Volume 9, Issue 2, March 2020, Page: 26-40
Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms
Arouna Oloulade, Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin
Adolphe Moukengue Imano, Electronic, Electrotechnic, Automatic, Telecommunications Laboratory (LEEAT), University of Douala, Douala, Cameroon
François-Xavier Fifatin, Polytechnic School of Abomey-Calavi (EPAC), University of Abomey-Calavi, Abomey-Calavi, Benin
Mahamoud Tanimomon, Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin
Akouèmaho Richard Dansou, Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin
Ramanou Badarou, Polytechnic School of Abomey-Calavi (EPAC), University of Abomey-Calavi, Abomey-Calavi, Benin
Antoine Vianou, Laboratory of Thermophysic Characterization of Materials and Energy Mastering, University of Abomey-Calavi, Abomey-Calavi, Benin
Received: Apr. 16, 2020;       Accepted: May 3, 2020;       Published: Jun. 20, 2020
DOI: 10.11648/j.epes.20200902.11      View  46      Downloads  39
Abstract
The distribution networks are more and more heavily loaded due to economic growth, industrial development and housing. The operation of these networks under these conditions generates voltage instabilities and excessive power losses. The present work consisted in the optimal integration of multi-GED (Decentralized Energy Generators) (Photovoltaic (PV), Fuel Cell (FC or PAC) and Wind Generator (WG)) and FACTS (SVC) in a Medium Voltage distribution’s departure of the Beninese Electrical Energy Company (SBEE), with a view to improve its technical performances. The diagnostic study of the Ouidah 122-nodes test network, before optimization, revealed that the active and reactive losses are 457.34588 kW and 625.41503 kVAr respectively. This network has high voltage instability with a minimum voltage of 0.80455 p.u. and a minimum VSI of 0.41897 p.u. The optimization of the size and positioning of GED and FACTS was based on the Non-dominated Sorting Genetic Algoritm II (NSGA II). After optimization with the NSGA II, a comparative study of the different combinations between the three GEDs and the SVC, made it possible to choose that of the placement of a 121 kW Wind Generator at node 75, a PV of 131 kW at node 51, a system of Fuel Cell (FC, PAC in french) of 700 kW at node 34, and an SVC of 2.126 MVAr at node 94 of the network. This positioning enabled a reduction of 65.11% in active losses and 65.12% in reactive losses. The voltage profile and the voltage stability are clearly improved, with a minimum voltage of 0.96993 p.u. and a minimum VSI of 0.88505 p.u. The initial investment for this project is seven hundred and seven million three hundred and fifty-two thousand three hundred and fifty-eight point seven CFA francs (707,352,358.7 CFA francs). The technical and economic evaluation shows that the payback period is approximately 4 years 6 months and 14 days. The relevant results obtained show that the method used is efficient and effective, and can be applied to other MV departures of the SBEE.
Keywords
GED, SVC, NSGA II, Optimun Position, Optimal Size
To cite this article
Arouna Oloulade, Adolphe Moukengue Imano, François-Xavier Fifatin, Mahamoud Tanimomon, Akouèmaho Richard Dansou, Ramanou Badarou, Antoine Vianou, Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms, American Journal of Electrical Power and Energy Systems. Vol. 9, No. 2, 2020, pp. 26-40. doi: 10.11648/j.epes.20200902.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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