Abstract
This paper discuss a modified Shuffled frog leaping algorithm to Long-term Generation Maintenance Scheduling to Enhance the Reliability of the units. Maintenance scheduling establishes the outage time scheduling of units in a particular time horizon. In a monopolistic power system, maintenance scheduling is being done upon the technical requirements of power plants and preserving the grid reliability. While in power system, technical viewpoints and system reliability are taken into consideration in maintenance scheduling with respect to the economical viewpoint. In this paper present a modified Shuffled frog leaping algorithm methodology for finding the optimum preventive maintenance scheduling of generating units in power system. The objective function is to maintain the units as earlier as possible. Varies constrains such as spinning reserve, duration of maintenance and maintenance crew are being taken into account. In case study, test system consist of 24 buses with 32 thermal generating units is used.
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References
Cohen, A., Sherkat, V.: Optimization based methods for operations scheduling. Proc. IEEE 75(12), 1574–1591 (1987)
Renaud, A.: Daily generation management at electricity de france: from planning towards real time. IEEE Trans. Autom. Control 38(7), 1080–1093 (1993)
Ferreira, L.A., Anderson, T., Imparato, C.F., Vojdani, A.F.: Short term resource scheduling in multi-area hydrothermal power systems. Electr. Power Energy Syst. 11(3), 200–212 (1989)
Shaw J.J., Bertsekas, D.P.: Optimal scheduling of large hydrothermal power system. IEEE Trans. Power Apparatus Syst. (PAS) 104, 286–293 (1985)
Shaw, J.: A direct method for security constrain unit commitment, pp. 25–31. IEEE/PES Summer Meeting, San Francisco (1994)
El-Kaib, A., Ma, H., Hart, J.: Environmentally constrained economic dispatch using Lagrangian relaxation method. IEEE Trans. Power Syst. 9(4), 1723–1729 (1994)
Guan, X., Luh, P.B.: Power system scheduling with fuzzy reserve requirements. IEEE Trans. Power Syst. 11(2), 864–869 (1996)
Tomsovic, Y.: A fuzzy linear programming approach to the reactive power/voltage control problem. IEEE Trans. Power Syst. 7(1), 287–293 (1992)
Miranda, V., Saraiva, J.T.: Fuzzy modeling of power system optimal load flow. IEEE Trans. Power Syst. 7(2), 843–849 (1992)
Li, Y., Luh, P.B., Guan, X.: Fuzzy optimization-based scheduling of identical machines with possible breakdown. In: Proceedings of IEEE 1994 International Conference on Robotics, San Diego, pp. 3347–3452 (1994)
Shahidehpour, M., Marwali, M.: Maintenance scheduling in restructured power system. Kluwer, Norwell (2000)
Leou, R.C.: A Flexible unit maintenance scheduling considering uncertainties. IEEE Trans. Power Syst. 16(3), 552–559 (2001)
Endrenyi, J.: The present status of maintenance strategies and the impact of maintenance on reliability. IEEE Trans. Power Syst. 16(4), 638–646 (2001)
Yamin, H.Y., Shahidehpour, S.M.: Long-term transmission and generation maintenance scheduling with network, fuel and emission constraints. IEEE Trans. Power Syst. 14(3), 1160–1165 (1999)
Rajan, C.C.A., Mohan, M.R., An evolutionary programming based tabu search for solving the unit commitment problem. IEEE Trans. Power Syst. 19(1), 577–589 (2004)
Eusuff, M.M., Lansey, K.E., Pasha, F.: Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Eng. Optim. 38(2), 129–154 (2006)
Zhang, X., Hu, X., Cui, G., Wang, Y., Niu, Y.: An improved shuffled frog leaping algorithm with cognitive behavior. In: Proceedings of the 7th World Congress Intelligent Control and Automation (2008)
Eslamian, M., Hosseinian, S.H., Vahidi, B.: Bacterial foraging-based solution to the unit-commitment problem. IEEE Trans. Power Syst. 24(3), 1478–1488 (2009)
