A joint research team has developed key technologies to realize "Urban Electrification" using artificial intelligence (AI). Their findings have been published in the journal Sustainable Cities and Society. The team includes researchers from the Renewable Energy System Laboratory and the Energy ICT Research Department at the Korea Institute of Energy Research (KIER)

Urban electrification aims to reduce the use of fossil fuels and introduce renewable energy sources, such as building-integrated solar technology, to transform urban energy systems. While this concept is relatively unfamiliar in the Republic of Korea, it is being promoted as a key strategy in the U.S. and Europe for achieving carbon neutrality and creating sustainable urban environments.

In traditional urban models, energy supply can be easily adjusted using fossil fuels to meet electricity demand. However, in electrified cities, the high dependence on renewable energy leads to greater variability in energy supply due to weather changes. This causes mismatches in electricity demand across buildings and makes the stable operation of the power grid more challenging.

In particular, Low-Probability High-Impact Events (LPHI), such as sudden cold snaps or extreme heat waves, can cause a sharp increase in energy demand while limiting energy production. These events pose a significant threat to the stability of the urban power grid, potentially leading to large-scale blackouts.

The research team developed an energy management algorithm based on AI analysis to address power grid stability issues and implemented it into a system. The demonstration of the developed system showed an 18% reduction in electricity costs compared to conventional methods.

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