The official website of the World Economic Forum has published an article titled "How Azerbaijan is leveraging AI for sustainable energy transformation.”
The article highlights that Azerbaijan is positioning itself at the forefront of artificial intelligence (AI) driven energy innovation, strongly focusing on integrating AI into its energy sector to improve efficiency, sustainability and grid optimization.
Amid global climate goals and commitments made at the 2024 UN Climate Conference (COP29), the country is exploring key AI applications to enhance renewable energy adoption, optimize energy consumption and promote decarbonization.
Azerbaijan’s energy sector holds significant potential for innovation, driven by the strategic opportunities identified in a local stakeholder assessment run by the World Economic Forum's Centre for the Fourth Industrial Revolution (C4IR) Azerbaijan.
One of the key opportunities includes leveraging AI to optimize energy production and distribution, improving data management and infrastructure, and enhancing energy efficiency through smart grid technologies. Collaboration between public and private sectors and partnerships with research institutions can accelerate AI integration, fostering a more sustainable and efficient energy future for Azerbaijan. Additionally, the country’s growing focus on renewable energy sources presents further avenues for AI-driven advancement.
Azerbaijan could position itself as a regional leader in green energy export to Europe through cables under the Black Sea. For instance, the renewable energy company Masdar has developed the 230-megawatt-capacity Garadagh solar power plant in Azerbaijan. It has signed agreements to build a further 1 gigawatt of clean energy projects in the country. Azerbaijan benefits from favourable wind and sunlight conditions, offering significant potential for developing and deploying wind and solar energy solutions.
The article also discusses several global solutions, which could be adapted as pilot projects and localized to the country context with scalability potential.
“One shortlisted project involves an AI-powered energy efficiency pilot for buildings in collaboration with BrainBox, which was found to reduce energy consumption by 30%, improve carbon emissions by 25-30% and deliver a 30% return on investment.
Another planned initiative is a renewable energy pilot leveraging the use case of Vestas' predictive maintenance solution for wind turbines, aiming to replicate its proven benefits, which include reliability, optimized maintenance processes and significantly enhancing the efficiency of renewable energy infrastructure,” the article states.
