Quantifying the correlations between the total household electrical demand of residential dwellings and their appliances-spaces demand: A clustering multi-method approach

Decoding and unveiling the complex behaviors of electrical demand are vital steps toward achieving optimal power planning and operation of the power grid. Residential demand is stochastic and unique; hence, discovering unique demand behavior patterns and characteristics is essential for achieving sustainability targets in the residential energy sector and zero-energy housing through improved renewable optimization, building energy management, and policy making. While such endeavors have already been made in recent research, little to no research has extended beyond the total demand of a dwelling at the main meter level to unveil behind-the-meter energy demand behavior correlations of many appliances and dwelling space demands, primarily owing to the difficulty in acquiring such data for long periods and for a large number of dwellings. In this study, the 2-year minutely sampled electrical demand data of 479 dwellings in a large residential complex in Osaka, Japan, with 18 behind-the-meter energy demand attributes (BTMEDAs) of appliances, dwelling space energy demand, and water and gas consumption, are analyzed to (a) investigate the seasonal diversity of demand behaviors at the main meter level, namely, total household demand (THD) and BTMEDAs. (b) Quantify the correlation between the THD of each dwelling and various BTMEDAs through a multi-method approach to determine the most impactful appliances/spaces on global electrical demand behaviors across different seasons. (c) Finally, we demonstrate how the cluster encoding method can enhance user data privacy while preserving the key association of various BTMEDAs characteristics with THD. The results depicted that 6% of the users have Very High (VH) energy demand behavior, 26% High (H), 35% Medium (M), and 33% Low (L), although behavior proportions change based on seasons. Furthermore, across all seasons, the living room’s outlet was a significant contributor to THD behaviors with a weight of 20.1%, followed by its AC with 15 % weight, and the Hallway and WC lighting outlets with 9.15%, despite having low average demand.