Short-Term Load Forecasting Using Fuzzy Logic

Jordan Blancas, Julien Noel

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

In this paper, fuzzy logic (FL) is applied to the problem of short-Term load forecasting (next day) in electrical power systems. To achieve this, it is necessary to select the historical data to be used and pre-process them using the c-means method, grouping them according to power levels (MW) to define the number of membership functions (MFs) to the fuzzy system, which is very important for the calculation of the lowest forecast error; finally, the historical data are entered into the fuzzy system implemented in MATLAB. This methodology is applied to predict the daily electrical load (demand) of the Peruvian Electrical System using the historical data of the actual demand executed for the study period and by calculating the MAPE error. It is shown that the FL offers better results than the conventional methodology for the forecast of the electrical load.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538658444
DOI
EstadoPublicada - 26 oct. 2018
Evento2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA - Lima, Perú
Duración: 18 set. 201821 set. 2018

Serie de la publicación

NombreProceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018

Conferencia

Conferencia2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA
País/TerritorioPerú
CiudadLima
Período18/09/1821/09/18

Huella

Profundice en los temas de investigación de 'Short-Term Load Forecasting Using Fuzzy Logic'. En conjunto forman una huella única.

Citar esto