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We've always tried to be efficient, to use resources and energy sparingly, and to generate minimum waste. In October 2010, we took the next logical step by putting our south facing roof to good use with PV (photo-voltaic) panels that generate solar electricity. The panels have a peak rated output of 3.3kW, but the actual output is generally less than that, and varies with time of day, time of year and the weather. Using published monthly averages for sunshine in this part of the country, I estimated that the panels would generate around 2.7MWh per year, which is about 10% more than our annual consumption. Of course that doesn't make us 'self sufficient', because we still need to import energy when we aren't generating, eg to power our lights at night, but we should export more than we import.
Installation was straight forward – we used Ardenham Energy . The panels are mounted on brackets that go under the tiles, and are fixed to the rafters. They feed DC power to an inverter mounted in the loft (see pictures below) which sends AC power down to the total generation meter in the cupboard with the normal meter (see pictures below). When the panels are generating, the light on the meter flashes at a rate proportional to the power. We wanted to be able to see the power without going to the cupboard and timing the flashes, so we use an Owl electricity monitor that sits on the kitchen worktop (see pictures below). It communicates with a sensor clipped round the power cable. We have another Owl meter to show the power that we are using (see below).
The first graph shows energy generated per week since installation in October 2010 . (For tidiness the graph starts with January as week 1, so the data for 2010 appear only at the right hand end). The grey line shows the average output through a typical year that I expected before installation. I derived it from published monthly averages for sunshine in Berkshire, normalised so that the total energy was the same as the figure derived from the manufacturer's data,
The graph shows a lot of fluctuation from week to week, which just reflects the variability of our weather. On a day when the panels could generate well over 2kW in the sun, they only generate a few hundred W if it is cloudy. The pattern varies from year to year, for example in 2011 we had a lot of sun in April/May, whereas in 2012 we had the highest weekly output at the end of March, and then quite a low output in April/May. 2013, 2014, 2015 and 2016 were different again. 2013 saw the highest amount of energy generated in any week since installation – 132kWh in early June.
The second graph shows cumulative energy generation through each complete calender year. Like the first graph, it starts in January and it uses the same colours for each year. Data from the end of 2010 are omitted since it wasn't a complete year.
In every year energy generation has been at least 10% more than my predicted figure of 2.7MWh – for the seven years: 3.17MWh, 3.14MWh, 3.00MWh, 3.24MWh, 3.17MWh, 3.15MWh, 3.00MWh, 3.10MWh,). The early part of 2013 started significantly lower than other years, caught up during the July heat wave and ended the year only slightly lower than the other years, but still above my prediction. 2015 was unusual – cumulative generation by the autumn was higher than all other years but very dull weather in the rest of the year brought the total lower. 2017 was quite high early in the first half of the year but a dull summer meant it finished almost as low as 2013. So far, 2014 has been the best year for total energy generation.
To see the underlying seasonal pattern, you have to remove the short term fluctuations due to the weather. I did that with rolling 5 week averages (ie the average of a period from 2 weeks before to 2 weeks after the week in question. That removes a lot of the variability, and averaging the values across more than one year removes much of the remaining variability to give the thick black line.
As you would expect, the output in winter is a lot lower than the rest of the year, but there is relatively little change in output from Spring through to early autumn, whereas you might expect a lot more to be generated in midsummer with longer days and the sun higher. There are two reasons this is not so. One is that however long the day, the sun can't shine directly on the panels for more than 12 hours, because during the other 12 hours, even if the sun is above the horizon and shining on the house, it is behind the panels. They still generate from the glow of the blue sky, but at much lower power – like when it is cloudy. The other reason is the angle of our roof, which is about 35° – too steep for maximum midsummer generation and better for the slightly lower spring and autumn sun. In fact 35° is ideal for maximising the overall output during the whole year (see: The Best Angle And Orientation For Solar Panels In The UK
The power varies during the day (even with a clear sky), and the daily pattern varies round the year. In summer, the days are long and the sun rises high, while in the winter the days are short and the sun is low in the sky, with spring and autumn in between. You might expect to see a similar pattern in what is generated., but there is a difference. The curve in winter is indeed lower and narrower, but there is relatively little variation between spring, summer and autumn. The curve in summer is not significantly higher than the curves in spring and autumn because the sun is behind the panels at both ends of the long summer days. The limited difference in height is because of the roof angle is optimal for spring and autumn but not for summer (as explained above).
