When you fit data, you must have a model in mind. You don't just take something that seems to fit well. Otherwise, a 547th degree polynomial will do the job, but it's really not useful.

Here, your fit seems to suggest that, when the wind is strong, fossil fuel usage increases again. What is the model, the hypothesis, which would explain that?

Also, have you checked if every coefficient of the model is statistically significant? I'd guess that the 3rd isn't.

My guess for the best fit would be something resembling a logistic function: when the wind tends to infinity, fossil fuels tend to 0. In your model, fossil fuels would tend to infinity, which is... unlikely.

If you don't want to come up with a model, you have solutions: a moving average or a local regression like LOESS, which has the advantage to give a confidence interval.

Conclusion: regressions need to mean something. They must not be chosen without a model, even just hypothetical, in mind.