MACHINE LEARNING FOR POWER SYSTEM

이 과정에서는 학생들에게 지도학습법 (선형회귀, 신경망, 서포트벡터머신, 결정트리 등)과 비지도학습법을 (K-Mean 클러스터링, Anomaly Detection 등)과 같은 기계 학습 기법을 소개합니다. 소개된 기계 학습 기법은 특히, 에너지 시장, 파워퀄리티, 신재생발전원 제어 등과 같은 전력시스템 및 스마트그리드 분야의 문제 해결에 사용되며, 전력계통계획, 운영 및 제어의 개선에 활용하는 것을 목표로 합니다.

Upon completing this course, the student should be able to: • Solve Problems using Python programing • Explain how data is generated in power systems and how are new technologies impacting the amount and quality of datasets • Understand popular data processing and analytic techniques • Implement existing packages to solve problems • Use machine learning methods to answer questions about power system operations • Choose appropriate methods based on objective and datasets

I. Attendance: • Regular class attendance is expected for all students at the University. You are not required but advised to attend all classes. • Please send your professor a brief e-mail to explain your absence in advance. • Your absence will not reduce your attendance rate if and only if you have a legitimate reason for missing a class (such as illness, death in family, a traffic accident, etc.). In case of an illness or emergency, you must supply a formal documentation that supports your claim. • Classes start on the hour. Please be respectful of your classmates by being on time. • All electronic equipment should be turned off and kept out of sight before lecture starts. II. Make-up Exams: Make‐ups for Midterm Exam will be available if and only if you have a legitimate reason for missing the exam (such as illness, death in family, a traffic accident, etc.). In case of an illness or emergency, you must supply a formal documentation that supports your claim. III. Late Submission Policy: Late submissions will not be graded. There will be no make-up for quizzes and homework/ assignments. Missed assignments and quizzes will result in a grade of zero (0). IV. Participation: In their book, The Adult Student's Guide to Survival & Success, Al Siebert, and Mary Karr suggest that the most effective learning technique of all is to study by asking and answering questions. Develop the habit of reading textbooks, taking lecture notes, and studying by asking and answering questions. When you do this, you save many hours of studying and have time to spend with your family or friends. There are several ways to go about asking and answering questions. When studying on your own, write questions that occur to you while you're reading and then go back and find the answers. If you're part of a study group, make a list of questions to ask the group. In the classroom, participate fully by asking questions and answering the ones posed by your instructor.