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2. Topics Today. Topic1: An expert system is proposed to search for most beneficial and efficient data exchange schemes while avoid harmful data exchange at the same time. In addition, the impact of data exchange on new measurement design and the issues on price of exchanged data are also discussed.
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Advisor: Dr. Garng M. Huang
Department of Electrical Engineering
Texas A&M University
releasing their transmission grids to form ISOs/RTOs while their own local state estimators are already in use.
Two RTOs merge into one Mega-RTOA Reasoning Machine (1)
For example, it is reasonable for b2 and b4 in B to extends to include b1 and b5 in A. But it does not follow the rule that b9 in B extends to include b10 or b14 in A.
For example, b9 in B extend only to b10 in A will form a new radial branch b9-b10, which violates this principle.
where bus b is in the common part of A and B
Then estimation result exchange from A to B on this bus will improve BCI(b,B) to the magnitude of BCI(b,A) .
B before data exchange
B after harmful data exchange
No bad data detected
Normalized Residues For Local Estimator B
No bad data detectedCase1:Harmful Data Exchange (2)
Local estimators after beneficial data exchangeCase2: Efficiency of Beneficial Data Exchange
Average BCI on the buses of B
Average Estimation Error on the buses of B
When we follow the data exchange scheme suggested in Case 2, state estimation in A can be run normally because the estimation result on b1 and b5 is exchanged from B to A (B is still observable even under such an accident).
wherethe dimension of Rnewis much lower than that of G
and are known already
0.004Estimation Accuracy and Boundary Discrepancy
Data Exchange Area
Table 1. Estimation Result Derivation
Fig.1 Local estimators after raw data exchange
A in Fig.1
B in Fig.1
A in Fig.1 after estimated data exchange
94Bad Data Detection Ability
Table 2. Normalized Residues For Local Estimator A and B
 Garng M. Huang and S.-C. Hsieh, “Fast Textured Algorithms for Optimal Power Delivery Problems in Deregulated Environments”, IEEE Trans. on Power Systems, Vol. 13, No. 2, pp. 493-500, May 1998.
 Garng M. Huang and Jiansheng Lei, “Measurement Design and State Estimation for Distributed Multi-Utility Operation”, North American Power Symposium 2001, pp. 504-509, October 2001.
 Garng M. Huang and Jiansheng Lei, “Measurement Design of Data Exchange for Distributed Multi-Utility Operation”, IEEE PES WM2002, January 2002.
 Garng M. Huang and Jiansheng Lei, “A Knowledge Based Data Exchange Design for Distributed Mega-RTO Operations”, Probabilistic Methods Applied to Power Systems 2002, September 2002.
 Garng M. Huang and Jiansheng Lei, “A Concurrent Non-Recursive Textured Algorithm for Distributed Multi-Utility State Estimation”, IEEE PES SM2002, July 2002.