Energy Management and Automation in Smart Grid

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 2 hours a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

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Overview

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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.

Syllabus

Smart Metering and Phasor Measurement Unit

Let us begin this module by understanding the technologies that enable real-time monitoring, measurement, and management of modern power systems. This module introduces the fundamentals of Advanced Metering Infrastructure (AMI), its characteristics, components, and the evolution from conventional metering systems to smart metering solutions. The module covers smart meter communication technologies, data management and analytics, cybersecurity challenges in advanced metering systems, and practical case studies on the Ukraine power grid cyberattack. It also explores smart meter-assisted outage management, Phasor Measurement Units (PMUs), Wide Area Monitoring Systems (WAMS), and the role of real-time dynamic state measurement projects in enhancing grid visibility, reliability, and operational efficiency.

Fault Management and Substation Automation in Smart Grid

Let us begin this module by understanding the importance of fault management, automation, and self-healing capabilities in modern smart grids. This module introduces various types of faults and failures that occur in power systems and their impact on grid reliability and stability. It covers blackout management strategies, self-healing grids, automation technologies, distribution automation systems, substation automation architectures, communication protocols, switchgear components, Fault Location, Isolation, and Restoration (FLIR) techniques used to improve system reliability and operational efficiency.

Smart Homes

Let us begin this module by exploring the concept of smart homes and their role in modern energy management. This module introduces the architecture, key components, and working principles of smart homes, along with their benefits in improving comfort, convenience, security, and energy efficiency. The module covers various smart home devices, communication standards for smart homes and smart buildings, and the integration of Internet of Things (IoT) technologies for intelligent monitoring and control. Real-world deployment case studies are also discussed to demonstrate practical smart home implementations and applications.

Energy Management System in Smart Grid

Let us begin this module by understanding the importance of energy management and customer participation in achieving smart grid objectives. This module introduces customer awareness initiatives, the objectives and implementation of Energy Management Systems (EMS), and the functions and tools used for monitoring and optimizing energy consumption. The module also covers Demand Side Management (DSM), implementation techniques, associated benefits and challenges, and the growing role of Artificial Intelligence (AI) and Machine Learning (ML) in improving energy efficiency, load management, and decision-making. Practical demonstrations using machine learning algorithms are included to illustrate modern demand-side management approaches.