The Impact of Ambient Temperature on the Output Power of Solar Panels

I have noticed the impact of traversing clouds on solar power output: Immediately after a cloud has passed, power surges to a record value. This can be attributed to the focusing effect of the surrounding clouds and/or cooling of the panels. Comparing data for cloudless days in May and June, I noticed a degradation of power – most likely due to higher ambient temperatures in June.

We had a record-breaking summer here; so I wondered if I could prove this effect, using data taken at extremely hot days. There is no sensor on the roof to measure temperature and radiation directly at the panels, but we take data taken every 90 seconds for:

  • Ambient air temperature
  • Global radiation on a vertical plane, at the position of the solar thermal collector used with the heat pump system.

I was looking for the following:

  • Two (nearly) cloudless days, in order to rule out the impact of shadowing at different times of the days.
  • These days should not be separated by too many other days, to rule out the effect of the changing daily path of the sun.
  • Ideally, air temperature should be very different on these days but global radiation should be the the same.

I found such days: August 1 and August 12 2015:

Daily PV ouput energies and ambient temperatures in August 2015

Daily output of the photovoltaics generator (4,77 kW peak), compared to average and maximum air temperatures and to the global radiation on a vertical plane. Dotted vertical lines indicate three days nearly without clouds.

August 12 was  a record-breaking day with a maximum temperature of 39,5°C. August 1 was one of the ‘cool’ but still perfectly sunny days in August. The ‘cold day’ resulted in a much higher PV output, despite similar input in terms of radiation. For cross-checking I have also included August 30: Still fairly hot, but showing a rather high PV output, at a slightly higher input energy.

August 2015 in detail:

Daily PV ouput energies and ambient temperatures in August 2015 - details

Same data as previous plot, zoomed in on August. Dotted lines indicate the days compared in more detail.

Overlaying the detailed curves for temperature and power output over time for the three interesting days:

PV power and ambient temperature over time

Detailed logging of ambient air temperature and output power of the photovoltaic generator on three nearly cloudless days in August 2015.

The three curves are stacked ‘in reverse order’:

The higher the ambient air temperature, the lower the output power.

Note that the effect of temperature can more than compensate for the actually higher radiation for the middle curve (August 30).

I have used global radiation on a vertical plane as an indicator of radiation, not claiming that it is related to the radiation that would be measured on the roof – or on a horizontal plane, as it is usually done – in a simple way. We measure radiation at the position of our ribbed pipe collector that serves as a heat source for the heat pump; it is oriented vertically so that it resembles the orientation of that collector and allows us for using these data as input for our simulations of the performance of the heat pump system.

Our house casts a shadow on the solar collector and this sensor on the afternoon; therefore data show a cut-off in the afternoon:

Global radiation on solar collector, vertical plane, August 2015

Global radiation in W per square meter on a vertical plane, measured at the position of the solar collector. The collector is installed on the ground, fence-like, behind the house, about north-east of it.

Yet, if you compare two cloudless days where the sun traversed about the same path (thus days close in the calendar) you can conclude that solar radiation everywhere – including the position on the roof – was the same if these oddly shaped curves are alike.

This plot shows that the curves for these two days that differed a lot in output and temperature, August 1 and 12, were really similar. Actually, the cooler day with higher PV output, August 1, even showed the lower solar radiation due to some spikes. Since the PV inverter only logs every 5 minutes whereas our system’s monitoring logs every 1,5 minutes those spikes might have been averaged out in the PV power curves. August 30 clearly showed higher radiation which can account for the higher output energy. But – as shown above – the higher solar power could not compensate for the higher ambient temperature.


Logging setup:

More Ice? Exploring Spacetime of Climate and Weather.

I have become obsessed with comparing climate data for different regions in the world and in different years (space + time).

