# How Do Heating Degree Days Vary With Temperature?

Once again heating degree days (HDD). In two of our previous postings we investigated the correlation between HDDs and energy consumption. The first posting aimed at highlighting the influence of the number of HDDS on gross energy consumption, while the second focused on more specific data, namely the amount of energy devoted to heating purposes. The results were not very encouraging, since no strong correlation between the two parameters could be found. In fact, we might have expected otherwise.

In this posting we aim at a more fundamental approach. Is is clear from the definition of HDD that changes in temperature are reflected in the number of days where the heating needs to be switched on. This argument is straightforward on a daily basis. But does it also hold if we take monthly averages instead? Intuitively, the answer would be yes. But what we want to know is to what extent a montly average temperature may be considered a reliable measure for determining the value of HDDs.

In order to find the solution to this riddle we analysed the data from Sweden during the period 2003 – 2011. The baseline heating temperature for our investigation was taken to be 20°C, but HDDs for other baseline temperatures may easily be calculated. Our analysis lead to the conclusion that there is a very strong and reliable (negative) correlation between the average outside temperature and the number of HDDs over the years. As the annual data show consistently the same pattern we are not surprised to find that the same relationship holds for the multi-annual averages taken over a 30-year period as is shown in Fi.g 1.

Fig. 1 Average temperature and HDD in Sweden over a 30-year period

After these enouraging findings we might wonder if we could go one step further and look at the correlation between the annual data. Thus, we take the annual average temperature and relate it to the number of HDDs per year. As the resolution gets coarser we might expect a weakening of the relationship. However, the results are once again quite stimulating since at annual level the relationship between the two sets of parameters does not seem to loosen.  This is demonstrated in Fig. 2.

Fig. 2 Annual average temperature and HDD, 2003-2011

There is a nice negative correlation between the mean outside temperature and the number of HDDs, similar to the one we have seen for the monthly data.

A numerical analysis of our findings leads to the conclusion that, on a monthly basis, one degree of temperature difference (T,in – T,out) in centigrade corresponds to 30.5 HDD. Thus, if the monthly average temperature drops by 1 °C the number of HDD increases by 30.5. As a consequence, the number of HDDs may be directly calculated from the mean temperatures. Needless to say, that this is in perfect agreement with our own expectations.

# Heating Demand and HDD

Heating degree days (HDDs) are supposed to serve as an indicator for heating demand. At first glance, everything seems obvious. HDDs are a smart combination of the temperature difference between the interior of a dwelling and the outside temperature and the number of days where the difference is valid. (See one of our previous articles for technical details).

In an earlier posting we investigated the link between HDD and gross energy consumption. Then the findings were not as convincing as one might expect. An increase in HDD does not necessarily mean that consumption is rising in the same way. On the contrary, in some cases the two parameters might even go in opposite directions.

Surely, primary energy demand is certainly too crude a measure to be strongly correlated to simple variations in temperature. Too many other factors like energy demand for transport purposes and manufacturing come into play. At the end of the day, domestic needs and especially heating constitute just a fraction of the total energy cocktail. Thus it is tempting to go one step further and look into a potential, and hopefully more clearcut relationship between HDD on the one hand and consumption figures for heating purposes on the other.

We performed such an analysis for the case of Austria, covering the years from 2003 till 2010. The source data have been taken from Eurostat and Statistik Austria. The consumption figures refer to three different sources, namely heating, warm water and cooling.

Fig. 1 HDD and energy consumption for heating purposes in Austria, HDD* = HDD/30.

The correlation between the two sets of data is obviously better than in our earlier analysis which was based on gross consumption figures. Nevertheless, there are notable deviations from an ideal scenario which require some interpretation.

Before the economic crisis of 2008 the amount of TWh that went into heating was fairly stable. Up to 2008 and again in 2010 HDDs show much larger deviations from the mean value than the consumption figures. In some years, 2004 and 2008 to be precise, the deviations have a different sign, thus going in opposite directions as can be seen in Fig. 2.

