Artificial Neural Network Base Short-Term Electricity Load Forecasting: A Case Study of a 132/33kv Transmission Sub-Station
<p>Forecasting of electrical load is extremely important for the effective and efficient operation of any power system. Good forecasts results help in minimizing the risk in decision making and reduces the costs of operating the power plant. This work focuses on the short-term load forecast of...
Main Authors: | Isaac Adekunle Samuel, Segun Ekundayo, Ayokunle Awelewa, Tobiloba Emmanuel Somefun, Adeyinka Adewale |
---|---|
Format: | Article |
Language: | English |
Published: |
EconJournals
2020-01-01
|
Series: | International Journal of Energy Economics and Policy |
Online Access: | https://www.econjournals.com/index.php/ijeep/article/view/8629 |
Similar Items
-
Análisis del Tipo y Valor de una Impedancia Limitadora de Corrientes de Cortocircuito Monofásicas a Tierra en el Nivel de 33 Kv para su Instalación en Estaciones Transformadoras 132 /33 /13,2 Kv
by: Matías E. Barlasina, et al.
Published: (2018-10-01) -
Implementation of Distributed Generation with Solar Plants in a 132 kV Grid Station at Layyah Using ETAP
by: Ghulam Mujtaba, et al.
Published: (2020-01-01) -
Analysis and Mitigation of Shunt Capacitor Bank Switching Transients on 132 kV Grid Station, Qasimabad Hyderabad
by: Sunny Katyara, et al.
Published: (2015-10-01) -
Lightning performance improvement of the Swaziland Electricity Board transmission system (66kV & 132kV lines)
by: Mswane, Luke Mdumiseni
Published: (2014) -
Trafikverkets effektstyrningssystem - EFS 132 kV : Bidraget till minskade förluster
by: Hasselstam, Jonas
Published: (2012)