Short-Term Solar Power Forecasting Using the Adaptive Network-Based Fuzzy Inference System

DOI

10.2991/cmfe-15.2015.152How to use a DOI?

Keywords

solar power generation forecasting; photovoltaic system; adaptive network-based fuzzy inference system

Abstract

This paper proposes an adaptive network-based fuzzy inference system (ANFIS) based forecasting method for short-term solar power forecasting. An accurate forecasting method for power generation of the photovoltaic (PV) system is urgent needed under the relevant issues associated with the high penetration of solar power in the electricity system. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of solar power generation of a PV system installed on the St. John’s University of Taiwan. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wen-Yeau Chang
AU  - Ho-Chian Miao
PY  - 2015/07
DA  - 2015/07
TI  - Short-Term Solar Power Forecasting Using the Adaptive Network-Based Fuzzy Inference System
BT  - Proceedings of the International Conference on Chemical, Material and Food Engineering
PB  - Atlantis Press
SP  - 645
EP  - 648
SN  - 2352-5401
UR  - https://doi.org/10.2991/cmfe-15.2015.152
DO  - 10.2991/cmfe-15.2015.152
ID  - Chang2015/07
ER  -