Statistical evaluation of lightning-related failures for the optimal location of surge arresters on the power networks

Direct lightning strokes cause unscheduled supply interruptions in power systems because of a failure of the insulation. Metal oxide surge arresters, as a proper protective device, have been widely adopted in power systems to reduce lightning initiated flashovers and, hence, increase the power quality and reliability of the systems. Based on a genetic algorithm approach, a cost effective solution is described to find the optimum location of surge arresters on a power network in order to minimise the global risk of the network, and to improve its reliability. A statistical approach to evaluate lightning failures has been introduced and an optimisation procedure developed to analyse the network in order to satisfy the power utility requirement for a specific value of risk and/or line performance with a minimum set of arresters, that is, at minimum cost. Not only the insulation flashover but also the failure of the arrester can affect the reliability of power systems. Therefore, both the failure of the insulation and that of the arrester are considered in the proposed method.

[1]  J.A. Martinez,et al.  Lightning performance analysis of overhead transmission lines using the EMTP , 2005, IEEE Transactions on Power Delivery.

[2]  George J. Anders,et al.  Probability Concepts in Electric Power Systems , 1990 .

[3]  Pritindra Chowdhuri Electromagnetic transients in power systems , 1996 .

[4]  P. Chowdhuri,et al.  Parameters of lightning strokes: a review , 2005, IEEE Transactions on Power Delivery.

[5]  A. Ametani,et al.  A method of a lightning surge analysis recommended in Japan using EMTP , 2005, IEEE Transactions on Power Delivery.

[6]  Lance D. Chambers The Practical Handbook of Genetic Algorithms: Applications, Second Edition , 2000 .

[7]  A. S. Morched,et al.  Transmission line arrester energy, cost, and risk of failure analysis for partially shielded transmission lines , 2000 .

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  Akira Asakawa,et al.  Energy absorption of surge arresters on power distribution lines due to direct lightning strokes-effects of an overhead ground wire and installation position of surge arresters , 1997 .

[10]  A.L. Orille-Fernandez,et al.  Optimization of surge arrester's location , 2004, IEEE Transactions on Power Delivery.

[11]  M. S. Savic,et al.  Technical and economical optimisation of overhead power distribution line lightning protection , 1998 .

[12]  Roy Billinton,et al.  Reliability evaluation of engineering systems : concepts and techniques , 1992 .

[13]  Masaru Ishii,et al.  Multistory transmission tower model for lightning surge analysis , 1991 .

[14]  H. Elahi,et al.  Modeling guidelines for fast front transients , 1996 .

[15]  Fridolin Heidler,et al.  Calculation of lightning current parameters , 1999 .

[16]  A. Greenwood,et al.  Electrical transients in power systems , 1971 .

[17]  S. Visacro,et al.  Novel approach for determining spots of critical lightning performance along transmission lines , 2005, IEEE Transactions on Power Delivery.

[18]  I. M. Dudurych,et al.  EMTP analysis of the lightning performance of a HV transmission line , 2003 .

[19]  Ramesh C. Bansal,et al.  International Journal of Emerging Electric Power Systems Optimization Methods for Electric Power Systems : An Overview , 2011 .

[20]  J.A. Martinez,et al.  Statistical evaluation of lightning overvoltages on overhead distribution lines using neural networks , 2005, IEEE Transactions on Power Delivery.