Program Overview

Program Overview

The Energy Internet and Smart Energy course is a professional elective course for master's students in power engineering. The course covers the overview of energy internet and smart energy, architecture and standards, new power generation technology, advanced power transmission technology, advanced energy storage technology, and distributed energy system, micro-energy grid systems, energy system modeling and optimization, applications of big data and machine learning in energy internet and smart energy, energy internet and smart energy projects and case studies.

Course Description

The course aims to enable students to understand and master the key technologies, development trends, and applications of energy internet and smart energy. It is an effective way for master students to develop scientific research interest and do frontier research related to energy.

Course Schedule

• Introduction to energy internet: understand the definition, characteristics, and status of energy internet (2 hours, Lecture, Shenghong Ju)
  • Advanced power generation technology: understand the principles and technologies of new energy power generation such as solar energy, wind energy, biomass energy, and tidal energy (4 hours, Lecture, Shenghong JU)
  • Advanced power transmission technology: understand the development trend of power transmission technology, including DC, AC, wireless, etc. (2 hours, Lecture, Shenghong JU)
  • Advanced energy storage technology: understand the development trend, the principles, and technologies of electricity storage, heat storage, and hydrogen storage (4 hours, Lecture, Shenghong JU)
  • Distributed energy and micro-grid system: understand the concept, composition, and key technology of multi-energy complementary energy system (2 hours, Lecture, Shenghong JU)
  • Energy system modeling: case study (2 hours, Lecture, Shenghong JU)
  • Energy system optimization: case study (2 hours, Lecture, Shenghong JU)
  • Smart energy company visiting study (2 hours, Visiting study, Shenghong JU)
  • Introduction of energy big data and machine learning in smart energy (2 hours, Lecture, Shenghong JU)
  • Machine learning Basics – I (Regression) (2 hours, Lecture, Shenghong JU)
  • Machine learning Basics – II (Classification) (2 hours, Lecture, Shenghong JU)
  • Machine learning Basics – III (Clustering) (2 hours, Lecture, Shenghong JU)
  • Energy big data case study and analysis (2 hours, Lecture, Shenghong JU)
  • Final presentation (2 hours, Discussions, Shenghong JU)

Grading Policy

The final grade will be evaluated by: Attendance (10%), homework (40%), and final presentation (50%).

Textbooks and References

1. Feng Qingdong, "Energy Internet and Smart Energy", Mechanical Industry Press, 2015.
2. Yuan Fei, Huang Shan, "Global Energy Internet Key Technology", Chemical Industry Press, 2019.
3. Wencong Su, Alex Huang, "The Energy Internet: An Open Energy Platform to Transform Legacy Power Systems into Open Innovation and Global Economic Engines", Woodhead Publishing, 2018.

Notes

None.