Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systems

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Lujano Rojas, JM (Author) Other; Zubi, G (Author) Other; Dufo Lopez, R (Author) Other; Bernal Agustin, JL (Author) Other; Atencio Guerra, JL (Author) Other; Catalao, JPS (Author) FEUP

Journal

Title: Journal of Computational Design and Engineering

Vol. 7

Pages: 177-194

ISSN: 2288-4300

Publisher: Oxford University Press

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

Other information

Authenticus ID: P-00S-369

DOI: 10.1093/jcde/qwaa016

Abstract (EN): This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 18