On May 4, 2015, we started up our photovoltaic generator. Here are some numbers and plots for the first month – and what I plan to do next.
Our generator has a rated power of 4,77 kWp (kilowatt peak), one module has 265 Wp. The generator would deliver 4,77 kW of electrical power under so-called standard testing conditions: An irradiance of 1000 W/m2 of light from the sun, a module temperature of 25%, and a standard spectrum of wavelengths determined by the thickness of the atmosphere light has to traverse (Air mass – AM 1,5, equivalent to sunlight hitting the earth at an angle of about 48° from the zenith).
Our 18 panels are mounted on two different roof areas, 10 of them (2,65 kWp) oriented south-east and 8 modules (2,12 kWp) south-west. The inclination relative to the surface of the earth is 30°, the optimum angle for PV at our latitude:
Positions of our PV panels on the roof.
We aimed at using our 30° upper roof spaces most efficiently while staying below the ‘legal threshold’ of 5 kW, avoiding a more complicated procedure for obtaining a permit to install them.
The standard conditions are typically met in spring here – not in summer – as the efficiency of solar panels gets worse with increasing temperature: for our panels -0,44% of rated power per °C in temperature difference. If the temperature is 60°C, peak power (for otherwise same irradiance and spectrum) would drop by 15% . We can already see this effect, when comparing two nearly cloudless days in May and in June. The peak power is lower in the first days of June when maximum daily air temperatures were already about 30°C:
Total output power (AC) of the PV generator and input power (DC) for each string as a function of time for two days. 1) May 11 – maximum ambient air temperature 23°C. 2) June 5 – maximum ambient air temperature 30,5°C.
The temperature-dependence of performance might in part explain impressive spikes in power you see after clouds have passed: The modules have a chance to cool off, and immediately after the cloud has gone away the output power is then much higher than in case of constant irradiance. Here is a typical example of very volatile output:
Output power of our PV generator when clouds are passing. The spikes (clear sky) show a peak power much higher than the constant value on a cloudless day in May; the troughs correspond to clouds shadowing the panels. The data logger included with the inverters only logs a data point every 5 minutes, so I parsed the inverter’s website instead to grab the current power displayed there every second (Using the inverter’s Modbus TCP interface would be the more professional solution, but parsing HTTP after reverse engineering the HTML structure is usually a quick and dirty ‘universal logging interface’.)
The maximum intermittent power here was about 4,4 kW!
Another explanation for the difference is local ‘focussing’ of radiation by specific configuration of clouds reflecting more radiation into one direction: Consider a cloudless region surrounded by clouds – a hole in the clouds so to speak. Then radiation from above might be reflected at the edges of that hole at a very shallow angle, so that at some place in the sunny spot below the power might be higher than if there were no clouds at all. Here is another article about this phenomenon.
A PV expert told me that awareness of this effect made recommendations for sizing the inverter change: From using one with a maximum power about 20% lower than the generator’s power a few years ago (as you hardly ever reach the rated power level with constant radiation) to one with matches the PV peak output better.
The figures from May 11 and June 5 also show that the total power is distributed more evenly throughout the day as if we would have had a ‘perfect’ roof oriented to the south. In the latter case the total energy output in a year would be higher, but we would not be able to consume as much power directly. But every kWh we can use immediately is worth 3 times a kWh we have to sell to the utility.
The next step is to monitor the power we consume in the house with the same time resolution, in order to shift more loads to the sunny hours or to identify some suckers for energy. We use more than 7000 kWh per year; more than half of that is the heat pump’s input energy. Our remaining usage is below the statistical average in Austria (3700 kWh per 2-person household) as we already did detective work with simpler devices.
Smart meters are to be rolled out in Austria in the next years, by 2020 95% of utilities’ clients should be equipped with them. These devices measure energy consumption in 15-minute intervals; they send the data to the utility daily (which runs a web portal where clients can access their data) but must also have a local interface for real-time logging given to clients on request. As a freshly minted owner of a PV generator I got a new ‘smart’ meter by the utility; but this device is just a temporary solution, not connected to the utility’s central system. It will be replaced by a meter from another vendor in a few years. Actually, in the past years we could read off the old analogue Ferraris meter and submit the number at the utility’s website. This new dumb smart meter, in contrast, requires somebody to visit us and read off the stored data once a year again, using its infrared interface.
I did some research on all possible options we have to measure the power we consume, the winner was another smart meter plus integrated data logger and WLAN and LAN interfaces. It has been installed yesterday ‘behind’ the official meter:
Our power distribution cabinet. The official (Siemens) smart meter is the rather large box to the left; our own smart meter with integrated data logger is is the small black one above it – the one with the wireless LAN antenna.
We will combine its data with the logging of ‘PV energy harvested’ provided by the inverter of the PV panels – an inverter we picked also because of the wealth of options and protocols for accessing it [*]
For the first month we can just have a look at daily energy balances from two perspectives (reading off the display of the dumb smart meter manually every day):
- The energy needed by appliances in the house and for hot water heating by the heat pump – 11 kWh per day: On average 56,5% in the first month come from the solar panels (self-sufficiency quota), and the rest was provided by the grid.
- The daily energy output of the solar generator was 23 kWh per day on average – either consumed in the house – this is the same cyan bar as in (1) – or fed into the grid. In this month we consumed 27% of the PV power directly (self-consumption quota).
Daily energy balance: 1) The energy we consume in the house – partly from PV, partly from the grid (left axis) and 2) The energy harvested by the PV generator – party used directly, partly fed into the grid (right axis).
[*] For German-speaking readers: I wrote a summary about different solutions for metering and logging in this case in this German article called ‘The Art of Metering’ – options are to use the official meter’s IR interface with yet another monitoring ‘server’, your own unrelated meter (as we did), a smart meter integrated with the inverter and using the inverter’s own data logging capabilities), or building and programming your own smart meter from scratch.