Probabilistic methodology for estimating the optimal photovoltaic capacity in distribution systems to avoid power flow reversals

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Juan M. Lujano-Rojas (Author) Other; Rodolfo Dufo-López (Author) Other; José L. Bernal-Agustín (Author) Other; José A. Domínguez-Navarro (Author) Other; João P. S. Catalão (Author) FEUP

Journal

Title: IET Renewable Power Generation

Vol. 12 No. 9

Pages: 1045-1064

ISSN: 1752-1416

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 7 Citations

Scopus - 7 Citations

INSPEC

Other information

Authenticus ID: P-00P-SVT

DOI: 10.1049/iet-rpg.2017.0777

Abstract (EN): The large-scale integration of photovoltaic generation (PVG) on distribution systems (DSs) preserving their technical constraints related to voltage fluctuations and active power (AP) flow is a challenging problem. Solar resources are accompanied by uncertainty regarding their estimation and intrinsically variable nature. This study presents a new probabilistic methodology based on quasi-static time-series analysis combined with the golden section search algorithm to integrate low and high levels of PVG into DSs to prevent AP flow in reverse direction. Based on the analysis of two illustrative case studies, it was concluded that the successful integration of PVG is not only related to the photovoltaic-cell manufacturing prices and conversion efficiency but also with the manufacturing prices of power electronic devices required for reactive power control.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20