Optimizing The Energy Efficiency of a Building in Turin (+IoT)

Modeling of a dummy house. Output: IDF file. SW: Design Builder;
IDF file parameters optimization to reduce the building power consumption regarding cooling, heating and electricity. Optimized parameters: insulation, glazing, WWR, and orientation. SW: Besos/EnergyPlus (Python);
3-years simulation of power consumption (for cooling and heating), electricity, inside and ouside temperatures. SW: Besos/EnergyPlus (Python);
Upload of the simulated data into a local database (InfluxDB);
Connection of a local platform (Grafana) with the local database (InfluxDB), and creation of a dashboard in Grafana to visualize the data;
InfluxDB data retrieval in SQL-like language, and energy signature characterization. Language: Python;
Forecasting of total power consumption (cooling power+heating power) with Arima model. Language: Python.

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
energyplus		energyplus
imgs		imgs
input		input
output		output
.gitignore		.gitignore
1-Optimization_besos.ipynb		1-Optimization_besos.ipynb
2-Simulations_hourly-3years.ipynb		2-Simulations_hourly-3years.ipynb
2-Simulations_hourly.ipynb		2-Simulations_hourly.ipynb
2-Simulations_monthly.ipynb		2-Simulations_monthly.ipynb
3-Uvalue_calculation.ipynb		3-Uvalue_calculation.ipynb
4-EnergySignature_InfluxDB.ipynb		4-EnergySignature_InfluxDB.ipynb
5-Preprocessing_for_Arima.ipynb		5-Preprocessing_for_Arima.ipynb
6-Arima.ipynb		6-Arima.ipynb
LICENSE		LICENSE
MQTT_Publisher.ipynb		MQTT_Publisher.ipynb
MQTT_Subscriber.ipynb		MQTT_Subscriber.ipynb
README.md		README.md
helperFunctions.py		helperFunctions.py

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