This course provides a comprehensive understanding of advanced technologies and applications that enable the transformation of conventional power systems into intelligent smart grids. It covers Advanced Metering Infrastructure (AMI), smart metering systems, Phasor Measurement Units (PMUs), fault management, self-healing grids, substation automation, smart home, energy management systems, demand side management, and the role of Artificial Intelligence (AI) in modern power networks.
The course introduces smart metering technologies, communication systems, data analytics, cybersecurity challenges, synchrophasor measurements, and wide-area monitoring techniques used for real-time grid monitoring and control. It further explores fault detection and restoration mechanisms, distribution and substation automation, intelligent protection systems, and self-healing capabilities that enhance grid reliability and resilience. In addition, the course discusses smart home technologies, Internet of Things (IoT)-enabled energy applications, communication standards for smart homes and smart buildings, and practical deployment case studies. The course also examines Energy Management Systems (EMS), Demand Side Management (DSM), customer participation strategies, and AI-driven solutions for energy optimization and demand forecasting in smart grids. Objectives By the end of this course, you will be able to: • Develop an understanding of Advanced Metering Infrastructure (AMI), smart metering technologies, and synchrophasor measurement systems used in modern smart grids. (BL2) • Explain the role of PMUs, Wide Area Monitoring Systems (WAMS), and real-time monitoring technologies in enhancing grid visibility and reliability. (BL2) • Analyze fault management techniques, self-healing mechanisms, and automation systems used in transmission and distribution networks. (BL4) • Understand the architecture and operation of distribution automation and modern substation automation systems. (BL3) • Describe smart home technologies, IoT-enabled devices, and communication standards used in intelligent residential energy systems. (BL2) • Explain the objectives, functions, and applications of Energy Management Systems (EMS) and Demand Side Management (DSM). (BL2) • Evaluate the role of Artificial Intelligence (AI) and Machine Learning (ML) in energy management, demand forecasting, and load optimization. (BL4) • Assess the contribution of advanced monitoring, automation, cybersecurity, and intelligent energy management technologies toward reliable, resilient, and sustainable smart grid operation. (BL5) This course focuses on advanced monitoring, automation, intelligent control, and energy management technologies that form the foundation of modern smart grids. It covers smart metering infrastructure, cybersecurity practices, power system automation, smart homes, energy optimization techniques, and AI-enabled applications that support efficient and sustainable grid operation. The course also discusses practical aspects of outage management, self-healing networks, fault restoration, smart building technologies, customer participation in energy management, and real-world smart grid deployment scenarios through conceptual discussions and case studies. To successfully complete this course, learners should have basic knowledge of electrical engineering, power systems, electrical machines, and transmission and distribution systems. Familiarity with smart grid concepts, communication systems, and basic data analytics will be beneficial. By enrolling in this course, participants will gain technical knowledge and practical insights applicable to modern smart grid technologies, utility operations, energy management systems, and intelligent power system applications, making it suitable for both students and industry professionals.
