Measuring and Evaluating the Soft Energy Efficiency Measures

1. Measuring and Evaluating the Soft Energy Efficiency Measures Heini-Marja Suvilehto ÅF-Infrastructure Ltd Virve Rouhiainen AdatoEnergia Ltd Niina Honkasalo ÅF-Consult Ltd Anni Sarvaranta ÅF-Consult Ltd Dennis Solid ÅF Industry Ltd 20-09-2012

2. Finnish energy policy and energy companies customers’ energy efficiency • The Energy Efficiency Agreements are a key instrument in Finland for the fulfilment of the obligations under the Energy Services Directive. • Apart from Energy Efficiency agreements there are two amendments to energy legislation that are central for enhancing energy companies’ customers’ energy efficiency • Government's regulation of electricity supplies and the inventory count (Government Decree 66/2009) . It focuses on metering. • Law on energy efficiency servicesfor companies operating on the energy market (Law 1211/2009) defines the energy companies obligation to promote efficient and sparing use of energy among their customers. It regulates the billing according to actual use and annual reporting of the energy use with relevant reference values.

3. The EU and the national policy measures to enhance energy efficiency

4. Soft measures are used here

5. The objective of the study was to: • To review the most recent international and national research on measuring and evaluating soft energy efficiency measures. • Investigate whether the Finnish energy utilities “soft” energy efficiency measures could be evaluated and quantified with help of the results from international/national research and suggest a methodology for quantification. • The last task was, if possible, to conduct the quantification of the effects in energy terms.

6. The evaluation process • Literature study • A rough estimation of the energy savings • A bottom-up approach to calculate energy saving fot the most relevant soft measures. • (Admissibility to EU energy saving obligations scheme)

7. Classification of the literature For using the empirical energy saving estimates from studies we set up high level of statistical significance as a requirement

8. Results from Literature study One of the interesting results from the EDRP (Energy Demand Research Project, Ofgem 2010) The smart meter itself provides no savings, but when it is combined with tailored higher savings are achieved. The segmentation of the customers includes end-user practises and preferred formats for received advice. The well-designed statistically proficient empirical studies we have summarised (EDRP 2010 and Darby 2005) support the findings of Korsunova’s (2010) doctoral dissertation: Energy Advice needs to be customized and it should include personal contact.

9. The quantification on aggregated level

10. The ‘Soft’ measures that the Finnish utilities provide to their customers are in following areas:

11. Quantification with bottom-up approach Quantification electricity

12. Quantification district heating

13. Data quality in the existing system

14. An alternative approach for monitoring & evaluation– indicators Trends or time series for demand of each measure. Here the two measures are advice on telephone which has increased loan of consumption gauges. Which is less popular

15. Results • Quantification is possible, however presently the estimates contain a large element of uncertainty • To reduce uncertainty • Conduct local large enough field experiments with appropriate experimental design (at minimum include a control group) • Choose the measures for trials on the basis of the literature study, e.g. small frequent messages seem to be working best, these could first be piloted and their effect could be established in a large trial. • Consider alternative ways to monitor such as introduction of indicators

16. Main findings • There are only a few empirical field experiments, the size of samples and test durations are quite small or the studies lack sufficient experimental design. • According to the reviewed studies, metering alone does not provide change in customer energy use and technology alone does not deliver energy savings; it needs to be combined with information (CER 2011; Ofgem 2010). • Multiple interventions, such as advice with feedback or advice with installation of efficiency measures, seem to give better results than single interventions (Darby 2010). • Smart metering and billing  accordingly provide approximately 1% savings (Ofgem 2010). Smart metering and billing accordingly together with tailored information  will provide approximately 3% energy savings (CER 2011; Ofgem 2010).