A Study of Forecasting Precision Enhancement of Short-term Wind Power Generation by use of NN Method

Author:

Kakuta Sho1,Wu Guohong1

Affiliation:

1. Tohoku Gakuin University

Publisher

Institute of Electrical Engineers of Japan (IEE Japan)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference16 articles.

1. (1) O. Suzuki, G. Wu, and T. Minakawa: “A Regional Demand Forecast by NN Method for Distributed Autonomous Voltage and Reactive Power Control System”, IEEJ Trans. PE, Vol. 125, No. 12, pp. 1261-1269 (2005-12) (in Japanese)

2. 鈴木 修.呉 国紅.皆川 保: 「自立分散型電圧無効電力制御システム高度化を目指したNN法による地域需要予測法の開発」, 電学論B, 125, 12, pp. 1261-1269 (2005-12)

3. (2) T. Senjyu, N. Urasaki, A. Yona, and T. Funabasi: “Application of Recurrent Neural Network to Several Hours Ahead Generating Power Forecasting for Wind Power Generator”, Proc. of 2006 Annual Conference of Power and Energy Society, IEE Japan, No. 49, pp. 40-1-6 (2006) (in Japanese)

4. 千住智信.浦崎直光.関根秀臣.興那篤史.舟橋俊久: 「リカレント型ニューラルネットワークを用いた風力発電機の短時間先出力電圧予測」, 平成18年電気学会電力.エネルギー部門大会, No. 49, pp. 40-1-6 (2006)

5. (3) H. Murata, S. Tatibana, Y. Kenmoku, H. Takikawa, and T. Sakakibara: “Insolation Forecast of Next Hour Using Multiple Regression Analysis with Insolation and Atmospheric Pressure Data”, The IEEJ 2005 Annual Meeting of the Institute of Electrical Engineers of Toukai, No. 107 (2005) (in Japanese)

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1. Short-Term Wind Power Prediction for Wind Turbine via Kalman Filter Based on JIT Modeling;Electrical Engineering in Japan;2016-11-01

2. Study on output prediction system of wind power generation using complex-valued neural network with multipoint GPV data;IEEJ Transactions on Electrical and Electronic Engineering;2012-11-26

3. Application of adaptive neuro-fuzzy inference for wind power short-term forecasting;IEEJ Transactions on Electrical and Electronic Engineering;2011-09-22

4. A Wind Power Forecasting Method and Its Confidence Interval Estimation;IEEJ Transactions on Electronics, Information and Systems;2011

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