An MISOCP-Based Decomposition Approach for the Unit Commitment Problem with AC Power Flows

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 approac...

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Vydáno v:IEEE transactions on power systems Ročník 38; číslo 4; s. 1 - 12
Hlavní autoři: Tuncer, Deniz, Kocuk, Burak
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.07.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Alternating current
Decomposition
Direct current
Electric power systems
Flow equations
Generators
Load flow
Lower bounds
Mathematical analysis
Mathematical models
Mixed integer
mixedinteger programming
Newton method
nonlinear programming
optimal power flow
Optimization
Power flow
Programming
Reactive power
Schedules
second-order cone programming
Systems planning
Unit commitment
ISSN:0885-8950, 1558-0679
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Shrnutí: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.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2022.3206136