Factorized solution of power system state estimation

• Autores: Catalina Gómez Quiles
• Directores de la Tesis: Antonio de la Villa Jaén (codir. tes.), Antonio Gómez Expósito (codir. tes.)
• Lectura: En la Universidad de Sevilla ( España ) en 2012
• Idioma: español
• Número de páginas: 184
• Tribunal Calificador de la Tesis: José Luis Martínez Ramos (presid.), José Antonio Aguado Sánchez (secret.), Esther Romero Ramos (voc.), Ali Abur (voc.), Thierry Van Cutsem (voc.)
• Materias:
  • Ciencias tecnológicas
    • Ingeniería y tecnología eléctricas
      • Transmisión y distribución
• Enlaces
  • Tesis en acceso abierto en: Idus
• Resumen

  • In this thesis a general two-stage factorized solution for nonlinear WLS problems has been developed, with two main applications: a geographically distributed multilevel hierarchical state estimation algorithm, suitable for very large-scale power systems covering multiple control areas; and a factorized multi-stage version, which enhances the convergence speed and reduces the computational effort.

    In the multilevel hierarchical state estimation, the way the algorithm can be customized to the system decomposition is analyzed, particularizing the methodology for the distribution feeder, substation, and transmission or multi-area system levels. Tests are performed on benchmark and realistic large-scale networks, including the entire European transmission system. The main advantage of this method lies in the possibility of filtering raw measurements at the specific location where they are captured, and then sending only local estimates for further processing by higher level state estimators. This multilevel estimator will be of special interest in upcoming systems, where the increased introduction of ICTs at lower levels and widespread interconnections at the regional transmission level are leading to an explosion of information which could be hardly managed by a single energy management system.

    In the second case, different approaches are proposed, all of them sharing a first linear stage, clearly showing computational efficiency and enhanced convergence speed compared to the conventional estimator. After a two-stage algorithm, the dissertation develops a bilinear three-stage state estimation factorization which virtually eliminates the need to iterate yielding the same solution as that provided by the Gauss-Newton iterative method. This is also extended to the case in which equality constraints are to be enforced.