Fuel Poverty in the UK

This time I would like to cover a very different aspect of energy and its usage in everyday life. So far there is  no apparent lack of energy, technically speaking. Energy is available in abundance, and the only restriction to using it is the price we are asked to pay for it. Thus big users will eventually find themselves paying a huge bill. But it´s not only big consumers who might face a hefty burden from their energy bill. More and more people are using a substantial amount of their available income in order to  buy the energy they need. In particular, this is true for heating which is also one of the biggest parts of private energy consumption.

The UK statistical office is collecting data on fuel poverty. The term refers essentially to energy needs for heating purposes and the relative amount of household income people have to spend in order to “maintain a satisfactory heating regime”, i.e. 21 °C in the main living area and 18 °C for other rooms. In particular, people are considered to suffer from fuel poverty if they have to spend more than 10% of the household income on fuel for heating.

The figure below gives a sketch of the situation in the recent past (2003 and 2009).

Number of fuel poor households in millions. Abbreviations: dc – dependent children, hh – household.

The first observation we make is that the number of fuel poor households has apparently dramatically increased between 2003 and 2009. During that period the number of households concerned has, on average, more than doubled. Thus, fuel poverty in the above sense is definitely increasing and showing a severe social impact. Energy is becoming a scarce and to some extent even luxurious commodity.

Another observation is that specific groups are particularly hit by this phenomenon. People without dependent children are more likely to suffer from fuel poverty than those having kids. Moreover, persons older than 60 years are also facing a greater risk of getting fuel poor. The same is true for single persons when compared to couples.

The causes for this are manifold. Energy prices are on the rise. They climb faster than the average income, especially for retired people. Another factor is certainly the economic crisis which hit a number of European countries in 2008. So far we are still far from a sustainable recovery. Therefore, we may well assume that the situation has aggravated in the meantime.

Yet another factor coming into play is related to economic circumstances: Many elderly people may not be able to afford refurbishing their houses such that they consume less energy, especially for heating. Renovating old houses is a costly undertaking which may simply go beyond many people´s financial capabilities.

Fuel poverty is a critical issue not only in the UK. Also other countries like Germany encounter the same problem. However, most of those countries do not collect the respective statistical data as is the case in the UK. Therefore, it is extremely difficult to assess the severity of fuel poverty for other countries. Taking into account that energy is of critical importance to the functioning of our societies, it would be highly desirable to collect those data in order to tackle the problem as soon as possible.

Household Energy Use – The Case of Switzerland

Modern societies need a considerable amount of energy, which is almost entirely used the three sectors industry (including services), mobility and household, at roughly equal parts. Thus, the energy consumed at home forms a substantial part of the entire final energy use.

In this posting we study the situation in Switzerland which is one of the most competitive and industrialized countries of Europe, though not being a member of the EU. All raw data for the subsequent investigation stem from Swiss Statistics which provides excellent information on all areas of consumption. In particular, we will focus on the period 2000-2010. The above-mentioned sectors had the following shares in the total final energy consumption in 2010: industry and services 35 %, mobility 34 % and household 30 %.

Total household energy use went up by 14.1% during the first decade of this century. However, this obvious increase does not take into account that the number of people living in Switzerland has also risen during that period. Thus, the relevant figure to look at is the consumption per capita, and here the situation looks quite different as can be seen in Fig. 1.

The trend line makes clear that the specific energy use per person has gone down over the years. The steep increase since 2007 is well in line with the number of heating degree days (HDD) following a similar pattern as can be seen in Fig. 2. Apparently, it has become colder between 2007 and 2010.

Fig. 2 Heating degree days (HDD) and heating effort in Swiss households.

The similarity between the red curves in Figs. 1 and 2 is not accidental, as more than 72 % of total household energy are used for heating purposes (in 2010). Thus, changes in the number of heating degree days should be reflected in the heating effort. Warm water makes up for another 12 % of household use while the remaining 16 % are shared among various sectors such as lighting, cooking, washing, drying, etc.

A closer look at the figures for warm water reveals that consumption has remained relatively stable (Fig. 3).  Taking into account the growing number of households (+ 11 %) during the period in question naturally leads to the conclusion that each household uses less and less warm water.

