Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms (CROSBI ID 537174)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Aunedi, Marko ; Škrlec, Davor ; Štrbac, Goran
engleski
Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms
Restructuring and deregulation of the electricity sector have altered the behavior of market layers, shifting the objective from cost minimization to profit maximization. Development of distributed generation units, along with concerns raised over the security of supply has prompted many customers to consider the installation of their own local capacity for generating electricity (and heat). This paper proposes a methodology for optimizing the operation of a portfolio of distributed units, based on profit maximization using genetic algorithms. Genetic algorithms are an optimization method based on the analogy with biological evolution, where the so-called population of solutions evolves through generations as a result of recombination, mutation and selection processes. Optimization is carried out based on the day-ahead forecast of hourly market prices of electricity. The method is tested on a set of distributed units, demonstrating the ability to find good solutions in an acceptable time period.
Dispersed storage and generation; Genetic algorithms; Optimization methods; Power generation scheduling
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Podaci o prilogu
780-785.
2008.
objavljeno
Podaci o matičnoj publikaciji
IEEE MELECON 2008 Proceedings
Gerard-Andre Capolino, Jean-François Santucci
Ajaccio: Institute of Electrical and Electronics Engineers (IEEE)
978-1-4244-1633-2
Podaci o skupu
IEEE MELECON 2008
predavanje
05.05.2008-07.05.2008
Ajaccio, Francuska