Weather conditions have an impact on peak reductions from dynamic pricing.
{"Image DocumentName": "Weather conditions have an impact on peak reductions from dynamic pricing.", "Image ImageDescription": "In an analysis of billing data for 70,000 households in the San Diego region during a five-year period, the nearby weather station\u2019s daily temperature data was matched to the start and end dates for each bill. Billing-period heating and cooling degree-days, which are highly predictive measures of home heating and cooling energy demand, were used for weather variables. When measured carefully to account for billing-cycle timing, local weather and geographic effects, the relationship between weather and residential electricity consumption was found to be statistically significant. Weather conditions and climate difference can be concluded as confounding factors. Reiss and White (2008) examined data from actual (metered) energy usage for a large representative sample of households in the San Diego region during a five-year period. In their analysis of billing data for 70,000 households in the San Diego region, Reiss and White construct a household\u2019s weather variables using the matched weather station\u2019s daily temperature data and the exact start and end dates for each bill. The weather variables are billing-period heating and cooling degree-days, which are highly predictive measures of home heating and cooling energy demand. When measured carefully to account for billing-cycle timing, local weather, and geographic effects, the relationship between weather and residential electricity consumption was found to be statistically significant. Hence, weather conditions and climate difference can be concluded as confounding factors.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}