Costs and benefits of tackling fuel poverty by improving energy efficiency in Wales in 2008

Transcription

1 Costs and benefits of tackling fuel poverty by improving energy efficiency in Wales in 2008 Dilys Burrell and Greg Shreeve page 1 of 16

2 Revision Date Issued Author Reviewed Approved Description 1 February 2013 DB & GS DM DM Issue to Welsh Government for discussion This report (including any drawings forming part of it) is intended for general guidance only and not as a substitute for the application of professional expertise. Any figures used are indicative only. The Energy Saving Trust gives no guarantee as to reduction of carbon emissions, energy savings or otherwise. Anyone using this publication (including drawings forming part of it) must make their own assessment of the suitability of its content (whether for their own purposes or those of any client or customer). The Energy Saving Trust cannot accept responsibility for any loss, damage or other liability resulting from such use. page 2 of 16

3 Contents 1. Headlines Background and methodology Overall costs and benefits Spread of costs across income bands Spread of costs across targeted households Conclusions and next steps...16 page 3 of 16

4 1. Headlines The Energy Saving Trust has recently undertaken modelling to estimate the costs and benefits of improving the homes of households living in fuel poverty. The modelling used the 2008 Welsh property and householder surveys. It considers the following for a number of different scenarios: Total estimated costs and benefits of home improvements Average cost per home improved, and how investment is spread across households, including those in different income bands. The cost of assisting different proportions of the households included in each scenario Key findings from the modelling include: The cost of improving homes in Wales so that householders are no longer in fuel poverty is significant. It would cost nearly 2.5 billion to reduce the required energy spend of all households in fuel poverty in 2008 to a level that would have meant they were not in fuel poverty in However, the potential benefits are also significant. The modelled 2.45 billion investment resulted in a potential reduction in energy bills worth 283 million in 2008 energy prices (which would be worth significantly more today). The modelled reduction in carbon dioxide emissions would also make a large contribution to greenhouse gas reduction targets in the residential sector 1. Other scenarios are less costly, for example reducing the fuel poverty gap for all households with low incomes and high modelled energy costs in 2008 is estimated to cost around 509 million. Some scenarios for investment result in potentially high costs associated with assisting better off households. The target group (i.e. fuel poor, severe fuel poor or households on low 1 It is important to be aware that 2008 fuel prices were used in this analysis, which will have the following implications: Costs for each scenario would be higher in there are more people in fuel poverty in 2013, therefore there would be more homes to treat. In addition, many people who were in fuel poverty in 2008 will be even deeper in fuel poverty in 2013, meaning that further home energy improvements would be required to achieve the target saving to remove them from fuel poverty. However, the estimated benefits will also be proportionately higher (i.e. the payback / cost-effectiveness should remain similar). It is also important to note that the actual bill savings and CO 2 reductions are likely to be lower than the figures quoted. This is because: Many households in Wales, particularly fuel poor households, will not heat their homes adequately (ie to the levels assumed in the energy modelling). Therefore the potential savings will be proportionately less. Many households, particularly fuel poor households who are more likely to under heat their homes, will take the benefits of home energy efficiency improvements in terms increased warmth and comfort rather than bill / CO 2 savings. This means that they may use the same amount of energy after improvements are made, but instead have a warmer and healthier home. This will have benefits in itself (including lower health costs). In reality, most households are likely to take some benefits in terms of improved warmth and comfort, and some in terms of reduced energy use. A comfort taking factor of 15% is often applied to energy efficiency policy analysis, which is increased to 40% when targeting fuel poor or low income households. page 4 of 16

5 incomes with high energy costs) and the target saving (i.e. whether reducing modelled bills so that they are equal to or less than the 10% modelled energy bill to income threshold, the average bill or reducing the fuel poverty gap by 50%) can have a big implication on the spread of investment across households in different income bands. Aiming to reduce the modelled energy costs of fuel poor households to the Welsh average results in just 24% of funds being invested in the poorest fifth of households in Wales. In contrast, aiming to remove households in severe fuel poverty from fuel poverty results in 80% being invested in the poorest households. Most households can be assisted for a relatively low proportion of the overall modelled costs in each scenario. The target group and the target saving also influences the spread of spending across the households concerned 60% of the target group can be assisted for less than 20% of the total costs in all but one scenario. This can be achieved by focussing on households that live in homes that are the cheapest to improve. However there are also a large proportion of homes that are very expensive to improve. Removing all households in severe fuel poverty in 2008 from fuel poverty would have cost 18,300 per household on average, with 20% of households requiring investment of more than 27,000. The reported income of some households is so low that it is very difficult to remove them from fuel poverty by improving the energy performance of their homes, and certainly not possible using the standard improvement measures included in the modelling. To achieve a reasonable ratio between modelled energy costs and very low reported incomes, many of these homes would require total renovation / re-building. We hope that the results of this modelling exercise, outlined in more detail below, will help to stimulate productive debate amongst decision makers and fuel poverty campaigners in Wales to ensure that efforts to tackle fuel poverty have the greatest possible impact. page 5 of 16