Fig. 3 Total energy used for warm water and consumption per household (/HH).

Fig. 4 shows the contribution of other sources of household energy use. Their aggregated consumption volume is relatively moderate as stated above. Nevertheless, as a whole they are not to be neglected although their individual shares are not as important as the ones for heating and warm water.

Fig. 4 Household energy use (except heating and warm water).

Whereas lighting, cooking and refrigerating (including freezing) have remained virtually unchanged over the years, washing (including drying) and miscellaneous have increased dramatically by 52 % and 32 %, respectively. This is well in line with a growing population as more people require more clothing to be washed. So there are some areas of energy consumption being more sensitive to the number of persons involved while others like lighting tend to be rather independent of population figures.

Thus, as stated in my previous posting, growing energy consumption figures (in absolute terms) should not be obscured by ignoring the simultaneous changes in the number of consumers. On an individual basis, we gradually tend to use less energy. This is the good news. But, of course, the crucial question is how much further we can get in becoming more energy efficient. Or, to put it differently, is there a limit and, if yes, where is it?

Measuring Heat Flow

Measuring the flow of heat (or energy, in general) is a tricky task. Generally speaking, one has to know the temperature on both sides of a wall, window etc. The temperature difference provides a measure of the drop in temperature and, consequently, the flow of energy through the object. So in principle one has to keep an eye on both sides of the object in question.

But what happens if only one side is accessible, like in a storage tank where measuring the temperature on the inner side of the vessel proves to be very difficult if not impossible? So how much energy does a hot water storage lose?

Luckily, there are solutions for measuring the heat flow by using a simple gadget. With a thermal flux sensor one may easily determine how much energy goes through a wall or a window or any other object. The sensor is attached to one side of the object and yields a signal which is directly proportional to the heat passing through the object and thus makes it possible to determine how much energy actually penetrates a window, wall, etc.

Performing such a measurement is easy and exciting as it may reveal some unexpected features of energy leaving or entering a dwelling.

We have performed a series of measurements in a house in Sweden over a couple of days and discovered some really interesting features. And yet, no sophisticated equipment was necessary. A heat flow sensor and a multimeter, that´s all it takes. The measurements took place during the last week of February 2012. Let us have a look at the results before we start discussing them in more detail (Fig. 1).

Fig. 1 Measuring the heat flow through a window.

The red curve shows the heat flow through a window facing a westerly direction. The outside temperature was approximately 7 °C in the morning. During the entire morning until 12:30 hrs the heat flow was relatively stable at about 3 W/sqm. Then shortly after 13:00 the sun slowly started finding its way through the window leading to a massive change in energy flow. In fact, we even observed an inversion of the energy flux, i.e. more energy was entering the living room than leaving it. This situation when the sun was delivering free energy through the window lasted until 15:30. Then it disappeared behind a nearby forest, and the energy flux got back to its normal behaviour which was governed by the temperature difference between the living room and the exterior. It goes without saying that during those hours of direct sun exposure the heating could effectively be switched off.

During the late afternoon a significant drop in outside temperature occurred (blue curve) while simultaneously the flow of energy was rapidly increasing reaching a plateau at almost 15 W/sqm after 18:00 hrs. Since at that time it was already dark outside the heat flow was no longer overlapped by indirect solar irradiation.

Now we are in a position to calculate the net heat flow during the measurement period. The heat loss was strongest in the evening when the outside temperature dropped drastically. During the early afternoon we had a net inflow of energy. The overall heat flow balance amounts to 0.063 kWh/sqm going through the window. Thus, by using relatively simple means we could perform a thermal analysis of a window.

The experimental setup is shown in Fig. 2.

Fig. 2  Measuring the heat flow via a heat flow sensor

More information and/or quotations please contact:  manfred.jacobi (at) gmail.com

Energy Efficiency – Potential Household Savings in Sweden

In a recent report we analysed the savings potential of the Swedish housing sector. Sweden has committed herself to save some 12.8 Mtoe of primary energy up to 2020. Taking into account that the country used some 51.4 Mtoe in 2010, and with a consumption goal in 2020 of about 41 Mtoe, this means that savings of some 20 % within the remaining decade are at stake.

