Comparative analysis of the optimal siting and sizing on different solar distributed generation models through stochastic method
Issue Date
2016
Abstract
With the optimization of solar distributed generation (DG), different methods and models are implemented for system improvement. However, the stochastic nature and intermittency of solar power is often neglected. This paper presents an approach in finding the optimal site and size of a solar DG unit in the context of minimizing power loss and improving voltage profile. Uncertainties of the solar irradiance are incorporated in the solar data. Also, different models of DG are considered, namely, unity power factor model, constant lagging power factor model and variable lagging power factor model. The technique is based on genetic algorithm (GA) and stochastic load flow calculations. The algorithm is applied to an IEEE 37-bus distribution system. The results indicate that a constant lagging power factor shows significant reductions on real and reactive power losses on the system with values of 19.179% and 21.004%, respectively. Also, the voltage deviation is reduced to 0.954 p.u.
Source or Periodical Title
IEEE PES Innovative Smart Grid Technologies Conference Europe
Page
485-490
Document Type
Conference Paper
College
College of Engineering and Agro-Industrial Technology (CEAT)
Physical Description
illustrations, graphs
Language
English
Subject
Distributed generation, genetic algorithm, optimization, photovoltaic power systems, solar energy
Recommended Citation
Caasi, J.K.L., Aguirre, R.A. (2016). Comparative analysis of the optimal siting and sizing on different solar distributed generation models through stochastic method, 485-490. DOI:10.1109/ISGT-Asia.2016.7796433.
Identifier
DOI:10.1109/ISGT-Asia.2016.7796433.
Digital Copy
yes