Earlier this year, the US’s renewable energy sector was tested when the State of Texas was thrown into darkness in what energy experts and politicians termed as an awakening for the government to invest in better green power infrastructure. Upgrading the grids is one way to deal with renewable energy microgrids’ shortcomings, but artificial intelligence technology could do better work. Artificial intelligence (AI) will consolidate renewable energy from different sources such as solar farms and wind farms to the main grid. The technology will also coordinate energy transmissions such that when there is excess power, the energy will be directed to energy storage batteries.
As global economies push for decarbonization to mitigate the impact of climate change, businesses, companies, government agencies, and households have invested in photovoltaic arrays, wind projects, and other microgrids to reduce their carbon footprint. The many green sources add complexity to the existing electric grid. The many electric charging stations being rolled out in the world will be drawing life from the grid simultaneously, resulting in power mishaps if they are not coordinated. The addition of energy to the primary grid from distributed energy systems (DERs) needs delicate balancing to match consumers’ power needs to avoid collapsing the grid.
When millions of EVs are charging in different parts of the country, while tens of thousands of microgrids are uploading electricity simultaneously, the whole process could lead to imbalances and chaos on electric grids. Energy utilities should consider ways to coordinate electrons’ flow from different sources and storage systems to where it is needed without interruptions or collapses. AI software will automate balancing the uploading and downloading of energy by sending excess power to the grid. Then the utilities will direct the power to where it is required. Besides, automated storage systems can hold excess energy whenever the demand is low to avoid wastage and automatically release it when the demand arises.
The centered system allows utilities and energy producers to forecast and control energy flow in seconds. The grid’s swift monitoring creates a more resilient and flexible energy flow without intermittency and unforeseen mishaps. Energy utilities and governments need to consider their role in ensuring that Texas’s energy blackout does not happen again. For instance, to augment their dwindling revenue as individuals shift to self-generated power, utilities could invest in AI software. The utilities could establish their software or collaborate with tech companies to realize AI technology.
According to BloombergNEF, dependence on utilities is going down. In Europe, the median power plant has reduced its capacity from 800megawatts (MW) to 562MW over the past eight years. This capacity is projected to fall to 32MW by midcentury.
Federal and state governments also need to rethink their funding options to include AI software incentives. However, the governments have to regulate the technology to guarantee integration with the existing grid, transparency, and fair access to all energy stakeholders.