The energy transition is at an inflection point. The changing climate demands an urgent shift from historical reliance on fossil fuels to widespread integration of renewables. Data, made possible by pervasive IoT, is the currency fueling new business models for utilities and end-users to speed up the energy transition.
In the coming year, IoT and data will play an integral role in advancing the energy transition. Here’s how:
1. Transforming current business models to support prosumer-driven renewables integration
In the past, power reliability was relatively simple. Power plants produced energy and then distributed that energy to end users. Today’s landscape is much more complicated. When energy is produced, there is a global urgency to reduce the environmental impact of production.
Decentralization of power distribution has taken hold. Distributed energy resources (DERs) are rapidly coming into the energy mix and are on pace to surpass fossil fuels in many countries around 2025. With the development of DERs, energy consumers are becoming producers, also known as prosumers. This prosumer transformation is opening a welcomed door for creating new business models to better serve commercial and industrial end-users with a sharp eye on sustainability goals.
In 2020, the acceleration of data will transform the common business model for utilities in both regulated and de-regulated markets. Yet, the burning question remains: How can utilities manage the profound impact renewables will have on their traditional business model? If you fast forward to a grid player 10 years from now, there could be a time where the need for energy from utilities is zero, as well as other times when everyone requires grid energy at the same time because of environmental factors, such as weather fluctuations. This scenario isn’t about choosing the right technology. Rather, it’s about leveraging innovation to create wholly new ways of doing business.
We can look to the early days of the internet as a strong parallel to what is now happening with utilities’ rapid adaptation to the energy transition. If you remember the early days of the internet, we were all paying by data volume. That is the current model: customers pay by kilowatt consumed per hour. In the internet space, we pay to be connected with a guaranteed level of bandwidth. You don’t pay by traffic anymore.
A similar disruption is brewing for the long-standing utility business model — one that will have to account for the rise of prosumers in the commercial and industrial space.
2. Moving from connecting things to managing data for 24/7 reliability with renewables
The story of IoT has evolved by leaps and bounds in recent years. No longer are we talking about connecting things and objects. Connectivity on a massive scale has arrived, and the groundwork for connecting grid infrastructure with proven, robust technologies has been solidified. But data quality and sharing are presenting new challenges. Twenty one percent of companies aren’t sharing their data enterprise-wide, and only 18% are using IoT to obtain energy and sustainability data, according to Schneider Electric. The focus this year will be on improving the quality of data from these connected assets and leveraging data insights to support reliable renewable integration.
IoT and data analytics are enabling the kind of energy flexibility needed to add more environmentally friendly sources of energy without giving up power reliability and availability. With flexibility on their side, end-users and utilities can manage the variability of renewals and power adjustments based on external conditions from grid operators. In fact, more than 200 big companies are committed to RE100, setting a public goal to source 100% of their global electricity consumption from renewable sources by a specified year. As of September 2019, those companies will demand more than 220 terawatt hours a year. This is equivalent to eliminating 40 coal-fired power plants in one year.
3. Strengthening collaborative ecosystems to bring AI, IoT and cybersecurity to new levels
When you look at IoT end to end, it’s clear that no company on the planet has a technology stack that can cover everything. There is a need for a collaborative ecosystem to design, install and operate IoT-based solutions, such as weather forecasting AI models that empower end-users to better forecast, control and lower energy use. This type of competitive collaboration is not new, yet it is a burning issue in the context of IoT because the complexity of an end-to-end approach really deserves to have multiple partners to get it right.
New generation developers want to work in open, collaborative ecosystems instead of betting their individual knowledge and expertise on narrow, proprietary use cases linked to only one company. The payoff here for the energy transition is a collaborative ecosystem teeming with specialists and experts coming together to respond urgently to the climate crisis.
Within this framework, we can expect an acceleration of data as a service (DaaS) opportunities. DaaS is the continuation of a movement we have seen in multiple industries in the past around open data. Either by regulation or decision, more organizations are publishing data sets for the sake of sustainability efforts. This approach could shift to a model associated with revenues. For example, if you are a large facility developer, you could create new revenue streams to make data sets available to improve building energy consumption within the parameters of data privacy and confidentiality.
Ecosystems can make these data sets available to third parties. In addition to fine-tuning more sophisticated energy-related AI models, data sets can push forward cybersecurity efforts. Although connectivity never comes without cyber risk, defenses enabled by AI can flag anomalies to initiate early rapid response to hackers targeting endpoints across grid infrastructure and end-user environments.
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