POWER SYSTEM STATE ESTIMATION - IIT Mandi

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Difficulties mitigated through useof state estimation• Variables of interest are indicative of: Margins to operating limits Health of equipment Required operator action• State estimators allow the calculation of these variablesof interest with high confidence despite: measurements that are corrupted by noise measurements that may be missing or grosslyinaccurate
Objectives of State Estimation• Objectives:‣ To provide a view of real-time power system conditions Real-time data primarily come from SCADA SE supplements SCADA data: filter, fill, smooth.‣ To provide a consistent representation for powersystem security analysis• On-line dispatcher power flow• Contingency Analysis• Load Frequency Control‣ To provide diagnostics for modeling & maintenance
Page 1 and 2: POWER SYSTEMSTATE ESTIMATIONPresent
Page 3: Introduction• Transmission system
Page 7 and 8: Power System State Estimation (Cont
Page 9 and 10: Power System State Estimation (Cont
Page 11 and 12: Consider a Simple DC Load Flow Exam
Page 13 and 14: Case with all meters have small err
Page 15 and 16: State Estimation: determining our b
Page 17 and 18: (Cont.,)‣Least Absolute Value(LAV
Page 19 and 20: (Cont.,)•12 2PDF( ) exp( / 2 )2
Page 21 and 22: Weighted least Squares-State Estima
Page 23 and 24: (Cont.,)• The type of Newton‟s
Page 25 and 26: (Cont.,)•J( x)xT 1H R (e H x) 0T
Page 27 and 28: (Cont.,)• To derive the [H] matri
Page 29 and 30: (Cont.,)•est1est25 2.5 0- 5 0 -40
Page 31 and 32: Solution of the weighted least squa
Page 33 and 34: (Cont.,)• Critical measurement: A
Page 35 and 36: Bad Data Detection and Identificati
Page 37 and 38: Chi-square probability density func
Page 39 and 40: (Cont.,)• The degrees of freedom
Page 41 and 42: Bad Data Identification•'(zi zi)
Page 43 and 44: Bad Data Analysis-Example•
Page 45 and 46: (Cont.,)• Forming the H matrix we
Page 47 and 48: (Const.,)•z1z23.01544Azz349.00123
Page 49 and 50: (Cont.,)•4f e / 100(0.00877) 100(
Page 51 and 52: (Cont.,)•' 1 T 1Rii(I HG H R )ReN
Page 53 and 54: Conclusion• Real time monitoring

POWER SYSTEM STATE ESTIMATION - IIT Mandi

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