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Showing 1 to 4 of 4 for “"Convex formulation"”.
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Low rank methods for optimizing clustering
… objective is NP-hard, and even though there is a convex relaxation of the objective, straightforward convex optimization approaches are too expensive for large datasets. We utilize low rank structures in the solution matrix of the convex formulation and use a low-rank factorization of the solution …
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Optimal coordination of distributed energy resources in smart grids enabled by distributed optimization and transactive energy
… of local information. First, we utilize a new convex formulation of the power grid based on current injection (CI) and McCormick Envelopes, to model distribution grids of meshed topology and unbalanced structure. The OPF problem is then solved for such grid structures, using the distributed …
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Adaptive sparse representations and their applications
… sparse models. Then, we propose novel problem formulations for learning square sparsifying transforms from data. The proposed algorithms for transform learning alternate between a sparse coding step and a transform update step, and are highly efficient. Specifically, as opposed to sparse coding …
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Control and optimization of modern power networks: hybrid AC/DC networks and inverter-based microgrids
… uptake of energy storage systems. The proposed formulation in this chapter allows the incorporation of various important features that have not been addressed in the literature. Previous literature on convexified optimal power flow had not investigated the case of unbalanced distribution …