Evolutionary Programming based Optimal Wind and Thermal Generation Dispatch with valve point effect
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This paper discusses an Evolutionary Programming Approach to obtain optimal wind and thermal generation dispatch. As wind power penetrations increase in current power systems, its impact to conventional thermal unit should be investigated due to the intermittency and unpredictability of wind power generation. Development of better wind thermal coordination economic dispatch is necessary to determine the optimal dispatch scheme that can integrate wind power reliably and efficiently. In this paper Evolutionary Programming (EP) is utilized to coordinate the wind and thermal generation dispatch and to minimize the total production cost in the economic dispatch considering wind power generation and valve effect of thermal units. Different test system incorporating one wind power plant is utilized for numerical simulation. Different simulations with and without wind power production are simulated. Simulation result shows the effect of wind power generation in reducing total fuel cost.
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Yue, C.D., Liu, C.M., Eric, M.L.L., "A Transition toward a Sustainable Energy Future: Feasibility Assessment and Development Strategies of Wind Power in Taiwan", Energy Policy, Vol. 29, pp.951-963, 2001.
Chang, T.J., Wu, Y.T., Hsu, H.Y., Chu, C.R., Liao, C.M., "Assessment of Wind characteristics and wind turbine characteristics in Taiwan", Renewable Energy, Vol. 28, 2003.
Bakirtzis, A.G., Dokopoulos, P.S., "Short Term Generation Scheduling in a Small Autonomous System with Unconventional Energy sources", IEEE Transactions on Power Systems, Vol.3,No.3, pp. 1230-1236,1988.
Kurian, S., Sindhu, T.K., Cheriyan, E.P., Review on developments in wind energy generation and its integration to utility grid, (2013) International Review on Modelling and Simulations (IREMOS), 6 (5), pp. 1523-1532.
Bart C. Ummels, Madeleine Gibescu, Engbert Pelgrum, Wil L Kling Arno J. Brand,"Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch",IEEE Transaction on Energy Conversion, Vol.22, No.1,pp. 44-51, 2007.
Doherty, R. and O'Malley, M., "A new approach to quantify reserve demand in systems with significant installed wind Capacity", IEEE Trans. Power Syst., Vol. 20, No.2,pp. 587–595, 2005.
Chen, C.L. and Chen, N., "Multi-area economic generation and reserve dispatch", in Proc. IEEE PICA Conf., pp.368–3732001.
Chen, C.L., Lee, T.L. and Jan, R.M., "Optimal wind–thermal coordination dispatch in isolated power systems with large integration of wind capacity", Energy Conversion Management, Vol. 47, No.18-19, pp.3456–3472, 2006.
Wood, A.J. and Wollenberg, B.F., Power Generation Operation and Control 2nd edn. (Wiley, New York 1996).
Chen, C.L., and Wang, S.C., "Branch- and-bound scheduling for thermal generating units", IEEE Transactions on Energy Conversion, Vol. 8, No.2,pp. 184–189, 1993.
Merlin, A., and Sandrin, P., "A new method for unit commitment at electricite De France",IEEE Transactions on Power Systems, Vol. 102, No.5, pp. 1218–1225, 1983.
Ismayil, C., Sreerama Kumar, R., Sindhu, T.K., Comparative analysis of genetic algorithm and fuzzy logic based automatic generation control of multi area power systems, (2013) International Review on Modelling and Simulations (IREMOS), 6 (1), pp. 136-144.
Juste, K.A., Kiat, H., Tanaka, E., and Hasegawa, J., "An evolutionary programming solution to the unit commitment problem",IEEE Transactions on Power Systems, Vol.14, No.4, pp. 1452–1459,1999.
Juste, K.A., Kiat, H., Tanaka, E., and Hasegawa, J., "Unit commitment by a tabu- search-based hybrid-optimisation technique", IEE Proceedings on Generation, Transmission and Distribution, Vol. 152, No.4,pp.563–574, 2005.
Zhuang, F., and Galiana, F.D., "Unit commitment by simulated annealing", IEEE Transactions on Power Systems, Vol.11, No.3, pp. 311–317,1990.
Mantawy, A.H., Abdel-Magid, Y.L., and Selim, S.Z., "A Simulated annealing algorithm for unit commitment", IEEE Transactions on Power Systems, Vol. 13, No.1, pp.197–204, 1998.
Pitono, J., Soeprijanto, A., Purnomo, M.H., Gunadin, I.C., Power generation optimization based on steady state stability limit using particle swarm optimization (PSO), (2013) International Review on Modelling and Simulations (IREMOS), 6 (4), pp. 1227-1232.
Victoire TAA, Jeyakumar AE,"Deterministically guided PSO for dynamic dispatch considering valve-point effects" International Journal of Electric Power System Research, Vol. 73, No.3,pp.313–322, 2005.
Kennedy J, "The particle swarm: Social adaptation of knowledge", IEEE Proceedings International Conference on Evolutionary Computation, Indianapolis, pp. 303-308,1997.
K. T. Chaturvedi, et al., "Particle swarm optimization with crazy particles for nonconvex economic dispatch," Applied Soft Computing, Vol. 9, pp. 962-969, 2009.
D.B.Fogel, Evolutionary Computation,Towards a New Philosophy of Machine Intelligence. (Piscataway, NJ: IEEE Press 1995).
T. Back, Evolutionary Algorithms in Theory and Practice. (New York: Oxford University Press, 1996).
L.J. Fogel, A.J. Owens and M.J. Walse, Artificial Intelligence through Simulated Evolution. (New York: Wiley, 1996)
N. Sinha, R. Chakrabarti and P. K. Chattopadhyay. "Evolutionary Programming Techniques for Economic Load Dispatch",IEEE Trans. Evolutionary Computation, Vol.1, No.1,pp. 83-94, 2003.
C.Jiejin, X. Ma, L. Li and P. Haipeng, "Chaotic particle swarm optimization for economic dispatch considering the generator constraints," Energy Conversion and management, Vol.48, No.2, pp. 645-653,2007.
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