Browsing by Subject "State Estimation"
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Item Multi-area network analysis(Texas A&M University, 2005-02-17) Zhao, LiangAfter the deregulation of the power systems, the large-scale power systems may contain several areas. Each area has its own control center and each control center may have its own state estimator which processes the measurements received from its local substations. When scheduling power transactions, which involve several control areas a system-wide state estimation solution is needed. In this dissertation, an estimation approach which coordinates locally obtained decentralized estimates while improving bad data processing capability at the area boundaries is presented. It is assumed that synchronized phasor measurements from different area buses are available in addition to the conventional measurements provided by the substation remote terminal units. The estimator with hierarchical structure is implemented and tested using different measurement configurations for two systems having 118 and 4520 buses. Furthermore, we apply this multi-area solution scheme to the problem of Total Transfer Capability (TTC) calculation. In a restructured power system, the sellers and buyers of power transactions may be located in different areas. Computation of TTC will then require system-wide studies. We investigate a multi-area solution scheme, which takes advantage of the system-wide calculated Power Transfer Distribution Factors (PTDF) in order for each area to calculate its own TTC while a central entity coordinates these results to determine the final value. The proposed problem formulation and its solution algorithm are presented. 30 and 4520 bus test systems are used to demonstrate the approach and numerically verify the proposed TTC calculation method.Item Multi-area power system state estimation utilizing boundary measurements and phasor measurement units ( PMUs)(Texas A&M University, 2006-10-30) Freeman, Matthew AThe objective of this thesis is to prove the validity of a multi-area state estimator and investigate the advantages it provides over a serial state estimator. This is done utilizing the IEEE 118 Bus Test System as a sample system. This thesis investigates the benefits that stem from utilizing a multi-area state estimator instead of a serial state estimator. These benefits are largely in the form of increased accuracy and decreased processing time. First, the theory behind power system state estimation is explained for a simple serial estimator. Then the thesis shows how conventional measurements and newer, more accurate PMU measurements work within the framework of weighted least squares estimation. Next, the multi-area state estimator is examined closely and the additional measurements provided by PMUs are used to increase accuracy and computational efficiency. Finally, the multi-area state estimator is tested for accuracy, its ability to detect bad data, and computation time.Item Using graph theory to resolve state estimator issues faced by deregulated power systems(2009-05-15) Lei, JianshengPower 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.