Fig.2 Energy demand for heating and HDD, deviation from mean value.

Both, in 2006 and 2009, consumption figures differ more significantly from their mean value than their respective counterparts in HDD.  However, we may consider this as an exception. In general, energy consumption for heating, cooling and warm water seems to be more inert than the fluctuations caused by weather conditions.

This is good news because it shows that our heating systems are much less sensitive to outside conditions than what we might expect in the first place. On the other hand, it may also indicate that dwellings having a high degree of thermal insulation of which there are many in Austria are less exposed to temperature fluctuations.

# Does Saving Energy Push Renewables?

Yes it does. Let us look at a concrete example in order to get the point. The EU plans to improve its energy efficiency by 20% by 2020. In other words, 20% less energy will be used by then, according to plans. The baseline is the primary energy consumption for 2010 which was 1770 Mtoe. Thus, if all measures are in place, by 2020 this figure should be down to 1416 Mtoe.

In all likelihood, the savings will concern almost exclusively the use of conventional energies (coal, nuclear, oil) whereas renewable energies will not be touched by this development. Therefore, we may safely assume that on the consumption side renewables will be equally well off  as they are now. In fact, this is a very conservative estimate. On the contrary, renewable energy use may well be expected to rise over the next decade. But let us stick to our conservative approach for the time being. In 2010, the consumption of renewables amounted to some 172 Mtoe corresponding to 9.7% of total consumption.

Fig. 1 EU Gross inland consumption in 2010

Given our  2020 scenario from above and keeping renewable consumption at 172 Mtoe, we may conclude that by then renewables account for about 12.2% of total consumption. Bear in mind that this is true even if energy production from renewable sources does not increase.

The projection for 2020 would consequently look like this.

Fig. 2 EU Gross inland consumption in 2020

Thus, by saving energy the relative weight of renewables in the energy mix is automatically increased. The bigger the savings on the one hand the bigger the extra share of renewable energies on the other.

By MJ

# Solar to Hydrogen – Can We Turn the Desert into a Hydrogen Plant?

Generating solar energy in the desert is a tempting challenge. The abundance of solar irradiation and the dry air with an almost cloudless sky provide almost perfect conditions for driving PV plants. Not surprisingly, people have thought about this possibility, and some projects have already been proposed which, however, so far have not developed beyond the first planning stages. Furthermore, these projects are still not on financially safe ground. In any case, they will require a tremendous amount of financing and that is, it seems, their most vulnerable point.

One of those futuristic project ideas, called Desertec, provides some insight into its deliverables and may thus be used as a reference. According to planning, it should be able to transmit in 2020 some 60 TWh of electrical energy from the north African desert right away to energy-hungry Europe. This roughly corresponds to the annual production of 6 nuclear plants. Electricity output is expected to grow continuously over the years with a target of 700 TWh annually in 2050.

One may, of course, question whether transmitting electricity over several thousands of kilometers is the smartest way of doing things. The losses in the transmission network will be significant, as discussed in an earlier posting. It´s not only the length of the distribution grid eating up a substantial part of the energy produced by the desert sun. As it does not make sense to transmit electricity during daytime only, part of the generated power would have to be stored for transmission during the night. This, too, consumes some energy which in turn reduces the efficiency of the whole project.

Rather than sending solar power via large distance cables to Europe, one may ask if using it for liquefying hydrogen might be a better option. Given the state-of-the-art technology the expected Desertec output for 2020 could provide some 6 Megatons of liquefied hydrogen annually which may be shipped across the Mediterranean for further useage.

Applying model calculations taking into account the losses during transportation and handling we found that this amount of liquid hydrogen could provide sufficient energy to drive some 3 million cars with an average annual driving distance of 20,000 km. This corresponds to the stock of registered vehicles in a country like Hungary (2008 data).

