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GENETIC ALGORITHM BASED SHORT-TERM SCHEDULING OF REACTIVE POWER CONTROLLERS

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Abstract (2. Language): 
This paper presents a genetic algorithm-based approach for short–term scheduling of reactive power controllers. The objective of this paper is to determine the proper settings of the control devices (capacitor banks and transformer taps) for the next 24 hours, which minimizing the active power losses without exceeding the allowed number of movements of the control devices per day, and maintaining satisfactory voltage profile under various loading conditions. A genetic algorithm (GA) approach is proposed in this paper. The GA algorithm is applied into two levels, at the first level, GA is implemented to determine the optimal reactive power dispatch (optimal settings of control devices) for each operating hour in the day, and then at the second level, GA is implemented again to find the final optimal reactive power dispatch for the whole day. The proposed method was applied to a modified IEEE 30-bus system to show the feasibility and the capability of the proposed method, the experiment was carried out and the results are presented in this paper.
1419-1426

REFERENCES

References: 

[1] J. J. Paserba, D. J. Leonard, N.W. Miller,
S. T. Naumann, M. G. Lauby, and F. P.
Senser, "Coordination of a distribution level
continuously controlled compensation device
with existing substation equipment for long
term VAR management", IEEE Transactions
on Power Systems, Vol: 9, pp.1034–1040,
1994.
[2] E. Baran and M. Y. Hsu, "Vot/Var control
at distribution substations", IEEE
Transactions on Power Systems, Vol: 14, pp.
312–318, 1999 .
[3] F. C. Lu and Y. Y. Hsu, "Reactive
power/voltage control in a distribution
substation using dynamic programming",
Proc. Inst. Elect. Eng. Gener. Transm.
Distrib,Vol: 142, pp. 639–644, 1995.
[4] Y. Y. Hsu and H. C. Kuo, "Dispatch of
capacitors on distribution system using
dynamic programming", Proc. Inst. Elect.
Eng., pt. C, Vol: 140, pp. 433–438, 1993.
[5] K. Y. Lee, Y. M. Park and J. L. Ortiz. "A
United Approach to Optimal Real and
Reactive Power Dispatch", IEEE Transaction
on Power Apparatus and Systems,Vol:104,
pp.1147-1153, 1985.
[6] J. A. Momoh, M. E. El-Hawary and R.
Adapa, "A Review of Selected Optimal Power
Flow Literature to 1993 Part II", IEEE
Transactions on Power Systems, Vol: 14, No:
1, pp. 96-111 , 1999.
[7] S. J. Cheng, O. P. Malik and G. S. Hope,
"An Expert Systems for Voltage and Reactive
Power Control of a Power System" IEEE
Transactions on Power Systems, Vol: 3, No: 4,
pp. 1449-1455, 1988.
[8] D. E. Goldberg, Genetic Algorithms in
Search, Optimization and Machine Learning,
Addison-Wesley, 1989.
[9] D. A.Coley, "An Introduction to Genetic
Algorithms for Scientists and Engineers",
World Scientific Publishing Co., 1999.
[10] V. Miranda, D. Srinivasan and L.
Proenca, "Evolutionary Computation in Power
Systems", Electrical Power and Energy
Systems, Vol: 20, No: 2, pp. 89-98, 1998.
[11] H. Yoshida K. Kawata Y. Fukuyama and
Y. Nakanishi, "A Particle Swarm
Optimization for Reactive Power and Voltage
Control Considering Voltage Stability",
Proceedings of the 1999 Intelligent Systems
Application to Power Systems (ISAP.99), Rio
de Janeiro (Brazil) , pp. 117-121,April 4-8,
1999.
[12] K. Iba, "Reactive Power Optimization by
Genetic Algorithm", IEEE Transactions on
Power Systems, Vol: 9, No: 2, pp. 685-692,
1994.
[13] G. A. Bakare, U. O. Aliyu and G. Krost,
"Computational Enhancement of Genetic
Algorithm via Control Device Pre-Selection
Mechanism for Power System Reactive Power
/ Voltage Control", Power Engineering
Society General Meeting Vol: 3, pp. 1698-
1703,13-17July,2

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