An MISOCP-based decomposition approach for the unit commitment problem with AC power flows

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Tuncer, Deniz and Kocuk, Burak (2023) An MISOCP-based decomposition approach for the unit commitment problem with AC power flows. IEEE Transactions on Power Systems, 38 (4). pp. 3388-3400. ISSN 0885-8950 (Print) 1558-0679 (Online)

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Abstract

Unit Commitment (UC) and Optimal Power Flow (OPF) are two fundamental problems in short-term electric power systems planning that are traditionally solved sequentially. The state-of-the-art mostly uses a direct current (DC) approximation of the power flow equations. However, utilizing the DC approach in the UC-level may lead to infeasible or suboptimal generator commitment schedules for the OPF problem. In this paper, we aim to simultaneously solve the UC Problem with alternating current (AC) power flow equations, which combines the challenging nature of both UC and OPF Problems. Due to the highly nonconvex nature of the AC flow equations, we utilize the mixed-integer second-order cone programming (MISOCP) relaxation of the UC Problem as the basis of our solution approach. The MISOCP relaxation is utilized for finding both a lower bound and a candidate generator commitment schedule. Once this schedule is obtained, we solve a multi-period OPF problem to obtain feasible solutions for the UC problem with AC power flows. For smaller instances, we develop two different algorithms that exploit the recent advances in the OPF literature and obtain high-quality feasible solutions with provably small optimality gaps. For solving larger instances, we develop a Lagrangian decomposition based approach that yields promising results.
Item Type: Article
Uncontrolled Keywords: Generators; Load flow; Mathematical models; mixedinteger programming; Newton method; nonlinear programming; optimal power flow; Programming; Reactive power; Schedules; second-order cone programming; unit commitment
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: Burak Kocuk
Date Deposited: 07 Sep 2023 16:03
Last Modified: 07 Sep 2023 16:03
URI: https://research.sabanciuniv.edu/id/eprint/47821

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