A Probabilistic Assessment of the Relationship Between Electric Load and Temperature in Albania Using Monte Carlo Simulation

This study analyzes the relationship between temperature and electric load demand in the Albanian Power System, using historical data of four selected months: January, April, July, and October. A Monte Carlo simulation approach is used to determine the degree of stochastic relationship between temperature and electric load, offering insights into seasonal variability and peak load risks. Linear regression models are developed for each month to characterize the temperature-load dependency, and probabilistic simulations are run to assess the relationship between electric load and temperature. The results demonstrate a great sensitivity of the load to high summer temperatures and emphasize the need for robust planning during extreme conditions.