POWER SYSTEM STATE ESTIMATION - IIT Mandi

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(Cont.,)• When using the WLS estimation method, detection andidentification of bad data are done only after the estimationprocess by processing the measurement residuals.J x ( z h( x) )' W z h(x)• The condition of optimality is that the gradient of J(x) vanishesat the optimal solution x, i.e., 1GX H WZ 0 1 1X G H WZ• An estimate z of the measurement vector z is given byZHX• The vector of residuals is defined as e = z - Hx; an estimate ofe is given byez h(x)
Bad Data Detection and Identification• Detection refers to the determination of whether or not themeasurement set contains any bad data.• Identification is the procedure of finding out which specificmeasurements actually contain bad data.• Detection and identification of bad data depends on theconfiguration of the overall measurement set in a givenpower system.• Bad data can be detected if removal of the correspondingmeasurement does not render the system unobservable.• A single measurement containing bad data can beidentified if and only if: it is not critical and it does not belong to a critical pair
Page 1 and 2: POWER SYSTEMSTATE ESTIMATIONPresent
Page 3 and 4: Introduction• Transmission system
Page 5 and 6: Objectives of State Estimation• O
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: (Cont.,)• Critical measurement: A
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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