J. Boland (Australia)
Applied simulation in the energy sector, wind farm output variability, sum of gamma distributions, correlative coherence • • • • The variability in output follows a gamma distribution1 . The rated capacity of Starfish Hill is 34.5 MW. If a wind farm of 69 MW were to be built at another site, we will assume there are to be 2 Starfish Hill wind farms at that site. The amount of variability at different time scales is important. We will present detailed results for the half hour var
At present, there is one fully operational wind farm generating electricity in South Australia, with capacity of 34.5 MW. There are several wind farms under construction at 5 sites, which will bring the total capacity to 400 MW. There are numerous proposed wind farms, which will eventually take the installed capacity up to 1000 MW at 6 sites. We need to estimate the total output variability of the wind farms over three time intervals. The variability at the 3 second time interval can affect the stability of the network. Variability at the 5 minute time interval can affect the market mechanisms since in Australia dispatch is at 5 minute intervals. Also, variability on a half hour time scale is critical since peaking plant still needs about that amount of time to ramp up. In this paper, we use correlative coherence analysis and methods of adding variables following a gamma distribution in order to estimate the total variability of wind farms of varying size at different locations.
Important Links:
Go Back
