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Wireless Sensor Networks (WSNs) have been widely recognized as a promising technology that can enhance various aspects of today's electric power systems, making them a vital component of the smart grid. Efficient aggregation of data collected by sensors is crucial for a successful WSN-based smart grid application. Existing works on the Minimum Latency Aggregation Scheduling (MLAS) problem in WSNs usually adopt the protocol interference model, which is a tremendous simplification of the physical reality faced in wireless networks. In contrast, the more realistic physical interference model has been proved to have the potential to increase the network capacity. In this paper, we propose a distributed algorithm to minimize the data aggregation latency under the physical interference model, which jointly considers routing, power assignment and transmission scheduling. We theoretically prove that our algorithm solves the MLAS problem correctly and the latency is bounded by √ 3(K + 1)2(Δ + log √2/K+1) + 6K2 + 4K + 2, where K is a model-specific 2 constant and Δ is the logarithm of the ratio between the lengths of the longest and shortest links in the network. Simulation results demonstrate that our algorithm can significantly reduce the aggregation latency compared to other schemes under the physical interference model. In networks where n nodes are uniformly distributed, our algorithm achieves an average latency between O(log3 n) and O(log4 n). We also discuss how to improve the energy efficiency through load-balancing techniques.