erickCantu/TheGreenCitySolutionsGroup
Forecasting building energy demand through time series analysis and machine learning.
Jupyter NotebookMIT
Issues
- 1
Dashboard? Plotly? Graphana?
#62 opened by erickCantu - 3
Define research question or target variable
#12 opened by suleenwong - 0
Final Presentation setup.
#63 opened by erickCantu - 0
Xticks for presentation figures
#72 opened by Leee-P - 0
FB Prophet model for time series forecasting
#29 opened by suleenwong - 0
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Update readme.md
#54 opened by erickCantu - 0
Review that all notebooks work properly after the features name change. (kWh to kW)
#50 opened by erickCantu - 0
collect domain knowledge on building energy controllers (put info in markdown file and push to repo)
#11 opened by suleenwong - 1
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- 1
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Running the OpenAI Gym
#18 opened by suleenwong - 1
Look into dealing with multiple seasonalities for the SARIMAX model (Fourier series for multiple seasonalities) as exogenous variables
#26 opened by suleenwong - 0
Midterm Stakeholder Presentation
#14 opened by suleenwong - 0
SARIMAX model for time series forecasting
#32 opened by suleenwong - 0
TBATS model for time series forecasting
#30 opened by suleenwong - 0
MLFlow
#13 opened by suleenwong - 0
Look into weekly seasonality for the data
#25 opened by suleenwong - 0
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Calculating a confidence interval for the average demand and solar generation plots
#9 opened by suleenwong - 0
Calculate electric consumption of the heat pump
#20 opened by Leee-P - 0
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Look into batteries within the simulation (calculate battery storage from json file)
#10 opened by suleenwong