Common failures of demand response

Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider

“…Changes in the number of daylight hours were considered as an influence on results, but the control group results indicate that this was not responsible for the observed changes. The 'Hawthorne effect' of being observed in a trial (AECOM, 2011 andIpakchi andAlbuyeh, 2009) may have had some impact, although this 18 Whilst it is tempting to conclude from the figures given earlier that Trial 1 was slightly more successful than Trial 2, it is important to note that 5 out of 10 (50%) of the households increased their off-peak consumption in the second trial in comparison to Trial 1, and that 'response fatigue' (Kim and Shcherbakova 2011) may mean the ordering of the trials played a role. There is also evidence that a few participants did not fully comprehend Trial 2, and this may have impacted on how they responded.…”

“…Whilst the results indicate that the first trial was a little more successful than the second in incentivising load-shifting, the fact that half the households increased their off-peak consumption in the second trial in comparison to Trial 1, suggests this is not a straight-forward conclusion. It is possible, moreover, that if the trials had been ordered differently, the results may have differed, as there is some evidence that there was greater engagement with the electricity monitoring equipment early on, as has been noted in other research (Hargreaves et al 2010), and a problem of 'response fatigue' has been reported in some dynamic pricing trials (Kim and Shcherbakova 2011). This raises too possible issues with whether such response levels would be sustained over time, something these six week trials were not designed to test.…”

Evaluation methods for market models used in smart grids

“…Previous research also shows that DLC through enabling technology significantly influence load shift and peak reduction in combination with dynamic market models (91). There are also indications that external variables such as social, economic, geographical locations may have an influence on dynamic market models and its impact on peak reduction and electricity consumption (92). For these reasons it would be wise to investigate these DR resources and their impact on electricity conservation, peak reduction, and load shift.…”

“…Due to the heavy burden of today's society concerning information flow, it is quite understandable that customers must be rather dissatisfied in seeking information needed to switch market model (92). Three of the most frequently given reasons for why consumers do not change electricity retailer were: customers were satisfied with their present retailer, customers were unsure about what retailer is the best and how they would perform a switch of retailer (46).…”

“…This could perhaps be done better by DLC, since electricity is perceived as a commodity that is not differentiated by quality and most people passively consume electricity. Therefore, electrical appliances could possibly be reprogrammed or relatively infrequently re-scheduled by the user to run at different times (92).…”