POE_techniques [v0.1 BETA]

Post-occupancy evaluation (POE) techniques

This project is further detailed in the following scientific article:

reference

Overview

This project involves a set of data-based fault detection and diagnosis techniques to deeply understand real building operation and identify potential building faults. The techniques are divided into three action areas, related to indoor environmental quality (A), energy systems (B), and occupants’ behaviour and perception (C).

Versions

-_v0.1 BETA - First version of the project_ 	- 23/07/2023
-_v0.2 comming soon..._				- 

Requirements to use POE_techniques

Python version

• Python 3.8+

Installing development requirements

---

pip install -r requirements.txt

How to use POE_techniques?

The approach is divided into different Jypyter Notebooks to guide the workflow.

A.Indoor environmental quality

• Notebook a1_Ventilation_diagnosis - CO2 concentration above 1000ppm.
• Notebook a2_Airtightness_diagnosis - CO2-based decay method.

B.Energy systems

• Notebook b1_Unsupervised_load_disaggregation - Load disaggregation through non-intrusive load monitoring (NILM).
• Notebook b2_Thermostat_Control_Diagnosis - Evaluation of the heating system working at full-load and partial-load operation.

C.Occupants’ behaviour and perception

• Notebook c1_Lighting_system_diagnosis - Percentage of time in which lighting is on in unoccupied spaces.
• Notebook c2_Discrepancies_occupancy_operation - Percentage of time in which fixed building/HVAC operating schedules don’t match with occupancy.

The directory structure

---

The directory structure of POE_techniques project looks like this:

POE_techniques/
│ 
├── LICENSE 				<- MIT license
├── README.md
├── requirements.txt   			<- The requirements file for reproducing the analysis environment
│          		
├── notebooks				<- Jupyter notebooks to guide the workflow 	
│   ├─ a1_Ventilation_diagnosis.ipynb        		
│   ├─ a2_Airtightness_diagnosis.ipynb 
│   ├─ b1_Unsupervised_load_disaggregation.ipynb 
│   ├─ b2_Thermostat_Control_Diagnosis.ipynb 
│   ├─ c1_Lighting_system_diagnosis.ipynb  
│   ├─ c2_Discrepancies_occupancy_operation.ipynb    		
│             		
├── data/				<- Monitoring data of a university building in the UK (Oxford)
│   ├─ *.csv files
│       
└──

Contributing researchers

---

• Dr Jesús Lizana
• Dr Elnaz Azizi
• Dr Scot Wheeler
• Jonathan Wheeler