RECONFIGURATION OF DISTRIBUTION SYSTEM INCLUDING LOAD PROFILES

ByAkash.Y

2013EES2831

Under the guidanceOf

Dr. A.R Abhyankar

16 Bus Distribution system

4 8 13

69 15

712 16

1410

AC AC AC1 2 3

sw16

sw2

sw1 sw5sw10

sw3

sw4

sw6

sw7

sw14

sw11

sw12

sw13

sw17

Normally closed switches

sw9

sw8

5 11

sw15

Chromosome and its interpretation

• This is how the chromosome generated for this topology looks like

• String Length 30

• 1-16 genes represent controllable switches on the lines.

• 14-29 genes represent load switches.

• ‘0’ gene is a flag for optimal load shedding.

• Switches after ‘0’ gene are left open.

• ‘-’ sign before a gene indicates the corresponding switch is open

16 1 18 22 9 28 25 19 5 20 29 27 2 26 7 24 23 11 10 21 17 6 12 4 -15 14 13 0 3 8

• ‘-’ sign or open condition decided by closing ones violating radiality.

• Example:

4 8 13

69 15

712 16

1410

AC AC AC1 2 3

sw16

sw2

sw1 sw5sw10

sw3

sw4

sw6

sw7

sw14

sw11

sw12

sw13

sw17

Normally closed switches

sw9

sw8

5 11

sw15

GA- Objective Function

The objective function is formulated as sum of Penalties

Weighted ratio of Unserved Load to the

Total Load in the system

Weighted Power Loss

of a particular Topology

Weighted ratio of branch

current deviations from max

current limit

Weighted ratio of

bus voltage

deviations from

nominal voltage

Weighted switch

operation cost

𝑓= 𝑊𝐿𝐿𝑃𝐿𝐿+ 𝑊𝐿𝑃𝐿+ 𝑊𝐼𝑂𝐼𝑂 + 𝑊𝑉𝐷𝑉𝐷+ 𝑊𝑆𝑊 𝐶𝑖𝑛𝑆𝑊𝑖=1

• This term represents the load which is not served for every candidate solution (Chromosome).

• If ‘0’ gene occurs at the beginning

• In this case after the ‘0’ gene all load switches from 17 to 29 are kept open and hence is a bigger value thereby having a high penalty in the objective function.

2 4 10 0 1 3 5 9 13 14 28 19 17 22 6 7 24 8 23 21 18 26 11 16 25 29 27 20 15 12

𝑊𝐿𝐿𝑃𝐿𝐿

𝑊𝐿𝐿𝑃𝐿𝐿

• These 3 terms in the objective function can be evaluated running a Distribution Load Flow (back ward forward sweep Teng’s method) for every member of population.

• The first term gives the power loss in a particular topology.

• The 2nd and 3rd terms are branch current deviations and node voltage deviations obtained from Load flow again

𝑊𝐿𝑃𝐿+ 𝑊𝐼𝑂𝐼𝑂 + 𝑊𝑉𝐷𝑉𝐷

Results• For fault at line between buses 4-6 :- The optimal topology is

as follows

4 8 13

69 15

712 16

1410

AC AC AC1 2 3

sw16

sw2

sw1 sw5sw10

sw3

sw4

sw6

sw7

sw14

sw11

sw12

sw13

sw17

sw9

sw8

5 11

sw15

GA fitness function = 0.4836Iterations=100Crossover probability =0.8Mutation probability = 0.02

Load flow results of the topology

S No Branch current(P.U) Node Voltage |V|(P.U)1 0.661 1.002 0.404 1.003 0.000 1.004 0.22 0.9775 1.661 0.9736 1.043 0.9767 0.141 0.9788 0.000 0.9539 0.529 0.942

10 1.039 0.95311 0.123 0.97312 0.782 0.93113 0.649 0.99114 0.062 0.98815 0.000 0.98816 0.412 0.978