Elbehairy, H., Elbeltagi, E., Hegazy, T.: Comparison of two evolutionary algorithms for optimization of bridge deck repairs. Comput. Aided Civ. Infrastruct. Eng. 21, 561–572 (2006)
Rahimi-Vahed, A., Mirzaei, A.H.: Solving a bi-criteria permutation flow-shop problem using shuffled frog-leaping algorithm. In: Soft Computing. Springer-Verlag, New York (2007)
Luo, X.-H., Yang, Y., Li, X.: Solving TSP with shuffled frog-leaping algorithm. Proc. ISDA 3, 228–232 (2008)
Elbeltagi, E., Hegazy, T., Grierson, D.: Comparison among five evolutionary-based optimization algorithms. Adv. Eng. Inf. 19(1), 43–53 (2005)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. Proc. IEEE Conf. Neural Netw. 4, 1942–1948 (1995)
Huynh, T.H.: A modified shuffled frog leaping algorithm for optimal tuning of multivariable PID controllers. In: Proceedings of the ICIT 2008, pp. 1–6
The IEEE reliability test system—1996. IEEE Trans. Power Syst. 14(3), 1010–1020 (1999)
Elbeltagi, E., Hegazy, T., Grierson, D.: A modified shuffled frog leaping optimization algorithm: application to project management. Struct. Infrastruct. Eng. 3(1), 53–60 (2007)
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Appendices
Appendix
- Ai, Bi, Ci :
-
the cost function parameters of unit I (Rs/MW2Â hr, Rs/MWÂ hr, Rs/hr)
- Fit (Pit):
-
production cost of unit I at a time t (Rs/hr)
- Pit :
-
output power from unit i at time t (MW)
- PDt :
-
system peak demand at hour t (MW)
- N:
-
Number of available generating units
- Rit :
-
reserve contribution of unit i at time t
- nt :
-
number of units
- Uit :
-
commitment state of unit i at time t (on = 1, off = 0)
- OMVC:
-
operation and maintenance variable cost
- OMFC:
-
operation and maintenance fixed cost
- Ts and Te:
-
Starting and ending stage of the time interval for jth unit
- I(t):
-
Reliability index of grid in period t
- αt(k):
-
kth maintenances resource at the tth period
- β:
-
Maximum number of maintenance generator in the same area
- di :
-
Maintenance duration of the ith generator
- si :
-
Maintenance starting period of the ith generator
Biographies
G. Giftson Samuel received his B.E. degree (Electrical and Electronics) from the Madurai Kamaraj University, Madurai, India in 1999 and M.E. degree (Power Electronics and Drives) from the Anna University, Chennai, India in 2004. He is currently pursuing Ph.D in Power System at Anna University, Chennai, India. He published technical papers in International and National Journals and Conferences. He is currently working as Assistant Professor in National Institute of Technology—Puducherry, Karaikal, India. His area of interest is power system optimization. He acquired Member in IEEE and Life member of ISTE.
C. Christober Asir Rajan born on 1970 and received his B.E. (Distn.) degree (Electrical and Electronics) and M.E. (Distn.) degree (Power System) from the Madurai Kamaraj University (1991 and 1996), Madurai, India. And he received his postgraduate degree in DI.S. (Distn.) from the Annamalai University, Chidambaram. He received his Ph.D in Power System at Anna University, Chennai, India. He published technical papers in International & National Journals and Conferences. He is currently working as Professor in Electrical Engineering Department at Pondicherry Engineering College, Puducherry, India. His area of interest is power system optimization, operational planning and control. He acquired Member in ISTE and MIE in India and Student Member in Institution of Electrical Engineers, London.
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Samuel, G.G., Rajan, C.C.A. (2014). A Modified Shuffled Frog Leaping Algorithm for Long-Term Generation Maintenance Scheduling. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_2
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