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Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology

机译：基于趋势 - 添加剂和季节乘法平滑方法的非常短期太阳能发电预测

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Stanislav Eroshenko; Alexandra Khalyasmaa; Rustam Valiev;
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1. Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology [J] . Stanislav Eroshenko, Alexandra Khalyasmaa, Rustam Valiev E3S Web of Conferences . 2018,第1期

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2. Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology [J] . Stanislav Eroshenko, Alexandra Khalyasmaa, Rustam Valiev E3S Web of Conferences . 2018,第3期

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3. Hybrid Forecasting Model for Very-Short Term Wind Power Forecasting Based on Grey Relational Analysis and Wind Speed Distribution Features [J] . Shi J., Ding Z., Lee W.-J., Smart Grid, IEEE Transactions on . 2014,第1期

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4. Very-short term forecasting of photovoltaic plants generation based on meteorological data from open sources using machine learning [C] . Alexandra Khalyasmaa, Stanislav Eroshenko, Duc Chung Tran International Conference on Smart Technologies in Computing, Electrical and Electronics . 2020

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5. Short Term Wind Power Forecast Error Analysis Using Statistical Methods --- A Study of the Reduction of the Regional Aggregated Wind Power Forecast Error by Spatial Smoothing Effects in the Maritimes. [D] . Han, Yu. 2008

机译：使用统计方法的短期风电预测误差分析---通过海上空间平滑效应减少区域性总风电预测误差的研究。
6. Intra-Minute Cloud Passing Forecasting Based on a Low Cost IoT Sensor—A Solution for Smoothing the Output Power of PV Power Plants [O] . Primož Sukič, Gorazd Štumberger 2017

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7. Neural Network Ensemble-based Solar Power Generation Short-Term Forecasting [O] . A. Chaouachi, R. M. Kamel, R. Ichikawa, 2011

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Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology

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