DocumentCode :
3580996
Title :
Probabilistic optimal power flow analysis of virtual power plant containing photovoltaic generation
Author :
Zhouyang Ren ; Wei Yan ; Chong Ding ; Juan Yu ; Xia Zhao
Author_Institution :
State Key Lab. of Power Transm. Equip. & Syst. Security & New Technol., Chongqing Univ. Chongqing, Chongqing, China
fYear :
2014
Firstpage :
1
Lastpage :
5
Abstract :
Based on Monte Carlo and interior point method, this paper presents a probabilistic optimal power flow analysis method for the virtual power plant (VPP) containing photovoltaic (PV) generation, which can take into account both the randomness and correlation of PV generators´ power outputs and loads at different locations. An optimal power flow model of VPP is firstly given to minimize the operation cost of VPP. The inverse transformation method and Cholesky decomposition technique are used to simulate the correlations between PV power outputs and loads, which obey Beta and Normal distributions respectively. Finally, the modified IEEE 30-bus test system is used to demonstrate the effectiveness and application of the presented method in the probabilistic optimal power flow analysis of VPP.
Keywords :
Monte Carlo methods; inverse transforms; load flow; photovoltaic power systems; power plants; Cholesky decomposition technique; IEEE 30-bus test system; Monte Carlo method; PV power outputs; VPP operation cost; interior point method; probabilistic optimal power flow analysis; virtual power plant; virtual power plant containing photovoltaic generation; Correlation; Generators; Load flow analysis; Load modeling; Power generation; Probabilistic logic; Monte Carlo; photovoltaic generation; probabilistic optimal power flow; virtual power plant;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2014 IEEE PES Asia-Pacific
Type :
conf
DOI :
10.1109/APPEEC.2014.7066012
Filename :
7066012
Link To Document :
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