American Journal of Electrical Power and Energy Systems

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Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms

Received: Apr. 16, 2020    Accepted: May 03, 2020    Published: Jun. 20, 2020
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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.

DOI 10.11648/j.epes.20200902.11
Published in American Journal of Electrical Power and Energy Systems ( Volume 9, Issue 2, March 2020 )
Page(s) 26-40
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

GED, SVC, NSGA II, Optimun Position, Optimal Size

References
[1] Abhilipsa Rath, Sriparna Roy Ghatak, Parag Goyal, “Optimal allocation of Distributed Generation (DGs) and static VAR compensator (SVC) in a power system using Revamp Voltage Stability Indicator”, In 2016 National Power Systems Conference (NPSC), pages 1–6, Bhubaneswar, India, December 2016. IEEE.
[2] Duong Quoc Hung, N. Mithulananthan, Kwang Y. Lee, “Optimal placement of dispatchable and nondispatchable renewable DG units in distribution networks for minimizing energy loss”, Electrical Power and Energy Systems 55 (2014) 179–186.
[3] Srinivas Nagaballi, Vijay S. Kale, «Application of Metaheuristic Algorithms for Optimal Allocation of DGs in Radial Distribution System», International Journal of Engineering Research in Computer Science and Engineering (IJERCSE), Vol 5, Issue 2, February 2018.
[4] P. Dinakara Prasasd Reddy, V. C. Veera Reddy, T. Gowri Manohar, “Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems”, Journal of Electrical Systems and Information Technology (2017).
[5] Athira Jayavarma, Tibin Joseph, Sasidharan Sreendharan, «Optimal Placement of Fuel Cell DG and Solar PV in Distribution System using Particle Swarm Optimization», IJSER, Volume 4, Issue 9, September – 2013.
[6] Ebrahim Farjah, Mosayeb Bornapour, Taher Niknam, Bahman Bahmanifirouzi, «Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network», Energies 2012, 5, 790-814.
[7] Minh Quan Duong, Thai Dinh Pham, Thang Trung Nguyen, Anh Tuan Doan, Hai Van Tran, «Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems», Energies 2019, 12, 174.
[8] Majid Aryanezhad, Elahe Ostadaghaee, Mahmood Joorabian, «Optimal Allocation and sizing of FACTS Devices Based Non-dominated Sorting Genetic Algorithm II», The 1st Iran Energy Association National Conference - 2013 Tehran, No. 13-EN-EPP-1242.
[9] Walaa Ahmed, Ali Selim, Salah Kamel, Juan Yu, Francisco Jurado, «Probabilistic Load Flow Solution Considering Optimal Allocation of SVC in Radial Distribution System», International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 5, No. 3.
[10] Mohamad Khairuzzaman Mohamad Zamani, Ismail Musirin, and Saiful Izwan Suliman, «Symbiotic Organisms Search Technique for SVC Installation in Voltage Control», Indonesian Journal of Electrical Engineering and Computer Science, 6 (2): 318, May 2017.
[11] Thishya Varshitha U., Balamurugan K., «Optimal placement of distibuted generation with SVC for power loss reduction in distributed system», ARPN Journal of Engineering and Applied Sciences, Vol. 1, No. 17, September 2017.
[12] A. Rath, S Roy Ghatak, «Technical and Economic Assessment of Power System by Incorporating Distributed Generation and Static VAR Compensator», Smart Grid, 3 (1): 6, 2016.
[13] Ali Ehsan, Qiang Yang, “Coordinated Investment Planning of Distributed Multi-Type Stochastic Generation and Battery Storage in Active Distribution Networks”, Transactions on Sustainable Energy, 2018 IEEE.
[14] Carlos D. Rodríguez-Gallegos, Dazhi Yang, Oktoviano Gandhi, Monika Bieri, Thomas Reindl, S. K. Panda, «A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators: An Indonesian case study», Energy 160 (2018) 410-429.
[15] A. OLOULADE, A. MOUKENGUE IMANO, A. VIANOU, R. BADAROU, «Contribution à l'étude de la répartition de puissance et à l'évaluation des pertes dans les réseaux de transport et de distribution de la communauté électrique du Bénin et de la société béninoise d'énergie électrique (CEB-SBEE)», Sciences, Technologies et Développement, Edition spéciale, pp 8è-90, Juillet 2016.
[16] Kabir A. MA, Abubakar A. S., Abdulrahman O., Salisu S., «A Matlab Based Backward-forward Sweep Algoritm for Radial Distribution Network Power Flow Analysis», IJSEI vol. 4, issue 46, November 2015.
[17] Nangboguina Madjissembay, Christopher M. Muriithi, C. W. Wekesa, «Load Flow Analysis for Radial Distribution Networks Using Backward/Forward Sweep Method», Open Access Journal, JSRE, Vol. 3 (3) 2016, 82-87.
[18] Thang VU, «Répartition des moyens complémentaires de production et de stockage dans les réseaux faiblement interconnectés ou isolés», U. Grenoble, Thèse, Février 2011
[19] R. RANJAN & D. DAS (2003): «Voltage Stability Analysis of Radial Distribution Networks», Electric Power Components and Systems, 31: 5, 501-511.
[20] Gundugallu Peddanna, Y. Siva Rama Kishore, «Power Loss Allocation of Balanced Radial Distribution Systems», IJSR, Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438.
[21] Herman Amour Vidjinnangni TAMADAHO, «Optimisation du positionnement d’un D-STATCOM dans un réseau radial de distribution pour l’amélioration des performances techniques du réseau HTA de Togba de la commune d’Abomey-Calavi», p. 113, UAC-EPAC, 2016-2017.
[22] Adrien BIO YATOKPA, Sakariyou MAHMAN, Koffi ABBLE, «Identification et catographie des potentialités et sources d'énergies renouvelables assorties des possibilités d'exploitation», PNUD, Juillet 2010.
[23] Barrios-Martinez E., Angeles-Camacho C., «Technical comparaison of FACTS controllers in parallel connection», Jornal of Applied Research and Technology (2017).
[24] Reza SIRJANI, Azak MOHAMED, Hussain SHAREEF, «Optimal placement and sizing of Static Var Compensator in power systems using Improved Harmony Search Algorithm», University Kebangsaan Malaysia (UKM).
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    Arouna Oloulade, Adolphe Moukengue Imano, François-Xavier Fifatin, Mahamoud Tanimomon, Akouèmaho Richard Dansou, et al. (2020). 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, 9(2), 26-40. https://doi.org/10.11648/j.epes.20200902.11

