Analysis of Weather, Time, and Mandatory Time-of-Use Pricing Effects on Aggregate Residential Electricity Demand

time-of-use;TOU;electricity;residential;temperature;weather;regression;Electrical and Computer Engineering

Miller, Reid

University of Waterloo

关键词: time-of-use;    TOU;    electricity;    residential;    temperature;    weather;    regression;    Electrical and Computer Engineering;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/9417/3/Miller_Reid.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

Residential electricity demand is affected by three types of external factors: weather, time, and the price of electricity. Ontario has mandated time-of-use pricing for all residential customers in the province. We implement a data-driven study using multiple linear regression to quantify the effects of mandatory time-of-use pricing on residential electricity demand in south west Ontario. In order to isolate the effects of this pricing policy on electricity demand, we first account for the combined effects of weather and time.Our treatment of temporal variables such as month, working days, and hour-of-day is consistent with prior work. However, there is no consensus in prior work for modelling the effects of temperature and weather over time. In temperate regions like Ontario, the relationship between residential electricity demand and temperature is notably non-linear across winter and summer seasons. A mild or extreme summer may skew the estimated impacts of time-of-use pricing if the effects of temperature are not properly accounted for. To address this challenge, we formulate a detailed comparison of existing methods used to transform dry-bulb temperature observations. We consider piecewise linear and natural spline transformations for modelling non-linearity. We also consider coincident weather observations such as humidity, wind chill, and qualitative weather conditions. Finally, we consider variable transformations that take into account the time delay or build-up of temperature that household thermal controls react to. We consider lagged observations, cooling degree-hour, heating degree-hour, moving average, and exposure-lag-response transformations. For all combinations of temperature variable transformations we report the explanatory power, out-of-sample prediction accuracy, and discuss impacts on model interpretability.Using the results from our temperature transformation comparison, we select a well-performing, descriptive model for use in a time-of-use case study. Ontario;;s time-of-use pricing policy is evaluated according to two of its stated objectives: energy conservation and shifting consumption out of peak demand periods. We show that during the summer rate season, time-of-use pricing is associated with electricity conservation across all price periods. The average demand change during on-peak and mid-peak periods is -2.6% and -2.4% respectively. Change during working day and non-working day off-peak periods is -0.9% and -0.6% but is not statistically significant. The peak-to-average ratio, a separate metric to measure shifted electricity demand, changed -0.8% under time-of-use pricing from 1.441 to 1.429. These results are consistent with prior time-of-use evaluations carried out within the province, though less pronounced compared to pilot studies.