Service Restoration in Distribution Systems based on Optimal Scheduling of Search for Fault Location and Switching Operation by Crews

Optimizing service restoration in distribution systems based on scheduling of crews considering priorities of loads

“…However, load priority was disregarded in our previous research 12,13 ; thus, important loads like hospitals could not be recovered on a priority basis under unknown fault locations. In addition, the previous studies 12,13 assumed that fault occurrence probability is distributed uniformly among manual switch sections; however, the number of equipment units is different in each section, and therefore, the fault occurrence risks were overestimated or underestimated. Thus, this paper proposes a method to realize quick service restoration by efforts of multiple crews; specifically, sections including fault locations are narrowed down, and restoration work scheduling is optimized with regard to important (high‐priority) loads and fault occurrence probability in different manual switch sections.…”

“…It is natural to assume that location faults in distribution systems are unknown; thus, we previously proposed a fault locating method to efficiently narrow down unknown fault locations 12 . In addition, we combined that method with work scheduling optimization to realize quick service restoration 13 . As distinct from many studies assuming that fault locations are known, we formulated work scheduling with unknown fault location as a MILP problem 13 ; as a result, service restoration work can be efficiently scheduled so as to minimize expectation of time‐integrated interrupted load capacity.…”

“…12 In addition, we combined that method with work scheduling optimization to realize quick service restoration. 13 As distinct from many studies assuming that fault locations are known, we formulated work scheduling with unknown fault location as a MILP problem 13 ; as a result, service restoration work can be efficiently scheduled so as to minimize expectation of time-integrated interrupted load capacity. However, load priority was disregarded in our previous research 12,13 ; thus, important loads like hospitals could not be recovered on a priority basis under unknown fault locations.…”

“…13 As distinct from many studies assuming that fault locations are known, we formulated work scheduling with unknown fault location as a MILP problem 13 ; as a result, service restoration work can be efficiently scheduled so as to minimize expectation of time-integrated interrupted load capacity. However, load priority was disregarded in our previous research 12,13 ; thus, important loads like hospitals could not be recovered on a priority basis under unknown fault locations. In addition, the previous studies 12,13 assumed that fault occurrence probability is distributed uniformly among manual switch sections; however, the number of equipment units is different in each section, and therefore, the fault occurrence risks were overestimated or underestimated.…”