This paper proposes a novel extended traffic network model to solve the logit-based stochastic user equilibrium (SUE) problem with elastic demand. In this model, an extended traffic network is established by properly ...
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This paper proposes a novel extended traffic network model to solve the logit-based stochastic user equilibrium (SUE) problem with elastic demand. In this model, an extended traffic network is established by properly adding dummy nodes and links to the original traffic network. Based on the extended traffic network, the logit-based SUE problem with elastic demand is transformed to the SUE problem with fixed demand. Such problem is then further converted to a linearly constrained convex programming and addressed by a predictor-corrector interior point algorithm with polynomial complexity. A numerical example is provided to compare the proposed model with the method of successive averages (MSA). The numerical results indicate that the proposed model is more efficient and has a better convergence than the MSA. (C) 2014 Elsevier B.V. All rights reserved.
This paper presents a current-based optimal power flow (OPF) with predictor-corrector interior point algorithm (PCIPA). The distinctive features of this OPF formulation are: i) the elements of Hessian matrix are all r...
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ISBN:
(纸本)9781424412969
This paper presents a current-based optimal power flow (OPF) with predictor-corrector interior point algorithm (PCIPA). The distinctive features of this OPF formulation are: i) the elements of Hessian matrix are all real, ii) the objective function and constraints are quadratic functions and such quadratic properties are explored in the development of a robust nonlinear OPF solution procedure. This paper also presents the proposed method can further decomposes into two optimal sub-problems (active and reactive). The computational results on power systems of IEEE 9 to 118 buses have shown that the proposed algorithms are very effective.
An equivalent current injection (ECI)-based hybrid current-power optimal power flow (OPF) model is proposed in this paper, and the predictor-corrector interior point algorithm (PCIPA) is tailored to fit the OPF for so...
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An equivalent current injection (ECI)-based hybrid current-power optimal power flow (OPF) model is proposed in this paper, and the predictor-corrector interior point algorithm (PCIPA) is tailored to fit the OPF for solving nonlinear programming (NLP) problems. The proposed method can further decompose into two subproblems. The computational results of IEEE 9 to 300 buses have shown that the proposed algorithms can enhance the performance in terms of the number of iterations, memory storages, and CPU times.
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