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Mesh grid power quality enhancement with synchronous distributed generation: optimal allocation planning using breeder genetic algorithm

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Warianty tytułu
PL
Poprawa jakości energii sieci kratowej dzięki synchronicznemu generowaniu rozproszonemu: optymalne planowanie alokacji przy użyciu algorytmu genetycznego
Języki publikacji
EN
Abstrakty
EN
This paper discusses optimal allocation planning of synchronous distributed generation (SDG) on mesh grid power system, using breeder genetic algorithm (BGA) method. This optimization technique was built to allocate SDG units for obtaining the smallest power losses, while all buses voltage awakens in standard value. Furthermore, the proposed method was tested on IEEE 30 bus test system, and the optimal solution was reached for three SDG unit installation on 27.73 MW + j1.502 MVAr total power, with 22.46% power losses reduction.
PL
W artykule omówiono optymalne planowanie alokacji synchronicznej generacji rozproszonej (SDG) w systemie elektroenergetycznym sieci kratowej z wykorzystaniem metody algorytmu genetycznego rozpłodnika (BGA). Ta technika optymalizacji została zbudowana w celu alokacji jednostek SDG dla uzyskania najmniejszych strat mocy, podczas gdy napięcie wszystkich magistrali zawiera się w wartości standardowej. Ponadto zaproponowana metoda została przetestowana na systemie testowym magistrali IEEE 30 i osiągnięto optymalne rozwiązanie dla instalacji trzech jednostek SDG o łącznej mocy 27,73 MW + j 1,502 MVAr, przy obniżeniu strat mocy o 22,46%.
Rocznik
Strony
82--86
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
  • Universitas Hasanuddin, Department of Electrical Engineering, Jalan Poros Malino km 6 Bontomarannu Gowa, Indonesia
  • Universitas Tadulako, Department of Electrical Engineering, Palu, Indonesia
  • Universitas Hasanuddin, Department of Electrical Engineering, Jalan Poros Malino km 6 Bontomarannu Gowa, Indonesia
  • Universitas Hasanuddin, Department of Electrical Engineering, Jalan Poros Malino km 6 Bontomarannu Gowa, Indonesia
  • Universitas Hasanuddin, Department of Electrical Engineering, Jalan Poros Malino km 6 Bontomarannu Gowa, Indonesia
Bibliografia
  • [1] Driesen J., Belmans R., Distributed Generation: Challenges and Possible Solutions, Proceeding of IEEE Power Engineering Society General Meeting, (2006), 1-8, MontrealQue, Canada.
  • [2] Pepermans G., Driesen J., Haeseldonckx D., Belmans R., D'haeseleer W., Distributed Generation: Definition, Benefits and Issues. Energy Policy, (2005), Vol. 33, Issue 6, 787-798
  • [3] Baiek M.M., Esmaio A.E., Nizam M., Anwar M., M.S. Atia M.S., Derivative Load Voltage and Particle Swarm Optimization to Determine Optimum Sizing and Placement of Shunt Capacitor in Improving Line Losses, Journal Of Mechatronics, Electrical Power, and Vehicular Technology, (2016), 67-76
  • [4] Rahman Y.A., Manjang S., Yusran., Ilham A.A, Evaluating the Effect Placement Capacitor and Distributed Photovoltaic Generation for Power System Losses Minimization in the Radial Distribution System, AIP Conference Proceedings 1941, 020027 (2018)
  • [5] Sikorski T., Power Quality in Low-Voltage Distribution Network with Distributed Generation, Przeglad Elektrotechniczny, (2015), Vol. 2015, No. 06, 32
  • [6] Yusran, Electromagnetic Field Impact on 150 kV RahaBaubau Transmission Line, IOP Conf. Ser.: Earth Environ Sci. 235 012107 (2019)
  • [7] Rao R.S., Ravindra K., Satish K., Narasimham S., Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation, IEEE Transactions on Power Systems, (2013), Vol. 28, 317-325
  • [8] Othman M., El-Khattam W., Hegazy Y.G., Abdelaziz A.Y., Optimal Placement and Sizing of Distributed Generators in Unbalanced Distribution Systems Using Supervised Big BangBig Crunch Method, IEEE Transactions on Power Systems, (2015), Vol. 30, 911-919
  • [9] Kang Q., Zhou M., An J., Wu Q., Swarm Intelligence Approaches to Optimal Power Flow Problem with Distributed Generator Failures in Power Networks, IEEE Transactions on Automation Science and Engineering, (2013), Vol. 10, 343-353
  • [10] Rahman Y.A., Manjang S., Yusran., Ilham A.A, Distributed generation’s integration planning involving growth load models by means of genetic algorithm, Archives of Electrical Engineering, (2018), Vol. 67, 667-682
  • [11] Kadir A.F.A., Mohamed A., Shareef H., Wanik M.Z.C., Ibrahim A.A., Optimal Sizing and Placement of Distributed Generation in Distribution System Considering Losses and THDv Using Gravitational Search Algorithm, Przeglad Elektrotechniczny, (2013), Vol. 2013, No. 04, 132
  • [12] El-Khattam W., Salama M.M.A., Distributed Generation Technologies, Definitions and Benefits, Electric Power Systems Research, (2004), Vol. 71,119-128
  • [13] Yusran, Ashari M., Soeprijanto A., Optimization Scheme of Distributed Generation Installation Growth Considering Network Power Quality, Journal of Theoretical and Applied Information (JATIT), (2013), Vol. 53, No.1, 30-39
  • [14] Basua A.K., Chowdhuryb S.P., Paul S., Microgrids: Energy Management by Strategic Deployment of DERs - A Comprehensive Survey, Renewable and Sustainable Energy Reviews, (2011), Vol. 15, Issue 9, 4348-4356
  • [15] Baghipour R., Hosseini S.M., Placement of DG and Capacitor for Loss Reduction, Reliability and Voltage Improvement in Distribution Networks using BPSO, International Journal of Intelligent Systems and Applications, (2012), Vol. 4, 57
  • [16] B. Bhattacharyya B., Rani S., Vais Ram I., Bharti Indradeo P., GA Based Optimal Planning of VAR Sources Using Fast Voltage Stability Index Method, Archives of Electrical Engineering, (2016), Vol. 65, 789
  • [17] Abou El-Ela A.A., S. Allam S.M., Shatla M.M., Maximal Optimal Benefits of Distributed Generation Using Genetic Algorithms, Electric Power Systems Research, (2010), Vol. 80, 869-877
  • [18] Sultana S., Roy P.K., Multi-Objective Quasi-Oppositional Teaching Learning Based Optimization for Optimal Location of Distributed Generator in Radial Distribution Systems, International Journal of Electrical Power & Energy Systems, (2014), Vol. 63, 534-545
  • [19] Mühlenbein H., Predictive Models for The Breeder Genetic Algorithm I. Continuous Parameter Optimization, Journal Evolutionary Computation, (1993), Vol. 1, Issue 1, 25-49
  • [20] Saadat H., Power System Analysis, 2nd ed, (2004), McGrawHill, Singapore
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c6c02636-c868-40f2-9948-336c44e7c91e
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