DocumentCode :
1774256
Title :
Medium and long term load forecasting method for distribution network with high penetration DGs
Author :
Mingxin Zhao ; Wei Liu ; Jian Su ; Lijun Zhao ; Xiaojing Dong
Author_Institution :
China Electr. Power Res. Inst.(CEPRI), China
fYear :
2014
fDate :
23-26 Sept. 2014
Firstpage :
442
Lastpage :
444
Abstract :
Middle and long term load forecasting is the essential basis for planning of distribution network. With high penetration DGs (distributed generation) integrated into network, the net load demand of HV/MV network become more complicated, load forecasting encounters greater challenge than ever. Volatility and intermittency of wind and solar power has greatly influenced the load characteristics. A new middle and long term load forecasting method for distribution network with DGs is proposed in this paper, which concerns time-varying characteristic of DG output power. Firstly, we get the conventional spatial load forecasting results. Then, we get yearly time-varying curves of DG output using Monte Carlo simulation. Lastly, superposing time-varying curves of conventional load and DGs, we can get the net-load forecasting result for distribution network, which is more accurate than ever.
Keywords :
Monte Carlo methods; load forecasting; power distribution planning; solar power; wind power; DG output power time-varying characteristic; Monte Carlo simulation; distribution network; high penetration DG; high penetration distributed generation; load characteristics; long term load forecasting method; medium term load forecasting method; net load demand; solar power intermittency; solar power volatility; spatial load forecasting results; wind power intermittency; wind power volatility; Abstracts; Biographies; Cities and towns; Economics; Load forecasting; Distributed generation; Load forecasting; Middle and long term; Superposition method; Time-varying Characteristic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electricity Distribution (CICED), 2014 China International Conference on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/CICED.2014.6991746
Filename :
6991746
Link To Document :
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