Issue link: https://fhpublishing.uberflip.com/i/796215
NETWORK / 25 / MARCH 2017 The Sunshine Tariff took the form of a Tempus-backed time-of-use tariff with a rate of 5p/kWh during the "sunshine hours" of 10am to 4pm and 18p/ kWh at other times. The short time allocated for sign-up and existing contract lock-ins meant the number of participants fell from an expected 240 to just 46. As a result, confidence in the findings was too low to apply to other populations, but the practical findings and qualitative insights are still useful when assessing the feasibility of the solar farm's offset connection and when gauging the reaction to domestic demand response. Participants were split into four sub-groups with differing levels of influence and automation. Group 1 simply switched to the tariff, group 2 was given feedback, group 3 had its hot water automated and group 4 had fully active load switching. All had a smart meter installed to record the data. As Matt Watson, innovation and low-carbon networks engineer at WPD, explains: "That was to try to understand not only whether people were interested, but what interested them and how they could shi'." According to the results of the five-month trial, the group with no automation was able to shi' an average of just 5% of demand to the off-peak period. Those with automation shi'ed an average of 13%, supporting the idea that automation can play a key role in enabling demand response. The higher the energy use, the higher the potential shi'. Those in the upper bracket shi'ed 18%, those in the mid shi'ed 10% and those with the lowest energy use shi'ed only 6%. Furthermore, it was found that participants' perceptions of their shi' were higher than the reality. This, says Tamar Bourne, smart energy lead and senior manager at Regen SW, was largely because participants used washing machines and dishwashers during the sunshine hours. "If you look at how much power on average those appliances use, it's relatively low," she explains. "I think that's why people felt they were doing a lot more, mainly because of the effort required to change those behaviours." Almost three-quarters (73%) of participants reported they would shi' to a time-of-use tariff again in future, while the data and post-trial interviews indicated there was little drop- off in shi'ing as time went on. Disappointingly, trial participants shi'ed an average of just 10% of demand into the target period. This suggests that without significant uptake of automation and incentive- based shi'ing, a time-of-use tariff alone will not prompt the required load to be diverted. As a result, the offset con- nection for the solar farm was not deemed viable. Some 650 homes, or 20% of the local mar- ket, would have to participate to offset the required demand, which would be unrealistic in the current environment. "WPD won't be rolling out an offset connection agreement be- cause of the practical challenges around how that would work," says Watson, citing the recruit- ment difficulties and the im- maturity of the demand-response sector as barriers to its viability. However, Watson and Bourne stress that the trial did show the need for a higher penetration of automation and also domestic half-hourl y settlement. Equally, simpler and more efficient meth- ods of switching suppliers are needed. This implies a need for the sector as a whole to embrace flexibility. Recruiting customers to time- of-use tariffs is as much a chal- lenge for the sector as a whole as it proved for WPD, Tempus, and Regen SW; as is ensuring engagement with smart meters. The technology of today may offer opportunities to evolve and reshape the electricity market from the producer to the consumer, but unless people can be understood and man- aged, its ability in practice will be limited. N Comparison of the whole cohort average weekday demand Sunshine Tariff trial against the control 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 kWh 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Sunshine Tariff Control average weekday Sunshine Tariff customers Comparison of demand profile for subgroups A and B against the control for the average weekday 0.5 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 kWh Sunshine Tariff Control average weekday Subgroup A average weekday Subgroup B average weekday