new 6 month chiller 1 data documented

credentials.txt

questions.txt

*.xlsx

*.pptx

*.pdf

desktop.ini

.vscode/

order: 4

---

The data is sourced from an Excel document. It is converted to `csv` for faster read/write operations.

## Data extraction

## Data type

The data are made available through the MetaSys application. The application is responsible for aggregating sensor readings in Engineering Science Building. It allows upto 14 days' of data and 10 fields to be viewed and copy-pasted to a spreadsheet at once.

Relevant fields are consolidated from various components (Cooling Towers, Chiller) into a survey. The survey is accessible in the navigation tree through the path:

```

Vanderbilt University

    METASYSPROD

        ESB Chiller 1

```

![MetaSys navigation](img/4-metasys-path.png)

Multiple columns may share names (for e.g each power measurement for the 4 fans in the 2 cooling towers is labelled `Output Power.Trend - Present Value`). Therefore the order of selection of columns is vital.

![MetaSys Fields](img/4-metasys-fields.png)

The data are copied to an excel document. Since the number of fields is greater than 10, two sheets are made (with suffixes _1 and _2) for the first 10 and remaining fields. The document is then fed to a pipeline to run basic pre-processing and clean-up tasks.

## Pre-processing

### Renaming fields

The fields were manually renamed to be consistent, illustrative, and unique. Details of field names can be seen in the [dataset description](5-dataset.md).

| Original Name                                                    	| Renamed     	|

|------------------------------------------------------------------	|-------------	|

| Starter Input Power Consumption.Trend - Present Value ()         	| PowChi      	|

| Cond Entering Water Temp.Trend - Present Value ()                	| TempCondIn  	|

| Cond Leaving Water Temp.Trend - Present Value ()                 	| TempCondOut 	|

| Evaporator Entering Water Temperature.Trend - Present Value ()   	| TempEvapIn  	|

| Evaporator Leaving Water Temperature.Trend - Present Value ()    	| TempEvapOut 	|

| Output Power.Trend - Present Value ()                            	| PowChiP     	|

| Output Power.Trend - Present Value ()                            	| PowConP     	|

| Output Power.Trend - Present Value ()                            	| PowFanA     	|

| Output Power.Trend - Present Value ()                            	| PowFanB     	|

| Flexim M-3 (WCM-1) volumetric flow rate.Trend - Present Value () 	| FlowEvap    	|

| Outside Air Temperature.Trend - Present Value                    	| TempAmbient 	|

| Outside Air Humidity.Trend - Present Value ()                    	| PerHumidity 	|

| Ambient Wet-Bulb.Trend - Present Value ()                        	| TempWetBulb 	|

| Chiller 1 Percent Load.Trend - Present Value ()                  	| PerChiLoad  	|

| Output Frequency.Trend - Present Value ()                        	| FreqFanA    	|

| Output Frequency.Trend - Present Value ()                        	| FreqFanB    	|

| Tower 1a Fan Output.Trend - Present Value ()                     	| PerFreqFanA 	|

| Tower 1b Fan Output.Trend - Present Value ()                     	| PerFreqFanB 	|

### Joining sheets

The data were manually copied to MS Excel in two sheets. Each row in each sheet is timestamped. Using those timestamps, all measurements for a particular time can be consolidated into a single row. This timestamp-matching necessitated by some timestamps missing from the second sheet.

### Data type

Ideally, all cells in the dataset are numerical. Some preprocessing is required to remove errant `???` symbols and text.

These operations are done in `ioops.py` when excel files are converted to csv.

## Units

### Units

Temperature values are recorded in degrees Farenheit. They are converted to Kelvin. Formulae in `thermo.py` rely on Kelvin values.

Fields with explicit units (`kWperTon`) are not converted.

## Field names

### Field names

Fields are manually renamed to remove spaces, punctuation characters, and application specific designations.

So the field measuring entering water temperature for a condenser will be `TempCondIn`.

## Missing temperature values

### Missing temperature values

The towers timeseries occasionally have missing values for `Outside Air Temperature`, `Outside Air Humidity`, and `Ambient Wet-Bulb` temperature. However, given two values, the third can be calculated.

These operations are defined in `thermo.py` and called in `preprocess.py` to clean up csv files.

## Missing/zero power values

### Missing/zero power values

In several measurements power is recorded as 0. However this may not reflect the actual state of the system and may simply be an error in logging/networking or a temporary fluctuation. Because the cause of a zero measurement is indeterminate, such records are not considered during analysis.

---

title: Dataset and system description

title: Datasets and system description

order: 5

hasequations: true

---

![System description](img/5-system-description.png)

The dataset provided is comprised of 2 timeseries:

1. Parameters for Chiller 1

2. Parameters for Chiller 2

*Note: All fields are converted to SI units (Kelvins, watts, $m^3 s^{-1}$). Except for `KWPerTon`.*

*Note: All fields are converted to SI units (Kelvins, watts, $m^3 s^{-1}$).*

## Schematics

![Towers](img/4-ChilledWaterSystem-towers.jpg)

## Cooling tower parameters

## System parameters

Each cooling tower has the following parameters:

Each cooling tower/chiller system has the following parameters:

1. `Time`: Timestamp in 5 minute increments.

16. `TempWetbulb`: Wet-bulb temperature.

17. `PerChilLoad`: Cooling load of the chiller as a fraction of maximum electrical capacity. The maximum cooling capacity in tons is 800 tons. The ratio `Tons / 800` should give roughly the same value as `PerChilLoad`.

17. `PerChiLoad`: Cooling load of the chiller as a fraction of maximum electrical capacity. The maximum cooling capacity in tons is 800 tons. The ratio `Tons / 800` should give roughly the same value as `PerChilLoad`.

And the following derived fields:

1. `PowIn`: Total input power calculated as a sum of all power fields.

And the following derived parameters:

1. `Tons`: Amount of cooling done. Calculated using evaporator temperature change and volume flow rates (`7`, `8`, and `13`).

## Datasets

2. `KWPerTon`: Measure of efficiency. Lower the better. Calculated from `2` and `18`.

For each of the 2 chillers (1 & 2), the data were recorded for six months from Spring Equinox (March 20, 2018) through Fall Equinox (September 23, 2018). Measurements were recorded at a 5 minute interval.

3. `PowIn`: Total input power calculated as a sum of all power fields.