A Genetic Algorithm-Based Approach for the Inspection Scheduling Planning in Power Distribution Networks.

The rising demand for energy and an still increasing world population are prompting the need to further improve power supply services upon a "zero interruption" target. This, combined with the process of shifting fossil fuel usage toward electrification, may escalate the economic and social impacts caused from interruptions. In this context, scheduled inspection plays a major role to manage risks. The challenge, however, is the trade-off of low O&M costs and high reliability. To solve that, this paper proposes a reliability-centered maintenance approach that combines heuristic and genetic algorithm (GA). The heuristic, based on benchmark practices, determines the cumulative total line length to be inspected to reach a targeted reliability level. The GA, on the other hand, yields a priority order list to portions of the grid to be inspected. The methodology relies on corporate systems historic data from outage management system, supervisory control and data acquisition, geographic information system and enterprise resource planning, typically available on power utilities. Tests are performed to a real 13.8 kV network in the South West of Brazil. Results demonstrate that the proposed methodology can significantly improve the decision-making by prioritizing feeder segments with higher load density, number of interruptions and voltage/current problems, up to a preset target, thus, improving reliability while limiting O&M costs. [ABSTRACT FROM AUTHOR]

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