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His current research interests include active distribution network security analysis and restoration. Wenchuan Wu (SM'14) received the B.S., M.S., and Ph.D. degrees from the Electrical Engineering

The growing interconnections of regional power systems and the large-scale integration of wind energy bring about the critical need to coordinate multiarea generation unit and tieline scheduling (MAUTS). It is recognized that because of the limitations on private data exchange and model management, it is suitable to address the multiarea power scheduling problem in a decentralized way. In this paper, the MAUTS problem is formulated using the adaptive robust optimization (RO) scheme to account for uncertain wind energy. Our model is decomposed into regional subproblems by augmented Lagrangian decomposition (ALD), which enables a fully distributed computation within an alternating direction multiplier method framework. To address the nonconvexity issue, a tractable alternating optimization procedure (AOP) is developed to obtain high-quality solutions with finite convergence for the nonconvex mixed-integer problem. Simulations on different test systems are conducted to show the computational performance, the solution quality, and scalability of the proposed method.Index Terms-Multiarea power systems, network-constrained generation unit commitment, robust optimization (RO), tie-line scheduling, wind energy uncertainty. 1949-3029