Abstract: With the growing demand for reliable and efficient power systems, the integration of cloud computing technology has emerged as a promising solution. This paper presents a unique perspective on the adoption of cloud computing in the power industry, exploring novel approaches and considerations for leveraging cloud infrastructure and services. Drawing from in-depth research and industry expertise, this paper delves into the transformative potential of cloud technology in power systems. It goes beyond the traditional discourse by examining unconventional use cases, such as dynamic load management, predictive maintenance, and demand response optimization, where cloud computing offers significant advantages. Addressing the concerns of power system practitioners, the paper explores the challenges and risks associated with cloud adoption, emphasizing the need for robust security measures, data privacy, and regulatory compliance. It provides novel insights and practical recommendations to guide industry professionals in navigating the complexities of cloud implementation while maintaining system integrity. By analyzing the potential economic and environmental benefits, this paper demonstrates how cloud computing can contribute to achieving a greener and more resilient power grid. It showcases innovative approaches, such as edge computing and distributed intelligence, that leverage the cloud to enable real-time monitoring, predictive analytics, and optimized resource allocation. Ultimately, this paper aims to inspire power industry professionals to embrace the transformative power of cloud computing. It encourages a forward-thinking mindset and promotes collaboration across sectors to unlock new possibilities for enhancing the efficiency, reliability, and sustainability of power systems.
Keywords: Cloud Computing, Power Systems, Dynamic Load Management, Predictive Maintenance, Demand Response Optimization, Security, Data Privacy, Regulatory Compliance, Collaboration, Interoperability, Scalability, Adaptability, Sustainable Energy, Edge Computing, Distributed Intelligence, Efficiency, Reliability, Sustainability.
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DOI:
10.17148/IJARCCE.2023.12684