Finally I have found the tool I was looking for; now I can compare average Ice Days quickly – days with a maximum temperature < 0°C. In the first quarter of 2014 there were:

5 Ice Days in Vienna

compared to

68 Ice days Days in the Canadian prairie, in Regina, Saskatchewan, Canada.

It seems that a typical winter in Regina is about as grim as the winter in Europe in 1962/63, a 250 year event that has its own Wikipedia entry (DE version for Europe, EN article for UK). In this winter temperature was below 0°C for up to 120 days even in lowland areas. It was the most persistent cold since 1739. In Canada and Greenland temperatures were unusually mild in that season:

GHCN GISS HR2SST 1200km Anom1203 1963 1963 1949 1978

I am interesting in the probability of extremely cold days in a row as this determines the size of the water tank to be used a heat source. The Austrian national weather service provides data since 1994. I used the daily average ambient temperatures as an input for a crude simulation – to determine the maximum volume of ice in the tank per year. So I did accounting of the energy in water tank:

  • How much energy is needed for space heating and hot water, based on ambient temperature and number of persons?
  • For a constant performance factor of 4 the heat extracted by the heat pump from the tank is 3/4 of this. The assumption is reasonable as long as the tank is big enough which means the tank temperature will not be lower than 0°C.
  • How much energy can be gained from ambient air? Air temperature needs to be some degrees higher than brine temperature which has typically less than 0°C in winter.
  • How big is the contribution of ground? If the tank would be fully frozen only this contribution would matter – then the system had turned into a geothermal one.

This was a much simpler exercise than detailed simulations I did for selected seasons before – based on and data taken every hour or even every 3 minutes. In the daily accounting approach, I did not take into account the detailed hydraulic schema, every switching of a valve or the temperatures ‘before’ and ‘after’ the heat exchangers in the tank and in the air. It also speeded up calculations to replace numerical simulations of the heat flow and the ‘temperature waves’ in the surrounding ground below the tank by simple estimates.

I compared the results to measured volume of ice for the past two seasons and to a detailed simulations for specific seasons. Since the maximum volumes of ice are approximately the same I consider the simple simulation good enough for providing an overview and some ‘feel’ about what different winters will result in.

Our tank is ~27m3 size in, thus allowing for ~25m3 of ice maximum as the volume is increased by 10% on freezing. It would have hit the limit in 1996 and 1997:

Volume of ice, water tank as a heat source of heat pump. Simulation for 1994-2013.

Volume of ice in the tank, determined by ambient temperature. The peak for 2005/2006 is in agreement with a ‘real’ detailed simulation, the peak for 2012/2013 with the measured value. The small peak for 2013 is still larger than the observed value as the simple simulation based on daily values only breaks down if the ‘lifetime’ of the ice peak is too small.

Every heat pump system has an option to switch to a heating element in case the heat source is exhausted. With air heat pumps, the ambient air simply gets too cold. Geothermal systems utilize a big volume of soil, so the source would be exhausted just as our tank when a large volume of soil is frozen. Limiting factors are the freezing point of brine and the thermodynamic properties of the refrigerant.

We would have used the heating element 2 times in 20 years for a few days. This could be prevented if the tank was built bigger; finally it boils down to an economic assessment:

  • Our house needs about 20.000 kWh per year of energy (hot water included) This is a conservative estimate – in the season 2013/14 we needed only 17.500 kWh.
  • As long as the tank is not frozen, the performance factor is 4 and thus 3/4 of this will be provided by ‘the environment’ / the tank: 15.000 kWh.
  • The remaining energy is the electrical energy consumed by the heat pump’s compressor: 5.000 kWh.
  • On a very cold day the heating energy is: 130 kWh (equivalent to 5,4 kW – so still below design heating load); about 98 kWh are extracted from the tank.
  • The tank contains about 2.000 kWh latent heat and can sustain about 20 very cold days.
  • The ‘ten year colds’ lasted for a few days more. Four more days would require about 500 kWh extra, by 1:1 heating.

I highlighted the essential numbers to be compared: Once in ten years, electrical heating energy would be higher by about 10%. On average (per year), this would add only  1%. 1% of the yearly utility bill’s total need to be compared to the costs of building a larger tank.

In an exceptional winter like season 1962/63 about two more months had to be sustained: Heating at worst case power for 60 days is equivalent to 7.800 kWh; and using a 1:1 heating element means an excess electrical energy of 5.850 kWh – those 3/4 of the total heating energy that would otherwise (before the tank is exhausted) be provided by ‘the environment’. This has to be compared to standard consumption for 250 years, that is: 250 times 5.000 = 1.250.000 kWh. Thus excess heating energy amounts to less than 0,5%.

One might argue that 250 years does not make sense as you might at best consider heating costs for one human being’s life time – and you might encounter such a season, or not. But after all, these numbers would just provide some way of comparing different heating systems – all of which would result in excessive heating costs in such a winter no matter what the fuel was.