Datortillämpningar i elkraftsystemet

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Från och med den 1 juni 2025 upphör möjligheten att redigera innehåll i kurswebben och studenter slutar bli inlagda. Redan existerande material kvarstår.

Läs mer här: Kurswebbens solnedgång den första juni

Overview

Efficient planning, operation and control of electric power systems are completely dependent on well functioning computer systems. A key function in these systems is the ability to analyse large amounts of data. Such analysis needs to be done both in off-line situations to optimize dispatch of generation, forecast production of RES, plan grid expansions and understand customer behaviour, but also in real-time to identify faults and risks of instability as well as decision support for automatic grid reconfiguration. For all these applications, the analysis of large amounts of high quality data - popularly know as Big Data - is critical for providing necessary support for decision-making or automated control actions.

Course Memo is available here.

Course Objectives

The aim of the course is to train the students in developing computer systems for advanced planning, operation and control of electric power systems. On completion of the course, the student will be able to:

Analyze the need for information exchange and suggest appropriate information models and protocols.
Create consistent information models for power systems control.
Develop database to store essential information about power system.
Define and implement a suitable machine learning algorithms for identification of power system state.

Prerequisites

EH2741 Communication & Control in Electric Power Systems.

Course Structure

The course consists of three blocks: Software development in Java, power system data modelling and machine learning. The software development block runs throughout the course and forms the basis for the two other blocks.

Software Development in Java starts from the basics of Java programming and introduces the student to software development in Java including aspects such as file input/output, XML parsing, and integration with databases.
Power System Data modelling is focused on modelling of power system data according to the Common Information model making it amenable for analysis in computer applications.
Machine learning finally, provides an introduction to simple techniques and algorithms focused on analyzing large amounts of data such as for example measurements from power systems.

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