Following our post last week on digitalisation in the energy sector, this week’s blog post will focus on how AI is shaping the future of energy monitoring with a focus on demand side response.
Rapid advances in artificial intelligence (AI) and machine learning (ML) mean that they have become key technologies for enabling demand side response. AI usage in energy management is expected to deliver a large economic uplift, amounting to a 1.6% – 2.2% boost in global GDP by 2030.
How AI can be used?
Approaches involving AI have been identified as vital for addressing the change in energy management and power systems. This includes the shift to decentralised production from renewables and the era of digitalisation. AI can be used to[RT1]
- Forecast power demand and generation
- Optimise maintenance
- Optimise the use of energy assets
- Provide stability
- Load forecasting
AI can also ease the load on humans by helping to automate scheduling frameworks and managing the multiple devices that are in use. It is estimated that machine learning could be used to help unlock up to 6GW of demand-side flexibility which can be shifted during the evening peak without affecting end users.
And for retail?
AI can be used to help companies transform the user experience by
- Providing a better understanding of usage patterns
- Providing insight into consumer behaviour
- Creating platforms for producers and consumers to trade
AI opens up a wide range of exciting possibilities for energy management systems that will greatly improve energy efficiently resulting in reduced overall cost. Due the nature of AI, these systems will become even better over time further improving energy savings as the system becomes more intelligent.