6 2. Background and methodology The Energy Saving Trust undertook research in 2012 into the costs and benefits of tackling fuel poverty by improving the energy efficiency of homes in Wales. The work was undertaken as part of Welsh Government s grant funding for the Energy Saving Trust in 2011/2012 to support energy efficiency and fuel poverty policy development. The research used the Energy Saving Trust / Association for the Conservation of Energy Refurbishment Calculator to estimate the costs and benefits associated with a number of different scenarios for reducing the cost of heating homes in Wales (the required energy spend). The data used for the modelling came from the Living in Wales 2008 household and property surveys currently the most up to date resource on fuel poverty levels in Wales (updated estimates of fuel poverty in Wales are due soon). As such these findings are based on 2008 levels of fuel poverty, building thermal performance and energy prices. The following scenarios were modelled: 1. Remove from fuel poverty (2008) this scenario models reducing the required energy spend of households in fuel poverty in Wales in 2008 to a level that would have meant they were not in fuel poverty in 2008; 2. Remove severely fuel poor from fuel poverty (2008) this scenario models reducing the required energy spend of households in severe fuel poverty in 2008 to a level that would have meant they were not in fuel poverty in 2008; 3. Reduce fuel poor spend to average (2008) this scenario models reducing the required fuel spend of households in fuel poverty in 2008 to the Welsh median; 4. Reduce severe fuel poor spend to average (2008) this scenario models reducing the required fuel spend of households in severe fuel poverty in 2008 to the Welsh median; 5. Reduce Low Income High [Energy] Cost (LIHC) households to average (2008) this scenario identifies households with a low reported income and high required energy spend, as highlighted in the Hills Fuel Poverty Review, and assesses the improvements needed to reduce their modelled energy spend to the Welsh median (although note that the high cost threshold is as defined in the interim report rather than the final report because this modelling was completed before the publication of the final report); 6. Reduce fuel poverty gap for LIHC households by 50% - The fuel poverty gap, as identified by the Hills Review, is the difference between a households modelled energy costs and the median for all households. This scenario investigates the costs and benefits associated with reducing the fuel poverty gap for LIHC households by 50%. It is important to be aware that the modelling assumes the same fuel prices and energy bills as used in the 2008 fuel poverty calculations (which were published in November 2010). Current energy prices are significantly higher than in This means that more households will be in fuel poverty in 2013, and therefore more households will need support to get out of fuel poverty in It also means that those households that were in fuel poverty in 2008 will be deeper in fuel poverty in 2013 (unless they have page 6 of 16

7 received assistance since then), so they will require more home energy improvements to meet a given fuel poverty threshold. However, higher energy prices also mean that the estimated energy bill savings associated with any investment would also be greater, as would the amount of money that would subsequently become available to spend in the Welsh economy if less was spent on energy bills. It is also important to be aware that the quoted energy bill and CO 2 savings assume a standard heating regime and standard costs for energy. Many households will not heat their home to the level assumed in the energy modelling either through choice or because they simply cannot afford to. Therefore the impact of the energy improvements on bills and CO 2 emissions will often be less than assumed by the modelling. Some households may indeed continue to spend the same amount of money on their bills, instead taking all of the benefits of improved efficiency in increased warmth (which of course can have a range of additional benefits if the temperature was previously insufficient, including improved health and wellbeing). In addition, if a householder pays more or less for their energy than the standard costs assumed, the potential bill savings will be relatively more or less. Further detail on each scenario can be found in separate short briefing notes available from the Energy Saving Trust, as can further information on the methodology and assumptions. page 7 of 16

