By Topic

Improving voltage profile in radial distribution systems using binary particle swarm optimization and probabilistic load flow

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ruiz-Rodriguez, F.J. ; Dept. Electr. Eng., Univ. of Jaen, Jaén, Spain ; Gomez-Gonzalez, M. ; Jurado, F.

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.

Published in:

Power Engineering, Energy and Electrical Drives (POWERENG), 2011 International Conference on

Date of Conference:

11-13 May 2011