Microgrids are continuing to drive the transformation and decentralization of our energy grid, but planning and managing microgrids can be complex. Balancing fuel availability, price, emissions, unpredictable energy demand and a variety of other factors require a microgrid to optimize the mix of resources in real-time, or better yet, predictively. Artificial intelligence (AI) can be used in the planning, deployment and operation of a microgrid to help developers, equipment providers and operators alike. The AI microgrid can predict the unpredictable.
A new white paper from Veritone explores how artificial intelligence makes microgrids more predictable, cost-effective and resilient. The author explains how artificial intelligence can provide continuous and real-time modeling of massive amounts of data in a way the human brain cannot. These models can then be used to efficiently orchestrate the inputs and outputs of a microgrid.
Veritone presents three different case studies around how they’ve used AI in the planning and development of microgrid projects. The real-world examples include a cryptocurrency mining data center, the US General Services Administration and an energy storage services provider.