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Journal ArticleDOI

A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

Adel Mellit, +1 more
- 01 May 2010 - 
- Vol. 84, Iss: 5, pp 807-821
TLDR
In this paper, a multilayer perceptron (MLP) model was proposed to forecast the solar irradiance on a base of 24h using the present values of the mean daily solar irradiances and air temperature.
About
This article is published in Solar Energy.The article was published on 2010-05-01. It has received 749 citations till now. The article focuses on the topics: Solar irradiance & Photovoltaic system.

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Citations
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Journal ArticleDOI

Subset Selection in Regression

TL;DR: Chapman and Miller as mentioned in this paper, Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40, 1990) and Section 5.8.
Journal ArticleDOI

Review of photovoltaic power forecasting

TL;DR: This paper appears with the aim of compiling a large part of the knowledge about solar power forecasting, focusing on the latest advancements and future trends, and represents the most up-to-date compilation of solarPower forecasting studies.
Journal ArticleDOI

Solar forecasting methods for renewable energy integration

TL;DR: In this article, the authors review the theory behind these forecasting methodologies, and a number of successful applications of solar forecasting methods for both the solar resource and the power output of solar plants at the utility scale level.
Journal ArticleDOI

Forecasting of photovoltaic power generation and model optimization: A review

TL;DR: In this paper, a comprehensive and systematic review of the direct forecasting of PV power generation is presented, where the importance of the correlation of the input-output data and the preprocessing of model input data are discussed.
Journal ArticleDOI

Review of solar irradiance forecasting methods and a proposition for small-scale insular grids

TL;DR: In this article, the authors present an in-depth review of the current methods used to forecast solar irradiance in order to facilitate selection of the appropriate forecast method according to needs.
References
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Book

Neural Networks: A Comprehensive Foundation

Simon Haykin
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
Book

Subset Selection in Regression

TL;DR: In this paper, Efroymson's algorithm was used to replace two variables at a time with all subsets using branch-and-bound techniques. But the results showed that one subset was better than another.
Journal ArticleDOI

Subset Selection in Regression

TL;DR: Chapman and Miller as mentioned in this paper, Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40, 1990) and Section 5.8.
Journal ArticleDOI

Artificial intelligence techniques for photovoltaic applications: A review

TL;DR: The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in photovoltaic systems application, mainly because of their symbolic reasoning, flexibility and explanation capabilities.
Journal ArticleDOI

Solar radiation model

TL;DR: In this article, the authors used the Angstrom-Prescott equation to predict the average daily global radiation with hours of sunshine for Hong Kong (22.3°N latitude, 114. 3°E longitude).
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