In the race to develop smarter and more efficient cities, utilities are beginning to turn to smart grid analytics to improve operations.
Adopting smart technologies that produce valuable data will help them improve distribution of critical resources and overall operational efficiency. It will also help utilities (and government) to achieve ever-increasing environmental targets.
The potential benefits for these organizations are enormous, which is why ReportsnReports projects that the smart grid analytics market will growing at a 25% CAGR to 2019.
Here are three specific ways in which smart grid analytics can be of benefit to utilities:
- Restoring services after weather related emergencies: Sensors that produce data about outages can help utilities pinpoint the areas with the most service disruptions and continuously monitor to dispatch repair crews to those areas as soon as issues arise. As these sensors continue to yield data over time, utilities may even be able to predict where outages are likely to occur in the future and take extra preventative measures.
- Improving security: We all understand the potential dangers of hackers getting into the power grid. Individuals or groups could wreak havoc on entire cities by shutting off traffic lights or shutting down power in neighborhoods. Analytics can help prevent these nightmare scenarios by enabling robust detection solutions.
- Balancing loads: Using analytics to predict loads helps utilities make more accurate projections and decisions about energy distribution; in turn, this helps organizations cut costs and ensure customers don't experience brownouts or blackouts.
Given the enormous challenge of overhauling an energy system that has been in place for over a century, it is vital that utilities choose the right IoT platform to monetize smart grid technologies.
For example, a platform that provides utilities with a powerful combination of connectivity and monitoring features can be invaluable as it deploys smart meters and other devices, as reliable connectivity is the key to collecting data for analysis.
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