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The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
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Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
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Resolución del problema de programación de la tienda de flujos híbridos en múltiples escenarios basado en un modelo

Xiang Tian1, Yang Kong1, Xiyu Liu2,3

  • 1School of Health Management, Binzhou Medical University, Yantai, Shandong, China.

PloS one
|September 3, 2025
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Resumen
Este resumen es generado por máquina.

Este estudio introduce una máquina de sonda mejorada con operaciones de sonda de varios niveles (IPMMPO) para problemas de programación de flujo híbrido. El nuevo modelo IPMMPO-CP supera significativamente los algoritmos y modelos existentes.

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Área de la Ciencia:

  • Investigación de las operaciones
  • Ciencias de la computación
  • Ingeniería industrial

Sus antecedentes:

  • El problema de programación de flujo híbrido (HFS) es crítico en las industrias de fabricación y producción.
  • Las máquinas de sonda ofrecen capacidades informáticas avanzadas para tareas de optimización complejas.
  • Los métodos existentes luchan con los diversos escenarios de los problemas de HFS.

Objetivo del estudio:

  • Desarrollar un nuevo enfoque para resolver problemas de programación de flujo híbrido de múltiples escenarios.
  • Introducir una máquina de sonda mejorada con operaciones de sonda de varios niveles (IPMMPO) y su modelo de programación de restricciones (CP) (IPMMPO-CP).
  • Para crear datos personalizados y bibliotecas de sondeo para varios tipos de problemas de HFS.

Principales métodos:

  • Librerías de datos generales y sondas diseñadas para escenarios HFS (máquinas paralelas idénticas/no relacionadas, sin espera/estándar).
  • Se han desarrollado conjuntos de tupla para el modelado de programación de restricciones (CP) como preprocesamiento de datos.
  • Propuso el modelo IPMMPO-CP para problemas de HFS con múltiples escenarios.

Principales resultados:

  • El modelo IPMMPO-CP demostró un rendimiento superior en una amplia gama de casos de problemas HFS.
  • El análisis comparativo mostró que el IPMMPO-CP superaba a 9 algoritmos representativos y a 2 modelos recientes de CP.
  • El método propuesto maneja efectivamente HFS con máquinas paralelas idénticas, máquinas paralelas no relacionadas y restricciones sin espera.

Conclusiones:

  • El IPMMPO-CP ofrece una solución potente y versátil para la programación compleja de la tienda de flujos híbridos.
  • Las bibliotecas de datos y sondas desarrolladas mejoran la aplicabilidad de las máquinas de sonda al HFS.
  • Esta investigación hace avanzar el estado de la técnica en la resolución de problemas de HFS de múltiples escenarios.