NDLI: Photovoltaic power forecasting using statistical methods: impact of weather data

Content Provider	IET Digital Library
Author	Giorgi, Maria Grazia De Congedo, Paolo Maria Malvoni, Maria
Abstract	An important issue for the growth and management of grid-connected photovoltaic (PV) systems is the possibility to forecast the power output over different horizons. In this work, statistical methods based on multiregression analysis and the Elmann artificial neural network (ANN) have been developed in order to predict power production of a 960 kWP grid-connected PV plant installed in Italy. Different combinations of the time series of produced PV power and measured meteorological variables were used as inputs of the ANN. Several statistical error measures are evaluated to estimate the accuracy of the forecasting methods. A decomposition of the standard deviation error has been carried out to identify the amplitude and phase error. The skewness and kurtosis parameters allow a detailed analysis of the distribution error.
Starting Page	90
Ending Page	97
Page Count	8
ISSN	17518822
Volume Number	8
e-ISSN	17518830
Issue Number	Issue 3, May (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-smt/8/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-smt.2013.0135
Journal	IET Science, Measurement & Technology
Publisher Date	2014-02-28
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Amplitude Error Identification ANN Decomposition Elmann Artificial Neural Network Grid-connected Photovoltaic System Italy Kurtosis Parameter Load Forecasting Meteorological Variable Measurement Multiregression Analysis Neural Computing Technique Neural Nets Phase Error Identification Photovoltaic Power Forecasting Photovoltaic Power System Power 960 KW Power Engineering Computing Power Grid Power Production Prediction Power System Economics Power System Identification Power System Managemen Power System Management Power System Measurement Power System Measurement And Metering Power System Operation Power System Planning And Layout PV System Regression Analysis Skewness Parameter Solar Power Stations Statistical Analysis Statistical Method Statistics Time Series Weather Data Impact
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering

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