Going over to the even more optimistic scenario for 2050, then the collective effort of all desert-based PV facilities sould  enable the production of at least 70 million tons of liquefied hydrogen. Transferring this figure into cars on the road, we find that this amount provides fuel for not less than 35 million autos. This is reoughly equivalent to the number of registered cars in Italy (2008 data).

In this way solar energy, via its hydrogen derivative, could become a serious competitor to gasoline and diesel. Its advantages are obvious with both, solar energy and hydrogen being available in virtually unlimited quantity.  Moreover, the environmental benefits with a substantial reduction in CO2 emissions are equally promising. Bear in mind that the transport sector is responsible for about 25% of all CO2 emissions in Europe.

# Heating degree-days

What are heating degree-days and what are the advantages and limitations of that conept? Generally speaking, heating degree-days (HDD) represent a sensible measure in order to estimate how much energy must be provided for heating purposes.

It´s cold outside, you turn on the heating. The colder it is, the more you have to heat, if you want to keep the room temperature at a convenient level. As a consequence, you need more energy, if the outside temperatures are lower. Thus the temperature difference between inside and outside to a large extent determines how much oil, gas, wood or electricty you need in order to keep your place cosy and warm.

But this is not the only parameter having an impact on your heating bill. Another factor of crucial importance is the numer of days you have to keep the heating running in the first place. Wintry weather conditions and their duration can vary considerably from one year to another. Last year, at the beginning of November, outside temperatures in northern Europe were already below 0° C. This year, however, in the same region the thermometer has hardly ever touched the freezing point, thus saving a lot of energy costs.

So we see that two crucial parameters determine the heating effort: the temperature difference between living room and outside on the one hand and the duration of the period when the heating is on.

Formally speaking, following the definition used by Eurostat, HDD may be defined as follows:

HDD = (18° C – Tm)*d,  if Tm <= 15° C  or

HDD = 0,  if Tm > 15° C

In this formula, d represents the number of days when heating is considered to be required and Tm is the mean outside temperature defined as Tm = (Tmin + Tmax)/2. Thus, Tm is an average value of minimum and maximum temperatures during a certain period. But when is the heating actually on? According to Eurostat the heating is on when Tm <= 15° C, whereas for Tm > 15° C it is off and then HDD = 0.

In this way, we have obtained an important indicator for the amount of energy which is needed in order to keep our living or working space at an agreable level.

However, HDD in itself is not sufficient to determine or even estimate the actual amount of energy necessary for heating purposes. To that end, more input is needed. In particular, we need to know how big the energy flow from our living and/or working premises to the outside world is. Clearly the heat flow is directly proportional to the difference in temperatures as indicated in the formula for HDD. Yet, the amount of heat passing from the cosy appartment to the cold and sometimes frosty environment also depends on the insulation we use in order to reduce the loss of heat. The insulation in turn is closely linked to the construction materials used.

Fig. 1 gives us an overview over HDD in the EU-27 and some selected countries. The raw data for this have been taken from Eurostat.

Fig. 1 HDD in EU-27 and selected countries, 1980-2009

Apparently, there is a clear distinction between several countries, depending on their geographical location. HDD for Germany and UK are closely following the EU average. The northern countries Sweden and Finland are placed well above that average, whereas the southern Member States Spain and Portugal find themselves well below that value. The mean deviation from the EU average amounts in the case of Sweden and Finland to 67% and 79%, respectively. Spain and Portugal, as the antipodes in HDD,  are as far as 43% and 60% below the European mean value, respectively.

HDD reflects the climatic conditions of each country. Average temperatures are considerably lower in Europe´s northern periphery and in the southern part. Therefore the difference in HDD between Finland (5800 on average) and Portugal (1300) is easily explained. Taking HDD as the only reference, Finland would need more than 4 times as much energy for heating than its couterpart. However, comparing these figures with the energy consumption per capita for both countries (Finland 5.3 ktoe and Portugal 2.2 ktoe, annual average for 1991-2010) yields a clear indication that there must be some features which tend to soften the sharp discrepancies. Among these are the standards for heat insulation (which can vary between different countries), the number of cooling degree days (having an opposite north-south tendency) and the level of industrialization.

