A Study on AI-Powered Smart Grid Security: Mitigating Cyber Threats in Distributed Energy Systems
Keywords:
AI, smart grid security, distributed energy systemsAbstract
The integration of Artificial Intelligence (AI) into smart grids has revolutionized the management and optimization of energy distribution, offering enhanced efficiency and flexibility in the operation of distributed energy systems. However, this innovation introduces new cybersecurity risks, as the increased connectivity of devices and systems makes them vulnerable to cyber-attacks. AI-powered smart grid security aims to mitigate these threats by employing advanced machine learning techniques and real-time data analytics to detect, respond to, and prevent cyber intrusions. This paper examines the role of AI in strengthening the cybersecurity posture of smart grids, with a focus on detecting anomalies, protecting critical infrastructure, and ensuring system resilience against attacks. It explores various AI methodologies, such as anomaly detection, predictive analytics, and reinforcement learning, that are being applied to enhance grid security. The paper also discusses the challenges and limitations of implementing AI-driven security solutions in distributed energy systems and provides case studies of successful applications in real-world scenarios. Ultimately, the study highlights the potential of AI in mitigating cyber risks while ensuring the security and reliability of smart grids in the face of evolving cyber threats.
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