Case 2: Fault at line between buses 13-15

4 8 13

9 15

712 16

1410

AC AC AC1 2 3

sw16

sw2

sw1 sw5sw10

sw3

sw4

sw6

sw7

sw14

sw11

sw12

sw13

sw17

sw9

sw8

5 11

sw15

GA fitness function = 0.4126Iterations=100Crossover probability =0.8Mutation probability = 0.02

6

Load flow results for above topology:

S.No Branch current Node Voltage |V|1 1.439 1.002 0.354 1.003 0.818 1.004 0.593 0.9495 1.728 0.9466 1.111 0.9417 0.141 0.9348 0.064 0.9519 0.53 0.939

10 0.257 0.95111 0.122 0.93912 0.000 0.92713 0.144 0.99714 0.000 0.99415 0.000 0.93216 0.389 0.934

Case 3: For Fault on line between buses 8-9

4 8 13

9 15

712 16

1410

AC AC AC1 2 3

sw16

sw2

sw1 sw5sw10

sw3

sw4

sw6

sw7

sw14

sw11

sw12

sw13sw9

sw8

5 11

sw15

GA fitness function = 0.459Iterations=100Crossover probability =0.8Mutation probability = 0.02

6

Load flow results for above topology

S.No Branch current Node Voltage |V|1 1.746 12 1.49 13 0 14 0.22 0.9425 0.755 0.9296 0 0.9777 0.262 0.9798 1.071 0.9779 0.543 0.917

10 0.915 0.97711 0 0.92912 0.781 0.90513 0.649 0.99214 1.136 0.97715 0.124 0.98916 0.412 0.979

Future work

• The present results are obtained through the classical reconfiguration problem. The future work is to integrate the load profiles in this problem formulation and obtain a robust model for distribution system restoration.

• The objective function in this case is

𝑓= (𝑊𝐿𝐿𝑃𝐿𝐿𝑡 + 𝑊𝐿𝑃𝐿𝑡 + 𝑊𝐼𝑂𝐼𝑂𝑡 + 𝑊𝑉𝐷𝑉𝐷𝑡 + 𝑊𝑆𝑊 𝐶𝑖 𝑛𝑆𝑊𝑖=1

𝑡𝑜𝑡=1 )

• In this scenario the Reconfiguration is done over a time frame (outage duration) and the load pattern and the priority of loads over the period is obtained through load profiling

𝑓= (𝑊𝐿𝐿𝑃𝐿𝐿𝑡 + 𝑊𝐿𝑃𝐿𝑡 + 𝑊𝐼𝑂𝐼𝑂𝑡 + 𝑊𝑉𝐷𝑉𝐷𝑡 + 𝑊𝑆𝑊 𝐶𝑖 𝑛𝑆𝑊𝑖=1

𝑡𝑜𝑡=1 )

References

[1] Kumar, Y. Das, B. Sharma, Jaydev “Multiobjective, Multiconstraint Service

Restoration of Electric Power Distribution System With Priority Customers,” Power

Delivery, IEEE Trans. Power Del. on , vol.23, no.1, pp.261,270, Jan. 2008.

[2] W. P. Luan, M. R. Irving, and J. S. Daniel. “Genetic algorithm for supply restoration

and optimal load shedding in power system distribution networks,” IEE Proc- Gen.

Transm. Distrib. vol. 149. no. 2 (2002): pp. 145-151, March. 2002.

[3] MICHALEWICZ, Z.: ‘Genetic algorithms + data structures = evolution programs’,

(Springer, 1996).

[4] S.Fudo, H.Genji, T.Fukuyama and Y.Nakanishi, “Comparative study of modern

heuristic algorithms to service restoration in distribution systems,” Power Delivery,

IEEE Trans. on , vol.17, no.1, pp.173-181, Jan. 2002.

[5] Chicco, G. Napoli, Roberto, Piglione, Federico, “Application of clustering

algorithms and self organising maps to classify electricity

customers,” Power Tech. Conference Proceedings, 2003 IEEE Bologna,

vol.1, pp.7-9. 23-26 June 2003.

[6] Jen-Hao Teng, “A direct approach for distribution system load flow

solutions, “Power Delivery, IEEE Trans. on , vol.18, no.3, pp.882-887, July

2003.