# Energy per capita

It doesn´t come as a surprise that bigger countries consume larger amounts of energy than smaller ones. In general, at least. And yet, there are exceptions to this rule. US consumption of primary energy was 2204.1 Mtoe in 2009 according to BP´s Statistical Review of World Energy 2011. In the same year Canada used some 312.5 Mtoe.  The two neighbours are roughly equivalent in terms of economic performance (with GDP per capita in the US being larger than the respective quantitiy for Canada). Thus the main reason for explaining the difference is by reference to the population numbers. Here the US with 307 millions outweighs Canada with 33 millions. However, there are also other factors coming into play, as we shall see later.

A nice example that population is not the only parameter steering energy needs is given by comparing Germany and Mexico. Although Mexico has considerably more inhabitants (107 millions vs. 82) its consumption figures are significantly lower than the German ones (167 Mtoe vs. 307 Mtoe).

A sensible quantity for measuring the energy hunger of a particular economy is the primary energy consumption per capita. In that way, size effects stemming from largely different populations are normalised. The philosophy behind this is similar to the one of energy intensity which measures consumption per unit of GDP.

In the following we consider a number of developed economies and look at their energy hunger per head. We will find out that there are considerable differences between those countries although, at first sight, they may appear to be very similar in nature. The raw data for the following investigations have been taken from BP´s Statistical Review of World Energy, from the UN Statistics Division and from the CIA World Factbook.

Fig. 1 Primary energy consumption per capita in ktoe, 1991-2010

Although each of these countries is part of the wealthier economies of our planet, their energy consumption per head reveals some striking differences. We may observe that during the past 20 years the figures have not changed dramatically. Norway´s figures, though, show some variation, however, without any clear trend to higher or lower values.

One of the intentions of our choice was to highlight consumption characteristics between northern and southern countries. And indeed, the southern branch consisting of Italy, Portugal and Spain is well separated from their northern counterparts Canada, Norway, Finland and Sweden. In fact, there is even a significant gap between Sweden and Finland on the one hand and Canada and Norway on the other.

Having the north-south distinction as a particular feature we may come forward with some explanations on the seemingly unbridgable gap between the northern and southern economies. Obviously, one of the strongest arguments is based on climatic variations. Average temperatures are lower in nordic countries than in the southern ones which explains part of the difference. In order to have a reliable measure on how energy consumption is triggered by climatic circumstances we apply the concept of heating-degree days (HDD) which is used by Eurostat. Apparently, there are two parameters governing the HDD: the temperature and the number of days when heating is necessary. Without going into details we may state that the  nordic countries (except Canada) had more than 5000 HDD in 2009, whereas the Mediterranean countries managed with well under 2000 HDD.

Although the HDD concept is able to explain much of the difference, it is still not reflecting reality in total. The other factor coming into play here is the economic performance of each country expressed in GDP per head. Here, too, we see a gap between the two blocs. In order to visualise differences we take the average of both, the GDP and the energy consumption per capita, and scrutinize the deviations of both of the blocs from the mean value. The result is given in Fig. 2.

Fig. 2 Deviation of GDP and energy consumption per head from average in %. Data from 2009.

Fig. 2 gives us an indication that the energy intensity (which is pegged to the GDP) is closely linked to the consumption per capita, thus reflecting the economic performance of a country and its inhabitants. Those countries with a higher GDP per head tend to have also a higher primary energy consumption per inhabitant than the countries with a below average GDP per capita.

