DocumentCode :
3535414
Title :
Improving voltage profile in radial distribution systems using binary particle swarm optimization and probabilistic load flow
Author :
Ruiz-Rodriguez, F.J. ; Gomez-Gonzalez, M. ; Jurado, F.
Author_Institution :
Dept. Electr. Eng., Univ. of Jaen, Jaén, Spain
fYear :
2011
fDate :
11-13 May 2011
Firstpage :
1
Lastpage :
6
Abstract :
The voltage regulation is one of the main problems to be dealt in distributed generation photovoltaic systems. Loads and distributed generation production can be assumed as random variables. Results demonstrate that the suggested method can be applied for the maintaining of voltages within established limits at all load nodes of a photovoltaic grid-connected system (PVGCS). To assess the performance of photovoltaic system, this work proposes a probabilistic model that takes into account the random nature of solar irradiance and load. In this paper is presented a new method employing discrete particle swarm optimization and probabilistic radial load flow. Computer simulation reduction evidences a better performance of the new probabilistic load flow in comparison to Monte Carlo simulation. Satisfactory solutions are reached in a smaller number of iterations. Hence, convergence is quickly reached and computational cost is low enough than that demanded for Monte Carlo simulation.
Keywords :
Monte Carlo methods; convergence of numerical methods; distributed power generation; iterative methods; load flow control; particle swarm optimisation; photovoltaic power systems; power distribution control; power generation control; power grids; probability; voltage control; Monte Carlo simulation; PVGCS; binary particle swarm optimization; computer simulation reduction; discrete particle swarm optimization; distributed generation photovoltaic systems; distributed generation production; photovoltaic grid-connected system; probabilistic radial load flow; radial distribution systems; voltage profile; voltage regulation; Equations; Load flow; Load modeling; Monte Carlo methods; Particle swarm optimization; Probabilistic logic; Random variables;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering, Energy and Electrical Drives (POWERENG), 2011 International Conference on
Conference_Location :
Malaga
ISSN :
2155-5516
Print_ISBN :
978-1-4244-9845-1
Electronic_ISBN :
2155-5516
Type :
conf
DOI :
10.1109/PowerEng.2011.6036548
Filename :
6036548
Link To Document :
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