Analyzing energy consumption peaks in Tanzania

Résumé fourni par la source

Abstract This paper presents the first statistical modeling of peak times in maximum daily energy consumption for major industrial and service-sector companies in Tanzania, representing the first such analysis for any African country. Using high-resolution automated meter reading data from six of Tanzania’s largest energy consumers collected between 2020 and 2023, we model the time of peak demand as a circular variable. Due to the observed multimodality in peak times, a finite mixture of von Mises distributions is applied, with model parameters estimated via Markov chain Monte Carlo. The optimal number of mixture components varies considerably across companies-ranging from 4 to 10-reflecting diverse and company-specific demand patterns. Key circular statistics, including mean resultant, variance, skewness, and kurtosis, reveal substantial differences in peak concentration and temporal distribution: industrial firms exhibit more predictable, clustered peaks, while utility companies show highly variable and dispersed demand. Likelihood ratio tests confirm that peak-time distributions are stable across years, months, and days, indicating structurally embedded operational rhythms.

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