Native organizations units: Department of Power, Electronic and Telecommunication Engineering
Category | Theoretical-methodological |
Scientific or art field | Electroenergetics |
ECTS | 7 |
Acquiring knowledge on problems in numeric analysis and classic optimization problems and knowledge on classic methods for solving them. Familiarizing with the advantages and disadvantages of these methods with special focus on their application while solving problems in power systems.
Recognizing numerical analysis problems, solutions and characteristic types of optimization problems. Knowing classical optimization methods. Making students capable of computing diverse numerical analysis problems and classic optimization problems by applying classic optimization methods.
Fundamentals of numerical analysis: functions, matrix algebra. System of linear algebraic equations: theorems, transformations of equivalence; permutation matrices; solving solutions (Gauss's elimination process, triangular decomposition) and optimal equation ordering (Tunney optimal schemes). Space matrices techniques: static and dynamic storage schemes. Matrix inversion: classical methods and matrix inversion lemmas. System of nonlinear algebraic equations: iterative solution corrections; bracketing a root and combined methods; basic and modified Newton-Raphson methods; basic and accelerated Gauss-Seidel methods. Regression analysis. Fundamentals of problem optimization: variables, objective function, constraints, feasible region, direction vector, step size, mathematical model, graphical interpretation, transformation and characteristics. Optimization methods: convex optimization (convex set and function, extreme point, convex problem, optimality conditions, convex programming); linear optimization (standard and canonical forms, Simplex method, Interior-point method, methods with and without calculation of derivatives, network problem, transport problem, assignment problem); nonlinear optimization (necessary and sufficient conditions, methods with and without calculation of derivatives, quadratic programming, Lagrange multipliers method); integer/discrete optimization (linear and nonlinear problems; all-integer, mix integer and 0-1 problems; catting plane methods; branch and bounds methods ); dynamic optimization; multi-objective optimization (Trade-off, Pareto optimization). Application of optimization methods: data modelling; optimal power flow; state estimation; network reconfiguration; economic dispatching; unit commitment; planning, etc.
Lectures; Auditory Practice; Consultations.
Authors | Title | Year | Publisher | Language |
---|---|---|---|---|
B.P.Demidovich, I.A.Maron | 1973 | English | ||
2009 | English | |||
2011 | English | |||
2015 | English |
Course activity | Pre-examination | Obligations | Number of points |
---|---|---|---|
Written part of the exam - tasks and theory | No | Yes | 70.00 |
Computer excersise defence | Yes | Yes | 20.00 |
Lecture attendance | Yes | Yes | 5.00 |
Exercise attendance | Yes | Yes | 5.00 |
Prof. Goran Švenda
Full Professor
Lectures
Assoc. Prof. Željko Popović
Associate Professor
Lectures
Assoc. Prof. Stevan Cvetićanin
Associate Professor
Lectures
Assoc. Prof. Stevan Cvetićanin
Associate Professor
Practical classes
Assoc. Prof. Željko Popović
Associate Professor
Practical classes
Assistant - Master Kristina Milić
Assistant - Master
Practical classes
Assoc. Prof. Stevan Cvetićanin
Associate Professor
Computational classes
Assoc. Prof. Željko Popović
Associate Professor
Computational classes
Assistant - Master Kristina Milić
Assistant - Master
Computational classes
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Address: Trg Dositeja Obradovića 6, 21102 Novi Sad
© 2024. Faculty of Technical Sciences.