Design of a Short-Term Load Forecasting System for Small Hydropower in the Context of Electricity Market

2013 ◽  
Vol 330 ◽  
pp. 178-182
Author(s):  
Shou Qiang Fu ◽  
Min Xiang Huang ◽  
Fei Fei Sun

On the basis of the analysis of influencing factors on small hydropower generation load, considering the characteristics of small hydropower load, this paper presents a short-term load forecasting system for small hydropower in the context of electricity market. It is composed of the following components: information collection and processing, load forecasting, information monitoring. The system uses a method to segment and cluster the load curves, then wavelet decomposition is applied to load data, and a complex forecasting model is taken. Meanwhile, fulfill feedback control through the part of information monitoring, and extended short-term load forecasting is introduced. The system can improve the overall level of short-term load forecasting for small hydropower.

2007 ◽  
Vol 12 (7) ◽  
pp. 633-638 ◽  
Author(s):  
Changyin Sun ◽  
Jinya Song ◽  
Linfeng Li ◽  
Ping Ju

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 393 ◽  
Author(s):  
Seyedeh Fallah ◽  
Mehdi Ganjkhani ◽  
Shahaboddin Shamshirband ◽  
Kwok-wing Chau

Electricity demand forecasting has been a real challenge for power system scheduling in different levels of energy sectors. Various computational intelligence techniques and methodologies have been employed in the electricity market for short-term load forecasting, although scant evidence is available about the feasibility of these methods considering the type of data and other potential factors. This work introduces several scientific, technical rationales behind short-term load forecasting methodologies based on works of previous researchers in the energy field. Fundamental benefits and drawbacks of these methods are discussed to represent the efficiency of each approach in various circumstances. Finally, a hybrid strategy is proposed.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 203086-203096
Author(s):  
Ya Gao ◽  
Yong Fang ◽  
Huanhe Dong ◽  
Yuan Kong

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