liuziyun0204's Stars
madagra/energy-ts-analysis
Jupyter notebook implementing time series forecasting of energy consumption data with different methods.
MohamadNach/Machine-Learning-to-Predict-Energy-Consumption
Building a machine learning model to predict energy consumption using LSTM (Long-Short Term Memory)
WillKoehrsen/prediction-documentation
Work related to predicting building energy consumption
pratha19/Hourly_Energy_Consumption_Prediction
This repo contains files and jupyter notebooks for the project- Predicting energy consumption of the entire region in southern CA served by the SDGE (San Diego Gas and electric) utility based on the past 5 years of hourly energy consumption data.
gitofanandaghosh/Energy-Demand-Forecasting
Projecting a society’s long-term electricity demand helps determine what capacity is needed for future energy generation. Accurate forecasts of electricity demand inform investment decisions about power generation and supporting network infrastructure. Of major interest to energy policymakers, power utilities, and private investors alike, forecasts are also essential for development professionals. Inaccurate forecasts, whether they over-or under predict demand, can have dire social and economic consequences. Underestimating demand results in supply shortages and forced power outages, with serious consequences for productivity and economic growth. Overestimating demand can lead to overinvestment in generation capacity, possible financial distress, and, ultimately, higher electricity prices. Several techniques have been developed over the last few decades to accurately predict the future of energy consumption. The main objective of this notebook is to create an energy demand forecasting system using Facebook Prophet. Facebook Prophet is an open-source library released by Facebook’s Core Data Science team. The data I am going to use for this particular task is the new york electricity demand dataset.