Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs

Abstract

The increasing concern for environmental conservation has spurred government initiatives towards energy efficiency. One of the key research areas in this regard is demand response, particularly focusing on differential pricing initiatives such as Time-of-Use (ToU). Differential tariffs are typically designed based on mathematical or statistical models analyzing historical electricity price and consumption data. This study proposes a methodology for identifying time intervals suitable for implementing ToU energy tariffs, achieved by analyzing electric power demand variability to estimate demand flexibility potential. The methodology transforms consumption data into variation via the coefficient of variation and, then, employs k-means data analysis techniques and the a priori algorithm. Tested with real data from smart meters in the Colombian electrical system, the methodology successfully identified time intervals with potential for establishing ToU tariffs. Additionally, no direct relationship was found between external variables such as socioeconomic level, user type, climate, and consumption variability. Finally, it was observed that user behavior concerning consumption variability could be categorized into two types of days: weekdays and non-working days.