Electricity — Time of use in Victoria
Since the introduction of smart metering, a question that I have always had is, ‘am I financially better off with a single rate tariff or a time of use tariff for my domestic electricity?’. The only real way to know is to crunch the data and compare the different options. City Power is my local distributor here and they offer my address in Melbourne, three different tariff options,
- A fixed tariff (which I have always been on)
2. A two rate tariff based upon time of use
3. A three rate tariff based upon time of use
My current retailer is Kogan Energy (figures from https://assets.kogan.com/files/energy/pdf/rates/2020june/KE-CP-200701-market.pdf). Kogan Energy offers plans on each of the tariffs from City Power. The plans have a daily charge of $0.9631 for the fixed rate and $1.0091 for the time of use tariffs. That is a saving of 4.61 cents per day or $1.38 per 30 day billing period for the single rate tariff.
For the fixed rate tariff (ignoring controlled load as they do not apply in my situation) the rate is 22.26c per kWh any time for any amount of consumption.
For the 2 rate tariff, peak is 29.25c per kWh and off-peak is 18.45c per kWh.
For the 3 rate tariff, peak is 27.79c per kWh, shoulder is 24.46c per kWh and off-peak is 18.04c per kWh.
By casual inspection, time of use tariffs are only cheaper during the off peak time. Off peak is usually after 10 or 11 PM to 7AM although there is some variation between the 2 and 3 rate tariffs. That said the 2 rate has a major advantage that all power is off peak on the weekend.
I have detailed electrical consumption data that I have been collecting. This measures consumption many times per second in Watt hours. All that was required was to get the inspiration to analyse this data and perform some analysis.
The first step was to resample the data into a more coarse frequency. Many times per second is too fine for this analysis. Hourly is a good resolution as it allows me to categorise hours of the day into the various tariffs that apply.
I then exported my hourly electricity data with some extra fields. The first is the amount of Wh consumed in the hour, the applicable 2 tariff for that hour, the applicable 3 tariff for that hour, as well as the min, max, median for Voltage, Current, Power, Power Factor and Frequency because I had these at hand.
Taking this hourly data, I developed some code to determine the applicable tariff based upon the day of the week and the hour of the day. I then converted Wh into kWh and multiplied the two figures to compute the price. As I had stored this data in a SQL database I was able to compute this for a calendar month.
On a 2 rate tariff, a single rate tariff saves $2.34 out of $39.95 spend. A saving of 5.87%.
On a 3 rate tariff, a single rate tariff saves $2.90 out of $39.95 spend. A saving of 7.27%.It looks like the all weekend off peak rate is what is driving the 2 rate time of use tariff to be lower than the 3 rate tariff. That said for my situation that is only $0.56 for an entire month of savings.
For my apartment and usage patterns, a single rate tariff is always cheaper for daily service charges and also the usage charges. As can be seen from the data the bulk of my consumption is outside of the cheaper off peak times. I might be able to move some consumption to off peak but not enough to make a difference. The bulk of my usage will be for electric oven, split system heating and cooling, refrigeration and television. Most of these items get their use during the shoulder / peak periods of the time of use. If we made extensive use of the clothes dryer I could schedule this to off peak times, but we use the dryer about 10 times per year.
As you can see from the data, I used less than 150kWh in July 2020 which is less than 5kWh per day. Some days I spend more on the daily access charge of $0.9631 than I do on electricity. My minimum consumption is approximately 1.5kWh to 2.0kWh to run refrigeration and standby electronics.
Technologies used:
Python: to load high resolution JSON files into SQLite database
Pandas: to resample high resolution data to hour records and compute the applicable tariff for each hour.
Pandas: to analyse the hourly data and present comparisons between the various options
I’ll continue to use a single rate tariff to save about $5 a month. I’ll be able to use these tools to compare any time of use tariffs that may present themselves in the future from Kogan or other retailers.
Disclaimer: This analysis is based upon data from my installation, current retailer and distributor. These figures may change and other dwellings may have different usage patters. I’d advise people to obtain their own meter readings from their electricity distributer to better understand their own time of day usage patterns.
