Hybrid probabilistic-harmony search algorithm methodology in generation scheduling problem

REFERENCES

• Aghamohammadi, M. R. (2008). Static security constrained generation scheduling using sensitivity characteristics of neural network. Iranian Journal of Electrical and Electronic Engineering, 4, 104–114.
   Google Scholar
• Basu, M. (2010). Economic environmental dispatch of hydrothermal power system. Electrical Power and Energy Systems, 32, 711–720.
   Web of Science ®Google Scholar
• Catalão, J. P. S., Mariano, S. J. P. S., Mendes, V. M. F., & Ferreira, L. A. F. M. (2007). Profit-based unit commitment with emission limitations: A multiobjective approach. IEEE Conference on Power Tech, IEEE, Lausanne, Swiss, pp. 1417–1422.
   Google Scholar
• Catalão, J. P. S., Mariano, S. J. P. S., Mendes, V. M. F., & Ferreira, L. A. F. M. (2008). Short-term scheduling of thermal units: Emission constraints and trade-off curves. European Transactions on Electrical Power, 18, 1–14.
   Web of Science ®Google Scholar
• Catalão, J. P. S., Mariano, S. J. P. S., Mendes, V. M. F., & Ferreira, L. A. F. M. (2009). Scheduling of head-sensitive cascaded hydro systems: A nonlinear approach. IEEE Transactions on Power Systems, 24, 337–346.
   Web of Science ®Google Scholar
• Chang, G. W., Aganagic, M., Waight, J. G., Medina, J., Burton, T., Reeves, S., & Christoforidis, M. (2001). Experiences with mixed integer linear programming based approaches on short-term hydro scheduling. IEEE Transactions on Power Systems, 16, 743–749.
   Web of Science ®Google Scholar
• Deb, K. (2003). Multi-objective optimization using evolutionary algorithms. New York: Wiley.
   Google Scholar
• Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6, 182–197.
   Web of Science ®Google Scholar
• Dehghanian, P., Hosseini, H., Moeini-Aghtaie, M., & Arabali, A. (2013). Optimal siting of DG units in power systems from a probabilistic multi-objective optimization perspective. Electrical Power and Energy Systems, 51, 14–26.
   Web of Science ®Google Scholar
• Fesanghary, M., Mahdavi, M., Minary-Jolandan, M., & Alizadeh, Y. (2008). Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems. Computer Methods in Applied Mechanics and Engineering, 197, 3080–3091.
   Web of Science ®Google Scholar
• Finardi, E. C., da Silva, E. L., & Sagastizábal, C. (2005). Solving the unit commitment problem of hydropower plants via Lagrangian Relaxation and Sequential Quadratic Programming. Computational and Applied Mathematics, 24, 317–342.
   Web of Science ®Google Scholar
• Franco, P. E. C., Carvalho, M. F., & Soares, S. (1994). A network flow model for short-term hydro-dominated hydrothermal scheduling problems. IEEE Transactions on Power Systems, 9, 1016–1022.
   Web of Science ®Google Scholar
• Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: Harmony search. Simulation, 76, 60–68.
   Google Scholar
• Guan, X., Ni, E., Li, R., & Luh, P. B. (1997). An optimization-based algotithm for scheduling hydrothermal power systems with cascaded reservoirs and discrete hydro constraints. IEEE Transactions on Power Systems, 12, 1775–1780.
   Web of Science ®Google Scholar
• Javadi, M. S., Esmaeel Nezhad, A., & Sabramooz, S. (2012). Economic heat and power dispatch in modern power system harmony search algorithm versus analytical solution. Scientia Iranica, 19, 1820–1828.
   Web of Science ®Google Scholar
• Kang, S. L., & Geem, Z. W. (2004). A new structural optimization method based on the harmony search algorithm. Computers and Structures, 82, 781–798.
   Google Scholar
• Maghouli, P., Hosseini, S. H., Buygi, M. O., & Shahidehpour, M. (2009). A multi-objective framework for transmission expansion planning in deregulated environments. IEEE Transactions on Power Systems, 24, 1051–1061.
   Web of Science ®Google Scholar
• Mahdavi, M., Fesanghary, M., & Damangir, E. (2007). An improved harmony search algorithm for solving optimization problems. Applied Mathematics and Computation, 188, 1567–1579.
   Web of Science ®Google Scholar
• Mahor, A., Prasad, V., & Rangnekar, S. (2009). Scheduling of cascaded hydro power system: A new self adaptive inertia weight particle swarm optimization approach. Paper presented at 2009 international conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, pp. 565–570.
   Google Scholar
• Marwali, M. K. C., & Shahidehpour, M. (2000). Coordination between long-term and short-term generation scheduling with network constraints. IEEE Transactions on Power Systems, 15, 1161–1167.
   Web of Science ®Google Scholar
• Nilsson, O., & Sjelvgren, D. (1997). Variable splitting applied to modeling of start-up costs in short term hydro generation scheduling. IEEE Transactions on Power Systems, 12, 770–775.
   Web of Science ®Google Scholar
• Ruiwei, J., Jianhui, W., & Yongpei, G. (2012). Robust unit commitment with wind power and pumped storage hydro. IEEE Transactions on Power Systems, 27, 800–810.
   Web of Science ®Google Scholar
• Shahrouzi, M., & Sazjini, M. (2012). Refined harmony search for optimal scaling and selection of accelerograms. Scientia Iranica, 19, 218–224.
   Web of Science ®Google Scholar
• Shi-Chung, C., Chen, C.-H., Fong, I. K., & Luh, P. B. (1990). Hydroelectric generation scheduling with an effective differential dynamic programming algorithm. IEEE Transactions on Power Systems, 5, 737–743.
   Web of Science ®Google Scholar
• Shiina, T., & Watanabe, I. (2004). Lagrangian relaxation method for price-based unit commitment problem. Engineering Optimization, 36, 705–719.
   Web of Science ®Google Scholar
• Sivasubramani, S., & Swarup, K. S. (2011). Multi-objective harmony search algorithm for optimal power flow problem. International Journal of Electrical Power and Energy Systems, 33, 745–752.
   Web of Science ®Google Scholar
• Wang, S., Shahidehpour, M., Kirschen, D., Mokhtari, S., & Irisarri, G. (1995). Short-term generation scheduling with transmission and environmental constraints using an augmented lagrangian relaxation. IEEE Transactions on Power Systems, 10, 1294–1301.
   Web of Science ®Google Scholar
• Xiaohong, G., Ni, E., Renhou, L., & Luh, P. B. (1997). An optimization-based algorithm for scheduling hydrothermal power systems with cascaded reservoirs and discrete hydro constraints. IEEE Transactions on Power Systems, 12, 1775–1780.
   Web of Science ®Google Scholar
• Yi, Z., Songzhe, Z., & Chowdhury, A. A. (2011). Reliability modeling and control schemes of composite energy storage and wind generation system with adequate transmission upgrades. IEEE Transactions on Sustainable Energy, 2, 520–526.
   Web of Science ®Google Scholar