Although the term “energy per capita” has some intrinsic limitations, it represents nevertheless a sensible quantity if we are to understand consumption patterns and their causes. It is particularly sensitive to take into account factors like the degree of economic development and the temperature zone of a given country. Otherwise our conclusions might be distorted, especially when comparing countries with different economic background and/or geographic distribution. It goes without saying that Canada will consume more energy per inhabitant than, say, Portugal, simply because of its relative positioning on the globe. However, geography does not account for everything. We have to make allowances for differences in industrial and economic power as well. And again Canada, having a considerably higher GDP per head, is better off  than Portugal. Putting everything together will allow us to draw the right conclusions from the rough picture the concept of “energy per capita” provides us with.

# Oil Dependency of Developed Economies

Oil is one of the major energy sources for a modern economy. Both, developed and developing economies depend heavily on it. So we may ask ourselves to what exent we depend on this critical source. Intuitively, we know that renewables are constantly gaining ground. However, the simple fact that oil prices continue to be a vital indicator for economic activity shows us that oil still keeps its dominant role in the energy mix.

In order to find out how our dependency on oil and oil products has developed over the past decade, we compare the economic output in terms of nominal GDP with the respective oil consumption figures. This is done for the EU, the United States and Japan. The period in question is running from 2000 to 2010. Both, the GDP and oil consumption are normalized to be equal to 100 in 2000. The raw data for our investigation have been taken from Eurostat and the Shell Statistical Review of World Energy 2011.

Let us start with the European Union. Fig. 1 gives us a nice impression about the decoupling of economic activity and oil consumption which has taken place in the past decade. A net gain in real GDP is accompanied by a significant drop in oil use.

Fig. 1 EU-27 oil dependency 2000-2010, 2000 = 100.

The underlying reasons for this significant development are twofold: on the one hand, oil is facing competition from other sources such as natural gas. On the other hand, oil using machinery, like car engines etc. are getting more efficient, i.e. using less energy per km/mile.

Fig. 2 displays the same analysis for the United States. Again, real GDP and consumption of oil are jeading in different directions. As in the case of EU-27, the decoupling becomes even more siginificant as of 2006/2007. Quite remarkably, during the economic crisis in 2008/2009 the relative drop in consumption was considerably bigger than the one in economic performance.

Fig. 2 US oil dependency 2000-2010, 2000 = 100

As a final example, let us have a look at the situation in Japan. In one of our previous post we have already observed that Japan excels particularly when it comes to energy intensity, i.e. economic output per unit of energy used. Having this in mind, we would expect quite similar findings for the case of oil consumption. Fig. 3 shows the results of our analysis.

Fig. 3 Japan´s oil dependency 2000-2010, 2000 = 100

Although Japan´s GDP has performed less favourably when compared to the US and the European Union, its oil dependency has fallen much stronger than the one of its competitors. The decoupling between economic performance and the respective oil consumption is already quite significant in the beginning of our observation period, getting larger during the years. Thus, the reduced consumption of oil and its products is one of the key factors in Japan´s successful struggle to obtain a higher economic output per unit of energy.

# Energy Intensity in Europe, the US and Japan

In the previous posting we analyzed the development of energy intensity at a European scale. The findings were twofold: on the one hand, we saw a clear tendency to lowering the amount of energy per unit of GDP. This means that energy is used in a more efficient way. On the other hand, there are still remarkable differences between the EU member states. The gap between, say, Spain and Denmark which amounted to 63.72 kgoe/1000 EUR in 1995 has actually widened over the years and was at 79.44 in 2009. Thus, Denmark has clearly done better than Spain during that period. This, in turn means, that there is substantial room for improvement on the Spanish side.

Arguably one might say, that Spain and Denmark are not at the same level in terms of productivity, and that is certainly a valid point. However, from the Spanish point of view it is strongly desirable to become more competitive and thus increase its productivity.

In this post we want to have a closer look at the energy intensity of the three main economies in the world having comparable levels of productivity: the EU, the US and Japan. The raw data for the following analysis have been taken from Eurostat. As usual, the quantity in question is measured in kgoe/1000 EUR of GDP.

