Introduction
This post repeats the analysis of the previous one, this time for the summer weather of 2014/15 in South Australia (SA), with 2016/17 wind farms.
The maximum demand in SA in summer 2014/15 was quite low, an outcome that the AEMO seems to give an unwarranted significance in its forecasting of future maximum demand. Also relevant to the AEMO demand forecasting is the fact that Queensland recently had its highest ever demand, something not meant to happen in a world of solar PV, increasing efficiency and prices, and “smart” consumers:
http://www.wattclarity.com.au/2017/01/queensland-demand-today-exceeds-the-previous-all-time-record/
The heatwaves of summer 2014/15 in SA fell mostly on weekends and the New Year holiday period, suggesting that intrinsic consumer demand was not as low as the raw demand data suggests.
Data Sources: see the previous post
Demand Data
The following figure shows the daily peak demands (blue curve) and the two major influences on them, the maximum temperature (at Adelaide Kent Town) in red and the times of weekends and holidays, marked with purple dots:
The four heatwaves in February 2015 all fell on weekends at critical times, in particular the 22nd February, the fourth in a sequence of very hot days, would have very likely produced a much higher peak demand if it had fallen on a working day. The only heatwave that was unaffected by the weekend demand reduction was in early January, but that was during the New Year holiday period, with schools and some businesses still on vacation. Intrinsic consumer demand was probably a lot higher than is suggested by the actual demand data.
Wind Data
The AEMO-estimated total wind power today from the 2014/15 weather is shown in the following figure, in terms of the daily maximum (red) and minimum (black):
The figure above shows the typical wind power variations in South Australia, often going from very high to very low in many days of summer. It is the deep wind power lulls, many lower than 50 MW, that causes the severe limitations on the impact of additional wind farms on peak demands on non-wind sources. The wind power data provided by the AEMO are 30-minute averages, and the minima will go to even lower values than shown above at times during each 30-minute interval.
Wind Power Impact
The following figure shows the daily peak demands (red squares), and the peak residual demands on non-wind sources (black curve):
The figure above shows that the highest peak demands on non-wind sources would be reduced by around 200 MW on average, i.e. by only around 10 MW for each of the 18 wind farms, but the reduction is only around 50 MW for what could have been the highest demand day, the 22nd February 2015. A simple way of seeing the impact of additional wind farms is to repeat the calculation of non-wind peak demands (black squares) with 50% more wind power (purple curve), shown in the following figure:
The figure above shows the barely perceptible effect of 50% more wind power on peak non-wind demands. The deep wind lulls of around 50 MW are the explanation, as they imply that each of the 18 existing wind farms are averaging a contribution of only several MW at the times of highest demand on non-wind sources.
CONCLUSIONS
Peak demand is not falling as fast as the AEMO may be assuming, increasing wind (and solar PV) cannot contribute significantly to additional firm capacity, conventional generators are closing down at a rapid rate, and no new ones are being built. This combination of circumstances can only end in tears.
climanrecon 