Electricity service interruptions compromise households' ability to meet energy demand, and thus increase energy insecurity. Interruptions can take the form of power outages, or involuntary disconnections due to nonpayment. To achieve equitable electricity access, it is crucial to understand how electricity loss varies across demographics. However, utilities often report outages at the system or county level and face few incentives to report disconnection metrics, making spatially granular analysis of interruptions challenging. This paper presents a new method of quantifying electricity reliability by classifying unlabeled advanced metering infrastructure (AMI) data, hence disaggregating power outages from disconnections in residential electricity consumption data. We use the Commonwealth Edison utility service territory in Illinois as a case study and evaluate how the duration and frequency of power outages (outage burden) change across ZIP codes. We find that the most outage-burdened regions are concentrated in rural counties, and regions with a higher percentage of low-income residents and people of color often carry higher outage burdens than the rest of the service territory. Our proposed method is the first to disaggregate AMI data into outages and disconnections, enabling more granular metrics for electricity reliability, highlighting gaps in energy accessibility and informing the identification of energy-insecure communities.