Publication Details
Abstract
Artificial intelligence (AI) is changing the energy sector by increasing the efficiency, reliability, and sustainability of renewable energy sources including solar, wind and hydroelectric power. Machine learning and predictive analytics are examples of AI tools that deal with challenges like the variability and unpredictability of these sources create energy management and sustain the integration of smart grids. With the urge towards the development of a sustainable energy infrastructure by such countries as Iraq, AI is a chance to utilize the available renewable sources more efficiently and produce energy necessary to distribute it to the economic and environmental advantages. Diversifying energy sources is what Iraq (with its oil deposits) is trying to do. The potential of renewable energy in Iraq is great as the country has good prospects of solar and wind energy. Renewable energy technologies are advancing and it is due to government policies and international investments. This diversification is augmented by solar, wind, and hydropower, and is aimed at improving energy security, job creation and environmental concerns to attain long-term stability of Iraq and international climate obligations. Neural networks, machine learning, and fuzzy logic are AI technologies that provide additional opportunities to make renewable energy systems more efficient. These technologies forecast the energy production, enhance the scheduling of energy resources, manage the complex data sets, and optimize the process of the system design and operation. These innovations are strategic to sustainability in Iraq, improving energy availability and adding to a more resilient grid. The Iraqi energy industry is on the rise of AI applications, with the predictive analytics of solar power to enhance the production and cost-efficiency of solar power. Another way that AI can support wind energy projects is through optimization of turbine operations and renewable energy inclusion into the grid, which makes them more stable and resilient.