How microgrids can harness AI to proactively protect community energy

Local and smart – the energy of the future

Technological innovation is at the heart of a successful energy transition. And as artificial intelligence begins to radically transform industries, Energy & Utilities is no exception. Here we look at the role that AI will play in creating responsive, smart microgrids that harness the power of local energy and empower local energy consumption.

Data and AI are at the heart of power grids’ efficiency and security. By the 2030s, the technical architecture of microgrids themselves will be optimized using data-rich models, digital twins, and real feedback across thousands of deployments. This creates sophisticated levels of efficiency and resilience that benefit local and national energy ecosystems.

Energy executives today are already realizing AI’s benefits by analyzing production scheduling scenarios using simulation modeling. In everyday usage in our 2030s community, constrained policy optimization (CPO) and deep reinforcement learning will be widely used to predict the times when energy is most cleanly and efficiently produced, for instance while the sun is shining, or the wind is blowing. It will then automatically store any excess in a range of formats of batteries or other forms of energy storage across the community while energy is cheap.

AI-driven microgrid management will also be able to forecast the times of high energy usage and then sell accumulated energy as prices rise. In parallel with this automated intelligence, active local prosumers will also participate in the energy ecosystem, making real-time choices around energy usage, storage, and reselling. Thus, micro-producers’ profit will be maximized while also reducing the expense for local end-users and putting them in greater control of their energy.

Finally – and critically – AI will determine when any part of the grid could falter. It will then trigger the “islanding” of the microgrid ahead of any grid outages or other potentially damaging fluctuations. This island mode creates an energy ecosystem in which all community buildings continue to be powered independently. Critical infrastructure such as hospitals, manufacturers and retailers, and data centers are protected from energy instability, thereby protecting an area’s commercial health and citizens’ welfare. Thanks to AI, this protection will not be reliant on human intervention, which ultimately bolsters the area’s resilience.