This data represents the ASHRAE - Great Energy Predictor III dataset on Kaggle link- https://www.kaggle.com/c/ashrae-energy-prediction/data

Discussions surrounding human impact on global climate change permeate our daily discourse. Poor management and proliferation of carbon-emitting processes are often scrutinized as contributors to climate change. Many initiatives have been prioritized to model and possibly reduce this contributor climate change. Some of these initiatives are based on the belief a reduction of high-energy consuming processes can minimize this impact. It follows the more we conserve energy, and reduce carbon emissions, the more society can reduce it’s impact on the global climate crisis.

One of the initiatives is driven by the organization ASHRAE, founded in 1894. ASHRAE is a global society advancing human well-being through sustainable technology for the built environment. The Society and its members focus on building systems, energy efficiency, indoor air quality, refrigeration and sustainability within the industry.

Kaggle recently hosted a competition with data provided by ASHRAE. By identifying baseline building power consumption models, ASHRAE can provide a reference point for future building retrofits (upgrades). This will assist determining cost models as a delta to green energy upgrades to buildings.

I modeled his energy consumption model on a carefully selected subset of the ASHRAE time series data using common libraries such as ARIMA, Facebook Prophet, and gradient boosting library XGBoost.