Logically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model
•Proposing a precise solver-based model for logic-based OPF problems.•Proposing recasts that accommodate the pre-solving and probing techniques of solvers.•Performing flexibility test of models under different conditions.•Performing efficiency test of the models by solving large-scale power systems....
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| Veröffentlicht in: | International journal of electrical power & energy systems Jg. 97; S. 240 - 249 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier Ltd
01.04.2018
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| ISSN: | 0142-0615, 1879-3517 |
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| Abstract | •Proposing a precise solver-based model for logic-based OPF problems.•Proposing recasts that accommodate the pre-solving and probing techniques of solvers.•Performing flexibility test of models under different conditions.•Performing efficiency test of the models by solving large-scale power systems.
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. |
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| AbstractList | •Proposing a precise solver-based model for logic-based OPF problems.•Proposing recasts that accommodate the pre-solving and probing techniques of solvers.•Performing flexibility test of models under different conditions.•Performing efficiency test of the models by solving large-scale power systems.
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. |
| Author | Sanches Mantovani, José Roberto Pourakbari-Kasmaei, Mahdi |
| Author_xml | – sequence: 1 givenname: Mahdi surname: Pourakbari-Kasmaei fullname: Pourakbari-Kasmaei, Mahdi email: mahdi.pourakbari@ieee.org – sequence: 2 givenname: José Roberto surname: Sanches Mantovani fullname: Sanches Mantovani, José Roberto |
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| Keywords | Logical constraint FACTS devices Mixed-integer nonlinear programming Optimal power flow Solver-based model Non-smooth terms |
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