These graphs are based on readings in 2011 on sunny days in spring (end April), mid summer, autumn (mid September) and winter (mid December). To reduce the effect of fluctuation due to passing clouds I took readings at or near each hour over several days, and then used the highest figure for each hour. NB – All times are shown in BST, so midday is at 13.00 for all curves.
Before we bought the panels, I predicted that we would export about 85% of what we generate. I had produced a model for generation at different times of day round the year using various published data, and a similar model for consumption based on knowing our approximate pattern of using various devices, and I had then compared the two models.
I can't measure exported energy directly, because I opted not to pay extra for a certified export meter. (We could have been paid a bit more than we do without a meter - where 50% is assumed - but the few pence per kWh extra did not justify the cost of the meter.)
I still wanted to see how my model matched reality, and I can work out how much energy we export by comparison of three separate things: the energy we generate (from the generation meter). the energy we import (from the normal meter) and the energy we consume. To measure consumption, I use an Owl electricity monitor that has a cumulative energy readout as well as the power display. That introduces a small error, because the Owl doesn't measure power directly but measures current and calculates power by assuming a fixed voltage and power factor of 1. That method is adequate for the Owl's intended educational use, but not quite accurate enough for my purposes. Quite a few of our devices, notably fluorescent lights and switched-more power supplies in electronic equipment, have a power factor less than 1. As a result the display reads a bit higher than true power consumption. I worked out an approximate correction factor by comparing consumption measured with the Owl with that measured by the Consumer Unit during times when there was no generation so the two should have been equal. This correction factor is used in the figures plotted below.
The graph shows the split between energy generated and exported (green), energy generated and used on site (pale blue) and energy imported (dark blue), throughout the year. So the area above the axis represents total energy generated (greatest in the summer) and the area below the axis represents the total energy imported (greatest in the winter) – all in kWh per week). The graph shows the average across all years since I started measuring consumption (April 2011, about 6 months after installation) to the end of last year. During this 81 month period we exported 77% of the energy we generated, and we only needed to import 70% of the energy that we consumed.
The graph below shows successive years separately, so there is more week to week variation. I haven't extended it beyond 2017 since it is already quite wide. The anomalous dip in GenUse (pale blue) in late summer 2016 was caused by the sensor around the power cable coming partly unclipped so the readings were lower than they should have been.)
We sell the power that we generate through Ecotricity's Microtricity scheme, which is backed by the Government's Feed-In Tariff. We also buy our gas and electricity from Ecotricity because they invest all of their profit in building new green energy sources, while charging less than the dominant suppliers. When I last checked, Ecotricity was investing far more per customer in new green production facilities than the large suppliers, including those that offer 'green tariffs'.
One thing we didn't consider when installing the panels is that the space underneath them is attractive for pigeaons seeking a sheltered nesting site. About six years after installation we noticed pigeon activity that grew to a significant colony over the next few years. We think they pigeons might have been displaced from old buildings that were demolished in the town centre. When one of the cables was dislodged we decided to fit protective guards round the panels. While cleaning up behind them, the contractors removed three nests. It took a while for the pigeons to take the hint and move elsewhere – some of them hung around (see picture taken a few days after fitting).
Click to enlarge.
Photovoltaic panels on the roof
Inverter in the loft
Total generation meter in cupboard
Generation & consumption monitors
Guard mesh + disgruntled pigeons
(Page updated 26-March-2019 )
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