As wind exploitation gains prominence in the power industry, the extensive use
of this intermittent source of power may heavily rely on our ability to select the best
combination of wind farming sites that yields maximal reliability of power systems at
minimal cost.
This research proposes a general method to minimize the wind park global power
output variance by optimally distributing a predetermined number of wind turbines over
a preselected number of potential wind farming sites for which the wind patterns are
statistically known. The objective is to demonstrate the benefits of diversification for the
reliability of wind-sustained systems through the search for steadier overall power
outputs.
Three years of wind data from the recent NREL/3TIER study in the western US
provides the statistics for evaluating each site for their mean power output, variance and
correlation with each other so that the best allocations can be determined. Some
traditional reliability indices such as the LOLP are computed by using sequential Monte
Carlo simulations to emulate the behavior of a power system uniquely composed of wind
turbines and a load modeled from the 1996 IEEE RTS.
It is shown that configurations featuring minimal global power output variances
generally prove the most reliable for moderate load cases, provided the sites are not
significantly correlated with the modeled load. Under these conditions, the choice of
uncorrelated/negatively correlated sites is favored. The correlations between the
optimized global wind power outputs and the modeled load are studied as well.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-08-7174 |
| Date | 2009 August 1900 |
| Creators | Degeilh, Yannick |
| Contributors | Singh, Chanan |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | application/pdf |
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