Result: Two-stage distributed generation optimal sizing with clustering-based node selection

Title:
Two-stage distributed generation optimal sizing with clustering-based node selection
Authors:
ROTARU, Florina, CHICCO, Gianfranco, GRIGORAS, Gheorghe, CARTINA, Gheorghe
Source:
Electrical power & energy systems. 40(1):120-129
Publisher Information:
Oxford: Elsevier, 2012.
Publication Year:
2012
Physical Description:
print, 54 ref
Original Material:
INIST-CNRS
Subject Terms:
Electrical engineering, Electrotechnique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Electrotechnique. Electroenergetique, Electrical engineering. Electrical power engineering, Electroénergétique, Electrical power engineering, Réseaux et lignes électriques, Power networks and lines, Divers, Miscellaneous, Centrales électriques, Electric power plants, Classification automatique, Automatic classification, Clasificación automática, Condition opératoire, Operating conditions, Condición operatoria, Dimensionnement, Dimensioning, Dimensionamiento, Dépendance du temps, Time dependence, Dependencia del tiempo, Evaluation performance, Performance evaluation, Evaluación prestación, Facteur efficacité, Effectiveness factor, Factor de eficacia, Fonction objectif, Objective function, Función objetivo, Indice affaiblissement, Loss factor, Indice debilitamiento, Méthode combinatoire, Combinatorial method, Método combinatorio, Méthode section divisée, Multistage method, Perte énergie, Energy loss, Pérdida energía, Production énergie répartie, Distributed power generation, Production énergie électrique, Electric power production, Producción energía eléctrica, Réseau distribution, Distribution network, Red distribución, Réseau électrique, Electrical network, Red eléctrica, Sensibilité, Sensitivity, Sensibilidad, Solution optimale, Optimal solution, Solución óptima, Clustering, Distributed generation, Energy losses, Optimal sizing, Voltage profile
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
The Gheorghe Asachi Technical University of lasi, Faculty of Electrical Engineering, Bd. Profesor Dimitrie Mangeron, nr. 21-23, 700050 lasi, Romania
Politecnico di Torino, Dipartimento di Ingegneria Elettrica, corso Duca degli Abruzzi 24, 10129 Torino, Italy
ISSN:
0142-0615
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=25872199
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Electrical engineering. Electroenergetics
Accession Number:
edscal.25872199
Database:
PASCAL Archive

Further Information

Nowadays, distributed generation (DG) is playing a significant role in the electrical energy systems. The diffusion of DG in the electrical networks could be beneficial to improve network operation, but excessive amounts of DG in operation could cause violations of the system constraints. This paper presents a new method to obtain the optimal size of DG sources in electrical distribution systems, taking into account the time-dependent evolution of generation and load. This method adopts a procedure composed of two nested calculation stages. The external stage is carried out by selecting a set of candidate nodes through a clustering-based approach based on normalised loss sensitivity factors and normalised node voltages. The internal stage is an exhaustive search driven by the calculation of an objective function with energy losses and voltage profile components, aimed at finding upgraded DG sizes using exhaustive search on a set of available sizes at the candidate nodes. The resulting method avoids the combinatorial explosion of the solutions to be analysed and determines pseudo-optimal DG sizing without violation of any of the system constraints under any operating condition. The proposed method is tested on a 20 kV rural distribution network, showing its effectiveness in obtaining the pseudo-optimal solution with a relatively low computational burden.