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https://hdl.handle.net/20.500.14279/22860
Τίτλος: | A Distributionally Robust AC Network-Constrained Unit Commitment | Συγγραφείς: | Dehghan, Shahab Aristidou, Petros Amjady, Nima Conejo, Antonio J. |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Λέξεις-κλειδιά: | Convexification;Decomposition;Distributionally Robust Optimization;Unit Commitment;Uncertainty | Ημερομηνία Έκδοσης: | 2021 | Πηγή: | IEEE Transactions on Power Systems, 2021 | Περιοδικό: | IEEE Transactions on Power Systems | Περίληψη: | This paper presents a distributionally robust network-constrained unit commitment (DR-NCUC) model considering AC network modeling and uncertainties of demands and renewable productions. The proposed model characterizes uncertain parameters using a data-driven ambiguity set constructed by training samples. The non-convex AC power flow equations are approximated by convex quadratic and McCormick relaxations. Since the proposed min-max-min DR-NCUC problem cannot be solved directly by available solvers, a new decomposition algorithm with proof of convergence is reported in this paper. The master problem of this algorithm is solved using both primal and dual cuts, while the max-min sub-problem is solved using the primal-dual hybrid gradient method, obviating the need for using duality theory. Also, an active set strategy is proposed to enhance the tractability of the decomposition algorithm by ignoring the subset of inactive constraints. The proposed model is applied to a 6-bus test system and the IEEE 118-bus test system under different conditions. These case studies illustrate the performance of the proposed DR-NCUC model to characterize uncertainties and the superiority of the proposed decomposition algorithm over other decomposition approaches using either primal or dual cuts. | URI: | https://hdl.handle.net/20.500.14279/22860 | ISSN: | 15580679 | DOI: | 10.1109/TPWRS.2021.3078801 | Rights: | © IEEE Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Article | Affiliation: | University of Leeds Cyprus University of Technology Semnan University Ohio State University |
Εμφανίζεται στις συλλογές: | Άρθρα/Articles |
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