The residential sector accounts for around 24% of the total electricity consumption in India. Recent studies show that air conditioners (ACs) have become a significant contributor to residential electricity consumption. Further, it is predicted that by 2037, the demand for ACs will increase by four times due to their affordability and availability. Not many studies have been found on residential AC usage patterns and the factors (AC load, setpoint, hours of usage) that influence household electricity consumption. This paper investigates the residential AC usage patterns and AC’s contribution to total residential electricity consumption. Twenty-five urban homes from a wet and dry climatic region of India were monitored for nine months (in 2019) to determine overall household electricity consumption patterns, AC usage, and indoor environment during summer, monsoon, and winter. Analysis of seasonal consumption patterns shows a significant difference in electricity usage between homes with ACs and homes without ACs during the summer season. The average electricity consumption for AC homes was 15.1 kWh/day during summer, 6.6 kWh/day during monsoon, and 6.1 kWh/day during the winter season. Results showed that AC alone contributed to 39% of the total household consumption in summers. The peak AC usage in all homes is observed during sleep hours which was generally between 10:00 pm and 6:00 am and the average AC runtime was 6.2 h. The average indoor temperature was recorded as 26.9 °C during the AC ON period. The AC peak load, i.e., the maximum electricity demand during the AC ON period, is 1.7 kW on average during the study period. The average annual consumption of homes with ACs was 2881 kWh, and for non-AC homes, the consumption was 2230 kWh. Findings from our analysis provide a detailed understanding of AC consumption profiles and the difference in electricity consumption characteristics between AC and non-AC homes across different seasons.

Air Conditioners (ACs) have become a major contributor to residential electricity consumption in India. Non-intrusive Load Monitoring (NILM) can be used to understand residential AC use and its contribution to electricity consumption. NILM techniques use ground truth information along with meter readings to train disaggregation algorithms. There are datasets available for disaggregation, but no dataset is available for a hot tropical country like India especially for AC event detection. Our dataset’s primary objective is to help train NILM algorithms for AC event detection and compressor operations. The dataset comprises of home-level electrical current consumption and manually tagged AC ground truth (ON/OFF status) data at 1-min interval, indoor environment temperature and relative humidity readings at 5-min interval and dwelling, AC and household characteristics. The data was collected from 11 homes located in a composite climate zone-Hyderabad, India for 19 summer days (May) 2019. The dataset consists of 1.6 million data points and 450 AC cycles with each cycle having a runtime of more than 60 min (> 2000 compressor ON/OF cycles). Public availability of such a dataset will allow researchers to develop, train and test NILM algorithms that recognize AC and identify compressor operations.