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