Pregled bibliografske jedinice broj: 345828
Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms
Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms // IEEE MELECON 2008 Proceedings / Gerard-Andre Capolino, Jean-François Santucci (ur.).
Ajaccio: Institute of Electrical and Electronics Engineers (IEEE), 2008. str. 780-785 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 345828 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms
Autori
Aunedi, Marko ; Škrlec, Davor ; Štrbac, Goran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
IEEE MELECON 2008 Proceedings
/ Gerard-Andre Capolino, Jean-François Santucci - Ajaccio : Institute of Electrical and Electronics Engineers (IEEE), 2008, 780-785
ISBN
978-1-4244-1633-2
Skup
IEEE MELECON 2008
Mjesto i datum
Ajaccio, Francuska, 05.05.2008. - 07.05.2008
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Dispersed storage and generation; Genetic algorithms; Optimization methods; Power generation scheduling
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
036-0361590-1587 - Planiranje i vođenje aktivnih razdjelnih mreža i mikromreža
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Davor Škrlec
(autor)