Decision, Optimization and Computacional Intelligence

Code:

EEC0112

Acronym:

DOIC

Keywords
Classification	Keyword
OFICIAL	Other Technical Areas

Instance: 2010/2011 - 2S

Active?	Yes
Responsible unit:	Power Systems
Course/CS Responsible:	Master in Electrical and Computers Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEEC	78	Syllabus (Transition) since 2010/2011	4	-	6	63	162
		Syllabus	4	-	6	63	162

Teaching language

Portuguese

Objectives

Problem formulation in the framework of multiple criteria decision analysis. Application of decision aid methodologies. (CDIO 1.3, 2.3)
Representation of uncertainties with fuzzy sets. Application of methods based on fuzzy reasoning. (CDIO 1.3, 2.1, 2.3, 4.3, 4.4)
Application of methods based on non-linear optimization. Understanding of the fundamentals of meta-heuristics and application to solve problems. (CDIO 1.3, 2.1, 2.3, 4.3, 4.4)
Understanding the concepts of neural computing and apply them to a diversity of problems. (CDIO 1.3, 2.1, 2.3, 4.3, 4.4)
Development of autonomous work ability (CDIO 2.5) and of team work ability (CDIO 3.1, 3.2, 3.3)

Program

General concepts related to multiple criteria analysis, risk and uncertainty. Decision aid methods. Fuzzy models for the study of power flows and optimal power flow calculation. Non-linear programming. Gradient methods. Non-linear programming with constraints. Linear and non-linear DC model for the optimal power flow problem with constraints. Evolutionary algorithms, particle swarm algorithms and other meta-heuristics. Neural Networks.

Mandatory literature

Grainger, John J.; Power System Analysis. ISBN: 0-07-113338-0
Vladimiro Miranda; Computação Evolucionária Fenotípica, 2005
Vladimiro Miranda; DESPACHO ECONOMICO DE SISTEMAS DE PRODUÇÃO-TRANSPORTE - modelização e algoritmos , 1996
Clemen, Robert T.; Making hard decisions with decision tools. ISBN: 0-534-36597-3
Vladimiro Miranda; Algumas Notas sobre Programação Não Linear, 1986
Manuel Matos; Notas sobre Ajuda à Decisão Multicritério

Teaching methods and learning activities

General theoretical classes with transparency or power point support. Theory/practice classes presenting study cases, solving problems and assisting students in their work assignments.

Software

The Mathworks - Matlab - Release 11.1

keywords

Technological sciences > Engineering > Electrical engineering
Technological sciences > Technology > Energy technology > Electricity grid systems
Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	56,00
Exam	Exame	6,00
Assignment on Meta-heuristics application	Trabalho escrito	30,00		2011-05-27
Assignment on Fuzzy Power Flow	Trabalho escrito	20,00		2011-05-02
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Autonomous study	Estudo autónomo	50
	Total:	50,00

Eligibility for exams

Delivery of all assignment works with approval of the work.

Calculation formula of final grade

Written exam (no help material) 50%
Set of assignments 50%
Approval in the course is conditioned to a minimum mark of 8/20 in both components.

Examinations or Special Assignments

Assignments to be delivered in the dates determined by the lecturers. These works, to be developed during classes and during the time of autonomous work, are valid for the course and their classification will remain fixed, no re-doing allowed.

Special assessment (TE, DA, ...)

By exam plus assignments. The classification of the assignments (not re-doable) will be composed with the exam following the rule above. Assignment reports must be delivered up to the same deadlines fixed for other students. In the special cases defined by NGA, an additional laboratory exam will be required.

Classification improvement

A second opportunity for the exam is available.
Distributed evaluation cannot by its nature be improved.