Abstract

• Loss of life and costs of a transformer fleet are optimised simultaneously. • An economic evaluation model using failure probability which is defined based on degree of polymerization is proposed. • Key ageing factors are considered in defining loss of life and modified cost models. • NSGA-II is employed for co-optimisation of the proposed objective function. Elaborating the technical and economic aspects of exploiting power transformers, this paper employs an objective function to optimise costs and loss of lives of transformers. Using non-dominated sorting genetic algorithm (NSGA-II), the objective function finds loading factors of power transformers which guarantee optimum values for both aspects. The proposed method is first performed on a transmission grid including 15 substations without considering failure probability of power transformers. Proving that the proposed method can optimise both technical and economic functions efficiently according to the results, the modified economic model which utilizes failure probability based on degree of polymerization is employed in the second step. It is shown that the economic evaluation considering failure probability and life expectancy of transformers leads to accurate and reliable values. The method helps utilities and companies to manage exploiting and loading of power transformer fleet (not just a single power transformer) and mitigate costs and loss of lives.

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