FORECASTING THE CONSUMPTION OF ELECTRICAL ENERGY ON THE CEB ELECTRICAL NETWORK IN LOME IN TOGO BY APPROACHES: SIMPLE LINEAR REGRESSION, RECURRENT NEURAL NETWORKS AND GENETIC ALGORITHMS
Journal: International Journal of Advanced Research (Vol.12, No. 04)Publication Date: 2024-04-18
Authors : Komla Kpomone Apaloo Bara;
Page : 01-17
Keywords : Consumption Electrical Energy Genetic Algorithms Meteorological Variables Recurrent Neural Networks. Simple Linear Regression;
Abstract
Forecasting the electrical power to be consumed requires planning production on several levels. In this work we used data from the Electric Community of Benin. Temperature, relative humidity, wind speed, normal direct irradiance, precipitation and diffuse radiation are the meteorological variables that made it possible to analyze the forecasts. The objective is to do learning with genetic algorithms, LSTM recurrent neural networks and simple linear regression after a characterization and a correlation study and then to submit the results to performance evaluation criteria. The results of the characterization made it possible to understand that certain variables are significant and influence the consumption of electrical energy. The study of the correlation gives 94% between direct normal irradiance and diffuse irradiance. Both give with the temperature 67% for one and 68% for the other. Regarding modeling, the results are bad with genetic algorithms if we take into account the correlation coefficient (R² = 28.84%), good with simple linear regression (R² = 69.08%) and very interesting for networks of recurrent neurons where we find: MAE = 0.11 MSE = 0.02 MAPE = 18.50% RMSE = 13.09% RRMSE = 18.25% and R² = 96.11%. Given these results, we deduce that short- and long-term memory recurrent neural networks (LSTM) are very well suited to predicting the electrical power consumed on the CEB electrical network.
Other Latest Articles
- A 6-Year-Old Boy with Generalized Weakness and Inability to Walk |Biomedgrid
- Secular Trend in Height of Japanese in The Past Century-How to Read Different Sources of Data |Biomedgrid
- Longitudinal Observation of Humoral Immune Response Along with Coagulation and InflammationSpecific Clinical Biomarkers in A COVID-19 Convalescent Donor Cohort |Biomedgrid
- Spread of tree of heaven (Ailanthus altissima (Mill.) Swingle) in urban area: a case study of Osijek (Republic of Croatia)
- Audiovježbe: računalni program za vježbe slušanja i terapiju tinitusa
Last modified: 2024-04-25 14:51:25