Name: Residential Electrical Long-Term Load Forecast: Using Artificial Neural Network: 11 (en Inglés)
SKU: 62088677
Price: 66.67 USD
Availability: InStock
Author: Agboola Olasunkanmi Johnson; Ameze Big-Alabo
ISBN: 9786207486670

portada Residential Electrical Long-Term Load Forecast: Using Artificial Neural Network: 11 (en Inglés)

Residential Electrical Long-Term Load Forecast: Using Artificial Neural Network: 11 (en Inglés)

Formato

Libro Físico

Editorial

Lap Lambert Academic Publishing

Autor

Agboola Olasunkanmi Johnson; Ameze Big-Alabo

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

ISBN13

9786207486670

Residential Electrical Long-Term Load Forecast: Using Artificial Neural Network: 11 (en Inglés)

Agboola Olasunkanmi Johnson; Ameze Big-Alabo (Autor) · Lap Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Residential Electrical Long-Term Load Forecast: Using Artificial Neural Network: 11 (en Inglés)"

The essentiality of electric load forecast for the effective design and management of electric power systems has been achieved in this study. PHEDC may plan for infrastructure construction, resource allocation, and energy management by using accurate long-term load forecasts of this study. In the context of the 11/0.415 kV feeder in Port Harcourt, Nigeria, we have discussed the use of ANNs for a long-term of ten (10) years of load forecasting. Curve fitting feed-forward artificial neural network has been used for the simulation on MATLAB 2020 environment, with six input datasets obtained from TCN, and PHEDCs' offices, and average temperature from NIMET-Abuja all in Nigeria from January, 2015-December, 2019. The regression plot of epoch 11 with training; R=1 and validation of 0.9999 has been achieved which indicates how efficient was the training of the dataset. Levenberg-Marquardt algorithm is used as an optimization technique in this study. It shows that ANN provides effective results on long-term electrical load forecasting of the Woji Estate Feeder with a total forecasted value of 29734.4 MWHR and an average value of 24778.67 MWHR at the end of the tenth year.