The Role of Artificial Intelligence in Wind Power Plants in Latin America
During the last decade, Latin American countries have been forced to shift their energy sources due to factors such as:
- The political instability, which generates uncertainty in investors, produces changes in regulations and generates corruption and social risk.
- Economic problems, which lead to an increase in fuel import prices or the maintenance of existing energy sources, also limit the ability of countries to invest in energy infrastructure.
- Lack of private investment, which prevents development in this field.
All of these problems have compiled to stress the need to reduce dependence on fossil fuels. This can happen through the creation of more sustainable energy sources capable of satisfying the growing energy demand and mitigating the effects of climate change, a project that has been developing for years and has been financed mainly by public institutions.
These changes have focused on the revolution of renewable energies, such as wind and solar power, which at a large scale represent more than 15% of the electric capacity of the Latin American region (Segui, P), with the rest of the capacity coming from electricity from thermal sources (such as coal, natural gas, oil) and hydroelectric energy. The problem with these last energy sources is their high polluting index, which is harmful to the environment and local communities. On the other hand, energies such as:
- Wind and solar energies are cleaner, safer for the environment, and more economical compared to non-renewable energies.
- They promote energy independence at the national level by reducing the reliance on fossil fuels.
- Renewable energy does not emit greenhouse gases or other atmospheric pollutants, contributing to the reduction of the carbon footprint in Latin America.
It also promotes sustainable development in the region.
The use of artificial intelligence (AI) has been a measure of great support. With its ability to collect, store, and analyze large amounts of data in real-time, AI makes it possible to optimize wind energy production. As stated by Guilherme Studart, CEO of the Brazilian startup Delfos Intelligent Maintenance, a provider of AI solutions for energy companies: “The most important thing about using AI is the introduction of correct data. If you include correct data in the system, you will have a correct diagnosis and then a correct solution to your problems.”
Now, to understand the role of AI in wind power plants, it is important to know about the three leading Latin American countries that use it.
- Firstly, we have Brazil, which according to Sfera Proyecto Ambiental, 2020 is the only Latin American country with a capacity of more than 20 GW; which also estimates that by 2025, it will be able to generate 70% of the installed wind capacity in Latin America. One of the great advantages of Brazil, in addition to the favorable geographical position, is the large manufacturers of electric turbines, such as GE and Alstom, that will launch the manufacturing of electric turbines and assembly of the supply chain in the region.
- In second place is Mexico, which despite suffering certain political and economic difficulties, managed to have the capacity to produce wind energy equal to 7 GW in operation (Sfera Proyecto Ambiental, 2020). Mexico has great potential to generate energy through renewable sources, since it has high levels of sunshine, water resources to install mini-hydraulic plants, and areas with intense and constant winds, among others.
- Lastly in this classification is Argentina with a wind capacity of 3.3 GW (Bnamericas, 2023). Around 75% of Argentina’s surface has winds suitable for the operation of turbines, so it has an ideal platform for the production of wind energy.
With this in mind, it is proposed that AI is a fundamental tool in the advancement and improvement of wind energy. According to Federico González, head of technical sales administration at Vestas Wind Systems:
“Digital analytics help analyze information from the wind sector and deliver the correct forecast in terms of wind speed, temperature, and solar irradiation. Digitalization solutions are the way to the future.”
Unlike traditional methods that are generally slow and expensive, AI offers real-time status monitoring, with sensors installed on wind turbines it is possible to collect large amounts of data, which are then processed using ML algorithms to identify patterns and anomalies.
With AI-enhanced wind energy, numerous benefits are achieved for citizens, such as a reduction in energy costs and environmental pollution. Companies also benefit, since studies reveal that AI-based systems save between 30% and 40% of costs associated with repairs and maintenance. They also impact the useful life of plants, improving the quality of maintenance and reducing the stress of materials by 10%. It is well-known that many wind farm owners seek to optimize forecasts and electricity production, such as the case of service and wind turbine provider Siemens Gamesa, who developed the digital platform Hermes in partnership with Microsoft to monitor the condition of turbine blades using AI (Bnamericas, 2023).
The Role of AI in the Evolution of Wind Energy: Advantages, Challenges, and Environmental Considerations:
To continue explaining the contribution of AI in the evolution of wind energy, it is noteworthy that the Danish renewable energy company Vestas Wind Systems, led by Dr. Pablo Ibarguengoitia and Naatik A.I, has been leading several digitalization projects of wind farms in several Latin American countries, using machine learning to constantly adapt and improve operations. This technology allows obtaining data in real time thanks to its work mode which consists mainly of trial and error, to create changes that improve wind energy production.
While there are several advantages to using AI in these projects, it is important to consider the potential drawbacks as well. These include:
- High initial investment costs: Implementing AI in projects requires significant investments in infrastructure, hardware, and software. Organizations need to allocate substantial resources to set up the necessary systems.
- Dependence on connectivity: AI projects rely on reliable real-time data transmission, which necessitates a strong and stable internet connection. Any disruptions in connectivity can hinder the effectiveness of AI applications.
- Maintenance and updates: ML and AI systems require regular maintenance and constant updates to ensure optimal performance. This involves ongoing monitoring, troubleshooting, and incorporating the latest advancements in AI technology.
- Electronic waste generation: The use of AI technologies contributes to the generation of electronic waste. Organizations must implement proper waste management practices to minimize the negative environmental impact associated with disposing of outdated AI equipment and components.
It’s crucial for businesses to weigh both the advantages and potential downsides before implementing AI in their projects, taking into account the costs, dependencies, and environmental considerations involved.
We can observe then that there are advantages and disadvantages to these innovations, but in general, it is considered that their implementation can provide a significant gain, increasing the generation of renewable energy, reducing costs, and producing little to no global warming emissions.
During the last few years, AI has represented an effective and profitable tool in the optimization not only of wind energy but also of green energies in general. As stated by Espen Mehlum, responsible for the energy and materials program on a comparative assessment of the World Economic Forum: “AI can be used both to optimize the construction, location, and operations of a wind farm, and more importantly, to optimize different systems, both in terms of consumption and production.”
Bibliographic References
Computerworld University. (May 28, 2021). Artificial Intelligence to enhance the efficiency of renewable energies. Website available at https://www.worldenergytrade.com/energias-alternativas/general/inteligencia-artificial-crucial-crecimiento-energias-renovables
Energias Renovables. (February 27, 2020). Artificial intelligence to maintain 100% wind production and optimize investments. Website available at https://www.energias-renovables.com/eolica/inteligencia-artificial-para-mantener-al-100-la-20200227
Jelmayer, R.; Ruddy, G. (July 8, 2019). AI in the energy sector: renewable sources will set the pace. Website available at https://www.bnamericas.com/es/reportajes/ia-en-el-sector-energetico-las-fuentes-renovables-marcaran-el-paso
Sfera Proyecto Ambiental. (January 9, 2022). Wind energy in Latin America. Website available at https://sferaproyectoambiental.org/2022/09/01/la-energia-eolica-en-latinoamerica-2/
World Energy Trade. (January 10, 2023). Artificial intelligence will be crucial to the growth of renewable energy. Website available at https://www.worldenergytrade.com/energias-alternativas/general/inteligencia-artificial-crucial-crecimiento-energias-renovables
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