Is a global time series model even better if the series are unrelated to each other? Or for example in case of wind speed forecasting the wind speed varies from location to location depending upon a lot of factors thus may be uncorrelated to each other. Even the. Will a global model perform better?

Although I wouldn't implement the global models suggested this paper says that a global model can be better even among unrelated series: https://arxiv.org/abs/2008.00444 Specifically: "Global methods are not more restrictive than local methods, both can produce the same forecasts without any assumptions about similarity of the series. Global models can succeed in a wider range of problems than previously thought." I would add that it depends on your data, if you have like 20 series it is probably better to hand-hold local models with unrelated series. Also, if you have any exogenous features, maybe like temperature or something, that tips the scales towards global models IMO.

Thanks