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The digitalization of the power distribution grid has surged over the past decade. This transformation has given rise to a host of new data-driven applications focused on condition monitoring and predictive maintenance. However, from the perspective of the distribution system operator, there remains uncertainty about what and how digital maintenance processes can be realized. Additionally, the lack of clarity regarding the relative payback of investments makes it difficult to plan investments in digital maintenance systems optimally. The existing literature does not provide a holistic investigation of proactive maintenance applications, specifically the interplay between how data selection, usage, and degree of digitalization impacts the development of proactive maintenance applications. In this paper, we therefore study the chain of design choices linked to the development of proactive maintenance systems, through a scoping review of existing approaches. Thereby, we offer a valuable resource for power distribution system operators in guiding their decision-making and implementation processes. Additionally, it enables us to point out gaps in existing literature, which can inform future studies. Furthermore, we provide an extendable Sankey diagram-based visualization tool, which enables researchers and practitioners alike to further investigate the complex relationships between proactive maintenance design choices. Eventually, we propose a conceptual model for power distribution systems operators to better understand the benefits of digitally enabled proactive maintenance systems, which can aid investment decision-making. • First review to study the full chain of proactive maintenance system design choices. • Decision flow-visualization provides a powerful investment-decision making tool. • Maintenance system digitalization is understood through a 2-axis conceptual model. • Future research should consider prescribing solutions based on assets’ condition. • Novel data and data-enrichment strategies provide future research-avenues.
Mortensen et al. (Wed,) studied this question.