23 January 2017 Short-term load forecasting study of wind power based on Elman neural network
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Proceedings Volume 10322, Seventh International Conference on Electronics and Information Engineering; 103223Q (2017) https://doi.org/10.1117/12.2265228
Event: Seventh International Conference on Electronics and Information Engineering, 2016, Nanjing, China
Abstract
Since wind power has intermittent, irregular and volatility nature, improving load forecasting accuracy of wind power has significant influence on controlling wind system and guarantees stable operation of power grids. This paper constructed the wind farm loading forecasting in short-term based on Elman neural network, and made a numerical example analysis. . Examples show that, using input delayed of feedback Elman neural network, can reflect the inherent laws of wind load operation better, so as to present a new idea for short-term load forecasting of wind power.
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Xinran Tian, Xinran Tian, Jing Yu, Jing Yu, Teng Long, Teng Long, Jicheng Liu, Jicheng Liu, } "Short-term load forecasting study of wind power based on Elman neural network", Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103223Q (23 January 2017); doi: 10.1117/12.2265228; https://doi.org/10.1117/12.2265228
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