Leveraging the Internet of Things and Analytics for Smart Energy Management

Realizing Holistic Benefits through Analytics
Here are a few ways to leverage the IoT and analytics simultaneously to realize benefits across the energy
management spectrum:
Asset efficiency analysis: Asset efficiency can be calculated for a variety of assets in real time. This also
helps determine the cost implications of non-optimal device performance. The efficiency of assets can
drop due to age or maintenance issues. Benchmarking techniques compute the optimal efficiency levels
at which the devices should run under the given set of environmental conditions. This can be used to
identify scenarios involving excessive energy consumption within a building.
Root cause analysis: This can be performed in cases where a higher than expected level of energy was
consumed. Given the IoT enabled data, the hypothesis generated through root cause analysis can be
statistically validated.
Predictive analytics on asset maintenance: The cost implications of maintaining all energy consuming
devices can be determined using predictive analytics. Similarly, warranty lifetime analysis can also be
performed to arrive at the optimal warranty period and costs. If certain devices are observed to fail early
in their lifecycle, the warranty tenure is expected to be long enough to cover all such early lifetime
failures. Also, while the device might not be likely to fail as a whole, certain components might be more
prone to failure than others. Furthermore, warranty analysis acquires importance if the error-prone
components in the device are expensive.
Correction and exception analysis: Analytical techniques help identify areas where power factor
correction might be required early on to enable cost savings. Analysis of exceptions, alarms, and manual
overrides to EMS is important to highlight the discrepancies that are likely to be registered in operations
from time to time. Such analysis helps determine the optimal state, the factors responsible for deviation,
and the preventive and corrective actions required to run the automated operations optimally.
Carbon emission analytics: Scenarios that help minimize the total carbon emissions from the
commercial buildings can be simulated using carbon emission analytics. Energy management standards
mandated by relevant laws can be taken into account for such simulation. This can help tailor energy
management solutions according to the location of the building.
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