One way to reduce the effects of synchronisation is to see how wind & solar, the main VRES can complement each other. ENTSO-E, the association of European transport grid operators offers an open-data platform that can also be access via a Python API.
The following charts show the solar and on-shore wind forecasts for Germany, aggregated by hour of day over a 3 month period of 2002 for each of the 4 seasons:
We can see that for this particular part of northern continental Europe, wind is generally stronger in the winter half of the year and due to the high latitude solar is much stronger in the summer than in the winter. Wind also shows a much higher day-to-day variance than solar, but practically evens out in terms of average intra-day patterns, while solar energy product is concentrated more deterministically on a few hours around mid-day. When combining the two types of resources, we (unsurprisingly) see a lower volatility than for each of the two sources. Before starting the analysis, I would have expected a more pronounced pattern of wind distribution across hours of the day (e.g. more wind during the night, less during mid-day) as well as possibly stronger negative correlation (less wind on blue-sky & sunny days and vice versa.).
Another way to look at the mismatch between supply and demand is to determine what amount of idealised storage would be needed to equalize them:
| Type | Avg Power (GW) | Total Energy (GWh) | Storage Capacity (GWh) | St. Power (GW) | St. Duration (h) | Capcity Ratio (%) | Stored Energy Ratio (%) |
|---|---|---|---|---|---|---|---|
| solar as base load | 6.4 | 55771.0 | 14156.6 | 31.7 | 447 | 25.38 | 60.87 |
| wind as base load | 11.3 | 99352.3 | 18382.9 | 29.7 | 620 | 18.5 | 33.82 |
| combined as base load | 17.7 | 155123.2 | 11826.1 | 42.1 | 281 | 7.62 | 28.0 |
| solar as 11.4% of load | 6.4 | 55771.0 | 15077.0 | 31.5 | 479 | 27.03 | 58.71 |
| wind as 20.3% of load | 11.3 | 99352.3 | 15680.7 | 29.4 | 533 | 15.78 | 32.76 |
| combined as 31.7% of load | 17.7 | 155123.2 | 9237.4 | 37.8 | 244 | 5.95 | 25.65 |
The simulation assumes a storage of 100% efficiency that would redistribute the variable rate wind & solar production into either a constant output corresponding to the yearly average ("base-load") or to a constant fraction of the actual load curve that corresponds to the yearly share of energy production.
We can see that in general solar requires a higher rate of storage capacity than wind - about 28% of storage capacity per amount of energy produced and about 60% of the energy needs to be cycled through storage instead of used directly when produced.
Reducing both sources significantly reduced the storage capacity needed, to about 6% of the energy produced and about 25% of the energy requiring storage.
This is still a daunting amount - equivalent to about 450 times the capacity of the new Nant de Drance pumped hydro power plant in Switzerland or the battery packs of 90M Tesla model S. Also the cycle efficiency of real storage systems are far from 100%. They range from 90% for batteries to about 70-80% for pumped hydro to less than 50% for P-to-X.
As we move into the next phase of large scale renewable energy deployment, storage technology will be the space to watch.
