TCS Clever Energy™

As per various energy council reports, a building consumes nearly 40% of world energy and emits 1/3^rd of GHG emission. Heating, Ventilation and Air conditioning (HVAC) are the primary energy consumers. Similarly, the industrial sector uses more delivered varied energy sources, consuming about 54% of the world’s total delivered energy. In the new normal, energy usage patterns are unpredictable, and the size and complexity of enterprise operations pose a challenge in understanding the energy footprint as well as opportunities for conservation. This greatly affects an organization’s ability to make informed decisions without compromising their business needs, be it for driving energy conservation initiatives, or to recognize the cost-saving and shift them towards net zero-emission.

TCS Clever Energy™ solution provides a comprehensive platform covering the varied energy functions of an organization that includes heating and cooling, process energy optimization, demand response, intelligent tariff management and carbon management. Its intelligent end-to-end architecture that supports integration of heterogeneous systems and assets such as smart meters and sensors, Building Management/Automation Systems (BMS), PLC/SCADA and so on, across enterprise, built in Digital Twin setup and AI/ML-based data models with augmented intelligence provide an integrated energy view, enables organizations to take an informed decision through predictive analytics and helps them to be energy efficient.

With this solution, we provide various distinguishing features to address an organization’s Energy and Emission Management concerns:

• Acquire real-time energy data from diverse infrastructure spread across geographies and legacy and proprietary systems to provide usage trend and actionable insights.
• Digital Twin setup and cognitive analytics enable to take an informed decision through predictive analytics to improve energy efficiency.
• Self-learning and Self-optimization features enable to adapt new buildings, new consumption patterns, outages, weather, and occupancy patterns.