The energy industry is one of the most fundamental sectors of our everyday lives, just like retail and telecommunications. While digitization has already reached a stable level in the latter two, the energy industry is still much in the old, analog-style. As a result, fears have often arisen in recent years that an overload of the power grid is inevitable and that a blackout could throw us back to the Stone Age. High-ranking experts strictly deny this, but it is, of course, a problem that should not be underestimated. Many millions of new electrical appliances enter our offices and households every year and increase total electricity consumption immensely. In Germany, the situation tends to be more relaxed in this respect, with exports of just under 21 terawatt-hours – in other words, Germany produces more electricity than it needs. However, there are enough countries that consume more than they can produce. If a rock were to start rolling in this fragile construct, it would also drag us down with it, since in such a scenario, Germany would no longer be able to produce enough electricity to cover the peak loads.
That is why greater digitization is also necessary to prevent such horror scenarios and strengthen our energy markets‘ confidence. One solution, from the field of AI, was presented today by big players Shell, Microsoft, C3 AI, and Baker Hughes. These companies are looking to leverage their respective capabilities and launch an open AI platform for energy markets – the Open AI Energy Initiative™ (OAI). This ecosystem is designed to support utilities, service providers, software vendors, and equipment providers to deliver interoperable solutions for energy markets.
When the platform is launched, some modules will already be available for use in real environments. These cover the topics of reliability of AI and energy assets, availability and performance of energy assets, and monitoring and optimization of energy industry processes. Here, the most urgent questions are thus directly addressed.
- What are the current risks to my assets?
- How can my engineers interpret the plant data correctly?
- How reliably are my plants running?
These questions are addressed with AI models and trained with real data from the plants‘ recovery so far. Due to the participating companies‘ synergy effects, it is possible to build directly on a broad wealth of data and knowledge so that economic potentials can be raised immediately and the energy production in the company can be made steadily cleaner, safer, and more efficient. Besides, Microsoft provides its Azure Cloud as an infrastructure provider to make the platform scalable and accessible from anywhere.
A detailed list of the services available at the beginning can be found here:
- Shell Predictive Maintenance for Control Valves
- Shell Predictive Maintenance for Rotating Equipment
- Shell Predictive Maintenance for Subsea Electrical Submersible Pumps
- iCenter – Turbomachinery Advanced Digital Services
- Bently Nevada System 1 Condition Monitoring Software
- Baker Hughes Valve Lifecycle Management
- BHC3 Reliability
- BHC3 Production Optimization
- BHC3 Inventory Optimization
- C3 AI CRM
If your company is active in the energy sector, and you have reliability and efficiency problems, you should definitely take a look at the AI initiative in the energy sector and critically consider implementing the methods presented there.
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