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Modeling and Control for Future Electric Energy Systems
Learn advanced principles of electric power system management, focusing on sustainable and efficient solutions for the future grid.
Learn advanced principles of electric power system management, focusing on sustainable and efficient solutions for the future grid.
Dive into the cutting-edge world of electric energy systems with this comprehensive MIT course. Explore the systemic principles governing future power grids, emphasizing smart grid technologies, data-driven decision-making, and power electronics control. You'll learn to model and manage diverse energy sources, including renewables, at both component and system levels. The course covers innovative approaches to hierarchical control, distributed cooperative systems, and strategies for integrating new technologies into existing infrastructure. Gain insights into real-world industry challenges and solutions, such as stable integration of diverse power resources and demand response. This course is ideal for professionals across disciplines engaged in the energy transition, offering valuable knowledge for power system planners, researchers, industry executives, and policymakers alike.
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What you'll learn
Master fundamental concepts for power systems planning, operations, and management
Understand the limitations of current hierarchical control and strategies for evolving to flexible end-to-end electricity service
Develop strategies for enhancing grid resilience and energy access using existing infrastructure
Model and control diverse energy technologies, including renewables, at component and system levels
Explore the role of smart grids, machine learning, and data-driven decision-making in sustainable electric energy systems
Analyze real-world industry problems and solutions in power system integration and management
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This advanced course explores the principles of modeling, simulation, and control for future electric energy systems. It addresses the pressing need for sustainable and efficient power grids in the face of growing global energy demand and climate change concerns. The curriculum covers a wide range of topics, including smart grid technologies, data-enabled machine learning, power electronics control, and data-driven decision-making. Students will learn how to model and control various energy technologies, with a focus on integrating intermittent renewable energy sources. The course emphasizes the transition from traditional hierarchical control to more flexible, end-to-end electricity services. It introduces innovative concepts like distributed cooperative systems solutions and explores strategies for achieving stable integration of diverse power resources, demand response, and fast storage at reasonable costs. Throughout the course, real-world industry problems and solutions are examined, providing practical insights into the challenges of modern power system management. The course also covers the development of next-generation software for system operation and the implementation of incentives for new technologies in electric energy markets.
Fee Structure
Instructors
Pioneering Renewable Energy Researcher Advancing Smart Grid Solutions
Dr. Pallavi Bharadwaj has established herself as an innovative researcher in sustainable energy systems, beginning with her gold medal-winning Bachelor's degree from Delhi College of Engineering in 2012. Her academic excellence continued through her Master's at the Indian Institute of Science, where she earned the All-India Best Thesis Award in Power Engineering. Her PhD research at IISc focused on power electronic energy conversion systems, leading to breakthrough developments including a cost-effective solar irradiation meter and novel methods for photovoltaic output prediction. As a Postdoctoral Research Associate at MIT's Laboratory for Information and Decision Systems (LIDS), she has made significant contributions to multi-energy systems optimization and microgrid cybersecurity. Her work includes developing mathematical models for complex airport power systems and creating algorithms for secure microgrid operations. Currently serving as an Assistant Professor at IIT Gandhinagar, she leads the Smart Power Electronics Lab focusing on photovoltaic power conversion, transportation electrification, green energy storage, and net-zero transition technologies. Her commitment to sustainable energy extends beyond research to organizing wellness activities for the postdoctoral community during her time at MIT
Pioneering Power Systems Engineer Advancing Smart Grid Technology
Dr. Rupamathi Jaddivada currently serves as Director of Innovation at SmartGridz, following her postdoctoral research at MIT. Her academic journey includes a BTech from JNTUH College of Engineering with a 3.9/4 GPA, an MS from Carnegie Mellon University with a 3.97/4 GPA, and a PhD in Electrical Engineering and Computer Sciences with a minor in Machine Learning from MIT, where she maintained a perfect 4.0 GPA. Her research focuses on complex electric energy systems, particularly the integration of reactive power dynamics for enhanced system control. At MIT, she co-instructed courses on power systems modeling and contributed to developing innovative "zoom in, zoom out" systems thinking approaches for energy networks. Her work emphasizes making power systems concepts accessible while advancing cutting-edge solutions for clean energy transition. Before her current role, she gained valuable experience through positions at IIT Madras, Deloitte, and as a Graduate Research Assistant at both Carnegie Mellon University and MIT, where she worked on dynamic modeling and control of microgrids.
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