8 3. Overall costs and benefits The modelling suggests that it would cost 2.45 billion to reduce the required energy spend of households in fuel poverty in Wales in 2008 to a level that would have meant they were not in fuel poverty in Indeed, even at this high cost, 5% of the fuel poor households would remain in fuel poverty. This is because their reported income is so low that the modelled home improvements cannot reduce required energy spend to less than 10% of their income. However, although expensive, this scenario results in a reduction in modelled energy spend of 283 million per year in 2008 prices, a payback of less than 10 years 2. With today s energy prices, the payback period would be even less. In addition the reduction in modelled energy use would result in 1.5MtCO 2 /yr fewer carbon dioxide emissions. This would make a large contribution towards the 2.2 MtCO 2 /yr reduction required in the residential sector by 2020 to meet the Welsh Government s 3% climate change target, although it is interesting to note that even this scale of refurbishment (improving over a quarter of homes) is not sufficient to meet the target. It is also important to understand, as highlighted above, that actual savings may not be as great as the modelled savings. The lowest total cost is associated with the scenario which seeks to reduce the fuel poverty gap for Low Income High [Energy] Cost (LIHC) households by 50%. The 509 million required investment could feasibly be secured from public funds over a 10 year period, although directing these funds to exactly the right LIHC households would be extremely difficult, if not impossible. This scenario also has the best simple payback ratio at just over 6 years and a reasonable level of modelled CO 2 savings (0.38MtCO 2 /yr), although this equates to just 17% of the 2020 target. Figure 1 below outlines the estimated costs and benefits associated with each scenario. Other interesting features include: Removing all households in severe fuel poverty in 2008 from fuel poverty in 2008 is estimated to cost nearly half as much as removing all households in fuel poverty from fuel poverty, even though there were just an estimated 60,000 households in severe fuel poverty compared to 330,000 in fuel poverty (the average cost per property is 2.5 times higher for removing households in severe fuel poverty from fuel poverty). Nearly 1 in 5 households in severe fuel poverty in 2008 could not be removed from fuel poverty by applying the energy performance improvements available in the model. This is mostly because the reported household income is very low; meaning that the modelled energy spend cannot be reduced to below 10% of the stated income. In some cases it is also because a limited number of efficiency measures can be applied to the home (e.g. a ground floor flat). Over a third of households in fuel poverty in Wales in 2008 already had a required fuel spend below the median for all households in Wales ( 1280). This could suggest that the main factor related to these households being fuel poor is low income rather than high energy costs. 2 A payback of under 10 years fits well with that estimated for the first year of the Nest scheme ( 2m estimated benefits resulting from 15.3m investment in home improvement packages). The first Nest Annual Report is available here page 8 of 16

9 Although the average cost per household assisted varies significantly across the scenarios, the average simple payback 3 is similar for all but one of the scenarios (between 9 and 11 years). This suggests that although more is spent per home in some scenarios, the additional measures installed have a similar payback period to those installed in scenarios involving a lower average spend per property. Figure 1: Summary of total costs and benefits associated with each scenario analysed Scenario Number of target households % achieving target saving Total cost Average cost per HH Total annual energy bill saving Average annual bill saving per HH Total Simple CO 2 payback saving (yrs) (MtCO 2 / yr) Remove from fuel poverty (2008) 330,000 95% 2,454m 7, m Remove severely fuel poor from fuel poverty (2008) 64,000 82% 1,164m 18, m 1, Reduce fuel poor spend to average (2008) 215,000 91% 2,107m 9, m 1, Reduce severe fuel poor spend to average (2008) 49,000 88% 635m 12,300 70m 1, Reduce LIHC household spend to average (2008) 148,000 92% 990m 6, m Reduce fuel poverty gap for LIHC households by 50% 148,000 98% 509m 3,400 81m the reduction in required fuel spend vs. the total cost, not taking into account environmental and other benefits page 9 of 16

