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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

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Electrocatalytic reduction has recently received increasing attention as a method of converting waste nitrate into value-added ammonia, but most studies have focused on complex strategies of catalyst preparation and little has been done in the way of large-scale demonstrations. Herein, we report that in situ activation of a pristine Ni electrode, either on a lab scale or a pilot scale, is effective in facilitating nitrate reduction to ammonia, exhibiting extraordinarily high activity, selectivity, and stability. The self-activated Ni cathode has a robust capacity to reduce nitrate over a wide range of concentrations and achieves great conversion yield, NH4 +–N selectivity, and Faradaic efficiency, respectively, 95.3, 95.5, and 64.4% at 200 mg L–1 NO3 ––N and 97.8, 97.1, and 90.4% at 2000 mg L–1 NO3 ––N, for example. Fundamental research indicates that Ni­(OH)2 nanoparticles are formed on the Ni electrode surface upon self-activation, which play crucial roles in governing nitrate reduction reaction (NO3RR) through the atomic H*-mediated pathway and accordingly suppressing hydrogen evolution reaction. More importantly, the self-activated Ni­(OH)2@Ni cathode can be easily scaled up to allow large volumes of real industrial wastewater to be processed, successfully transferring nitrate into ammonia with high yields and Faradaic efficiency. This study demonstrates a new, mild, and promising method of cleaning nitrate-laden wastewater that produces ammonia as a valuable byproduct.

Distributed generators can be integrated in geographically distributed areas and microgrids of active distribution networks (ADNs), and can operate independently. On the basis of the alternating direction method of multipliers, the authors describe an efficient fully distributed algorithm to solve multi-area economic dispatch problems in ADNs without requiring a central coordinator. The physical interpretation of the distributed algorithm and a proof for its convergence are both given. Network losses are taken into account by exploiting the features of ADNs. Two other popular distributed algorithms, including Lagrangian relaxation and auxiliary problem principle, are also implemented and compared with numerical tests. They discuss numerical results that demonstrate the effectiveness and efficiency of the algorithm.