2. Daylight Savings Time Impact

3. DST Impact  Goal - estimate the change in energy due to DST  Approach – Measure energy before and after the DST date

4. DST Impact  Two days were used for comparison Selected one day before the DST change and one after Attempted to make sure that the weather was as close as possible Chose the same day of the week Used 560 residential sample accounts from GPC  Compared the five morning hours and five evening hours Any potential DST impact would occur the during 5am - 9am and 7pm - 11pm hours

5. DST Impact  Chose April 3 and April 17, 2003 Both days were Thursday Similar hourly temperature morning3-Apr17-Aprevening3-Apr17-Apr 5am52597pm7166 6515886866 7515896665 85558106465 960 116364 average5459average6665

6. DST Impact  kW demand between the two days was not significantly different kW3-Apr17-Apr morning10.19.9 evening11.411.7  Paired t-test was used to statistically determine if the difference in usage was significant t-test results showed no change in usage after the DST shift

7. DST Impact  Repeated the analysis with two random days  Chose April 1 and April 8, 2004 mean temp1-Apr8-Apr morning3958 evening4867  April 1 was a much colder day than April 8

8. DST Impact  Unlike the first test, there was a significant difference in usage between the two days mean kW1-Apr8-Apr morning10.17.4 evening9.98.2  April 1, which was much colder, had a higher kW usage than April 8  This process was repeated with other days, yielding similar results

9. DST Impact  Conclusions When temperatures are somewhat similar, there is no significant difference in usage Temperature has an impact on demand DST does not affect demand

10. DST Impact  A separate analysis was done using Alabama residential data ANOVA test (similar to paired t-test) was used Looked at each day for the entire week before and after DST Examined the two hours before/after sunrise  Identical conclusions were reached Temperature is the key driver of demand DST does not influence demand