kanch91 / project-energy

Time-series analysis of the electricity load consumption in the Mumbai Metropolitan Region.

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arima deep-learning-models exponential-smoothing-models forecasting gru-model keras-tensorflow lstm-model moving-average rnn-model sarimax statistical-models time-series-analysis

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project-energy

This project is for analysing the time-series algorithms via a study of electricity load forecasting on univariate and multivariate datasets in the MM Region using various classical/moving averages (SMA, WMA, CMA, EMA), exponential smoothing methods (SES, DES, TES), statistical models (ARIMA, SARIMAX) & DL models (LSTM, GRU, RNN) for univariate and multivariate datasets using Keras API

Datasets

It is divided into two primary datasets:

Univariate dataset having only the load
Multivariate dataset having weather (Temperature, Dew Point, Humiditiy, Wind Speed, Pressure) as well as the load

Models

Each of the dataset forecasts using the following methods:

Classical Methods: SMA, WMA, CMA, EMA
Exponential Methods: SES, DES, TES
Deep Learning Models: LSTM, GRU, RNN
Statistical Models: ARIMA, SARIMAX