The effect of energy prices on life-cycle costs

Published:  04 October, 2012

BSRIA, whole life costs, lighting, T5, T8
Analysing investments — David Churcher.

How good an investment is an energy-saving measure such as replacing T8 fluorescent tubes with T5? David Churcher of BSRIA takes a detailed look at the figures.

The price of energy is a key factor in almost every life cycle costing analysis as it is often the most significant cost item throughout the life of a building or building system. This is particularly the case for building services. Most cost items in life-cycle costing are assumed to rise at an across-the-board rate of inflation, which can be allowed for by ignoring inflation and using present-day prices for future costs. However, experience tells us that energy does not behave in this way.

According to the DECC Energy Price Statistics, electricity prices have risen by 75% in real terms over the last 10 years. This is also about the average of price rises seen for gas and coal over the same period, which makes sense as gas and coal are widely used to generate electricity. Looking to the future, it might be reasonable to think that prices will continue to rise at about the same rate.

DECC’s report ‘Fossil fuel price projections’ sets out a range of scenarios for price movements of oil, gas and coal from 2010 until 2030. For coal, real prices by 2030 are expected to be between 14% lower and 67% higher than 2010 prices. For gas, real prices by 2030 are expected to be between 2% higher and 127% higher. Taking a crude average of the predictions of coal and gas prices suggests a rise of 25% every 10 years for coal and 65% every 10 years for gas.

Assuming that the electricity price will rise by an average of the coal and gas prices, this indicates a rise of 45% every 10 years. This is significantly different from the historic trend of 75% increase over 10 years, and a reasonable figure may be somewhere in between — say a real increase of 60% every 10 years. This is equivalent to 4.85% increase each year, to allow for compound increases over 10 years to make 60%.

A lighting example

The example we will look at to illustrate this assessment of energy prices is the decision whether or not to replace T8 lamps with T5 lamps.

Consider an existing office building fitted out with T8 lamps rated at 25 W each delivering 2200 lm with a life expectancy of 20 000 h. An office floor fitted with 60 lamps will have a power consumption of 1500 W. If the lamps are on for 10 hours per day, Monday to Friday this is equivalent to 3.9 MWh of electricity per year. The lamps cost £2.50 each.

The lamps could be replaced with T5s rated at 28 W each delivering 2900 lm, also with a life expectancy of 20 000 h. The same office floor will now require 45 lamps to give the same level of illumination, giving a power consumption of 1260 W which is equivalent to 3.28 MWh of electricity per year. The lamps cost £3 each. Converter kits also have to be bought so that the existing luminaires can be used, costing £15 each.

The 20 000 hour life of each lamp is equivalent to eight years of operation. But the luminaire converters are a one-off purchase, so in this example the study period is be extended to 24 years to cover three lifecycles of the lamps.

In both cases, the building occupier is currently paying £0.10/kWh for electricity. But this is expected to rise by 4.85% every year, as argued above.

A discount rate has to be selected for the analysis. A typical rate in the private sector would be between 5% and 10%, say 7% in this case. For the public sector, a discount rate of 3.5% is recommended by HM Treasury.

The results of the life cycle calculation using BSRIA’s in-house LCC spreadsheet are shown in Table 1.

Modelling energy prices using probabilities

The above assessment of future changes in electricity price may be thought quite crude. More sophisticated modelling can be done with appropriate software. BSRIA is a partner in the EU Framework 7 research project CILECCTA which is developing software for analysing life-cycle costs and environmental impacts using probabilities. The same example has been analysed using a beta version of the software, but this time allowing electricity price to increase randomly each year between pre-set limits based on all the above DECC energy-price information. The results of running the life cycle cost calculations through 5000 simulations are shown in Table 2.

In conclusion

The calculations show that the life-cycle costs change according to the discount rate, which is to be expected, and also with the modelling methodology. However, the important conclusion is that in both cases switching to T5 lamps has the lower life-cycle cost, using the input data provided. However, for a private-sector occupier the difference is close to the margin of error — meaning that the case for switching is weaker. For a public-sector occupier the difference is more significant, and the recommendation to switch to T5 lamps is more robust.

In this case the results are very sensitive to the projected change in electricity cost, and for a more substantial project some more in-depth analysis would be recommended.

David Churcher is a principal research consultant with BSRIA’s sustainable building group.


Department of Energy & Climate Change, 2011, DECC fossil fuel price projections, London.

Department of Energy & Climate Change, Energy price statistics, (accessed 14 August 2012)


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