Lei, Jiansheng (2007-05). Using graph theory to resolve state estimator issues faced by deregulated power systems. Doctoral Dissertation. Thesis uri icon

abstract

  • Power industry is undergoing a transition from the traditional regulated environment to the competitive power market. To have a reliable state estimator (SE) in the power market environment, two major challenges are emerging, i.e. to keep SE running reliably even under a contingency and to run SE over a grid with extremely large size. The objective of this dissertation is to use graph theory to address the above two challenges. To keep SE running reliably under a contingency, a novel topological approach is first proposed to identify critical measurements and examine network observability under a contingency. To advance the classical topological observability analysis, a new concept of contingency observability graph (COG) is introduced and it is proven that a power system network maintains its observability under a contingency if and only if its COG satisfies some conditions. As an application of COG, a two-stage heuristic topological approach is further developed based on the new concept of qualified COG (QCOG) to minimize the number of measurements and RTUs under the constraint that the system remains observable under any single contingency. To overcome the disadvantages of existing SE over extremely large networks, a textured distributed state estimator (DSE), which consists of the off-line textured architecture design and the on-line textured computation, is proposed based on COG and a new concept of Bus Credibility Index (BCI). The textured DSE is non-recursive, asynchronous and avoids central controlling node. Numerical tests verify that the performance of the new textured DSE algorithm improves greatly compared with existing DSE algorithms in respect of bad data detection and identification. Furthermore, the software implementation for DSE is formulated as an information integration problem over regional power markets, and is very challenging because of its size and complexity. A new concept of semantic knowledge warehouse (SKW), together with the proposed concepts of semantic reasoning software component (SRSC) and deduction credibility, is developed to implement such an information integration system.
  • Power industry is undergoing a transition from the traditional regulated environment
    to the competitive power market. To have a reliable state estimator (SE) in the power
    market environment, two major challenges are emerging, i.e. to keep SE running reliably
    even under a contingency and to run SE over a grid with extremely large size.
    The objective of this dissertation is to use graph theory to address the above two
    challenges.
    To keep SE running reliably under a contingency, a novel topological approach is
    first proposed to identify critical measurements and examine network observability
    under a contingency. To advance the classical topological observability analysis, a new
    concept of contingency observability graph (COG) is introduced and it is proven that a
    power system network maintains its observability under a contingency if and only if its
    COG satisfies some conditions. As an application of COG, a two-stage heuristic
    topological approach is further developed based on the new concept of qualified COG
    (QCOG) to minimize the number of measurements and RTUs under the constraint that
    the system remains observable under any single contingency.
    To overcome the disadvantages of existing SE over extremely large networks, a
    textured distributed state estimator (DSE), which consists of the off-line textured
    architecture design and the on-line textured computation, is proposed based on COG and
    a new concept of Bus Credibility Index (BCI). The textured DSE is non-recursive,
    asynchronous and avoids central controlling node. Numerical tests verify that the performance of the new textured DSE algorithm improves greatly compared with
    existing DSE algorithms in respect of bad data detection and identification. Furthermore,
    the software implementation for DSE is formulated as an information integration
    problem over regional power markets, and is very challenging because of its size and
    complexity. A new concept of semantic knowledge warehouse (SKW), together with the
    proposed concepts of semantic reasoning software component (SRSC) and deduction
    credibility, is developed to implement such an information integration system.

publication date

  • May 2007