The Future of Sustainable Energy: How Greece Employs AI to Reduce Emissions
Ihita Ghosh | John Morozov
In the race to develop systems that optimize human efficiency, environmental protection is treated as a second-class citizen. Recently, the energy required to operate AI data centers has led to concerns among environmentalists. However, with the integration of AI technologies in the sustainable development sector, countries, specifically Greece, have been able to improve renewable energy infrastructure. By optimizing the operation and placement of sustainable energy infrastructure, AI has helped enhance efficiency in the industry. As a result, investment in green energy has risen significantly, contributing to long-term growth. This suggests that employing AI in roles to reduce carbon emissions can help countries diminish negative externalities. Emerging markets, in particular, may be able to capitalize on these advancements, given their rapid economic growth rates. According to the World Development Report published by the World Bank, “developing countries [may be able] to leapfrog development challenges by reducing human error, optimizing complex production and distribution processes, and facilitating decision-making.”
The usage of AI in sustainable development is seen in the renewable energy valleys in Crete, Greece. This model allows the area to diversify its energy production, rather than relying on more traditional energy sources that release high carbon emissions. With the emergence of new technologies, systems that harness and produce sustainable energy have become digitalized and independent. For example, microgrids have been enhanced to optimize energy storage, improve interconnectivity, and develop resilience to adverse weather conditions. Future research may focus on improving energy efficiency and facilitating the transition from traditional energy to sustainable ones. The Crete REV-Lab also advocates developing a tool to support investors in making investment decisions, allowing for the efficient allocation of investment funds. Equipping investors to navigate investing in the sustainable energy market makes the industry more accessible. Therefore, the technologies Greece is beginning to implement in its sustainable energy markets suggest that AI may aid the sector’s long-term growth.
The second method of optimizing renewable energy is through deep learning algorithms. A study conducted at the University of Thessaly in Greece introduces GREENIA, an AI that optimizes the placement of renewable energy-harnessing equipment using an algorithm. Jaya, the optimization algorithm, is fed training data that allows it to make energy production forecasts and correct itself. This data is then validated against testing data to ensure accurate predictions. After testing in real-world scenarios, the study shows that GREENIA significantly improved the placement of energy infrastructure across geographical regions over 30 days, increasing energy production by 145.57 MWh. This is significant as enhancing placements can help maximize energy captured and reduce the number of structures utilized in the energy-harvesting process. Subsequently, this lowers the total cost of energy infrastructure while increasing the amount of energy captured. Therefore, AI software may serve as a powerful tool, enabling policymakers to optimize their renewable energy goals. This allows the sector to become more profitable and attracts investors, contributing to long-term growth.
Reliance on green technology compared with traditional energy forms reduces emissions and contributes to environmental preservation. Greece, in particular, may be interested in conservation due to its large tourism-based economy. Therefore, a large amount of research is poured into the sustainable development sector. This research is beneficial in the long run and creates more growth opportunities. In the short term, however, there are many concerns regarding the energy required in AI data centers, which produce large amounts of emissions. According to the United Nations’ Intergovernmental Panel on Climate Change, generating and consuming energy produce the largest amount of greenhouse gas emissions. Solutions that mitigate these short-term externalities include introducing carbon emissions monitoring systems and regulating the energy consumption of AI data centers. Greece employs this approach by implementing AI tools and technologies in various projects throughout Athens to tackle issues related to climate change. By successfully implementing such policies, other emerging market economies may be able to strive towards a more eco-friendly future, while also growing their sustainable energy sub-economies.
Although the development of AI technologies has raised concerns over climate change, the effective integration of these technologies in the sustainable development industry will help enhance energy production in the future. As further research focuses on optimizing the capture of sustainable energy, the sector’s main problems related to high equipment costs with little return can be solved. With the growth of the sustainable energy industry, there may be more interest in solutions that help preserve the environment, thereby benefiting the environmental sector. The short-term externalities may also be offset with further monitoring and regulations. Greece has been successful in implementing such technology and may further reduce emissions by developing more efficient algorithms. With the extreme effects of climate change, focusing on sustainable solutions has become essential. By implementing AI in sustainable solutions, emerging market economies may replicate Greece’s success and reduce carbon emissions.
Ihita Ghosh is a junior majoring in Economics-Mathematics at Barnard College. Planning to pursue a PhD in Economics, she is particularly interested in topics such as disaster risk hedging, macroeconomics, and technology.