On Monday 16th October, Storm Ophelia raged through Ireland. With lots of reliable wind energy around for a change, one might have expected high levels of wind power.
Monday, 30 October 2017
Storm Ophelia
On Monday 16th October, Storm Ophelia raged through Ireland. With lots of reliable wind energy around for a change, one might have expected high levels of wind power.
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Typical of Eirgrid. If they had operated these wind turbines to their maximum the grid would have collapsed . As most wind turbines would have cutoff at 90 kilometres per hour wind and when the wind speed dropped back to less than 90 kilometres the wind turbines would have started back up again only to cut back out again when the wind speed exceeded 90 kilometers per hour to cut back out again. Probably a couple of minutes production having to be replaced by synchronous production within seconds to prevent grid failure. The forecasts looked good on the screen though until actuals made the forecast a bit of a joke. Like the wind program itself
ReplyDeleteWhat was the demand for electricity during the storm? You have not factored this in to your pathetic argument.
ReplyDeleteHow many power lines were damaged as result of the storm?
The cherry picking of data is alarmingly worrying.
The cut off point of wind turbines is a fact. Not many people know about it, so while you have valid points, the point of the article was to inform those who did not know about it. The mainstream media do not bring up these facts. I have gone into depth on previous articles about impact of demand.
DeleteDemand figures are irrelevant during this particular period. As it is wind speed variability above cut off speed dropping back for short periods of surging production to be followed in a couple of minutes with a massive drop as wind speeds exceed cut off. Is the real issue. This would have crashed the grid nation wide. Then there may have been demand but no supply . These apologists for the wind scam should start living in the real world. Eirgrid are playing games with their forecasts.
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