PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Barnacles mating optimizer for loss minimization of optimal reactive power dispatch

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Optymalizator Barnacles w celu minimalizacji strat optymalnej dystrybucji mocy biernej
Języki publikacji
EN
Abstrakty
EN
A recent evolutionary optimization algorithm, Barnacles Mating Optimizer (BMO) algorithm is proposed to solve one of the optimal reactive power dispatch (ORPD) problems viz. loss minimization in power system. The concept of Hardy-Weinberg principle and sperm-cast process of barnacles is adopted in BMO to balance the exploitation and exploration in solving the optimization problem. Optimal reactive power dispatch (ORPD) on the other hand is one of the complex optimization problems in power system operation. BMO is utilized to obtain the optimal combination of control variables such as generator voltages, transformer tap setting and injected MVAR or known as reactive compensation devices to achieve the minimum losses in the power system. To show the effectiveness of proposed BMO, it is tested on IEEE-30 bus system which consists of 25 control variables and also has been tested on the large system of power network viz. IEEE-118 bus system. The obtained results from BMO are compared with other well-known optimization algorithms in the literature. The obtained comparison results indicate that proposed BMO is effective to reach minimum loss for ORPD problem.
PL
Zaproponowano najnowszy ewolucyjny algorytm optymalizacji, algorytm Barnacles Mating Optimizer (BMO), aby rozwiązać jeden z problemów z optymalnym rozprowadzaniem mocy biernej (ORPD), a mianowicie. minimalizacja strat w systemie elektroenergetycznym. Koncepcja zasady Hardy'ego-Weinberga i procesu odlewania nasienia pąkli została przyjęta w BMO w celu zrównoważenia eksploatacji i eksploracji w rozwiązaniu problemu optymalizacji. Natomiast optymalne dysponowanie mocą bierną (ORPD) jest jednym ze złożonych problemów optymalizacji pracy systemu elektroenergetycznego. BMO służy do uzyskania optymalnej kombinacji zmiennych sterujących, takich jak napięcia generatora, ustawienie zaczepów transformatora i wstrzykiwany MVAR lub znane jako urządzenia kompensacji reaktywnej, w celu osiągnięcia minimalnych strat w systemie elektroenergetycznym. Aby pokazać skuteczność proponowanego BMO, został przetestowany na systemie magistrali IEEE-30, który składa się z 25 zmiennych sterujących, a także został przetestowany na dużym systemie sieci energetycznej, a mianowicie. System magistrali IEEE118. Otrzymane wyniki z BMO są porównywane z innymi znanymi algorytmami optymalizacyjnymi w literaturze. Uzyskane wyniki porównawcze wskazują, że proponowane BMO jest skuteczne w osiąganiu minimalnych strat związanych z problemem ORPD.
Rocznik
Strony
59--63
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
  • Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang 26600 Pekan Pahang, Malaysia
  • Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang 26600 Pekan Pahang, Malaysia
  • Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang 26600 Pekan Pahang, Malaysia
  • Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang 26600 Pekan Pahang, Malaysia
Bibliografia
  • [1]. P. Subbaraj and P. N. Rajnarayanan, "Optimal reactive power dispatch using self-adaptive real coded genetic algorithm," Electric Power Systems Research, vol. 79, no. 2, pp. 374-381, 2009/02/01/ 2009.
  • [2]. Q. H. Wu, Y. J. Cao, and J. Y. Wen, "Optimal reactive power dispatch using an adaptive genetic algorithm," International Journal of Electrical Power & Energy Systems, vol. 20, no. 8, pp. 563-569, 1998/11/01/ 1998.
  • [3]. Q. H. Wu and J. T. Ma, "Power system optimal reactive power dispatch using evolutionary programming," IEEE Transactions on Power Systems, vol. 10, no. 3, pp. 1243-1249, 1995.
  • [4]. M. Varadarajan and K. S. Swarup, "Differential evolutionary algorithm for optimal reactive power dispatch," International Journal of Electrical Power & Energy Systems, vol. 30, no. 8, pp. 435-441, 2008/10/01/ 2008.
  • [5]. B. Zhao, C. X. Guo, and Y. J. Cao, "A multiagent-based particle swarm optimization approach for optimal reactive power dispatch," IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1070-1078, 2005.
