Grey-Box Modeling for Photo-Voltaic Power Systems Using Dynamic Neural-Networks

Al-Messabi, N., Goh, C. and Li, Y. (2017) Grey-Box Modeling for Photo-Voltaic Power Systems Using Dynamic Neural-Networks. In: 2017 Ninth Annual IEEE Green Technologies Conference (GreenTech), Denver, CO, USA, 29-31 Mar 2017, pp. 267-270. (doi: 10.1109/GreenTech.2017.45)

Abstract

There exists various ways of modeling and forecasting photo-voltaic (PV) systems. These methods can be categorized, in board-way, under either definite equations models (white or clear-box) or heuristic data-driven artificial intelligence models (black-box). The two directions of modeling pose a number of drawbacks. To benefit from both worlds, this paper proposes a novel method where clear-box model is extended to a grey-box model by modeling uncertainities using focused time-delay neural network models. The grey-box or semi-definite model was shown to exhibit enhanced forecasting capabilities.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Goh, Dr Cindy Sf and Li, Professor Yun and AL-MESSABI, Naji
• Authors: Al-Messabi, N., Goh, C., and Li, Y.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISSN: 2166-5478
• Copyright Holders: Copyright © 2017 IEEE
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher