Objectives and competences
This course aims to analyze a practical example from the field of electrical engineering and, based on the analysis, to use an optimization algorithm to find optimal solutions to the problem.
Content (Syllabus outline)
• Overview of optimization methods suitable for power system optimizations.
• Optimization methods, suitable for optimizing the power system's nonlinear and constrained optimization problems: linear programming, nonlinear programming, dynamic programming, decomposition methods, and evolutionary strategies.
• Guidelines for optimizations in the power system with evolutionary strategies: what model structure is suitable for optimizations, how to introduce constraints, how to define the criterion function, how to introduce penalty functions, how to evaluate the criterion function, when and how to use one or more criterion functions.
• Introduction: structure of the generalized power system, elements of the power system, control of the power system, optimization of the power system in the time domain.
• Electric power system models: the concept of working, reactive and apparent power, three-phase system and three-phase power transmission, model of synchronous machine, models of transmission lines and transmission network, models of loads.
• Examples of optimizations in the power system: optimization of energy flows, optimization of operating diagrams of various production units, minimization of losses in transmission lines in the case of balanced operation, minimization of transmission losses in distribution lines in the case of asymmetries and the presence of higher harmonic components.
Learning and teaching methods
• lectures,
• tutorial,
• project,
• lab work,
• homework assignments.
Intended learning outcomes - knowledge and understanding
On completion of this course the student will be able to
- demonstrate knowledge and understanding of power system operation and control,
- analyse optimisation problem, mathematically describe optimisation problem and choose an appropriate optimisation tool,
- define appropriate objective function, constraints and penalties,
- apply acquired knowledge for different kinds of power system optimisations.
Intended learning outcomes - transferable/key skills and other attributes
• Communication skills: expression in homework and lab work reports, project presentations, oral lab work defense, and oral examination.
• Use of information Technology: use of software tools for power system optimizations.
• Calculation skills: calculation of dynamic responses and different operating states in electric power systems.
• Problem-solving: defining optimization problem, constraints, penalties, and objective function, and choosing an appropriate optimization algorithm
Readings
• H. Požar: Osnove energetike 1, 2, 3, Školska knjiga, Zagreb, 1992.
• J. A. Momoh: Electric Power System Applications of Optimization, Marcel Dekker, New York, 2001.
• K. V. Price, R. M. Storn, J. A. Lampinen: Differential Evolution - A Practical Approach to Global Optimization, Springer, Berlin, 2005.
• U. K. Chakraborty, Advances in Differential Evolution, Springer, Berlin, 2008.
Prerequisits
Basic knowledge in mathematics, physics, electrical engineering and power system operation and control is recommended
Additional information on implementation and assessment 