Course syllabus - AI-driven Decision Support Systems for Energy and Production Operations

3.0 credits

ERA323

Spring semester 2025

Second cycle

A1N (Second cycle, has only first-cycle course/s as entry requirements)

Energy Engineering

School of Business, Society and Engineering

2024-08-19

Literature lists

Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.

Objectives

The objective of this course is to develop understanding of practical AI solutions and learning systems in real life SCADA systems.

Learning outcomes

When people finish the course, they are expected to：
1. Understand frameworks and concepts of SCADA system
2. Understand concepts and models of learning system
3. Know applied ML/DL in MPC, prediction and optimization
4. How AI support decision making

Course content

1. Introduction of SCADA System: framework, datastream, functions, models
2. Introduction of Learning System: concepts, functions, models
3. Prediction, Modeling and Optimization: machine learning and deep learning solutions
4. Information Fusion for Decision Support
5. Case Study

Specific requirements

75 credits in energy engineering, production technology, mechanical engineering, product and process development, computer technology and/or computer science or equivalent or 40 credits in technology and at least 2 years of full-time professional experience from a relevant area within industry. In addition, English A/English 6 are required

Examination

Home examination (HEM1) 1 credit, grade: Fail (U) eller Pass (G)
Assignment (INL1) 2 credit, grade: Fail (U) eller Pass (G)

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Two-grade scale