At the core of energy, you will find data
Today, a world without a guaranteed energy supply is unimaginable. Humanity survives and progresses because of energy.
The industrial revolution was propelled by an increase in both quality and quantity of energy1. It led eventually to the world as we see it today.
As the human population has grown exponentially over the years, so has the demand for energy1,2. We are at the point where we cannot rely on traditional energy sources. The effort now is towards renewable and sustainable sources of energy.
A new energy market is emerging
With the advent of sustainable energy, the energy industry is moving from centralised production to distributed generation. This paradigm change will also result in a quantum change in complexity, because not only will the number of energy consumers grow, but so will the number of producers. We have talked about Distributed Energy Solutions before.
Plummeting retail margins prompt a revisit of business models and new innovation to introduce new value-added services that vie for customers’ attention and create a preference. Smart metering enables extremely granular customer segmentation, even load disaggregation to analyse the consumption at the level of individual home appliances. On the grid side, combining the Internet of Things (IoT) with machine learning allows building autonomous systems that provide real-time load forecasts based on energy prices, weather and other parameters.
How you use data will determine your future
None of this new world of energy and utilities is possible without data, and the insights derived from data4. No longer is data a by-product of business processes but lies at the core of new business models and innovations. These include a shift from demand-driven dynamic pricing models to a future energy bazaar where individuals trade their energy surpluses – from the smart virtual grid that balances renewable and non-renewable energy sources in response to weather and demand, to better understanding the customers using consumption behaviours.
The path towards this data-driven future is gradual. But the need to walk the path is imminent. The key steps to be taken are:
- Modernise the data infrastructure to leverage real-time or near-real-time insights
- Create new data visualisation capabilities that assist in visual data exploration. Think not reports, but information delivery
- Move to data-driven, algorithm-assisted business processes built on machine learning and artificial intelligence
Fortunately, the tools already exist
To be prepared, energy companies need a common data platform that brings with it the abilities to manage data, visualise complex relationships and build predictive services built using machine learning/deep learning algorithms. At the same time, the platform enables retrospective analytics that the business needs. This is exactly what Tieto’s Smart Utility energy solution includes. It takes advantage of real-time data, allowing both the energy company and the customers to follow the status of the services in (near) real time.
All of the above will irreversibly happen – and like in any business, early adopters will gain a significant advantage.
- Grubler A (2004). Transitions in Energy Use. IIASA Research Report (Reprint). IIASA, Laxenburg, Austria: RP-04-005. Reprinted from Encyclopedia of Energy, 6:163-177 .
- Stern, D.I. & Kander, A., (2012) The Role of Energy in the Industrial Revolution and Modern Economic Growth. The Energy Journal, 33(3).
- Alahakoon, D. & Yu, X., (2016). Smart electricity meter data intelligence for future energy systems: a survey. IEEE Transactions on Industrial Informatics, 12(1), 425-436.
- Jiang, H., Wang, K., Wang, Y., Gao, M. & Zhang, Y. (2016). Energy big data: A survey. IEEE Access, 4, 3844-3861.