Allocation of power quality monitors by Clonal Algorithm

This paper presents the application of Clonal Algorithm technique for detection of Voltage Sags and Swells with few meters, in order to monitor short-circuit conditions occurring in the electrical network. It is considered possible conditions of symmetry. These conditions make the problem even more complicated. All the proposed method steps are described, from the construction of the antibodies, cloning, mutation of clones, maturation, to the selection of novel antibodies. The algorithm starts with a large number of monitors, and then decrease this number to find a configuration with a minimum number of monitors that ensure monitoring of all short-circuit conditions. The evaluation of the methodology performance for the 63-buses network is presented.

[1]  Felix F. Wu,et al.  Network reconfiguration in distribution systems for loss reduction and load balancing , 1989 .

[2]  P.F. Ribeiro,et al.  Transmission systems power quality monitors allocation , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[3]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[4]  Azah Mohamed,et al.  Optimal power quality monitor placement using genetic algorithm and Mallow’s Cp , 2013 .

[5]  M.H.J. Bollen,et al.  An optimal monitoring program for obtaining Voltage sag system indexes , 2006, IEEE Transactions on Power Systems.

[6]  Azah Mohamed,et al.  A New Approach for Optimal Power Quality Monitor Placement in Power System Considering System Topology , 2012 .

[7]  Azah Mohamed,et al.  A novel quantum-inspired binary gravitational search algorithm in obtaining optimal power quality monitor placement , 2012 .

[8]  Wilingthon Guerra Zvietcovich,et al.  Optimal allocation of meters for monitoring voltage sags and swells using the GRASP-VNS optimisation algorithm , 2013, 2013 IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America).

[9]  H. Shareef,et al.  Optimal power quality monitor placement in power systems based on particle swarm optimization and artificial immune system , 2011, 2011 3rd Conference on Data Mining and Optimization (DMO).

[10]  Wilsun Xu,et al.  Voltage Sag State Estimation for Power Distribution Systems , 2005, IEEE Transactions on Power Systems.

[11]  Junwei Cao,et al.  Optimization of the power quality monitor number in Smart Grid , 2014, 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[12]  Nelson Kagan,et al.  Using Genetic Algorithms and Fuzzy Programming to Monitor Voltage Sags and Swells , 2011, IEEE Intelligent Systems.

[13]  M. Kezunovic,et al.  A novel method for transmission network fault location using genetic algorithms and sparse field recordings , 2002, IEEE Power Engineering Society Summer Meeting,.

[14]  C. Ammer,et al.  Determination of the optimum measuring positions for power quality monitoring , 2004, 2004 11th International Conference on Harmonics and Quality of Power (IEEE Cat. No.04EX951).

[15]  Azah Mohamed,et al.  Optimal power quality monitor placement in power systems using an adaptive quantum-inspired binary gravitational search algorithm , 2014 .

[16]  Azah Mohamed,et al.  Nowa metoda oceny rozmieszczenia monitorów jakości energii w systemie energetycznym z uwzgle{ogonek}dnieniem jego topologii , 2012 .

[17]  M. Eldery.  A novel power quality monitoring allocation algorithm , 2006, 2006 IEEE Power Engineering Society General Meeting.