Unit Commitment

SEMI-DEFINITE OPTIMIZATION FOR SECURITY CONSTRAINT INTELLIGENT UNIT COMMITMENT Under the Esteemed guidance of Asst.Prof. Mr. B.DURGA PRASAD Submitted by M.RAMU

Objective To get the operational and optimal power flow constraints by meeting the security and economy. Formulate in-exhaustive combination of units in real time.

Unit Commitment We have few generators (units). Also we have some forecasted load. It turns out that we cannot just FLIP the switch of certain unit ON and use them. We need to think a head and based on the forecasted load.

Limitations of conventional unit commitment Some crew constraint are ignored. Exhausted combinations. Individual unit commitment is not considered. Unfeasible solutions. Ignoring physical feasibility of individual unit.

WHY SDP Managing large amount of data. Automation of collection processing and reporting is critical to timelines and accuracy. It reduces the process errors. We have enough software's to solve.

SDP to solve UC SDP one minimizes a linear function subjected to constraint that an offline combination are symmetric matrix is positive definite. Robust objective function can formulated in SDP. Simple method to transform inequality constraints into equality constraints. Parallel processing of handling constraints.

Objective function Formation of SDP problem Primal: Dual: Min.A 0 . X max . b T y s.t.A t . X = b i i = 1,…,m X ≥0 L(X , y) = A 0 . X − µ ln |X| − y i (b i − A i . X) The Lagrangian function is

Unit commitment Objective function formation This objective function followed by various constraints 1.power balance constraints. 2.transmission flow constraints. 3.spinning and operating reserves. 4.ramp rate limitations. 5.start up and shut down characteristics of units. 6.active power limits. 7.Reactive power limits. 8.bus voltage limit.

SCUC reformulated as SDP Solution Semi-definite matrix values from SCUC semi-definite matrix X= The group of active resources and their commitment state variables The group of reactive resources and their commitment state variables

Process of solving SDP based SCUC problem

Formulae Co-ordination function( λ )=(p d +∑b/2c)/(∑1/2c) Equaling generation p g =( λ -b)/2c Power demand (p d )=p g1 +p g2 +p g3 Total cost F T =F 1 +F 2 +F 3

Work on possibilities P d =178.69 b 1 =13.50; b 2 =32.60; b 3 =32.60 Λ 1 =13.64; λ 2 =32.95; λ 3 =32.95 P g1 =175; p g2 =178.69; p g3 =178.69 Consider limits and flip all generators. i.e [1 1 1]

Cont’ P d =176.86 b 1 =13.50; b 2 =32.60; b 3 =32.60 Λ 1 =13.64; λ 2 =34.10; λ 3 =34.10 P g1 =176.86; p g2 =176.86; p g3 =176.86 Consider limits and flip generators. i.e [1 0 0]

Cont’ P d =213.54 b 1 =13.50; b 2 =32.60; b 3 =32.60 Λ 1 =13.67; λ 2 =33.04; λ 3 =33.04 P g1 =212.50; p g2 =220; p g3 =220 Consider limits and flip generators. i.e [1 1 0]

Cont’ P d =213.18 b 1 =13.50; b 2 =32.60; b 3 =32.60 Λ 1 =13.68; λ 2 =33.04; λ 3 =33.04 P g1 =213.18; p g2 =213.18; p g3 =213.18 Consider limits and flip generators. i.e [1 1 1]

Securing un-Expected states . Eyed on active and reactive power limits Monitor the ramp rate and shut down of units. Maintain reserve and predict to meet ahead of threats . Make sure of maintain voltage as 1p.u

Results G = 178.6900 178.6900 178.6900 168.4500 168.4500 168.4500 161.8400 161.8400 161.8400 157.8300 157.8300 157.8300 158.1600 158.1600 158.1600 163.6900 163.6900 163.6900 176.8600 176.8600 176.8600 198.2100 198.2100 198.2100 209.6700 209.6700 209.6700 223.5400 223.5400 223.5400 233.1800 233.1800 233.1800 240.8000 240.8000 240.8000 247.0300 247.0300 247.0300 248.4700 248.4700 248.4700 253.8300 253.8300 253.8300 270.9000 270.9000 270.9000 290.1200 290.1200 290.1200 251.6800 251.6800 251.6800 250.8900 250.8900 250.8900 242.1000 242.1000 242.1000 242.0500 242.0500 242.0500 231.6800 231.6800 231.6800 198.0700 198.0700 198.0700 190.6900 190.6900 190.6900 X =16875 16300 16300 Y = 1250 500 500 L = 13.6430 32.9574 32.9574 13.6348 32.9369 32.9369 13.6295 32.9237 32.9237 13.6263 32.9157 32.9157 13.6265 32.9163 32.9163 13.6310 32.9274 32.9274 13.6415 32.9537 32.9537 13.6586 32.9964 32.9964 13.6677 33.0193 33.0193 13.6788 33.0471 33.0471 13.6865 33.0664 33.0664 13.6926 33.0816 33.0816 13.6976 33.0941 33.0941 13.6988 33.0969 33.0969 13.7031 33.1077 33.1077 13.7167 33.1418 33.1418 13.7321 33.1802 33.1802 13.7013 33.1034 33.1034 13.7007 33.1018 33.1018 13.6937 33.0842 33.0842 13.6936 33.0841 33.0841 13.6853 33.0634 33.0634 13.6585 32.9961 32.9961 13.6526 32.9814 32.9814

Cont’ C=CONVENTIONAL UNIT COMMITMENT 1 1 1 1 1 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 1 0 1 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0

Cont’ C*=SECURED UNIT COMMITMENT 1 1 1 1 1 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 1 0 1 1 0 1 1 1* 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0

Mat lab logic for SCUC Formulate security constraints to avoid loop-holes (threats) in a operational UC. Limitations are helpful to form loops in SCUC. Fixed (0/1) of each unit state can be rounding by the unit commitment .

Conclusion and future scope Our scuc is physically feasible to be one of best available options in actual power system operation. Schedule of generating units can be definite. Need to check more cases at different kind of units and try to get with reduced computations.

References Semi-Definite Programming based method for security constraint unit commitment with operational and optimal power flow constraints. X. Bai, H.Wei. PADHY N.P.: ‘Unit commitment: a bibliographical survey’, IEEE Trans. Power Sits., 2004, 19, pp. 1196–1205. FU Y., SHAHIDEHPOUR M., LI Z.: ‘Security-constrained unit commitment with AC constraints’, IEEE Trans. Power Syst.,2005, 20, pp. 1538–1550. Electrical power by S.L.Uppal. Power Generation, Operation and Control-by A.J.Wood and B.F.Wollenberg, John weley & sons inc.1984.

Unit Commitment

More Related Content

What's hot (20)

Viewers also liked (20)

Similar to Unit Commitment (20)

Recently uploaded (20)

Unit Commitment