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Publikace detail

Distribution of wind power plants to reduce variability of renewable generation
Autoři: Debnath Dhrupad | Musilek Petr | Heckenbergerová Jana
Rok: 2014
Druh publikace: článek ve sborníku
Název zdroje: Proceedings of the 2014 15th International Scientific Conference on Electric Power Engineering, EPE 2014
Název nakladatele: IEEE (Institute of Electrical and Electronics Engineers)
Místo vydání: New York
Strana od-do: 291-296
Tituly:
Jazyk Název Abstrakt Klíčová slova
cze Rozmístění větrných elektráren pro snížení variability produkované enegrie Tento příspěvek zkoumá možnosti optimálního prostorového rozložení větrných elektráren za účelem snížení variability v produkované energii. K této optimalizaci je použito simulated annealing a kvadratické programování.
eng Distribution of wind power plants to reduce variability of renewable generation As the penetration of wind power into generation mix increases, the issue of its integration into the power grid becomes more and more important. The variability of wind power generation is a major concern as wind is highly intermittent. This may result in significant overproduction at times, followed by complete unavailability of wind power at other periods. This intermittency must be compensated for by other, conventional generation sources such as coal and gas fired power plants. This reduces the overall efficiency of the system due to the need of running some generators as spinning reserves, and lowers the overall contribution of renewable generation to the mitigation of greenhouse gas emissions. This paper examines the possibility to optimize the spatial distribution of wind power plants over an extended area to decrease the overall variability of wind power generation in a system. In particular, it considers the integration of spatially distributed wind power generation in the wind-rich province of Alberta, Canada. The distribution of power plants is optimized using simulated annealing and quadratic programming. The results clearly show that the variability of wind power generation can be reduced if the wind resources are integrated over a wide geographic area. Electric power generation; Electrical engineering; Greenhouse gases; Power plants; Quadratic programming; Simulated annealing; Spatial distribution