#MakeOverMonday Week 32 2019
For this week we received a bigger dataset, so first of all, lets do some exploring with Python code for the practice.
The dataset has 796,453 rows and 12 columns. Mmm something to be aware of, 11 of the columns have a name that start with a space. So, if I want to refer to them, I need to use that space as well.
The information is from 01-01-2012 to 03-08-2019, so on charts you need to be aware that the sum om 2019 is not comparable with the sums of other years.
There are 8 types of energy sources in this dataset:
- Biomass: run on imported timber or use sawmill waste.
- CCGT: Combined Cycle Gas Turbines are gas turbines whose hot exhaust are used to drive a boiler and steam turbine. This two-stage process makes them very efficient in gas usage. They are also quite fast to get online, so they are used to cover peak demand and to balance wind output.
- Pumped: These are small hydro-electric stations that can use overnight electricity to recharge their reservoirs. Mainly used to meet very short-term peak demands.
The other columns are an ID number, a timestamp, the demand (the total Giga Watt demand of the entire UK) and the frequency (the grid frequency is controlled to be exactly 50Hz on average, but varies slightly)
The Frequency and the Solar columns are decimal numbers the others are whole numbers and the timestamp is an object.
There are no missing values at all. There must be some doubles, looking at the timestamp, because there are 796,401 unique timestamps in the 796,453 rows. But 52 rows on the whole dataset can be negligible. Every row did get an unique ID, because here I see the same row count as rows in the dataset.
I used the Quick Insights option of Power BI and got insights that do not tell me anything. So I started to make some myself.
First I looked at the uses by year (2012-2018) for each source.
- Coal goas down
- Nuclear stays around the same level
- CCGT grew up to 2016 and now flattens out on the downside.
- Wind is going up since 2016
- Pumped, goes down since 2016
- Hydro show some fluctuation, but stay’s around its average
- Biomass: uses going up
- Solar is showing an intense growth in 2017 and it stay’s high in 2018 and that growth is so much that when you plot it in a line chart with coal, with had the highest use in 2012 that the coal line goes flat in the bottom of the chart, so I do not consider the information in the solar column of a good quality.
The 3 mean sources in 2012 where Coal, CCGT and Nuclear and in 2018 that is CCGT, Nuclear and Wind.
The demand on GW has gone down over the years with 724,444,951 GW
Found insights, did not yet find a story to tell. Lets take some rest and continue an other day.