The energy industry is undergoing a rapid transformation in recent past owing to the enhanced role of renewables and enhanced data-driven models making the value chain smarter. In the context of the primary constituents of this sector comprising of coal, power, renewables, solar energy, oil, and gas, there is a huge role AI can play.
We illustrate some key use cases below:
1. Smart Grid
The biggest disruption in power in recent times is in the smart grid which is quite flexible in comparison to the traditional grid. AI can be a huge enabler in the form of providing optimal configurations etc to create a really smart and efficient grid.
2. Distribution Losses
By thorough analysis of data related to losses AI can help prevent transmission and distribution losses.
3. Fine Tune Supply
In the case of the smart grid, there are tons of consumer data available in the form of consumption patterns, etc which can help fine-tune supply from the smart grid.
4. Conserve Consumption
Data from the smart grid ecosystem in terms of precise data of load patterns etc can help in dynamic configuration of the grid-like lesser load during afternoon times can help conserve consumption via switching off during those lean times.
5. Consumption Production
Via microgrids, today houses can become net suppliers to the grid and make money. Via proper analytics of consumption production tradeoff homes can make money.
6. Controlling & Optimization
Via powerful visualization tools and analytics tools power grid configurations can be controlled and optimized efficiently.
7. Preventive Maintenance
Overall across the energy sector, there is a need to imbibe the notion of preventive maintenance. Machinery like turbines, windmills, etc is very often subject to repairs and maintenance. By an AI-enabled preventive maintenance platform, all these equipment can resort to a preventive indication of faults and thereby avoiding reactive maintenance. This is a huge cost saving for the energy industry. They could even prevent major disasters from happening by flagging them early.
8. Image Classification
Using image Classification and AI processes like that In the context of oil gas and coal industry there is a huge role AI can play in the analysis of mine earth or seismic data highlighting potential areas for digging. This is a huge cost saver.
9. Optimal Placements
In the case of solar cells, etc optimal placements can be obtained by the use of AI algorithms.
10. Optimal Supply Chain
By use of sensors combined with AI, an optimal supply chain can be designed for transportation of coal oil gas, etc..
11. Predicting Movements
Use of AI can be done to better predict potential movements in stock indices based on commodities.
12. Autonomous Transportation
Via use of autonomous trucks several mining companies are optimizing transportation costs from remote mines.
13. Chatbot for Customer Service
Last but not the least using AI in customer service, for example, a power company using a ChatBot to resolve customer queries.
