Probabilistic decomposition-based security constrained transmission expansion planning incorporating distributed series reactor

This study presents a probabilistic transmission expansion planning model incorporating distributed series reactors, which are aimed at improving network flexibility. Although the whole problem is a mixed-integer non-linear programming problem, this study proposes an approximation method to linearis...

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Veröffentlicht in:IET generation, transmission & distribution Jg. 14; H. 17; S. 3478 - 3487
Hauptverfasser: Yuan, Zhi, Wang, Weiqing, Wang, Haiyun, Ghadimi, Noradin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 04.09.2020
Schlagworte:
approximation method
BD algorithm
Benders decomposition algorithm
developed optimal power flow problem
distributed series reactors
integer programming
linear programming
linear sub‐problem
load flow
mixed‐integer nonlinear programming problem
Monte Carlo methods
network flexibility
nonlinear programming
optimal number
optimality gap
power generation planning
power system security
power transmission planning
power transmission reliability
probabilistic decomposition‐based security
probabilistic transmission expansion planning model
probability
Research Article
stage problem
transmission expansion planning incorporating distributed series reactor
transmission lines
power generation planning
integer programming
nonlinear programming
distributed series reactors
Benders decomposition algorithm
linear programming
Monte Carlo methods
network flexibility
approximation method
mixed-integer nonlinear programming problem
power transmission planning
power transmission reliability
transmission expansion planning incorporating distributed series reactor
probability
probabilistic decomposition-based security
transmission lines
power system security
optimality gap
probabilistic transmission expansion planning model
linear sub-problem
BD algorithm
optimal number
developed optimal power flow problem
stage problem
load flow
ISSN:1751-8687, 1751-8695
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Beschreibung
Zusammenfassung:This study presents a probabilistic transmission expansion planning model incorporating distributed series reactors, which are aimed at improving network flexibility. Although the whole problem is a mixed-integer non-linear programming problem, this study proposes an approximation method to linearise it in the structure of the Benders decomposition (BD) algorithm. In the first stage of the BD algorithm, optimal number of new transmission lines and distributed series reactors are determined. In the second stage, the developed optimal power flow problem, as a linear sub-problem, is performed for different scenarios of uncertainties and a set of probable contingencies. The Benders cuts are iteratively added to the first stage problem to decrease the optimality gap below a given threshold. The proposed model utilises the Monte Carlo simulation method to take into account uncertainty of wind generations and demands. Several case studies on three test systems are presented to validate the efficacy of the proposed approach.
ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2019.1625