Energy, cost, and emission end-use profiles of homes: An Ontario (Canada) case study

Abstract

Providing information on the temporal distributions of residential electricity end-uses plays a major role in determining the potential savings in residential electricity demand, cost, and associated emissions. While the majority of the studies on disaggregated residential electricity end-use data provided hourly usage profiles of major appliances, only a few of them presented analysis on the effect of hourly electricity consumption of some specific end-uses on household costs and emissions. This study presents side-by-side analysis of energy, cost, and environment effects of hourly electricity consumption of the main electricity end-uses in a sample of homes in the Canadian province of Ontario. The data used in this study are drawn from a larger multi-stakeholder project in which electricity consumption of major end-uses at 25 homes in Milton, Ontario, was monitored in five-minute intervals for six-month to two-year periods. In addition to determining the hourly price of electricity during the monitoring period, the hourly carbon intensity is determined using fuel type hourly generation and the life cycle greenhouse gas intensities specifically determined for Ontario’s electricity fuel mix. The hourly load, cost, and emissions profiles are developed for the central air conditioner, furnace, clothes dryer, clothes washer, dishwasher, refrigerator, and stove and then grouped into eight day type categories. The side-by-side analysis of categorized load, cost, and emission profiles of the seven electricity end-uses provided information on when the maximum usage of specific end-uses occurs and which end-uses are “behaviour based” and which are “outdoor temperature based”. The share of each end-use in total household load, cost, and emissions is determined and load, cost, and emission share distributions are compared. The results of this study present valuable information to homeowners for reducing their electricity consumption and to system operators for reducing peak loads.