Fig. 1 Energy intensity in the EU, US and Japan, kgoe/1000 EUR

First, we observe a decline of energy intensity in all three economies. However, this decline is much more pronounced in the EU and the US than in Japan. During the period in question the US saw its intensity figure falling by 25.6%, while Europe faced a decline of 20.9%. Japan, on the other hand, came down by a mere 11.8%. Why is that so? It seems that Japan has already reached a saturation level when it comes to using energy in the most efficient way. The US and Europe have considerably improved their output figures, delivering a higher GDP per unit of energy used.

Nevertheless, there is still a huge gap between the two “Western” economies and Japan. Clearly, the gap is narrowing. In 1995, it was some 104.9 kgoe/1000 EUR between the EU and Japan, while the respective difference between the US and Japan was 134.6. In 2009, this has come down to 73.5 (EU-Japan) and 85.7 (US-Japan), respectively. Thus, the United States are still using almost twice as much energy per unit of GDP as Japan.

Improving productivity and introducing energy saving measures are the key parameters if we want to perform equally well as Japan. Clearly, Japanese economy has set the baseline which we should try to achieve. It is possible to bring energy intensity down to less than 100 kgoe/1000 EUR. However, this may take several decades given the current level of progress.

# Energy Intensity

Common opinion holds that if economic activity is increasing the consumption of energy will follow suit. At first glance this seems a convincing argument: producing 10 cars uses 5 times more energy than producing 2 cars. However, reality is not quite that simple.

First of all, there are scale effects coming into play. You do not switch on the whole production chain for each car individually, but rather try to produce the whole lot “in one go” which means that the entire production process will become more efficient which, in turn, helps saving energy. This essentially means that the scaling factor in the above example is no longer 5 but less than that.

Apart from making economic processes more efficient there are other factors which determine the level of energy intensity. Introducing energy saving measures, using machinery with a lower energy consumption, changing consumption patterns and other issues may lead to a lower energy intensity. So what is energy intensity? It is defined as the inland consumption of energy (coal, oil, gas, electricity and renewables) per unit of GDP within a certain period, usually one year.

As energy is an important cost factor it is desireable to minimize its use per economic output. This is true not only at the level of entreprises or businesses, but also for the economy as a whole. If we manage to produce more with the same (or even less) energy we may in the long run reduce our import dependency. However, so far the successful lowering of the energy intensity at European level has not yet led to a significant reduction of energy imports from third countries.

In Fig. 1 we see the energy intensity in kg of oil equivalent (kgoe) per 1000 EUR of GDP for EU-27, EU-15, Germany, France, Italy, UK and Spain from 1990 to 2009. Note that there are no data available for 1990 for EU-27. EU-15 and Germany (year of unification between East and West Germany). All data are taken from Eurostat.

Fig. 1 Energy intensity in kgoe/1000 EUR of GDP

One striking observation is that all countries of our selection as well as the EU as a whole have managed to reduce their energy intensity considerably since 1995. At EU-27 level the respective level has gone down by almost 21 %. Germany could reduce its energy intensity by almost 18 %, whereas UK managed to cut it by more than 30 %. On the other hand, the figures for the southern countries Italy and Spain are less impressive with 6.8% and 6.1%, respectively.

Another remarkable feature of our data sample is that intensity lines for individual countries generally do not cross. The line representing France is always above the one representing Italy. At first glance, this may imply some “intrinsic factors” like climate conditions, differences in economic profile (agriculture, heavy industry etc.) which may explain a certain “unbridgeable” gab between countries. However, as our figure clearly indicates, it is indeed possible that country lines cross each other. UK, starting out at an energy intensity well above Italy in 1995, has succeeded to fall consistently below the Italian level. Moreover, this is not a short term fluctuation, but rather can be safely considered a consistent trend. This, in turn, indicates that energy saving measures may have a significant impact on the efficiency of energy usage.

The decoupling of economic performance and energy consumption can be seen in the following two figures referring to Germany and Denmark, respectiveley. In order to facilitate the visibility of the effect we had to adjust the figures somewhat as will be explained immediately. Fig. 2 shows the case of Germany during the period 2001-2009.