  • [6]. J. Polprasert, W. Ongsakul, and V. N. Dieu, "Optimal Reactive Power Dispatch Using Improved Pseudo-gradient Search Particle Swarm Optimization," Electric Power Components and Systems, vol. 44, no. 5, pp. 518-532, 2016/03/15 2016.
  • [7]. M. H. Sulaiman, Z. Mustaffa, M. R. Mohamed, and O. Aliman, "Using the gray wolf optimizer for solving optimal reactive power dispatch problem," Applied Soft Computing, vol. 32, no. 0, pp. 286-292, 2015.
  • [8]. K. b. o. Medani, S. Sayah, and A. Bekrar, "Whale optimization algorithm based optimal reactive power dispatch: A case study of the Algerian power system," Electric Power Systems Research, vol. 163, pp. 696-705, 2018/10/01/ 2018.
  • [9]. R. Ng Shin Mei, M. H. Sulaiman, Z. Mustaffa, and H. Daniyal, "Optimal reactive power dispatch solution by loss minimization using moth-flame optimization technique," Applied Soft Computing, vol. 59, pp. 210-222, 2017/10/01/ 2017.
  • [10]. A. H. Khazali and M. Kalantar, "Optimal reactive power dispatch based on harmony search algorithm," International Journal of Electrical Power & Energy Systems, vol. 33, no. 3, pp. 684-692, 2011/03/01/ 2011.
  • [11]. G. Chen, L. Liu, Z. Zhang, and S. Huang, "Optimal reactive power dispatch by improved GSA-based algorithm with the novel strategies to handle constraints," Applied Soft Computing, vol. 50, pp. 58-70, 1// 2017.
  • [12]. Yalçın E, Taplamacıoğlu MC, and Ç. "The Adaptive Chaotic Symbiotic Organisms SearchAlgorithm Proposal for Optimal Reactive Power Dispatch Problem in PowerSystems," Electrica, vol. 19, no. 1, pp. 37-47, 2019.
  • [13]. H. Buch and I. N. Trivedi, "On the efficiency of metaheuristics for solving the optimal power flow," Neural Computing and Applications, vol. 31, no. 9, pp. 5609-5627, 2019/09/01 2019.
  • [14]. M. S. Saddique et al., "Solution to optimal reactive power dispatch in transmission system using meta-heuristic techniques―Status and technological review," Electric Power Systems Research, vol. 178, p. 106031, 2020/01/01/ 2020.
  • [15]. M. H. Sulaiman, Z. Mustaffa, M. M. Saari, and H. Daniyal, "Barnacles Mating Optimizer: A new bio-inspired algorithm for solving engineering optimization problems," Engineering Applications of Artificial Intelligence, vol. 87, p. 103330, 2020/01/01/ 2020.
  • [16]. M. H. Sulaiman et al., "Barnacles Mating Optimizer: A Bio- Inspired Algorithm for Solving Optimization Problems," in 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 27-29 June 2018, pp. 265-270, doi: 10.1109/SNPD.2018.8441097.
  • [17]. J. F. Crow, "Hardy, Weinberg and language impediments," (in eng), Genetics, vol. 152, no. 3, pp. 821-825, 1999.
  • [18]. M. H. Sulaiman, Z. Mustaffa, and M.-M. Saari, "Using the Barnacles Mating Optimizer for Economic Emission Load Dispatch Problems," Przegląd Elektrotechniczny, vol. 07/2020, pp. 141-144, 2020.
  • [19]. R. D. Zimmerman, C. E. Murillo-Sánchez, and R. J. Thomas, "MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education," IEEE Transactions on Power Systems, vol. 26, no. 1, pp. 12- 19, 2011.
  • [20]. K. Ayan and U. Kılıç, "Artificial bee colony algorithm solution for optimal reactive power flow," Applied Soft Computing, vol. 12, no. 5, pp. 1477-1482, 2012/05/01/ 2012.
  • [21]. A. Ghasemi, K. Valipour, and A. Tohidi, "Multi objective optimal reactive power dispatch using a new multi objective strategy," International Journal of Electrical Power & Energy Systems, vol. 57, pp. 318-334, 2014/05/01/ 2014.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e386d3e8-bf20-40ad-94a3-3ac4e2ce5a4f
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.