@article{ART001630075},
author={황미영 and 김성호 and Unil Yun and KwangDeuk Kim and 류근호},
title={Building of Prediction Model of Wind Power Generationusing Power Ramp Rate},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2012},
volume={17},
number={1},
pages={212-218}
TY - JOUR
AU - 황미영
AU - 김성호
AU - Unil Yun
AU - KwangDeuk Kim
AU - 류근호
TI - Building of Prediction Model of Wind Power Generationusing Power Ramp Rate
JO - Journal of The Korea Society of Computer and Information
PY - 2012
VL - 17
IS - 1
PB - The Korean Society Of Computer And Information
SP - 212
EP - 218
SN - 1598-849X
AB - Fossil fuel is used all over the world and it produces greenhouse gases due to fossil fuel use. Therefore, it cause global warming and is serious environmental pollution. In order to decrease the environmental pollution, we should use renewable energy which is clean energy. Among several renewable energy, wind energy is the most promising one. Wind power generation is does not produce environmental pollution and could not be exhausted. However, due to wind power generation has irregular power output, it is important to predict generated electrical energy accurately for smoothing wind energy supply. There, we consider use ramp characteristic to forecast accurate wind power output. The ramp increase and decrease rapidly wind power generation during in a short time. Therefore, it can cause problem of unbalanced power supply and demand and get damaged wind turbine. In this paper, we make prediction models using power ramp rate as well as wind speed and wind direction to increase prediction accuracy. Prediction model construction algorithm used multilayer neural network. We built four prediction models with PRR, wind speed, and wind direction and then evaluated performance of prediction models. The predicted values, which is prediction model with all of attribute, is nearly to the observed values. Therefore, if we use PRR attribute, we can increase prediction accuracy of wind power generation.
KW - Prediction accuracy;Prediction model;Wind power generation;Ramp;Power Ramp Rate(PRR)
DO -
UR -
ER -
황미영, 김성호, Unil Yun, KwangDeuk Kim and 류근호. (2012). Building of Prediction Model of Wind Power Generationusing Power Ramp Rate. Journal of The Korea Society of Computer and Information, 17(1), 212-218.
황미영, 김성호, Unil Yun, KwangDeuk Kim and 류근호. 2012, "Building of Prediction Model of Wind Power Generationusing Power Ramp Rate", Journal of The Korea Society of Computer and Information, vol.17, no.1 pp.212-218.
황미영, 김성호, Unil Yun, KwangDeuk Kim, 류근호 "Building of Prediction Model of Wind Power Generationusing Power Ramp Rate" Journal of The Korea Society of Computer and Information 17.1 pp.212-218 (2012) : 212.
황미영, 김성호, Unil Yun, KwangDeuk Kim, 류근호. Building of Prediction Model of Wind Power Generationusing Power Ramp Rate. 2012; 17(1), 212-218.
황미영, 김성호, Unil Yun, KwangDeuk Kim and 류근호. "Building of Prediction Model of Wind Power Generationusing Power Ramp Rate" Journal of The Korea Society of Computer and Information 17, no.1 (2012) : 212-218.
황미영; 김성호; Unil Yun; KwangDeuk Kim; 류근호. Building of Prediction Model of Wind Power Generationusing Power Ramp Rate. Journal of The Korea Society of Computer and Information, 17(1), 212-218.
황미영; 김성호; Unil Yun; KwangDeuk Kim; 류근호. Building of Prediction Model of Wind Power Generationusing Power Ramp Rate. Journal of The Korea Society of Computer and Information. 2012; 17(1) 212-218.
황미영, 김성호, Unil Yun, KwangDeuk Kim, 류근호. Building of Prediction Model of Wind Power Generationusing Power Ramp Rate. 2012; 17(1), 212-218.
황미영, 김성호, Unil Yun, KwangDeuk Kim and 류근호. "Building of Prediction Model of Wind Power Generationusing Power Ramp Rate" Journal of The Korea Society of Computer and Information 17, no.1 (2012) : 212-218.
