# 302.731 Design- and Operational Optimization This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_21",{id:"j_id_21",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_23",{id:"j_id_23",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});}); 2022W

2022W, VU, 2.0h, 3.0EC

## Properties

• Semester hours: 2.0
• Credits: 3.0
• Type: VU Lecture and Exercise
• Format: Presence

## Learning outcomes

After successful completion of the course, students are able to...

• classify optimization problems and select appropriate solution methods.
• interpret linear and mixed-integer-linear optimization problems geometrically, implement them in MATLAB, and solve them using appropriate solution procedures.
• formulate Unit Commitment problems with given linear models of aggregates and demand curves as optimization problems.
• linearize nonlinear operational behavior and implement it using SOS1, SOS2 and convex approximation.
• formulate and solve typical configuration and dimensioning problems in energy systems (e.g.: storage integration) as mixed-integer-linear optimization problems.
• solve multiobjective optimization problems with two objective functions using the weighted sum method and represent Pareto fronts.

## Subject of course

The (energy-) efficiency of industrial companies can often be significantly increased by precisely arranging the design and operation of all components. Due to the complexity and dynamics of industrial processes, this potential can only be exploited with computer-aided optimization. In this course, students learn to formulate mathematical optimization problems and to solve them using appropriate methods. The focus lies on mixed-integer-linear optimization (MILP) and suitable linearization methods to approximate nonlinear plant behavior appropriately.

## Teaching methods

• Each lesson consists of a lecture part with subsequent exercise part.
• Independent study of the examples, as well as submission and discussion of the results.

Immanent

## Course dates

DayTimeDateLocationDescription
Thu09:00 - 12:0006.10.2022 - 26.01.2023CAD-Labor Saal 3 VU
Design- and Operational Optimization - Single appointments
DayDateTimeLocationDescription
Thu06.10.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu13.10.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu20.10.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu27.10.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu03.11.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu10.11.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu17.11.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu24.11.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu01.12.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu15.12.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu22.12.202209:00 - 12:00CAD-Labor Saal 3 VU
Thu12.01.202309:00 - 12:00CAD-Labor Saal 3 VU
Thu19.01.202309:00 - 12:00CAD-Labor Saal 3 VU
Thu26.01.202309:00 - 12:00CAD-Labor Saal 3 VU

## Examination modalities

• 60 % - Active participation (preparation and presentation of coding assignments)
• 40 % - Written lecture examination

## Course registration

Begin End Deregistration end
31.08.2022 12:00 31.10.2022 12:00 31.01.2023 12:00

## Curricula

Study CodeObligationSemesterPrecon.Info
066 445 Mechanical Engineering Mandatory elective
Course requires the completion of the introductory and orientation phase
066 473 Chemical and Process Engineering Mandatory elective
066 482 Mechanical Engineering - Management Mandatory elective
Course requires the completion of the introductory and orientation phase

## Literature

No lecture notes are available.

German