Biogeography-based optimization for voltage stability improvement and reactive reserve management

This paper proposes a biogeography-based optimization algorithm to enhance the voltage stability of a power system. It computes the optimal quantity of reactive power support with a view to place the static VAR compensator at the most appropriate nodes. The scheme inflicts an effective management of VAR resources in the process of improving the voltage profile and reducing the network losses. It includes the results of IEEE 30-node system to illustrate the feasibility of the approach.

Biogeography-based optimization for voltage stability improvement and reactive reserve management

This paper proposes a biogeography-based optimization algorithm to enhance the voltage stability of a power system. It computes the optimal quantity of reactive power support with a view to place the static VAR compensator at the most appropriate nodes. The scheme inflicts an effective management of VAR resources in the process of improving the voltage profile and reducing the network losses. It includes the results of IEEE 30-node system to illustrate the feasibility of the approach.

___

  • C.W. Taylor, Power System Voltage Stability, New York, McGraw-Hill, 1994.
  • A.K. Sinha, D. Hazarika, “A comparative study of voltage stability indices in a power system”, Electrical Power and Energy Systems, Vol. 22, pp. 589–596, 2000.
  • B. Singh, N.K. Sharma, A.N. Tiwari, “Prevention of voltage instability by using FACTS controllers in power systems: a literature survey”, International Journal of Engineering Science and Technology, Vol. 2, pp. 980–992, 20 J. Zhu, K. Cheung, D. Hwang, A. Sadjadpour, “Operation strategy for improving voltage profile and reducing system loss”, IEEE Transactions on Power Delivery, Vol. 25, pp. 390–397, 2010.
  • M. Tripathy, S. Mishra, “Bacteria foraging-based solution to optimize both real power loss and voltage stability limit”, IEEE Transactions on Power Systems, Vol. 22, pp. 240–248, 2007.
  • S.H. Song, J.U. Lim, S.I. Moon, “FACTS operation scheme for enhancement of power system security”, Bologna Power Tech Conference, Vol. 3, pp. 36–41, 2003.
  • P.S. Venkataramu, T. Ananthapadmanabha, “Installation of unified power flow controller for voltage stability margin enhancement under line outage contingencies”, Iranian Journal of Electrical and Computer Engineering, Vol. 5, pp. 90–96, 2006.
  • A. Subramanian, G. Ravi, “Voltage collapse enhancement and loss reduction by reactive power reserve”, International Journal of Computer Applications, Vol. 12, pp. 32–42, 2011.
  • H. Liu, J. Peng, “Research of a new reactive power optimization method consider of the voltage optimization of the whole electric network”, Power and Energy Engineering Conference, pp. 1–4, 2009.
  • H. Yoshida, K. Kawata, Y. Fukuyama, S. Takayama, Y. Nakanishi, “A particle swarm optimization for reactive power and voltage control considering voltage security assessment”, IEEE Transactions on Power Systems, Vol. 15, pp. 1232–1239, 2000.
  • J. Lin, X. Wang, W. Zheng, “Reactive power optimization based on adaptive immune algorithm”, Proceedings of the International Multi Conference of Engineers and Computer Scientists, pp. 19–21, 2008.
  • D. Simon, “Biogeography-based optimization”, IEEE Transactions on Evolutionary Computation, Vol. 12, pp. 702–713, 2008.
  • A. Bhattachary, P.K. Chattopadhyay, “Solution of optimal reactive power flow using biogeography-based optimization”, International Journal of Energy and Power Engineering, Vol. 3, pp. 269–277, 2010.
  • A. Bhattacharya, P.K. Chattopadhyay, “Biogeography-based optimization for different economic load dispatch problems”, IEEE Transactions on Power Systems, Vol. 25, pp. 1064–1077, 2010.
  • R. Rarick, D. Simon, F.E. Villaseca, B. Vyakaranam, “Biogeography-based optimization and the solution of the power flow problem”, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 1029–1034, 2009.
  • G.W. Stagg, A.H. El-Abiad, Computer Methods in Power System Analysis, New York, McGraw-Hill, 1968. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Singapore, Pearson Education, 2000.
  • J. Kennedy, R.C. Eberhart, “Particle swarm optimization”, Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948, 1995.
Turkish Journal of Electrical Engineering and Computer Science-Cover
  • ISSN: 1300-0632
  • Yayın Aralığı: Yılda 6 Sayı
  • Yayıncı: TÜBİTAK
Sayıdaki Diğer Makaleler

Role of energy management in hybrid renewable energy systems: case study-based analysis considering varying seasonal conditions

Recep YUMURTACI

Multiobjective differential evolution-based performance optimization for switched reluctance motor drives

Hédi YAHIA, Noureddine LIOUANE, Rachid DHIFAOUI

Actor-critic-based ink drop spread as an intelligent controller

Hesam SAGHA, İman Esmaili Paeen AFRAKOTI, Saeed BAGHERISHOURAKI

Simulation of a large electric distribution system having intensive harmonics in the industrial zone of Konya

Hasan EROĞLU, Musa AYDIN

Capability-based task allocation in emergency-response environments: a coalition-formation approach

Afsaneh FATEMI, Kamran ZAMANIFAR, Naser NEMATBAKHSH

A new multiobjective optimal allocation of multitype FACTS devices for total transfer capability enhancement and improving line congestion using the harmony search algorithm

Abbas ESMAEILI, Saeid ESMAEILI

An automated prognosis system for estrogen hormone status assessment in breast cancer tissue samples

Fatih SARIKOÇ, Adem KALINLI, Hülya AKGÜN, Figen ÖZTÜRK

OPF-based reactive power planning and voltage stability limit improvement under single line outage contingency condition through evolutionary algorithms

Sakthivel PADAIYATCHI, Mary DANIEL

A real-time extraction of active and reactive current using microcontrollers for a multipulse STATCOM

Mehmet Ali ANADOL, Musa AYDIN, Tankut YALÇINÖZ

A blind digital signature scheme using elliptic curve digital signature algorithm

İsmail BÜTÜN, Mehmet DEMİRER