One of the biggest savings potentials is supposed to be hidden in the building stock. Household energy use accounts for 23 % of the total final energy consumption in Sweden and the largest part of it is eaten up by heating purposes. In the following we look into the consumption figures for heating and warm water in Swedish households. The raw data for our investigation have been taken from Eurostat, Statistics Sweden and the Swedish Energy Agency.

The average energy consumption in kWh/sqm according to year of construction is distributed as follows:

Fig. 1 Average annual energy consumption for heating and warm water in Sweden.

The latest construction types use significantly less energy per sqm than the older ones. This is in line with our expectations. For single dwellings average consumption has dropped by some 40 % from 153 kWh/sqm to 91 kWh/sqm. For multi-dwellings the decrease was not as dramatic. Nevertheless, average consumption went down from its maximum value of 170 kWh/sqm to 125 kWh/sqm (26 %).

The consumption figures per category are displayed in Fig. 2.

Fig. 2 Energy consumption for heating and warm water by year of construction.

Taking the latest construction technology as a reference, we may calculate how much energy could be saved if the entire building stock was refurbished according to that standard. The results are shown in Fig. 3.

Fig. 3 Calculated savings potential by year of construction.

As regards the single housing sector refurbishing the oldest part of it would account for 50 % of the total savings potential of that sector. Obviously, the younger part of the building stock would only contribute very little (2 %) to the entire potential.  In total, we could expect to save some 9.9 TWh for single dwellings and 5.5 TWh for multi-dwellings. Thus the entire savings potential from the housing sector would amount to 15.4 TWh which corresponds to 24 % of all energy used for heating and warm water.

This is an impressive number although in terms of Mtoe its equivalent is a mere 1.3 Mtoe. Thus we may conclude that renovating the Swedish housing stock would provide savings of about 10 % of the entire reduction goal set by the Swedish government (12.8 Mtoe). Having said that we have to admit that the biggest part of the task is still to be done.

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.

Heating Degree Days and Energy Consumption

Heating degree days (HDD) may serve as an indicator for the amount of energy used for heating purposes. The correlation seems to be pretty obvious: a larger number of HDD should inevitably lead to a corresponding increase in energy consumption. This relationship should, as a consequence, be reflected by the amount of primary energy used. Of course, heating is not the only way to consume energy. Traffic, industrial production and services equally request their share in primary energy demand.

In Germany, heating accounts for about 30 % of total final energy consumption. Thus, if the number of HDD is up by, say, 10 % then we would expect the consumption figures to increase accordingly. The question is to what extent the latter would reflect changes in HDD. Let us demonstrate this via a simple thought experiment. Imagine Germany consumed 100 units of final energy in 2009, 30 of which were used for heating. The number of HDD was x. In 2010 HDD increased by 10% compared to the previous year. Thus we would expect a total of 33 units being absorbed for thermal comfort. Everything else remaining unchanged, the total final energy consumption in 2010 would amount to 103 units. Thus, the total consumption figure would be up by 3% in 2010.

Does this argument also hold good for primary energy consumption? Let us have a look at two countries of similar size and climatic conditions, namely Germany (Fig. 1) and UK (Fig. 2). The source data have been taken from BP Statistical Review of World Energy 2011 and Eurostat. The figures show primary energy consumption per capita (CPC) in tons of oil equivalent (toe) and the number of HDD in the respective country.

Fig. 1 Primary energy consumption per capita (in toe) and HDD in Germany

Consumption figures in Germany reflect changes in HDD only partially, as expected. At the end of our observation period we even note that a significant rise in HDD is met by a slump in consumption per capita. Between 1994 and 1996 HDD went up by more than 27%. The respective rise in CPC was a mere 3.3%.

The UK data are as follows.

Fig. 2 Primary energy consumption per capita (in toe) and HDD in UK

Again, the changes in consumption per capita are much less pronounced than the respective variations in HDD. In 1995/96 HDD increased by some 11.5 %, whereas CPC went up by 4.5 % only. As in the German case, towards the end of the obervation period a clear upward trend in HDD is met by a significant drop in CPC.

Heating degree days have certainly their merits when it comes to estimating energy needs for thermal comfort. However, on a more global scale, their usefulness is relatively limited. In any case, their importance should not be overrated.