By Rémy sfez, business manager network - February 21, 2018
Big Data as a means to keep Energy OpEx under control
For many Telecom operators (Telcos), energy OpEx exceed 20% of total OpEx, especially in developing countries. With stagnating ARPUs, increasing competition and more investments required to meet consumers and businesses’ data needs, keeping control of energy consumption is becoming a critical objective.
Controlling energy consumption has a positive impact on both spending and image
Reducing energy consumption impacts a business in several ways:
- By decreasing its Energy OpEx: Energy OpEx depends on energy -consumption and –price. In countries where energy prices are soaring, energy OpEx can become a huge share of costs.
- By reducing its carbon footprint: this is key from the perspectives of :
o Company rating: some rating agencies take into account Social Responsibility as part of their assessment criteria
o Image: some customers may churn in the favor of a Telco whose “green” reputation is well known, and
o (potentially) carbon taxes
Carbon footprint depends on energy consumption and on the emission factor of the country where the Telco operates (which reflects the extent to which this country’s energy mix is based on carbon).
IT & networks are a major source of energy consumption
As a typical figure, approximately 80% of a Telco’s energy consumption is from their IT and Networks (ITN), with buildings and vehicles accounting for the remaining 20%.
Big Data: a powerful way of identifying sources of ITN energy savings
Many sources of information are available to Telcos, to help them keep control of their ITN energy OpEx:
• energy invoices
• energy probes (measuring energy consumption, at least at the site level)
• the ITN equipment OSS (Operating Sub-Systems), possibly with information on: traffic, QoS, energy consumption, settings, temperature …
• network- and site- inventories
To date, still very little of this data is used to control the ITN energy OpEx: Big Data is a means to combine these many pieces of information in order to detect and leverage areas of energy OpEx savings: the key to this approach is to find appropriate use cases.
“Cost Assurance” use cases may be the simplest ones to implement. They are applicable to the Telco’s contracts with 3rd-Parties like Power companies, Tower companies, RAN sharing partners, ...
- Detection of invoicing errors: this generates refunds to the Telco
- Optimization of the subscribed power: given the consumption profile of a site, its subscribed power may be optimized so as to reduce the overall fees for energy consumption and for subscription.
More complex use cases may be relevant to the operation (or even the engineering) of ITN equipment. For example, Big Data may be used so as to
- Assess and benchmark the energy efficiency of a site in its operation phase (by using the PUE – Power Usage Efficiency – indicator)
- Identify sites whose energy efficiency is significantly low (as per the benchmark) and
- For such sites, identify areas of energy efficiency improvement, which may be diverse:
o correction of temperature settings,
o replacement of air conditioning with a more efficient solution (eg hybrid air conditioning / free cooling, ventilation..)
o swap of obsolescent rectifiers
There are actually numerous possible use cases, and part of the effort is to analyze data, “create” impactful use cases (ie “quick wins” or use cases whose savings potential is high) and specify them for Big Data implementation.
The road to comprehensive Big Data implementation is long, but perspectives are very promising: Google recently announced that they achieved 15% energy savings for some of their Data Centers thanks to this approach.