Siemens Partners with Vigilent
Electrification and automation giant Siemens has strengthened its partnership with and made an investment in dynamic cooling optimization specialist Vigilent to broaden its thermal optimization offerings for datacenter operators.
The addition of Vigilent's software should enable Siemens to extend its Building Performance & Sustainability offering into addressing cooling inefficiencies in the white space. Its latest offering - White Space Cooling Optimization - uses machine learning, automation and controls to generate energy savings and more reliable infrastructure.
The datacenter sector is at the early stages of broader adoption of artificial intelligence (AI) technology to improve facility efficiency, availability, management and capacity planning. Vigilent provides the machine-learning software to dynamically manage datacenter cooling equipment, enabling cooling systems to be flexed in real time based on the IT load and environmental conditions - and generating significant energy savings. When integrated with other facility-improvement measures from Siemens such as Demand Flow, datacenter operators can further optimize operational performance spanning from the cooling tower to the server rack and ensure greater reliability of facilities.
With this partnership, Siemens' thermal optimization for datacenters can now address both chiller plant and white-space cooling optimization. The goal is to improve datacenter energy efficiency and reliability by optimizing the performance of the cooling systems. The offering set also encompasses various facility improvement measures such as airflow management, containment systems, hot-spot analysis and adjusted supply water temperature setpoints.
These offerings fall under Siemens' Building Performance and Sustainability (BPS) group, which consists of 800 employees across 30 countries. BPS's strategy is to improve building (including datacenters) performance through energy and sustainability advisory services using a total energy management approach (supply and demand-side) and technical asset (e.g. chiller, pumps, etc.) performance optimization. The company says its BPS unit guaranteed customers total savings of €147m ($168m) globally in 2017 and exceeded this guarantee by 23% on average.
BPS services also include supply-side power generation (e.g. cogeneration, photovoltaics, energy storage) where the company says customer demand is high for off-grid resiliency offerings, particularly from datacenter operators. Other datacenter-specific macro-level trends that the company considers demand drivers for its BPS offerings include more software-driven/data-driven datacenters, the Internet of Things (IoT) and edge computing, and the convergence of IT and facility management, among others.
All part of the wider IDCMS offering, the Vigilent system will be integrated into Siemens' Desigo CC building management platform and leverage the automation capabilities of the BMS. Data generated by the Vigilent system is expected to be available soon on its Clarity LC DCIM via the BMS platform. In the meantime, alarms from Desigo CC can be pushed to Clarity LC using existing integration.
From a go-to-market perspective, Siemens intends to reach beyond datacenters into verticals such as airports. The company reports that it already has 80,000 buildings (including datacenters) connected to its IoT cloud platform that can potentially be addressed. One option available for datacenter owners and operators is Siemens' off-balance sheet financing option called Building Efficiency as a Service. This delivery model leverages its Financial Services division to finance an upgrade project, for instance, and the customer would pay a portion of the realized energy savings back to Siemens on a quarterly or otherwise basis.
For more than eight years, Siemens has provided Demand Flow (chiller plant optimization), which is available globally. This offering focuses on simplifying chiller SYStem operations and ensuring environmental quality (e.g. controlling humidity) and more efficient runtime, which should extend the lifetime of the equipment. The company claims that its Demand Flow services have resulted in 20-50% energy savings on average for its costomers.
Historically, projected variations in IT loads led to the design of datacenter cooling SYStems that were overprovisioned for the white space and were susceptible to hot spots. As part of its White Space Cooling Optimization offering, Siemens can now address these inefficiencies by using Vigilent's SYStem to automate and control cooling in the white space.
The Vigilent SYStem provides continuous monitoring by collecting environmental and power data from sensors at the IT rack level and on the cooling units. This data is transmitted wirelessly to a network manager unit, which forwards it to Vigilent's AI engine. There, the software aggregates the collected data, employs machine learning to determine the influence of each cooling unit across the white-space floor, and develops a predictive model to determine the optimum settings. The control commands are then sent through the network manager to modules on the cooling equipment.
This approach replaces fan setpoints on the air-handling units with dynamically optimized fan speeds based on workload demand and in real time. The Vigilent machine-learning algorithms then learn from the effects of previously transmitted control actions and improve over time. Essentially, the cooling capacity is converted from fixed to variable to match variations in IT loads at the rack level.
The key benefits of white-space cooling optimization include lower energy costs, improved IT capacity utilization (e.g. identifying stranding capacity), real-time insights into operational and asset performance, predicting equipment issues before they occur, and more reliable environmental conditions. The effect is greater datacenter reliability and availability. Vigilent notes that across over 500 installations of its SYStem, customers have experienced a 38% savings on cooling energy on average.
Siemens measures the simple energy savings payback for its thermal optimization offering set at two to three years. In addition, thermal risk can be reduced and maintenance decisions can be more informed.