toward Industry 4.0, AI-driven cooling orchestration systems are becoming increasingly viable. These systems go beyond traditional automation by predicting thermal loads based on occupancy, weather, process intensity, and machine activity, and then self-adjusting to minimize carbon output.

We are actively working on integrating AI modules into its automation and edge-control platforms, enabling facilities to move toward autonomous cooling decisions. The technology is particularly useful in environments with variable load patterns—like EV manufacturing, pharma cleanrooms, and smart warehouses. However, widespread adoption will depend on infrastructure readiness, data quality, and workforce upskilling.