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This repository contains scripts and models for analyzing energy data and making predictions on various key metrics related to renewable energy, gas plants, and coal plant phase-out. The primary focus is on using linear regression and multiple linear regression (MLR) models to derive actionable insights.

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SauravBhowmick/Predictions-through-Regression

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Energy Data Engineering-1

Linear and multilinear regression.

Predicting the future dates

Problem statement: Analyse the data and predict the future dates for renewable energy sources.

Features:

Data Analysis:

  • Comprehensive analysis of energy data to identify trends and patterns.

Linear Predictions:

  • Renewable Energy: Predicted the date when the share of renewables will exceed 85%.
  • Gas Plants: Predicted the date when the share of gas plants will drop below 10%.
  • Coal Plants: Predicted the date when all coal plants will be phased out.

MLR Regression Model for Day-Ahead Price:

  • Developed and evaluated multiple linear regression models to find the best fitting model for predicting the day-ahead energy price.

Conclusion

We found the future dates for renewable sources.

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This repository contains scripts and models for analyzing energy data and making predictions on various key metrics related to renewable energy, gas plants, and coal plant phase-out. The primary focus is on using linear regression and multiple linear regression (MLR) models to derive actionable insights.

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