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Description:
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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 . |