How Digital Transformation Can Advance the Decarbonization of Data Centers

Increasing demand for data processing and storage is catalyzing energy consumption.

The data center industry already accounts for 1% of global electricity use. This rising demand directly impacts electrical infrastructure as growingly complex devices are generating torrents of data. The costlier solution to more sustainable operations is implementing updated hardware and energy storage technology in every data center. However, a more affordable, immediate remedy can be found in software technology.

As advancements in digital technology continue to require digital infrastructure to make it all work – fiber, network, storage, etc. – the demand for digital infrastructure that happens behind the scenes often goes unnoticed. This invisible infrastructure for data centers encompasses a wide range of systems and technologies that are essential for the reliable, efficient operation of data centers but are not typically visible to end users or customers.

As digital technologies are utilized to decarbonize data centers across the globe by optimizing energy usage, how can organizations best harness the power of digital transformation to optimize efficiency and lower carbon emissions at their data centers?

Increasing Efficiency with Data Center Infrastructure Management Tools

Data Center Infrastructure Management (DCIM) tools help organizations manage and monitor their data centers, playing a critical role in maintaining the uptime and efficiency of these hubs. With real-time monitoring, asset management, capacity planning, and automated reporting, organizations can ensure they’re effectively managing the energy and operational efficiencies of their data centers, quickly identifying and resolving potential issues.

DCIM technology provides real-time monitoring of data center operations, including monitoring the health of servers, storage systems, and network devices. A centralized view of all data center assets, including servers, storage systems, and networking equipment, helps administrators track equipment utilization, warranty information, and service records. Tracking the usage of power and cooling resources and alerting administrators when there is a potential issue prevents downtime caused by power and cooling failures.


Environmental conditions in the data center, including temperature, humidity, and airflow, can also be monitored by DCIM tools. This helps ensure that the data center operates within the recommended environmental conditions, reducing the risk of equipment failure. Tracking and optimizing energy usage also helps to reduce energy costs and the data center’s overall carbon footprint.

Optimizing Usage with AI and Edge Computing in Smart Grids

With the appropriate infrastructure, smart grids have the power to alleviate the complexities of today’s energy generation and usage. Integrating artificial intelligence (AI) and edge computing in smart grids can help data centers improve their energy demand prediction, reduce waste, improve response times, and optimize energy storage.

One key area where AI can be utilized in smart grids is in predicting energy demand. AI algorithms can analyze data from various sources, such as weather forecasts, historical demand patterns, and other relevant factors, to make accurate predictions about energy demand. The data center can then use this information to manage energy consumption more effectively and minimize waste. Edge computing also plays a critical role in the smart grid space, as it allows data processing to occur closer to the source, reducing the amount of data that needs to be transmitted over the network and thus reducing latency and improving response times. It also notably enables real-time decision-making based on data analysis, which can lead to improved energy efficiency.

AI and edge computing can also optimize energy usage in smart grids by using smart sensors and smart devices. These devices can collect data on energy usage and transmit it to the data center for analysis, while AI algorithms then identify patterns and anomalies in the data, allowing for proactive maintenance and troubleshooting. Additionally, AI can analyze energy usage and battery capacity data to determine the ideal times to charge and discharge energy storage devices, reducing waste and improving efficiency as a result.

Advancing the Data Center Industry

Ultimately, the increasing demand for data processing and storage is driving up energy consumption in the data center industry. To address this challenge, organizations can implement DCIM technology to monitor and optimize energy usage in real-time while also using AI and edge computing in smart grids to predict energy demand and optimize energy storage. These technologies can help organizations reduce their carbon footprint and energy costs while maintaining the uptime and efficiency of their data centers. By leveraging the power of digital transformation, organizations can effectively decarbonize their data centers and contribute to a more sustainable future.

About the Author

Adam Compton is Director of Strategy at Schneider Electric. Our mission is to be your digital partner for Sustainability and Efficiency. We drive digital transformation by integrating world-leading process and energy technologies, end-point to cloud connecting products, controls, software and services, across the entire lifecycle, enabling integrated company management, for homes, buildings, data centers, infrastructure and industries.

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