A Mixed Integer Disjunctive Model for Transmission Network Expansion

By L. Bahiense, G. C. Oliveira, M. Pereira, S. Granville. IEEE Power Engineering Review, 2001

365 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/40017ca8e99f81cb537b802de845f9ac47e5167e

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Citations in the corpus

PyPSA: Python for Power System Analysis (2017, methodology): “the bilinearity with a disjunctive big-M relaxation [44]; this will be incorporated into the main code base of PyPSA soon.”
A New Strategy for Transmission Expansion in Competitive Electricity Markets (2002, methodology): “Starting from Garver’s paper [2] in 1970, a variety of techniques such as branch-andbound algorithm [2], [3], sensitivity analysis [4]‐[6], Benders decomposition [7]‐[9], simulated annealing [10], genetic algorithms (GAs) [11], tabu search algorithms [12], and GRASP [13], [ 14 ] were used to study t”
A New Method for Spatial Power Network Planning in Complicated Environments (2012, methodology): “2161351 studied in [18]–[26] usually assume that candidate electric power line routes are given.”
A method for transmission system expansion planning considering probabilistic reliability criteria (2005, methodology): “Various techniques, including branch and bound, sensitivity analysis, Bender decomposition, simulated annealing, genetic algorithms, tabu search, and greedy randomized adaptive search procedure (GRASP), have been used to study the problem [8]–[17].”
A Mixed-Integer Linear Programming Approach for Multi-Stage Security-Constrained Transmission Expansion Planning (2012, methodology): “Due to the inherent complex nature of the TEP problem, the linearized DC power flow model is usually used [2]–[8].”
Transmission expansion planning with re-design (2010, background): “In general, the transmission expansion planning problem is solved in two variants, considering or not generation redispatch; see [4, 14, 16].”
Strategies to Reduce the Number of Variables and the Combinatorial Search Space of the Multistage Transmission Expansion Planning Problem (2013, methodology): “It seems that the nonlinearity of the DC model cannot be removed without transferring it to a disjunctive model, where for each candidate transmission line a binary variable is used [3], [18].”
Multistage Model for Distribution Expansion Planning With Distributed Generation—Part I: Problem Formulation (2008, methodology): “This nonlinearity is avoided by adopting an extension of the linear disjunctive model successfully used in planning the expansion of transmission networks [36], [37].”
An Engineering-Economic Approach to Transmission Planning Under Market and Regulatory Uncertainties: WECC Case Study (2014, background): “Values of above this minimum would still enforce constraint (8), but can cause numerical difficulties in branch-and-bound algorithms [35].”
Classification of publications and models on transmission expansion planning (2003, methodology): “Several methods have been proposed to obtain the optimum solution for the transmission expansion problem, mostly using classical optimization techniques like linear programming [5]‐[9], dynamic programming [10], nonlinear programming [11], and mixed integer programming [ 12 ]‐[18].”