10 4. Spread of costs across income bands The spread of costs across households in different income bands in Wales (i.e. in the poorest fifth of or the richest fifth of households in Wales, or any of the bands in between) differs by scenario (see Figures 2 and 3). In all but one of the scenarios, the majority of spending is on households in the lowest income band in Wales. This is as to be expected as households in lower income bands are more likely to be fuel poor 4. However, nearly 25% of modelled costs are associated with households in the top two income bands (the richest 40%) in the reduce fuel poor spend to average scenario. This is because it attempts to reduce the modelled energy spend of all target households to below 1,250 per year. Higher income fuel poor households 5 may live in larger, more expensive to treat properties, therefore although the total number of higher income fuel poor households may be relatively small, the level of investment required to bring their required spend down to the average is high. This results in a greater average spend on better off households compared to very low income household (see Figure 4). By contrast, the scenarios that target households with low incomes and high modelled energy costs result in a greater proportion of the overall spend being targeted towards poorer households (almost three quarters of modelled spend is amongst the poorest fifth of households in both LIHC scenarios). 4 However, some low income households may not be in fuel poverty. The first Nest Annual Report (available at suggests that 45% of households that received a home energy improvement package under the scheme in 2011/12 were not in fuel poverty, even though they were on means tested benefits. It would be interesting to explore the characteristics of these households to understand why they are better off in terms of their energy bills than other low income households. 5 Even relatively well-off households can be defined as fuel poor if their modelled energy spend is high - a household with an income of 40,000 would be fuel poor if their modelled bill was over 4,000. Clearly the situation faced by this household with 3,000 a month remaining income would not be as serious as a household with 15,000 income and 1,500 bills (leaving just over 1000 a month for housing, bills, food and all other costs). Although 4000 sounds like a lot for a household to spend on energy, the assumptions made in standard household energy models mean that this level of modelled spend is not uncommon, particularly in larger, off-gas homes with poor energy performance page 10 of 16

11 Figure 2: Chart showing distribution of costs across households in different income bands. The size of each segment is determined by the cost associated with helping households in each income band. In contrast to Figure 5, the number of households in each income band varies. Figure 3: Tables showing the modelled level of investment in households in the poorest and richest fifths in Wales Scenario Investment in households in the poorest fifth in Wales % of total investment under this scenario No. of target households in the poorest fifth Av. investment per HH in poorest fifth Remove from fuel poverty (2008) 1.6b 65% 198,000 7,900 Remove severely fuel poor from fuel poverty (2008) 933b 80% 53,000 17,900 Reduce fuel poor spend to average (2008) 516m 24% 75,000 6,000 Reduce severe fuel poor spend to average (2008) 393m 65% 43,000 9,300 Reduce LIHC household spend to average (2008) 684m 69% 101,000 6,600 Reduce fuel poverty gap for LIHC households by 50% 336m 66% 101,000 3,200 page 11 of 16

12 Figure 4: The average spend per household is higher for households in the richest fifth in Wales in many scenarios. This is probably because higher income households tend to live in bigger, more expensive to treat homes (e.g. a large detached rural property with solid walls and off the gas network) page 12 of 16

13 5. Spread of costs across targeted households Each scenario also results in a different spread of costs across targeted households. Some scenarios involve fairly even spending on all households targeted (e.g. the reduce severe fuel poor spend to average scenario). Others see the majority of households requiring just basic, low cost improvements. In these scenarios a large proportion of the target households can be assisted at a relatively low cost, however some households require a very high level of investment, and often the majority of costs are associated with improving a small number of very expensive to improve homes (see Figures 5, 6 and 7). Interesting findings include: More than 80% of households can be assisted for less than 50% of the total modelled cost in both scenarios that target all fuel poor households. In all of the scenarios, 20% of households targeted can be assisted at a relatively low cost. The modelled cost to reduce the required energy spend of 20% of households in fuel poverty so that they were not in fuel poverty in 2008 is 139m costing on average less than 2,100 per property. The Welsh Government has spent or levered in around 120m for home energy improvements in Wales since In addition there have been significant levels of additional CERT and CESP activity. Assuming that this was spent on the same measures as defined in these scenarios and that it was effectively targeted on households in fuel poverty, Welsh Government activity could have had a significant impact on the number of households in fuel poverty in the absence of energy price rises. Very high levels of investment per household are required to help some households meet the thresholds set 7. The cost of improving the most expensive 40% of households in the remove from fuel poverty scenario is 2.12 billion. This is more than 80% of the total cost of the scenario. The modelled cost of improvements for the remaining 60% of households is less than 350 million. In the remove severe fuel poor from fuel poverty scenario the average investment required per household for the most expensive 20% of homes to improve is over 30,000. Households requiring the upper levels of investment will include those with a very low reported income (therefore requiring large reductions in modelled energy spend to bring them below the 10% fuel poverty threshold in the traditional fuel poverty definition scenarios) and those living in properties that require very expensive improvements to achieve any level of energy efficiency improvement. 6 Assuming 20m per year for 4 years for HEES / Nest and 40m for arbed 7 The fact that very high levels of investment are required to help some households to meet the thresholds set in every scenario supports the case for the investment limits and value for money criteria used to manage spending on home energy improvement packages available under Nest (see page 7 of the first Nest Annual Report available at for more information) page 13 of 16

