Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 345828

Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms


Aunedi, Marko; Škrlec, Davor; Štrbac, Goran
Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms // IEEE MELECON 2008 Proceedings / Gerard-Andre Capolino, Jean-François Santucci (ur.).
Ajaccio: 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 : IEEE, 2008, 780-785

ISBN
978-1-4244-1633-2

Skup
IEEE MELECON 2008

Mjesto i datum
Ajaccio, Francuska, 5-7.5.2008

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:

Avatar Url Davor Škrlec (autor)


Citiraj ovu publikaciju:

Aunedi, Marko; Škrlec, Davor; Štrbac, Goran
Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms // IEEE MELECON 2008 Proceedings / Gerard-Andre Capolino, Jean-François Santucci (ur.).
Ajaccio: IEEE, 2008. str. 780-785 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Aunedi, M., Škrlec, D. & Štrbac, G. (2008) Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms. U: Gerard-Andre Capolino, J. (ur.)IEEE MELECON 2008 Proceedings.
@article{article, editor = {Gerard-Andre Capolino, J.}, year = {2008}, pages = {780-785}, keywords = {Dispersed storage and generation, Genetic algorithms, Optimization methods, Power generation scheduling}, isbn = {978-1-4244-1633-2}, title = {Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms}, keyword = {Dispersed storage and generation, Genetic algorithms, Optimization methods, Power generation scheduling}, publisher = {IEEE}, publisherplace = {Ajaccio, Francuska} }
@article{article, editor = {Gerard-Andre Capolino, J.}, year = {2008}, pages = {780-785}, keywords = {Dispersed storage and generation, Genetic algorithms, Optimization methods, Power generation scheduling}, isbn = {978-1-4244-1633-2}, title = {Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms}, keyword = {Dispersed storage and generation, Genetic algorithms, Optimization methods, Power generation scheduling}, publisher = {IEEE}, publisherplace = {Ajaccio, Francuska} }




Contrast
Increase Font
Decrease Font
Dyslexic Font