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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Logically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model

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Author(s):
Pourakbari-Kasmaei, Mandi [1] ; Sanches Mantovani, Jose Roberto [1]
Total Authors: 2
Affiliation:
[1] State Univ Sao Paulo, Dept Elect Engn, Ilha Solteira - Brazil
Total Affiliations: 1
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 97, p. 240-249, APR 2018.
Web of Science Citations: 9
Abstract

There is increasing evidence of the shortage of solver-based models for solving logically-constrained AC optimal power flow problem (LCOPF). Although in the literature the heuristic-based models have been widely used to handle the LCOPF problems with logical terms such as conditional statements, logical-and, logical-or, etc., their requirement of several trials and adjustments plagues finding a trustworthy solution. On the other hand, a well-defined solver-based model is of much interest in practice, due to rapidity and precision in finding an optimal solution. To remedy this shortcoming, in this paper we provide a solver-friendly procedure to recast the logical constraints to solver-based mixed-integer nonlinear programming (MINLP) terms. We specifically investigate the recasting of logical constraints into the terms of the objective function, so it facilitates the pre-solving and probing techniques of commercial solvers and consequently results in a higher computational efficiency. By applying this recast method to the problem, two sub-power- and sub-function-based MINLP models, namely SP-MINLP and SF-MINLP, respectively, are proposed. Results not only show the superiority of the proposed models in finding a better optimal solution, compared to the existing approaches in the literature, but also the effectiveness and computational tractability in solving large-scale power systems under different configurations. (AU)

FAPESP's process: 16/14319-7 - Online carbon footprint Allocation- a joint Price- and carbon Footprint: responsive demands model to reduce the GHG emissions and manage the electricity demand
Grantee:Mahdi Pourakbari Kasmaei
Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 14/22828-3 - A mixed-integer nonlinear programming paradigm to solve multi fuel-based environmentally-constrained active-reactive optimal power flow
Grantee:Mahdi Pourakbari Kasmaei
Support Opportunities: Scholarships in Brazil - Post-Doctoral