| Autor: |
Amlashi, Y. Bostani, Afrakhte, H. |
| Předmět: |
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| Zdroj: |
International Review on Modelling & Simulations; Apr2011, Vol. 4 Issue 2, p819-823, 5p, 3 Diagrams, 3 Charts, 3 Graphs |
| Abstrakt: |
Wind power generation is noteworthy as the fastest-growing of all renewable energy sources to meet the global commitment to climate change. However, due to fluctuating and intermittent behavior of wind power, it is difficult to estimate its suitable penetration level into the electricity grid. The power output from wind depends on a number of factors that one of them is the wind speed. Thus, clustering of speed data, considering the steady changing of wind speed in different times is of great importance. The novelty of this paper is proposing two estimation scheme for clustering of speed data namely fuzzy c-means (FCM) and particle swarm optimization (PSO) algorithms. Then, the amount of probable output power is determined by means of discrete Markov chains apiece. Finally, in order to illustrate the proposed methods efficiency and ability, they are experimentally compared to each other. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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