Variable supply
This first example model's the hourly output of a given installed capacity of wind, wave, tidal or solar. The model is not really doing much, it is just loading the capacity factors for every hour from the 10 year dataset and multiplying by the installed capacity. The total electricity generated is calculated as the sum of the electricity generation in each hour and printed along with the average capacity factor at the end.
The units here are not important. The example could just as well be in MW's or GW's. kW's where chosen as the model examples are focused around building a hourly model that's relatable to an average households energy demand. The kW's of installed capacity could just relate to a small share of a much larger wind turbine, solar farm, wave or tidal power installation.
Running the model for each of these generation types with the same installed capacity the results are as follows:
| Onshore wind | Offshore wind | Wave | Tidal | Solar | |
|---|---|---|---|---|---|
| Installed capacity | 1.0kW | 1.0kW | 1.0kW | 1.0kW | 1.0kW |
| Annual generation | 2834 kWh | 4204 kWh | 2482 kWh | 2092 kWh | 826 kWh |
| Capacity factor | 32% | 47% | 28% | 23% | 9% |
In all of the examples above the installed capacity of the renewable generator was the same (1.0kW) but we can see straight away that there is a significant difference in the total electricity generated by each type. A unit of offshore wind generates just over 5 times as much energy as a unit of solar pv using the zerocarbonbritain dataset. By itself this is not enough information to evaluate the effectiveness of a technology, we would need to compare the costs per unit of installed capacity, embodied energy per unit of installed capacity, how well a particular solution matches demand, the land areas required, the availability of the resource to name just a few of the many factors that need to be weighed up but it does highlight one of the important factors.