Probabilistic load flow procedure for assessing the distributed generation impact on the high voltage network

2011 ◽  
Author(s):  
F. Careri ◽  
C. Genesi ◽  
P. Marannino ◽  
M. Montagna ◽  
S. Rossi ◽  
...  
Keyword(s):  
Distributed Generation ◽  
High Voltage ◽  
Load Flow ◽  
Probabilistic Load Flow ◽  
Probabilistic Load

Distributed Network Power Flow of Distributed Generation

2012 ◽  
Vol 614-615 ◽  
pp. 1693-1699
Author(s):  
Qi Yang ◽  
Meng Cong Liu ◽  
Ying Chen ◽  
Yun Xiao Bai
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Flow ◽  
Simulation Method ◽  
Energy System ◽  
Load Flow ◽  
Probabilistic Load Flow ◽  
Probabilistic Load ◽  
Node Voltage ◽  
The Impact

With constrains imposed by natural conditions, the power generated from wind power, solar power and other intermittent energy system has great randomness and volatility. Thus, the impact from the intermittent energy to the system voltage and power flow is uncertainty. In view of this problem, this paper studies the characteristics of these double random variables and correlation. By using the typical probabilistic load flow and Monte Carlo simulation method, this paper poses the probability load flow adapted to the intermittent distributed generation. Finally, taking IEEE33 distribution system for example, this paper obtains the mutual relationship between the power from the intermittent distributed generation and the probability distribution of the node voltage, current distribution of each branch.

scholarly journals Probabilistic Load Flow Method Based on Modified Latin Hypercube-Important Sampling

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3171 ◽  
Author(s):  
Quan Li ◽  
Xin Wang ◽  
Shuaiang Rong
Keyword(s):  
Distributed Generation ◽  
Large Scale ◽  
Sampling Method ◽  
Latin Hypercube Sampling ◽  
Load Flow ◽  
Power Grids ◽  
Latin Hypercube ◽  
Importance Sampling Method ◽  
Probabilistic Load Flow ◽  
Probabilistic Load

The growing amount of distributed generation has brought great uncertainty to power grids. Traditional probabilistic load flow (PLF) algorithms, such as the Monte-Carlo method (MCM), can no longer meet the needs of efficiency and accuracy in large-scale power grids. Latin Hypercube Sampling (LHS) develops a sampling efficiency and solves the correlation problem of distributed generation (DG) access nodes for accuracy analyses. In this paper, a modified Latin Hypercube-Important Sampling method is proposed for higher efficiency and precision by using the importance sampling method before LHS and the Cholesky decomposition method in correlation calculations. The simulation results are presented using a modified IEEE 30-bus system and are compared with traditional MCM and LHS.

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