Analysis of electric energy consumption profiles using a machine learning approach: A Paraguayan case study
F Morales, M García-Torres, G Velázquez… - Electronics, 2022 - mdpi.com
Correctly defining and grouping electrical feeders is of great importance for electrical system
operators. In this paper, we compare two different clustering techniques, K-means and …
operators. In this paper, we compare two different clustering techniques, K-means and …
Machine learning for electric energy consumption forecasting: Application to the Paraguayan system
F Morales-Mareco, M García-Torres… - Logic Journal of the …, 2024 - academic.oup.com
In this paper we address the problem of short-term electric energy prediction using a time
series forecasting approach applied to data generated by a Paraguayan electricity …
series forecasting approach applied to data generated by a Paraguayan electricity …
A Novel Short Electric Load Forecasting Approach Using a Multivariate Transformer Neural Network and CEEMDAN
BM Elsayed, MM Eladany, MH Elfar… - … Middle East Power …, 2023 - ieeexplore.ieee.org
Accurate electrical load forecasting is a difficult task due to the nonlinearity and high volatility
of time series data. In this research, the “decomposition and ensemble” methodology is …
of time series data. In this research, the “decomposition and ensemble” methodology is …
Electrification systems for off-grid rural communities in Ecuador
J Jarrín-Diaz, R Sánchez-Figueroa… - … Autumn Meeting on …, 2022 - ieeexplore.ieee.org
Population growth and technological advances have led to unprecedented consumption of
fossil fuels, which has negative consequences due to environmental pollution. In this …
fossil fuels, which has negative consequences due to environmental pollution. In this …