Probabilistic Models for Residential and Commercial Loads with High Time Resolution

This paper develops the annual load profiles for residential load and two types of commercial loads, located at the same climate zone characterized as mixed-marine. Each annual load profile is generated based on a probabilistic approach, in an hourly scale, and assessed based on external validity indices relying on both supervised learning and unsupervised learning. Furthermore, the paper presents a method to increase the daily resolution of each generated profile from 24 samples per day representing 24 hours, to 120 samples in each hour, increasing the daily profile to 2,880 samples. For illustration, the proposed method is applied on the generated residential and one of the commercial load profiles. This study contributes to the literature by developing numerical load profiles for residential and commercial loads. The residential load profile can be used to represent the electricity consumption in the residential sector while the commercial load profiles can be utilized to represent the electricity consumption in the commercial sector.