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Power Forecasting in Photovoltaic System using Hybrid ANN and Wavelet Transform based Method

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Title Power Forecasting in Photovoltaic System using Hybrid ANN and Wavelet Transform based Method
 
Creator Singh, Pooja
Mandpura, Anup Kumar
Yadav, Vinod Kumar
 
Subject Bior-orthogonal filter
Decomposition
Feed forward network
PV generation
Sustainable development
 
Description 63-74
Solar energy is a sustainable, renewable energy which is a part of latest industry standards of operation in line with
industry 4.0. Solar power variability leads to fluctuation and uncertainty in Photovoltaic (PV) output power. It is a
significant issue with regard to the high penetration of PV power generation. The solar irradiance is affected by weather
conditions, and varies with geographical locations. Accurate PV power output forecasting is essential for the planning and
scheduling alternate sources of conventional power. In this paper we propose a frequency domain approach for forecasting
of short-term PV output power. The wavelet transform allows identification of periodic components with time localization,
whereas the Artificial Neural Network (ANN) technique allows us to model the non-linearities in the PV time series. In this
paper, PV power data for the city Bareilly, Uttar Pradesh is forecasted. Numerical simulations show that the proposed
forecasting method for PV power output, shows a significant increase in accuracy over other similar methods. The root
Mean Square Error, Mean Absolute Error for the proposed method are also calculated and compared with state-of-the art
methods for PV power forecasting.
 
Date 2023-01-16T10:44:36Z
2023-01-16T10:44:36Z
2023-01
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61204
https://doi.org/10.56042/jsir.v82i1.69939
 
Language en
 
Publisher NIScPR-CSIR, India
 
Source JSIR Vol.82(01) [January 2023]