A Techno-Economic Framework for Replacing Aged XLPE Cables in the Distribution Network

In this paper, a stochastic framework is proposed for optimizing replacement strategies of aged XLPE cables in the electric power distribution network. The proposed framework facilitates realizing an economic value for the risk of unplanned outages, thereby shifting the paradigm of replacing aged XLPE cable from a technical decision that is solely based on diagnostic measurements to a techno-economic strategy. The proposed framework constitutes of three main phases: (1) obtaining a distribution for the aging process of XLPE cable due to water-trees, (2) modeling the replacement of the aged XLPE cable as a Markov decision process, and (3) applying a linear programming algorithm in order to solve for the optimal replacement policy. Based on the proposed framework, a critical health index is defined for optimum replacement, depending on the installation costs of a new cable and the unplanned outage cost.

[1]  Chengke Zhou,et al.  Review of recent research towards power cable life cycle management , 2017 .

[2]  Richard E. Brown,et al.  Electric Power Distribution Reliability , 2002 .

[3]  J. Densley,et al.  Ageing mechanisms and diagnostics for power cables - an overview , 2001 .

[4]  Oguzhan Alagöz,et al.  Optimally solving Markov decision processes with total expected discounted reward function: Linear programming revisited , 2015, Comput. Ind. Eng..

[5]  A. Bulinski,et al.  On-site diagnostics of medium-voltage underground cross-linked polyethylene cables , 2011, IEEE Electrical Insulation Magazine.

[6]  F. d'Epenoux,et al.  A Probabilistic Production and Inventory Problem , 1963 .

[7]  Theodore J. Sheskin,et al.  Markov Chains and Decision Processes for Engineers and Managers , 2010 .

[8]  Wang Fan,et al.  An approach to power transformer asset management using health index , 2009, IEEE Electrical Insulation Magazine.

[9]  G. Stone,et al.  The Application of Weibull Statistics to Insulation Aging Tests , 1979, IEEE Transactions on Electrical Insulation.

[10]  Refat Atef Ghunem,et al.  Traceability and on-site calibration of the NRC-MSS depolarization current measurements , 2016, 2016 Conference on Precision Electromagnetic Measurements (CPEM 2016).

[11]  Surachai Chaitusaney,et al.  Optimal budget allocation for preventive maintenance of distribution system considering customer outage cost and reliability indices , 2017, 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).

[12]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[13]  Muhammad Buhari,et al.  Modelling of Ageing Distribution Cable for Replacement Planning , 2016, IEEE Transactions on Power Systems.

[14]  Yasuo Suzuoki,et al.  Economic evaluation of cable replacement considering annual failure probability , 2002, Conference Record of the the 2002 IEEE International Symposium on Electrical Insulation (Cat. No.02CH37316).

[15]  Magdy M. A. Salama,et al.  Asset management techniques for transformers , 2010 .

[16]  M. Abou-Dakka.  Towards a smart replacement strategy of power cables based on the depolarization principle , 2012, 2012 Annual Report Conference on Electrical Insulation and Dielectric Phenomena.