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The increasing integration of artificial intelligence (AI) and cloud technology into renewable energy systems presents a significant opportunity to enhance the efficiency, reliability, and cost-effectiveness of energy production, distribution, and management. These technologies enable real-time data analysis, predictive maintenance, and improved decision-making, essential for managing variable renewable energy sources. However, the ethical implications, such as data security, privacy concerns, and the environmental footprint of cloud infrastructure, remain underexplored. This paper addresses the research gap by analyzing these ethical challenges through two detailed case studies: AI-driven smart grids and green data centers. The case studies highlight practical issues like cyberattacks, data breaches, algorithmic bias, and the sustainability of data centers. The paper proposes a comprehensive ethical framework, focusing on fairness, transparency, and environmental responsibility, to guide the responsible adoption of AI and cloud technologies in the renewable energy sector. The findings provide critical insights into balancing technological innovation with ethical considerations, fostering a sustainable and equitable energy transition.
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Emmanuel Dibie (2024) studied this question.
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