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Hourly Energy Consumption Forecasting

Home Page: https://ankithajinu-hourlypowerconsumption-app-0nho8c.streamlitapp.com/

License: Apache License 2.0

Jupyter Notebook 99.93% Python 0.07%
datacleaning differencing forecasting linear-regression random-forest sarima-model seasonality timeseries xgboost-model

forecasting_energy_consumption_project's Introduction

Forecasting_Energy_Consumption_Project

Hourly Energy Consumption Forecast -->

Business Objective:

PJM Hourly Energy Consumption Data

PJM Interconnection LLC (PJM) is a regional transmission organization (RTO) in the United States. It is part of the Eastern Interconnection grid operating an electric transmission system serving all or parts of Delaware, Illinois, Indiana, Kentucky, Maryland, Michigan, New Jersey, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, West Virginia, and the District of Columbia.

The hourly power consumption data comes from PJM's website and are in megawatts (MW).

The regions have changed over the years so data may only appear for certain dates per region.

Split the last year into a test set- can you build a model to predict energy consumption?

Find trends in energy consumption around hours of the day, holidays, or long term trends?

Understand how daily trends change depending of the time of year. Summer trends are very different than winter trends.

Forecast for next 30 days.

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