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In this paper, we provide a time-series distribution test system. This test system is a fully observable distribution grid in Midwest U.S. with smart meters (SM) installed at all end users. Our goal is to share a real U.S. distribution grid model without modification. This grid model is comprehensive and representative since it consists of both overhead lines and underground cables, and it has standard distribution grid components such as capacitor banks, line switches, substation transformers with load tap changer and secondary distribution transformers. An important uniqueness of this grid model is it has one-year smart meter measurements at all nodes, thus bridging the gap between existing test feeders and quasi-static time-series based distribution system analysis. 

Transmission line maintenance scheduling (TLMS) plays an important role in enhancement of component reliability. When conducting short-term TLMS, system operators should consider not only operating costs but also operating constraints, particularly with increasing integration of large-scale wind generation. This paper proposes a stochastic security-constrained model to establish short-term TLMS in consideration of wind generation. Possible scenarios, generated by the Latin hypercube sampling (LHS) technique, are simulated to represent wind power volatility. For each line to be maintained during the maintenance windows, Kirchoff’s law is enforced by using a big-M formulation. Unit commitment is also considered to coordinate TLMS to achieve the best maintenance strategies. The whole problem is modeled as a mixed integer linear programming problem, which is solved by the CPLEX solver. Numerical tests on a six-bus system and a modified IEEE 118-bus system show the effectiveness of the proposed model and the algorithm.