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Course, academic year 2018/2019
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Introduction to Smart Grids - NOPT056
Title in English: Úvod do inteligentních energetických sítí
Guaranteed by: Department of Theoretical Computer Science and Mathematical Logic (32-KTIML)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:1/1 Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Additional information: https://ktiml.mff.cuni.cz/~fink/teaching/smart_grids/
Guarantor: RNDr. Jiří Fink, Ph.D.
Classification: Informatics > Informatics, Software Applications, Computer Graphics and Geometry, Database Systems, Didactics of Informatics, Discrete Mathematics, External Subjects, General Subjects, Computer and Formal Linguistics, Optimalization, Programming, Software Engineering, Theoretical Computer Science
Annotation -
Last update: T_KTI (16.04.2015)
A smart grid is a modernized electrical grid that uses analog or digital information and communications technology to gather and act on information in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. Aim of the course is introducting students to the recent problems in modern energy systems, mathematic modelling and optimization methods used to control electrical devices.
Aim of the course - Czech
Last update: RNDr. Jiří Fink, Ph.D. (01.05.2018)

Cílem předmětu je seznámit studenty se současnými problémy v energetice, s matematickým modelováním jednotlivých problémů a optimalizačními algoritmy používanými k jejich řešení.

Course completion requirements - Czech
Last update: RNDr. Jiří Fink, Ph.D. (01.05.2018)

Zkouška z probíraných témat nebo prezentace článků.

Literature -
Last update: RNDr. Jiří Fink, Ph.D. (01.05.2018)

Y. A. Çengel and A. J. Ghajar. Heat and mass transfer: fundamentals and applications. McGraw-Hill, 2011.

Çengel, Yunus A., and Michael A. Boles. Thermodynamics: An Engineering Approach. 7th ed. New York: McGraw-Hill, 2011.

Beale R. and Jackson T.: Neural Computing: An Introduction, IOP Publishing, Bristol and Philadelphia, 1990

Mitchell, M.: Introduction to genetic algorithms. MIT Press, 1996.

W. Saad, Z. Han, H. V. Poor and T. Basar, "Game-Theoretic Methods for the Smart Grid: An Overview of Microgrid Systems, Demand-Side Management, and Smart Grid Communications," in IEEE Signal Processing Magazine, vol. 29, no. 5, pp. 86-105, 2012.

K. Dvijotham, P. Van Hentenryck, M. Chertkov, M. Vuffray, S. Misra, Graphical Models for Optimal Power Flow, Proceedings of 22nd International Conference on Principles and Practice of Constraint Programming (CP 2016).

Syllabus -
Last update: RNDr. Jiří Fink, Ph.D. (01.05.2018)

A smart grid is a modernized electrical grid that uses analog or digital information and communications technology to gather and act on information in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity.

One the main problems in Smart Grids is balancing energy production and consumption. In 20th century, the production of electricity was concentrated in a group of large power stations (mainly coal, nuclear or water) and these sources were designed to be able to control their output according to demands. However in recent years, the production from renewable energy sources (especially solar and wind) have been significantly increasing. These sources cannot be easily controlled and furthermore, their future output is hard to estimate. Therefore, devices and batteries are being developed to be able to plan their consumption according to the availability of the electricity network. Efficient usage of these devices requires advanced algorithms that can estimate production and consumption of energy, schedule each devices according to their possibilities and dynamically react on every event in real time.

Syllabus

Introduction: Discussion of recent problems in the area of Smart Grids which we will study during the semester

Mathematical modelling: Production and consumption of energy in distribution networks

Data prediction: Statistical methods, neural networks

Planning: Optimization methods based on linear and convex programming and evolutionary programming

Game theory, auction methods, Power Exchange

Thermodynamics and house heating

Electrical engineering and modelling of transmission networks

Entry requirements:

Basic knowledge of mathematical modelling and optimization, e.g. Optimization metods

Course Page:

https://ktiml.mff.cuni.cz/~fink/teaching/smart_grids/

 
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