Cart (Loading....) | Create Account
Close category search window

Neural Network Estimation of Microgrid Maximum Solar Power

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chatterjee, A. ; Ohio State Univ., Columbus, OH, USA ; Keyhani, A.

The integration of photovoltaic (PV) generating stations in the power grids requires the amount of power available from the PV to be estimated for power systems planning on yearly basis and operation control on daily basis. To determine the PV station maximum output power, the PV panels must be placed at an optimal tilt angle to absorb maximum energy from the sun. This optimal tilt angle is a nonlinear function of the location, time of year, ground reflectivity and the clearness index of the atmosphere. This paper proposes a neural network (NN) to estimate the optimal tilt angle at a given location and thus an estimate of the amount of energy available from the PV in a microgrid.

Published in:

Smart Grid, IEEE Transactions on  (Volume:3 ,  Issue: 4 )

Date of Publication:

Dec. 2012

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.