14 Figure 5: Chart showing the distribution of costs across the total number of households assisted. In contrast to Figure 2, each segment represents an equal number of households - the size of each segment is influenced by the cost of assisting that fifth of the households. So the dark blue segment represents the cost of improving the least costly homes in each scenario, and the light blue segment the most costly. Figure 6: Table showing the investment required to assist 60% of target households in each scenario Scenario Investment required to assist 60% of households % of total investment Max. cost per household (least expensive 60%) No. of households assisted Remove from fuel poverty (2008) 334m 14% 3, ,500 Remove severely fuel poor from fuel poverty (2008) 470m 39% 20,200 31,800 Reduce fuel poor spend to average (2008) 115m 12% 8,500 45,000 Reduce severe fuel poor spend to average (2008) 127m 20% 15,000 25,800 Reduce LIHC household spend to average (2008) 115m 12% 2,500 60,600 Reduce fuel poverty gap for LIHC households by 50% 71m 14% 2,200 60,600 page 14 of 16

15 Figure 7: Table showing the modelled costs associated with the most expensive to improve homes in each scenario Scenario Range of costs of assisting the most expensive fifth of households Total modelled cost of assisting the most expensive fifth of households No. of households in homes in the most expensive fifth Av, cost of improving homes in most expensive fifth Remove from fuel poverty (2008) 13,500-52, b 65,000 23,200 Remove severely fuel poor from fuel poverty (2008) 27,600-52, m 12,800 31,400 Reduce fuel poor spend to average (2008) 21,000-52, b 43,000 27,500 Reduce severe fuel poor spend to average (2008) 23,000-52, m 10,400 29,600 Reduce LIHC household spend to average (2008) 12,000-52, m 28,400 12,800 Reduce fuel poverty gap for LIHC households by 50% 3,200-47, m 28,400 25,000 page 15 of 16

16 6. Conclusions and next steps This analysis demonstrates that the total cost of achieving fuel poverty targets by improving the energy performance of homes in Wales is significant. In the current financial climate it is unlikely that this level of investment could be secured from public funds. Therefore it is important that the limited funding available reaches those households most in need of support. The current approach to targeting Nest capital investment focussing on households on means tested benefits and living in very inefficient homes appears sensible. The scenarios in this analysis which focus on Low Income High [Energy] Cost (LIHC) households seem relatively achievable in terms of the level of investment required ( 50m - 100m a year for 10 years). They also appear to focus investment well on low income households. In contrast, the scenarios focusing on all fuel poor households include potentially significant costs associated with improving the homes of better off households. Although the total estimated cost of reducing the required energy spend of all LIHC households is relatively achievable at 100m a year for 10 years (this isn t all that far off the current level of investment assuming 20m a year for Nest, 10m a year on average for arbed and 29m a year for ECO), the real challenge is finding these households, who won t always be the first to come forward for support. In addition, although most households can be assisted for a relatively small proportion of the total cost in every scenario, some households require significant investment to reach the target saving even the least ambitious scenarios. For example, 20% of homes require more than 12,000 investment in the scenario which seeks to reduce the fuel poverty gap of LIHC households by 50%. Indeed, in each scenario some homes are not suitable for enough add on improvements to bring their required energy spend down to the target level, even at any cost. This could be because they are not suitable for many of the measures included in the modelling (e.g. a ground floor flat) or because the reported income of the household is so low that it is impossible to reduce their energy bill to a sufficient level. This analysis suggests that there is significant potential for cost effective home energy efficiency improvements in Wales. On average, investing over 2.4 billion in the estimated 330,000 households in fuel poverty in 2008 would pay back in less than 10 years (although there will of course be great variations in cost effectiveness of the individual measures identified). There will be significant additional potential for cost effective measures in the remaining 1 million homes in Wales. These measures could greatly improve the quality of life of many households by making their homes warmer and more efficient, as well as making an essential contribution to tackling our greenhouse gas emissions 8. The challenge will be to encourage those householders that are not eligible for publicly funded measures to make these improvements, using initiatives like the Green Deal where necessary. We hope that this analysis will stimulate discussion about getting the limited public funding available for home energy improvements to those that need it most. We also hope that is will encourage debate about how the remainder of households in Wales can be assisted to improve the warmth, efficiency and condition of their homes. 8 Our residential emissions modelling report, Achieving residential sector climate change targets in Wales looks at this in more detail. page 16 of 16