scholarly journals Short Term Load Forecasting for Erbil Distribution System Using ANN and Wavelet Transform

2009 ◽  
pp. 334-339
Author(s):  
A. A. Rasool ◽  
A. A. Fttah ◽  
I.B.S adik
Keyword(s):  
Wavelet Transform ◽  
Distribution System ◽  
Load Forecasting ◽  
Short Term ◽  
Short Term Load Forecasting

Very short term load forecasting of a distribution system with high PV penetration

2017 ◽  
Vol 106 ◽  
pp. 142-148 ◽  
Author(s):  
Saeed Sepasi ◽  
Ehsan Reihani ◽  
Abdul M. Howlader ◽  
Leon R. Roose ◽  
Marc M. Matsuura
Keyword(s):  
Distribution System ◽  
Load Forecasting ◽  
Short Term ◽  
Short Term Load Forecasting ◽  
Pv Penetration

scholarly journals ANN based Short-Term Load Curve Forecasting

2018 ◽  
Vol 13 (6) ◽  
pp. 938-955
Author(s):  
Violeta Eugenia Chis ◽  
Constantin Barbulescu ◽  
Stefan Kilyeni ◽  
Simona Dzitac
Keyword(s):  
Distribution System ◽  
Load Forecasting ◽  
Software Tool ◽  
Regression Curve ◽  
Short Term ◽  
Load Curve ◽  
Consumption Data ◽  
Short Term Load Forecasting ◽  
System Operator ◽  
Linear Regression Curve

A software tool developed in Matlab for short-term load forecasting (STLF) is presented. Different forecasting methods such as artificial neural networks, multiple linear regression, curve fitting have been integrated into a stand-alone application with a graphical user interface. Real power consumption data have been used. They have been provided by the branches of the distribution system operator from the Southern-Western part of the Romanian Power System. This paper is an extended variant of [4].

scholarly journals Short-term Load Forecasting for Microgrids Based on Discrete Wavelet Transform and BP Neural Network

2014 ◽  
Vol 8 (1) ◽  
pp. 738-742 ◽  
Author(s):  
Chong Gao ◽  
sheng Huang ◽  
Hai-feng Wang
Keyword(s):  
Wavelet Transform ◽  
Load Forecasting ◽  
Discrete Wavelet ◽  
Short Term ◽  
Short Term Load Forecasting ◽  
Micro Grid ◽  
Grid Load ◽  
The Time Domain ◽  
National Economies ◽  
Better Than

Electricity is of great vital and indispensable to national economies. A new short-term load forecasting for micro grid is proposed in this paper. After comparing and analyzing all load characteristic in the time domain and frequency domain, we apply wavelet transform to decompose the load signal. After that, the training set and text set are selected in consideration of the effects generated by the temperature and day type. At length, BP natural network is employed you forecast the micro grid load. The final result proves that the forecasting precision of the method we propose is obviously better than the traditional ones. What’s more, our method has Strong adaptability and good generalization ability.

Sign in / Sign up

Export Citation Format

Share Document