A decision model for analysing the effectiveness of powerline maintenance teams

Smart grids and networks are changing the relationship of energy providers to their customers. The prospect is that the customer will no longer be uninformed and non-participative and in the future will become informed, active and involved. The net consequence is projected to generate a demand side responsiveness that few current energy providers have been able to truly comprehend. Systems and infrastructures that were originally developed in the early years of the 20th century are nevertheless being maintained and expanded rapidly under a deregulated and changing environment. Measuring the performance of maintenance teams as they change asset configurations is stretching existing systems and challenging management and control processes in the service providers and asset owner institutions. In addition, the aging workforce and existing large scale institutions are not expected to have the necessary capabilities, competencies or organisational structures to meet the demands of the consumer or technological issues. Therefore, it is imperative that the new technologies promote an increased investment in the ‘human asset’ to create the next generation of power and telecommunication maintenance engineers. Additionally, advances in the ‘informational asset’ through cognitive systems and decision support models are substantially mirroring advances in the understanding of variety and subtleness of coordination required to deploy the new maintenance engineers. The consequence is to provide the components (technology, people and systems) with the skills and capabilities to accomplish the asset expansion and maintenance tasks that the customers are demanding from the energy providers. How these components are organised and supported is explained through a decision support and operational model that is proposed, in this paper. The DEA model proposed here is expected to overcome and resolve the limitations of the current management and operational work practices. It is expected to assist management with new work techniques and practices and measure the efficiency and effectiveness to help the power industry develop work practices, contracts and monitor performances in a consistent yet flexible manner and meet the demands of their customers for continual improvements.