Fig. 2 Germany´s inland consumption vs. GDP

The figures for the GDP are given in G€, whereas – for better visibility – inland consumption has been scaled as Mtoe*5. This puts the two curves close to each other and clearly indicates the respective trends.

Fig. 3 shows a similar pattern for Denmark. Here again, the GDP is plotted in G€, and inland consumption is put on a scale of Mtoe*10.

Fig. 3 Inland consumption and GDP in Denmark

Both, Fig. 2 and Fig. 3 show the impact of the economic crisis starting in 2008 on economic output and inland consumption. Nevertheless, during the years before the financial crisis it is obvious that an increase in GDP comes together with a decreasing energy consumption.

One question to be asked is whether there is a lower limit to the energy intensity which cannot be undercut. One is inclined to think that a country´s level of energy intensity may be largely determined by factors such as climatic conditions, the level of industrialization etc. However, it is possible that northern countries may “beat” the southern ones, as the case of UK and Italy indicates. Moreover, there are substantial differences even between countries situated a similar latitudes like Italy and Spain. This, in turn, may indicate that there is still a considerable potential for improvement in the case of Spain.

Summing up, we can conclude that it is possible for developed economies to have a growing GDP while at the same time keeping energy consumption stable or even lowering it.

# Using Solar Energy in Sweden

In general, we tend to believe that Nordic countries are unsuitable when it comes to using solar panels. And indeed, at first glance this may seem like an odd idea: winters are long, dark and snowy making solar installations practically useless. Thus, whenever energy is needed most the solar pathway is blocked. However, the other side of the medal may becomes apparent during summer when the sun is shining much longer hours than in southern Europe.

The first question to be asked is, of course, how much sunshine is available in Sweden? The answer depends very much on where you are as can be seen from the picture below

Fig. 1 Average sunshine hours in Sweden (Source: SMHI)

From this we conclude that the South generally receives more sunshine than the North. Furthermore, we see that a big part of the country gets on average more than 1600 hours of sunshine per year. As a reference we may compare this to one of the sunnier parts of Germany, the south-western federal state of Baden-Württemberg which has an average of about 1600 hours.

However, it is not only the number of hours that counts, but more importantly, we have to look at the amount of irradiation coming from the sun onto a particular spot of the Earth´s surface. Here the data are as follows: a substantial part of Sweden (once again, predominantly in the southern areas up to about the latitude of Stockholm) gets more than 925 kWh/sqm of global irradiation. The respective values for Baden-Württemberg are some 1100 kWh/sqm. Thus the better part of Sweden receives only about 15% less irradiation than the south-west of Germany.

We may therefore safely conclude that the situation for using solar energy in Sweden is far from hopeless. On the contrary, it appears that there is some potential for using it, all the more since solar panels have been improved significantly over the past years.

Let us examine the issue by picking a particular location. The city of Linköping is located some 200 km south-west of Stockholm. There, solar irradiation is about 950 kWh/sqm per year. Using solar modules with an efficiency of 10% , facing south at an angle of 45 degrees would safely provide us with an annual output of 95 kWh/sqm. Thus, a panel surface of  at least 10 sqm should yield an output of roughly 1000 kWh, which is considered to be the threshold where solar panels become economically viable. Using a module of that size would correspond to estimated savings of about 1400 SEK (150 EUR) per year (at current electricity prizes). Taking this savings potential into account we conclude that the installation costs of the solar module of about 20000 SEK (2200 EUR) may well be amortized after a bit more than 14 years.

Needless to say, that this amortization period would be shortend in case of increasing electricity prices and/or shrinking costs for installing the PV modules. Both these assumptions are quite realistic since energy costs, on the one hand, are very likely to rise (especially over the next years due to e.g. carbon taxes) whereas module costs, on the other hand, are expected to go down. In this context it may be worthwhile noting that module prices in Germany have slumped some 25% since January 2011.