German Energy Agency (Deutsche Energie-Agentur – dena) has recently published an in-depth report about opportunities for using Artificial Intelligence in the energy sector called “Artificial Intelligence – from Hype to Reality for the Energy Industry”. Here’s what can you learn about from this market analysis and its implications for our research & development activity.
Dena analysis covers nine fields of application for AI in the energy industry:
- Optimizing operations
- Optimizing inventory and other strategic business decisions
- Predictive maintenance
- Maintenance, repairs, and dismantling
- Security measures
- Making it easier for active consumers to participate
- Product and marketing measure customization
- Process automation for measurements, bills, and general distribution
Each of the fields is assessed in terms of its technical maturity, AI diffusion, data availability and quality, energy system security, renewable energy diffusion and integration, system operation improvement, and CO2 reduction. Based on these criteria, the most promising fields of application for AI turned out to be predictions, optimizing operations, and optimizing inventory and other strategic business decisions.
The report also talks about the general economic and regulatory assessment of the fields. It focuses on the regulation of energy operations and includes the social aspects of AI implementation. It’s also worth reading the report because its conclusions will influence our future, as changes in the energy industry are inevitable and closely related to The European Green Deal. The Deal encourages investments in environment-friendly technologies.
The summary of all fields of the application shows that Artificial Intelligence can not only make a crucial contribution to the successful transformation of the digital energy system’s future, but it’s also indispensable.
We recommend reading the report, available here:
Artificial Intelligence in Globema’s energy industry solutions
As a Research & Development Center, we have several years of experience in implementing innovative solutions that use AI methods for the energy sector:
- 4RES – an application that provides short- and medium-term Renewable Energy Sources production predictions. It uses aggregated prediction models for energy suppliers and producers.
- ElGrid – a computational tool for analysis, optimization, and predicting low- and medium-voltage energy network occurrences, as well as connected dispersed sources and energy inventories.
- GlobIQ – an IT platform that uses image and speech recognition for collecting data about spatially dispersed network assets, used in following tools:
- LV Topology – a mobile application controlled by voice and gestures that allows the user to capture data about energy infrastructures and create network topology in the field.
- LocDoc – an application for automating scanned document categorization (papers, maps, decisions, protocols, etc.) and creating a spatial database based on their content (dates and locations).