RichardFindlay/day-ahead-probablistic-forecasting-with-quantile-regression
Using an integrated pinball-loss objective function in various recurrent based deep learning architectures made with keras to simultaneously produce probabilistic forecasts for UK wind, solar, demand and price forecasts.
This project helps energy analysts and traders accurately predict day-ahead electricity market conditions by providing probabilistic forecasts for UK wind and solar generation, electricity demand, and wholesale prices. It takes historical energy data as input and produces a range of possible future values, helping you understand the uncertainty in market movements.
No commits in the last 6 months.
Use this if you need to make informed decisions about energy trading or grid management by understanding the likely range of future energy supply and prices, not just a single predicted value.
Not ideal if you need a simple point forecast (a single predicted value) without considering the probability distribution, or if you are not working with UK energy market data.
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Language
Python
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Category
Last pushed
Nov 20, 2022
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