|
چکیده
|
Energy distribution networks rely heavily on the stability and predictability of household electricity consumption, which varies significantly across periods. This study employs half-hourly smart meter electrical data and a questionnaire survey dataset from over 3600 Irish households to analyze hourly and monthly electricity consumption patterns. We uncovered critical temporal variations in consumer electrical consumption patterns and suggested an innovative dynamic pricing tariff using advanced time series analysis, harmonic modelling, and an iterative error-driven adjustment method. These insights drive the development of a dynamic electricity pricing model, incorporating time-based tariffs segmented into night, day, and peak periods, with further seasonal adjustments to account for demand fluctuations. Our proposed model achieves an exceptional R² of 0.9995 and an RMSE of 0.2469c/kWh, demonstrating a robust alignment between one year of historical consumption data used as the training dataset and the subsequent six months used as the test dataset. This dynamic pricing model offers a promising solution for managing peak demand and enhancing grid stability. It enhances active consumer participation in demand-side management, paving the way for more efficient, sustainable energy distribution.
|