Team Size Optimization for Power Restoration in Workforce Management

Kılkıl E., Nasiboğlu E.

12th International Statistics Days Conference, İzmir, Turkey, 13 - 16 October 2022, pp.53

  • Publication Type: Conference Paper / Summary Text
  • City: İzmir
  • Country: Turkey
  • Page Numbers: pp.53
  • Dokuz Eylül University Affiliated: Yes


A scientific and reasonable power emergency supplies workforce management is essential to speed up the restoration process after damage of a power system. In this study simulation approach is proposed for annual planning of power restoration workforce related to an GDZ electricity distribution company. Workforces are employed to restore power after interruptions throughout the province on service point. According to the electricity distribution network, locations and field sizes, service points are divided into 29 operation centers, each to restorate power interruptions. The scale of the study is a discrete, stochastic and multi-criteria problem due to the nature of the electricity distribution system therefore determining the size of the team in each service point over the year is challenging. Given this background, firstly, an event definition was made for the period from the occurrence of the interruption notification to its completion. Time intervals in events have stochastic lengths because they are affected by unpredictable factors. Using the outage data of the last two years, monthly outage frequency estimations were made for each operation center. The probability distributions of each event were determined and distributons are simulated. Monthly labor demand is then forecasted based on an optimistic scenario where there is a large enough labor resource at the time of the outage to keep the downtime level to a minimum for the operations centers. Finally, for purpose of validation of workforce distribution multicriteria model are developed. The model is based on a survey of relevant data, especially those related to the need to perform tasks on the lines, as the number of consumers, voltage lines, transformers, so on. Multicriteria model is grouped according to theoperation centers. Correlations between model coefficients and estimates of operations center team size are examined. The presented model is expected to increase efficiencies by focusing especially on peak hours, with optimum design teams that ensure the distribution of workforce according to operation centers, minimizing customer interruptions and personnel costs. Keywords: decision making, mathematical programming, statistical analysis, power interruption, workforce planning