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    Arouna Oloulade; Adolphe Moukengue Imano; François-Xavier Fifatin; Mahamoud Tanimomon; Akouèmaho Richard Dansou, et al. Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms. Am. J. Electr. Power Energy Syst. 2020, 9(2), 26-40. doi: 10.11648/j.epes.20200902.11

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    AMA Style

    Arouna Oloulade, Adolphe Moukengue Imano, François-Xavier Fifatin, Mahamoud Tanimomon, Akouèmaho Richard Dansou, et al. Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms. Am J Electr Power Energy Syst. 2020;9(2):26-40. doi: 10.11648/j.epes.20200902.11

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  • @article{10.11648/j.epes.20200902.11,
      author = {Arouna Oloulade and Adolphe Moukengue Imano and François-Xavier Fifatin and Mahamoud Tanimomon and Akouèmaho Richard Dansou and Ramanou Badarou and Antoine Vianou},
      title = {Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms},
      journal = {American Journal of Electrical Power and Energy Systems},
      volume = {9},
      number = {2},
      pages = {26-40},
      doi = {10.11648/j.epes.20200902.11},
      url = {https://doi.org/10.11648/j.epes.20200902.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.epes.20200902.11},
      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.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Contribution to the Economic and Optimal Planning of Multi-GED and a FACTS in a Distribution Network by Genetics Algorithms
    AU  - Arouna Oloulade
    AU  - Adolphe Moukengue Imano
    AU  - François-Xavier Fifatin
    AU  - Mahamoud Tanimomon
    AU  - Akouèmaho Richard Dansou
    AU  - Ramanou Badarou
    AU  - Antoine Vianou
    Y1  - 2020/06/20
    PY  - 2020
    N1  - https://doi.org/10.11648/j.epes.20200902.11
    DO  - 10.11648/j.epes.20200902.11
    T2  - American Journal of Electrical Power and Energy Systems
    JF  - American Journal of Electrical Power and Energy Systems
    JO  - American Journal of Electrical Power and Energy Systems
    SP  - 26
    EP  - 40
    PB  - Science Publishing Group
    SN  - 2326-9200
    UR  - https://doi.org/10.11648/j.epes.20200902.11
    AB  - 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.
    VL  - 9
    IS  - 2
    ER  - 

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Author Information
  • Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin

  • Electronic, Electrotechnic, Automatic, Telecommunications Laboratory (LEEAT), University of Douala, Douala, Cameroon

  • Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin

  • Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin

  • Polytechnic School of Abomey-Calavi (EPAC), University of Abomey-Calavi, Abomey-Calavi, Benin

  • Laboratory of Thermophysic Characterization of Materials and Energy Mastering, University of Abomey-Calavi, Abomey-Calavi, Benin

  • Section