Electricity Demand Forecasting based on Smart Meter Data

Based on the Kaggle dataset (https://www.kaggle.com/jeanmidev/smart-meters-in-london), the goal of this study is to compare several well known machine learning algorithms on the task of time series forecasting. A report is also provided showing the results of the comparison.

The studied algorithms are:

SARIMA
RANDOM FOREST
LINEAR REGRESSION
DECISION TREES
SUPPORT VECTOR MACHINES
MULTILAYER PERCEPTRON

The problem statement

Case Study

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Data Preprocessing

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Forecasting Algorithms Comparison

Results

Next Hour Forecasting

Study Full Report

The full report of this study can be found under the report directory of this repo

Study Results Presentation

A quick presentation on the study can be found under the of this repo.