Analiza na naravi osnovanih algoritmov in njihova uporaba pri reševanju problemov v elektroenergetiki

MARUŠIČ, MIHA (author), Rudež, Urban (mentor)

Ker so viri, čas in denar v resničnem svetu vedno omejeni, moramo najti rešitve za optimalno porabo teh pomembnih virov. Za reševanje večine optimizacijskih problemov resničnega sveta potrebujemo mnogokrat zapleteno optimizacijsko orodje. Na naravi osnovani meta-hevristični algoritmi so eni izmed najpogosteje uporabljenih algoritmov za optimizacijo. Algoritem kresničk je eden od teh algoritmov. V tem delu so analizirani optimizacijski algoritmi od tradicionalnih metod do modernih meta-hevrističnih algoritmov, s poudarkom na algoritmih osnovanih na naravi. To delo poskuša predstaviti zgodovino in aplikacijo teh algoritmov. Prvo poglavje predstavi algoritme in analizira bistvo algoritma. Potem se razpravlja osnovno oblikovanje optimizacijskega problema in moderne pristope s pogleda inteligence rojev. Pregledana je kratka zgodovina na naravi osnovanih algoritmov. Drugo poglavje analizira ključne komponente na naravi osnovanih algoritmov s pogleda njihovih evolucijskih operatorjev in funkcionalnosti. Glavni cilj je podati pregled teh algoritmov. V tretjem poglavju se predstavi standardni algoritem kresničk in potem so na kratko predstavljene različice. Analizirane so tudi karakteristike algoritma kresničk. Četrto poglavje predstavi implementacijo algoritma kresničk pri reševanju problema optimalne razporeditve obratovanja elektrarn z minimiziranjem stroškov goriva in upošteva omejitve generatorjev in izgube prenosa. Temu sledi kratek pregled na naravi osnovanih algoritmov v elektroenergetskih sistemih.

• Language: Slovenian
• Keywords: algoritmi, optimizacijski algoritmi, hevristika, meta-hevristika, NFL teorem, na naravi osnovani algoritmi, inteligenca rojev, evolucijski operatorji, algoritem kresničk, optimalna razporeditev obratovanja
• Work type: Undergraduate thesis
• Organization: FE - Faculty of Electrical Engineering
• Year: 2016
• PID: 20.500.12556/RUL-84814
• Publication date in RUL: 05.09.2016

MARUŠIČ, MIHA, 2016, Analiza na naravi osnovanih algoritmov in njihova uporaba pri reševanju problemov v elektroenergetiki [online]. Bachelor’s thesis. [Accessed 26 March 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=84814

Secondary language

• Language: English
• Title: Analysis of nature inspired algorithms and their application in electrical power engineering

Abstract

Because resources, time and money are always limited in real world applications, we have to find solutions to optimally use these valuable resources. To solve most real world optimization problems we need sophisticated optimization tools. Nature inspired meta-heuristic algorithms are among the most widely used algorithms for optimization. Firefly algorithm is one of these algorithms. In this work optimization algorithms are analyzed from traditional methods to modern meta-heuristic algorithms, with an emphasis on nature inspired algorithms. This work is attempts to present the history and applications of these algorithms. The first chapter introduces algorithms and analyzes the essence of the algorithm. Then the general formulation of an optimization problem is discussed and modern approaches in terms of swarm intelligence. A brief history of nature inspired algorithms is reviewed. The second chapter analyzes the key components nature inspired algorithms in terms of their evolutionary operators and functionalities. The main aim is to provide an overview of these algorithms. In the third chapter the standard firefly algorithm is introduced and then the variants are briefly reviewed. The characteristics of firefly algorithm are also analyzed. The forth chapter presents the implementation of firefly algorithm in solving the economic dispatch problem by minimizing the fuel cost and considering the generator limits and transmission losses. This is followed by a short review of applications nature inspired algorithms in power systems.

• Keywords: algorithms, optimization algorithms, heuristics, meta-heuristics, NFL theorems, nature inspired algorithms, swarm intelligence, evolutionary operators, firefly algorithm, economic dispatch