An outage detection framework for power distribution networks is proposed. Given the tree structure of the distribution system, a framework is developed combining the use of real-time power flow measurements on edges of the tree with load forecasts at the nodes of the tree. Components of the network are modeled. A framework for the optimality of the detection problem is proposed relying on the maximum missed detection probability. An algorithm is proposed to solve the sensor placement problem for the general tree case. Finally, a set of case studies is considered using feeder data from the Pacific Northwest National Laboratories and Pacific Gas and Electric. We show that a 10 \% loss in mean detection reliability network wide reduces the required sensor density by $60 \%$ for a typical feeder if efficient use of measurements is performed.
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