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Linfeng Yang

Researcher at Guangxi University

Publications -  33
Citations -  591

Linfeng Yang is an academic researcher from Guangxi University. The author has contributed to research in topics: Integer programming & Nonlinear programming. The author has an hindex of 12, co-authored 33 publications receiving 386 citations. Previous affiliations of Linfeng Yang include University of Sydney.

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A Distributed Dual Consensus ADMM Based on Partition for DC-DOPF With Carbon Emission Trading

TL;DR: The proposed method (dc-ADMM-P) adopts a novel strategy which uses consensus ADMM to solve the dual of dc-DOPF-CET while only discloses boundary branches information among adjacent subsystems, and shows the improvement of convergence performance by reducing the number of dual multipliers and employing a new update strategy for the multiplier.
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A hybrid MILP and IPM approach for dynamic economic dispatch with valve-point effects

TL;DR: In this article, a hybrid approach combining mixed-integer linear programming (MILP) and the interior point method (IPM), abbreviated as MILP-IPM, is proposed to solve a DED-VPE problem in which complicated transmission loss is also included.
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A novel projected two-binary-variable formulation for unit commitment in power systems

TL;DR: In this paper, a two-binary-variable (2-bin) MIQP formulation for the thermal unit commitment (UC) problem in power systems is proposed, which is the tightest and most compact model and can be solved most efficiently.
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Outer Approximation and Outer-Inner Approximation Approaches for Unit Commitment Problem

TL;DR: A new separable model for the unit commitment (UC) problem and three deterministic global optimization methods for it ensuring convergence to the global optimum within a desired tolerance are proposed.
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Tight Relaxation Method for Unit Commitment Problem Using Reformulation and Lift-and-Project

TL;DR: The proposed tight relaxation method is competitive with general-purpose mixed integer programming solvers based methods for large-scale UC problems due to the excellent performance and the good quality of the solutions it generates.