Könyv Modeling of Short Term Load Forecasting for Khartuom State Using ANN Ashraf Musa

Modeling of Short Term Load Forecasting for Khartuom State Using ANN

Szerző: Ashraf Musa
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
17 175 Ft
Electric load forecasting is the process used to forecast future electric load, given historical loa...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2017
oldal
96
EAN
9783659851124
Enbook ID
16758040
Súly
161
Méretek
150 x 220 x 6

Teljes leírás

Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%.

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