Artificial intelligence (AI) emerges as a vital companion and savior for humanity in the realm of renewable energy, as described by Ibrahim Al-Jarra, an AI professor at the University of Jordan. It contributes to human awareness of the climate they inhabit and supports them in facing challenges that may not have crossed their minds.
The utilization of AI in renewable energy facilitates the acquisition of indicators and future forecasts that aid in wind energy production, relying on weather data analysis. It also enhances solar energy production and accurately predicts output volume.
Moreover, AI contributes to increasing the efficiency and presence of renewable energy operations. Its algorithms can improve the operation and maintenance of renewable energy infrastructure, ultimately extending its lifespan and reducing overall costs. For example, by predicting the precise timing for maintenance of wind turbines or solar farms using drones flying above these installations.
Employing such algorithms results in reduced carbon emissions, ensuring the maximized utilization of clean energy potential. Additionally, they are used to enhance the environmental efficiency of resources by operating and developing smart systems and infrastructure that minimize energy wastage.
The International Climate Action Organization has introduced AI-driven solutions for climate action in developing countries, including less developed and small island nations, beginning with innovative adaptation technologies.
AI can optimize agricultural food systems and crop management by predicting the best planting times, assessing soil health, monitoring pest and disease outbreaks. Precision agriculture, which relies on AI, can also reduce water usage, promote sustainable farming practices, and boost food production.
For instance, the development agency, IAGAD, utilizes AI to enhance impact-based forecasting by the Climate Prediction and Application Centre in agriculture sectors in East Africa, which is key to food security, livelihoods, and economic development.
Regarding renewable energy systems, efficiency and reliability can be enhanced through AI algorithms that predict energy demand, optimize grid operations, seamlessly integrate renewable energy sources, reduce greenhouse gas emissions, and promote the transition to low-emission energy solutions. One notable example is the Global Renewable Energy Atlas, which is a live atlas aiming to map and measure solar and wind energy installations on a facility scale using AI imagery and satellite data, allowing users to assess clean energy transition progress and track trends over time.
Furthermore, there are practical applications of how AI is deployed in climate action initiatives. For instance, Google’s DeepMind model utilizes AI to enhance cooling systems in data centers, reducing energy consumption and emissions. AI recommendation systems have led to improved energy usage efficiency in data centers.
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